Patent Grant
11293032
The ASCII file, entitled 79403SequenceListing.txt, created on Oct. 28, 2019 comprising 20,892,831 bytes, submitted concurrently with the filing of this application is incorporated herein by reference.
The present invention, in some embodiments thereof, relates to isolated polynucleotides and polypeptides which can increase the yield (e.g., biomass, grain quantity and/or quality, seed yield, oil yield), growth rate, vigor, abiotic stress tolerance (ABST), water use efficiency (WUE), nitrogen use efficiency (NUE) and/or fertilizer use efficiency (FUE) of a plant.
The ever-increasing world population and the decreasing availability in arable land for agriculture affect the yield of plants and plant-related products. The global shortage of water supply, desertification, abiotic stress (ABS) conditions (e.g., salinity, drought, flood, suboptimal temperature and toxic chemical pollution), and/or limited nitrogen and fertilizer sources cause substantial damage to agricultural plants such as major alterations in the plant metabolism, cell death, and decreases in plant growth and crop productivity.
Drought is a gradual phenomenon, which involves periods of abnormally dry weather that persists long enough to produce serious hydrologic imbalances such as crop damage, water supply shortage and increased susceptibility to various diseases.
Salinity, high salt levels, affects one in five hectares of irrigated land. None of the top five food crops, i.e., wheat, corn, rice, potatoes, and soybean, can tolerate excessive salt. Detrimental effects of salt on plants result from both water deficit, which leads to osmotic stress (similar to drought stress), and the effect of excess sodium ions on critical biochemical processes. As with freezing and drought, high salt causes water deficit; and the presence of high salt makes it difficult for plant roots to extract water from their environment. Thus, salination of soils that are used for agricultural production is a significant and increasing problem in regions that rely heavily on agriculture, and is worsen by over-utilization, over-fertilization and water shortage, typically caused by climatic change and the demands of increasing population.
Suboptimal temperatures affect plant growth and development through the whole plant life cycle. Thus, low temperatures reduce germination rate and high temperatures result in leaf necrosis. In addition, mature plants that are exposed to excess heat may experience heat shock, which may arise in various organs, including leaves and particularly fruit, when transpiration is insufficient to overcome heat stress. Heat also damages cellular structures, including organelles and cytoskeleton, and impairs membrane function. Heat shock may produce a decrease in overall protein synthesis, accompanied by expression of heat shock proteins, e.g., chaperones, which are involved in refolding proteins denatured by heat. High-temperature damage to pollen almost always occurs in conjunction with drought stress, and rarely occurs under well-watered conditions. Combined stress can alter plant metabolism in novel ways. Excessive chilling conditions, e.g., low, but above freezing, temperatures affect crops of tropical origins, such as soybean, rice, maize, and cotton. Typical chilling damage includes wilting, necrosis, chlorosis or leakage of ions from cell membranes. Excessive light conditions, which occur under clear atmospheric conditions subsequent to cold late summer/autumn nights, can lead to photoinhibition of photosynthesis (disruption of photosynthesis). In addition, chilling may lead to yield losses and lower product quality through the delayed ripening of maize.
Nutrient deficiencies cause adaptations of the root architecture, particularly notably for example is the root proliferation within nutrient rich patches to increase nutrient uptake. Nutrient deficiencies cause also the activation of plant metabolic pathways which maximize the absorption, assimilation and distribution processes such as by activating architectural changes. Engineering the expression of the triggered genes may cause the plant to exhibit the architectural changes and enhanced metabolism also under other conditions.
In addition, it is widely known that the plants usually respond to water deficiency by creating a deeper root system that allows access to moisture located in deeper soil layers. Triggering this effect will allow the plants to access nutrients and water located in deeper soil horizons particularly those readily dissolved in water like nitrates.
Suboptimal nutrient (macro and micro nutrient) affect plant growth and development through the whole plant life cycle. A common approach to promote plant growth has been, and continues to be, the use of natural as well as synthetic nutrients (fertilizers). Thus, fertilizers are the fuel behind the “green revolution”, directly responsible for the exceptional increase in crop yields during the last 40 years, and are considered the number one overhead expense in agriculture. Of the three macronutrients provided as main fertilizers [Nitrogen (N), Phosphate (P) and Potassium (K)], nitrogen is often the rate-limiting element in plant growth and all field crops have a fundamental dependence on inorganic nitrogenous fertilizer. Nitrogen usually needs to be replenished every year, particularly for cereals, which comprise more than half of the cultivated areas worldwide. For example, inorganic nitrogenous fertilizers such as ammonium nitrate, potassium nitrate, or urea, typically accounts for about 40% of the costs associated with crops such as corn and wheat.
Nitrogen is an essential macronutrient for the plant, responsible for biosynthesis of amino acids and nucleic acids, prosthetic groups, plant hormones, plant chemical defenses, and the like. In addition, nitrogen is often the rate-limiting element in plant growth and all field crops have a fundamental dependence on inorganic nitrogen. Thus, nitrogen is translocated to the shoot, where it is stored in the leaves and stalk during the rapid step of plant development and up until flowering. In corn for example, plants accumulate the bulk of their organic nitrogen during the period of grain germination, and until flowering. Once fertilization of the plant has occurred, grains begin to form and become the main sink of plant nitrogen. The stored nitrogen can be then redistributed from the leaves and stalk that served as storage compartments until grain formation. Phosphorous and Potassium have a direct correlation to yield and general plant tolerance.
Since fertilizer is rapidly depleted from most soil types, it must be supplied to growing crops two or three times during the growing season, particularly for cereals, which comprise more than half of the cultivated areas worldwide. For example, inorganic nitrogenous fertilizers such as ammonium nitrate, potassium nitrate, or urea, typically accounts for 40% of the costs associated with crops such as corn and wheat. In addition, the low nitrogen use efficiency (NUE) of the main crops (e.g., in the range of only 30-70%) negatively affects the input expenses for the farmer, due to the excess fertilizer applied. Moreover, the over and inefficient use of fertilizers are major factors responsible for environmental problems such as eutrophication of groundwater, lakes, rivers and seas, nitrate pollution in drinking water which can cause methemoglobinemia, phosphate pollution, atmospheric pollution and the like. However, in spite of the negative impact of fertilizers on the environment, and the limits on fertilizer use, which have been legislated in several countries, the use of fertilizers is expected to increase in order to support food and fiber production for rapid population growth on limited land resources. For example, it has been estimated that by 2050, more than 150 million tons of nitrogenous fertilizer will be used worldwide annually.
Increased use efficiency of nitrogen by plants should enable crops to be cultivated with lower fertilizer input, or alternatively to be cultivated on soils of poorer quality and would therefore have significant economic impact in both developed and developing agricultural systems.
Genetic improvement of fertilizer use efficiency (FUE) in plants can be generated either via traditional breeding or via genetic engineering. Attempts to generate plants with increased FUE have been described in U.S. Pat. Appl. No. 20020046419 to Choo, et al.; U.S. Pat. Appl. No. 20050108791 to Edgerton et al.; U.S. Pat. Appl. No. 20060179511 to Chomet et al.; Good, A, et al. 2007 (Engineering nitrogen use efficiency with alanine aminotransferase. Canadian Journal of Botany 85: 252-262); and Good A G et al. 2004 (Trends Plant Sci. 9:597-605).
Yanagisawa et al. (Proc. Natl. Acad. Sci. U.S.A. 2004 101:7833-8) describe Dof1 transgenic plants which exhibit improved growth under low-nitrogen conditions.
U.S. Pat. No. 6,084,153 to Good et al. discloses the use of a stress responsive promoter to control the expression of Alanine Amine Transferase (AlaAT) and transgenic canola plants with improved drought and nitrogen deficiency tolerance when compared to control plants.
Yield is affected by various factors, such as, the number and size of the plant organs, plant architecture (for example, the number of branches), grains set length, number of filled grains, vigor (e.g. seedling), growth rate, root development, utilization of water, nutrients (e.g., nitrogen) and fertilizers, and stress tolerance.
Crops such as, corn, rice, wheat, canola and soybean account for over half of total human caloric intake, whether through direct consumption of the seeds themselves or through consumption of meat products raised on processed seeds or forage. Seeds are also a source of sugars, oils and metabolites used in industrial processes. The ability to increase plant yield, whether through increase dry matter accumulation rate, modifying cellulose or lignin composition, increase stalk strength, enlarge meristem size, change of plant branching pattern, erectness of levees, increase in fertilization efficiency, enhanced seed dry matter accumulation rate, modification of seed development, enhanced seed filling or by increasing the content of oil, starch or protein in the seeds would have many applications in agricultural and non-agricultural uses such as in the biotechnological production of pharmaceuticals, antibodies or vaccines.
Studies have shown that plant adaptations to adverse environmental conditions are complex genetic traits with polygenic nature. Conventional means for crop and horticultural improvements utilize selective breeding techniques to identify plants having desirable characteristics. However, selective breeding is tedious, time consuming and has an unpredictable outcome. Furthermore, limited germplasm resources for yield improvement and incompatibility in crosses between distantly related plant species represent significant problems encountered in conventional breeding. Advances in genetic engineering have allowed mankind to modify the germplasm of plants by expression of genes-of-interest in plants. Such a technology has the capacity to generate crops or plants with improved economic, agronomic or horticultural traits.
WO publication No. 2004/104162 discloses methods of increasing abiotic stress tolerance and/or biomass in plants and plants generated thereby.
WO publication No. 2004/111183 discloses nucleotide sequences for regulating gene expression in plant trichomes and constructs and methods utilizing same.
WO publication No. 2004/081173 discloses novel plant derived regulatory sequences and constructs and methods of using such sequences for directing expression of exogenous polynucleotide sequences in plants.
WO publication No. 2005/121364 discloses polynucleotides and polypeptides involved in plant fiber development and methods of using same for improving fiber quality, yield and/or biomass of a fiber producing plant.
WO publication No. 2007/049275 discloses isolated polypeptides, polynucleotides encoding same, transgenic plants expressing same and methods of using same for increasing fertilizer use efficiency, plant abiotic stress tolerance and biomass.
WO publication No. 2007/020638 discloses methods of increasing abiotic stress tolerance and/or biomass in plants and plants generated thereby.
WO publication No. 2008/122980 discloses genes constructs and methods for increasing oil content, growth rate and biomass of plants.
WO publication No. 2008/075364 discloses polynucleotides involved in plant fiber development and methods of using same.
WO publication No. 2009/083958 discloses methods of increasing water use efficiency, fertilizer use efficiency, biotic/abiotic stress tolerance, yield and biomass in plant and plants generated thereby.
WO publication No. 2009/141824 discloses isolated polynucleotides and methods using same for increasing plant utility.
WO publication No. 2009/013750 discloses genes, constructs and methods of increasing abiotic stress tolerance, biomass and/or yield in plants generated thereby.
WO publication No. 2010/020941 discloses methods of increasing nitrogen use efficiency, abiotic stress tolerance, yield and biomass in plants and plants generated thereby.
WO publication No. 2010/076756 discloses isolated polynucleotides for increasing abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, and/or nitrogen use efficiency of a plant.
WO2010/100595 publication discloses isolated polynucleotides and polypeptides, and methods of using same for increasing plant yield and/or agricultural characteristics.
WO publication No. 2010/049897 discloses isolated polynucleotides and polypeptides and methods of using same for increasing plant yield, biomass, growth rate, vigor, oil content, abiotic stress tolerance of plants and nitrogen use efficiency.
WO2010/143138 publication discloses isolated polynucleotides and polypeptides, and methods of using same for increasing nitrogen use efficiency, fertilizer use efficiency, yield, growth rate, vigor, biomass, oil content, abiotic stress tolerance and/or water use efficiency.
WO publication No. 2011/080674 discloses isolated polynucleotides and polypeptides and methods of using same for increasing plant yield, biomass, growth rate, vigor, oil content, abiotic stress tolerance of plants and nitrogen use efficiency.
WO2011/015985 publication discloses polynucleotides and polypeptides for increasing desirable plant qualities.
According to an aspect of some embodiments of the present invention there is provided a method of increasing yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of a plant, comprising expressing within the plant an exogenous polynucleotide comprising a nucleic acid sequence encoding a polypeptide at least 80% identical to SEQ ID NO: 480-812, 5174-7015, 7017-7021, 7024, 7026-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, 9143-9176 or 9177, thereby increasing the yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of the plant.
According to an aspect of some embodiments of the present invention there is provided a method of increasing yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of a plant, comprising expressing within the plant an exogenous polynucleotide comprising a nucleic acid sequence encoding a polypeptide selected from the group consisting of SEQ ID NOs:480-812, 5174-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, and 9143-9177, thereby increasing the yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of the plant.
According to an aspect of some embodiments of the present invention there is provided a method of increasing yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of a plant, comprising expressing within the plant an exogenous polynucleotide comprising a nucleic acid sequence at least 80% identical to SEQ ID NO: 1-479, 813-5173, 8511, 8513, 8515, 8517, 8519, 8521, 8523, 9096-9141 or 9142, thereby increasing the yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of the plant.
According to an aspect of some embodiments of the present invention there is provided a method of increasing yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of a plant, comprising expressing within the plant an exogenous polynucleotide comprising the nucleic acid sequence selected from the group consisting of SEQ ID NOs: 1-479, 813-5173, 8511, 8513, 8515, 8517, 8519, 8521, 8523, and 9096-9142, thereby increasing the yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of the plant.
According to an aspect of some embodiments of the present invention there is provided an isolated polynucleotide comprising a nucleic acid sequence encoding a polypeptide which comprises an amino acid sequence at least 80% homologous to the amino acid sequence set forth in SEQ ID NO: 480-812, 5174-7015, 7017-7021, 7024, 7026-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, 9143-9176 or 9177, wherein the amino acid sequence is capable of increasing yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of a plant.
According to an aspect of some embodiments of the present invention there is provided an isolated polynucleotide comprising a nucleic acid sequence encoding a polypeptide which comprises the amino acid sequence selected from the group consisting of SEQ ID NOs: 480-812, 5174-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, and 9143-9177.
According to an aspect of some embodiments of the present invention there is provided an isolated polynucleotide comprising a nucleic acid sequence at least 80% identical to SEQ ID NO:1-479, 813-5173, 8511, 8513, 8515, 8517, 8519, 8521, 8523, 9096-9141 or 9142, wherein the nucleic acid sequence is capable of increasing yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of a plant.
According to an aspect of some embodiments of the present invention there is provided an isolated polynucleotide comprising the nucleic acid sequence selected from the group consisting of SEQ ID NOs: 1-479, 813-5173, 8511, 8513, 8515, 8517, 8519, 8521, 8523, and 9096-9142.
According to an aspect of some embodiments of the present invention there is provided a nucleic acid construct comprising the isolated polynucleotide of some embodiments of the invention, and a promoter for directing transcription of the nucleic acid sequence in a host cell.
According to an aspect of some embodiments of the present invention there is provided an isolated polypeptide comprising an amino acid sequence at least 80% homologous to SEQ ID NO: 480-812, 5174-7015, 7017-7021, 7024, 7026-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, 9143-9176 or 9177, wherein the amino acid sequence is capable of increasing yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of a plant.
According to an aspect of some embodiments of the present invention there is provided an isolated polypeptide comprising the amino acid sequence selected from the group consisting of SEQ ID NOs: 480-812, 5174-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, and 9143-9177.
According to an aspect of some embodiments of the present invention there is provided a plant cell exogenously expressing the polynucleotide of some embodiments of the invention, or the nucleic acid construct of some embodiments of the invention.
According to an aspect of some embodiments of the present invention there is provided a plant cell exogenously expressing the polypeptide of some embodiments of the invention.
According to an aspect of some embodiments of the present invention there is provided a transgenic plant comprising the nucleic acid construct of some embodiments of the invention.
According to some embodiments of the invention, the nucleic acid sequence encodes an amino acid sequence selected from the group consisting of SEQ ID NOs: 480-812, 5174-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, and 9143-9177.
According to some embodiments of the invention, the nucleic acid sequence is selected from the group consisting of SEQ ID NOs: 1-479, 813-5173, 8511, 8513, 8515, 8517, 8519, 8521, 8523, and 9096-9142.
According to some embodiments of the invention, the polynucleotide consists of the nucleic acid sequence selected from the group consisting of SEQ ID NOs: 1-479, 813-5173, 8511, 8513, 8515, 8517, 8519, 8521, 8523, and 9096-9142.
According to some embodiments of the invention, the nucleic acid sequence encodes the amino acid sequence selected from the group consisting of SEQ ID NOs: 480-812, 5174-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, and 9143-9177.
According to some embodiments of the invention, the plant cell forms part of a plant.
According to some embodiments of the invention, the method further comprising growing the plant expressing the exogenous polynucleotide under the abiotic stress.
According to some embodiments of the invention, the abiotic stress is selected from the group consisting of salinity, drought, water deprivation, flood, etiolation, low temperature, high temperature, heavy metal toxicity, anaerobiosis, nutrient deficiency, nutrient excess, atmospheric pollution and UV irradiation.
According to some embodiments of the invention, the yield comprises seed yield or oil yield.
According to some embodiments of the invention, the method further comprising growing the plant expressing the exogenous polynucleotide under nitrogen-limiting conditions.
According to some embodiments of the invention, the promoter is heterologous to the isolated polynucleotide.
According to some embodiments of the invention, the promoter is heterologous to the host cell.
Unless otherwise defined, all technical and/or scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention pertains. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of embodiments of the invention, exemplary methods and/or materials are described below. In case of conflict, the patent specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and are not intended to be necessarily limiting.
Some embodiments of the invention are herein described, by way of example only, with reference to the accompanying drawings. With specific reference now to the drawings in detail, it is stressed that the particulars shown are by way of example and for purposes of illustrative discussion of embodiments of the invention. In this regard, the description taken with the drawings makes apparent to those skilled in the art how embodiments of the invention may be practiced.
In the drawings:
The present invention, in some embodiments thereof, relates to isolated polynucleotides and polypeptides, nucleic acid constructs, transgenic cells and transgenic plants comprising same and methods of generating and using same, and, more particularly, but not exclusively, to methods of increasing yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality abiotic stress tolerance, and/or fertilizer use efficiency (e.g., nitrogen use efficiency) of a plant.
Before explaining at least one embodiment of the invention in detail, it is to be understood that the invention is not necessarily limited in its application to the details set forth in the following description or exemplified by the Examples. The invention is capable of other embodiments or of being practiced or carried out in various ways.
The present inventors have identified novel polypeptides and polynucleotides which can be used to increase yield, growth rate, biomass, oil content, vigor, abiotic stress tolerance and/or fertilizer (e.g., nitrogen) use efficiency of a plant.
Thus, as shown in the Examples section which follows, the present inventors have utilized bioinformatics tools to identify polynucleotides which enhance yield (e.g., seed yield, oil yield, oil content), growth rate, biomass, vigor, fiber yield and/or quality, abiotic stress tolerance and/or fertilizer (e.g., nitrogen) use efficiency of a plant. Genes which affect the trait-of-interest were identified based on expression profiles and gene copy number of genes of several Barley, Arabidopsis, Sorghum, Maize, Brachypodium, Foxtail Millet, and Soybean ecotypes, accessions and varieties in various tissues, developmental stages, ABST and fertilizer-limiting conditions; as well as homology with genes known to affect the trait-of-interest and using digital expression profile in specific tissues and conditions (Tables 1, 3-50, Examples 1 and 3-11 of the Examples section which follows). Homologous polypeptides and polynucleotides having the same function were also identified (Table 2, Example 2 of the Examples section which follows). The novel polynucleotides were cloned into nucleic acid constructs (e.g., binary vectors, Table 51, Example 12 of the Examples section which follows), transformed into Agrobacterium tumefaciens cells, and transgenic Arabidopsis plants transformed with the isolated polynucleotides were generated (Example 13 of the Examples section which follows) for evaluation of the effect of the transgene on plant performance. Transgenic plants over-expressing the identified polynucleotides were found to exhibit increased seed yield, oil content, biomass, and growth rate (Tables 52-64; Examples 14-16 of the Examples section which follows), and increased tolerance to abiotic stress conditions. Altogether, these results suggest the use of the novel polynucleotides and polypeptides of the invention for increasing yield (including oil yield, seed yield and oil content, fiber yield and/or quality), growth rate, biomass, vigor, abiotic stress tolerance and/or fertilizer (e.g., nitrogen) use efficiency of a plant.
Thus, according to an aspect of some embodiments of the invention, there is provided method of increasing yield, growth rate, biomass, vigor, oil content, fiber yield, fiber quality, fertilizer use efficiency (e.g., nitrogen use efficiency) and/or abiotic stress tolerance of a plant, comprising expressing within the plant an exogenous polynucleotide comprising a nucleic acid sequence encoding a polypeptide at least about 80%, at least about 81%, at least about 82%, at least about 83%, at least about 84%, at least about 85%, at least about 86%, at least about 87%, at least about 88%, at least about 89%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99%, or more say 100% homologous to the amino acid sequence selected from the group consisting of SEQ ID NOs: 480-812, 5174-7015, 7017-7021, 7024, 7026-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, 9143-9177, thereby increasing the yield, growth rate, biomass, vigor, oil content, fiber yield, fiber quality, fertilizer use efficiency (e.g., nitrogen use efficiency) and/or abiotic stress tolerance of the plant.
As used herein the phrase “plant yield” refers to the amount (e.g., as determined by weight or size) or quantity (numbers) of tissues or organs produced per plant or per growing season. Hence increased yield could affect the economic benefit one can obtain from the plant in a certain growing area and/or growing time.
It should be noted that a plant yield can be affected by various parameters including, but not limited to, plant biomass; plant vigor; growth rate; seed yield; seed or grain quantity; seed or grain quality; oil yield; content of oil, starch and/or protein in harvested organs (e.g., seeds or vegetative parts of the plant); number of flowers (florets) per panicle (expressed as a ratio of number of filled seeds over number of primary panicles); harvest index; number of plants grown per area; number and size of harvested organs per plant and per area; number of plants per growing area (density); number of harvested organs in field; total leaf area; carbon assimilation and carbon partitioning (the distribution/allocation of carbon within the plant); resistance to shade; number of harvestable organs (e.g. seeds), seeds per pod, weight per seed; and modified architecture [such as increase stalk diameter, thickness or improvement of physical properties (e.g. elasticity)].
As used herein the phrase “seed yield” refers to the number or weight of the seeds per plant, seeds per pod, or per growing area or to the weight of a single seed, or to the oil extracted per seed. Hence seed yield can be affected by seed dimensions (e.g., length, width, perimeter, area and/or volume), number of (filled) seeds and seed filling rate and by seed oil content. Hence increase seed yield per plant could affect the economic benefit one can obtain from the plant in a certain growing area and/or growing time; and increase seed yield per growing area could be achieved by increasing seed yield per plant, and/or by increasing number of plants grown on the same given area.
The term “seed” (also referred to as “grain” or “kernel”) as used herein refers to a small embryonic plant enclosed in a covering called the seed coat (usually with some stored food), the product of the ripened ovule of gymnosperm and angiosperm plants which occurs after fertilization and some growth within the mother plant.
The phrase “oil content” as used herein refers to the amount of lipids in a given plant organ, either the seeds (seed oil content) or the vegetative portion of the plant (vegetative oil content) and is typically expressed as percentage of dry weight (10% humidity of seeds) or wet weight (for vegetative portion).
It should be noted that oil content is affected by intrinsic oil production of a tissue (e.g., seed, vegetative portion), as well as the mass or size of the oil-producing tissue per plant or per growth period.
In one embodiment, increase in oil content of the plant can be achieved by increasing the size/mass of a plant's tissue(s) which comprise oil per growth period. Thus, increased oil content of a plant can be achieved by increasing the yield, growth rate, biomass and vigor of the plant.
As used herein the phrase “plant biomass” refers to the amount (e.g., measured in grams of air-dry tissue) of a tissue produced from the plant in a growing season, which could also determine or affect the plant yield or the yield per growing area. An increase in plant biomass can be in the whole plant or in parts thereof such as aboveground (harvestable) parts, vegetative biomass, roots and seeds.
As used herein the phrase “growth rate” refers to the increase in plant organ/tissue size per time (can be measured in cm2 per day).
As used herein the phrase “plant vigor” refers to the amount (measured by weight) of tissue produced by the plant in a given time. Hence increased vigor could determine or affect the plant yield or the yield per growing time or growing area. In addition, early vigor (seed and/or seedling) results in improved field stand.
Improving early vigor is an important objective of modern rice breeding programs in both temperate and tropical rice cultivars. Long roots are important for proper soil anchorage in water-seeded rice. Where rice is sown directly into flooded fields, and where plants must emerge rapidly through water, longer shoots are associated with vigour. Where drill-seeding is practiced, longer mesocotyls and coleoptiles are important for good seedling emergence. The ability to engineer early vigor into plants would be of great importance in agriculture. For example, poor early vigor has been a limitation to the introduction of maize (Zea mays L.) hybrids based on Corn Belt germplasm in the European Atlantic.
It should be noted that a plant yield can be determined under stress (e.g., abiotic stress, nitrogen-limiting conditions) and/or non-stress (normal) conditions.
As used herein, the phrase “non-stress conditions” refers to the growth conditions (e.g., water, temperature, light-dark cycles, humidity, salt concentration, fertilizer concentration in soil, nutrient supply such as nitrogen, phosphorous and/or potassium), that do not significantly go beyond the everyday climatic and other abiotic conditions that plants may encounter, and which allow optimal growth, metabolism, reproduction and/or viability of a plant at any stage in its life cycle (e.g., in a crop plant from seed to a mature plant and back to seed again). Persons skilled in the art are aware of normal soil conditions and climatic conditions for a given plant in a given geographic location. It should be noted that while the non-stress conditions may include some mild variations from the optimal conditions (which vary from one type/species of a plant to another), such variations do not cause the plant to cease growing without the capacity to resume growth.
The phrase “abiotic stress” as used herein refers to any adverse effect on metabolism, growth, reproduction and/or viability of a plant. Accordingly, abiotic stress can be induced by suboptimal environmental growth conditions such as, for example, salinity, water deprivation, flooding, freezing, low or high temperature, heavy metal toxicity, anaerobiosis, nutrient deficiency, atmospheric pollution or UV irradiation. The implications of abiotic stress are discussed in the Background section.
The phrase “abiotic stress tolerance” as used herein refers to the ability of a plant to endure an abiotic stress without suffering a substantial alteration in metabolism, growth, productivity and/or viability.
Plants are subject to a range of environmental challenges. Several of these, including salt stress, general osmotic stress, drought stress and freezing stress, have the ability to impact whole plant and cellular water availability. Not surprisingly, then, plant responses to this collection of stresses are related. Zhu (2002) Ann. Rev. Plant Biol. 53: 247-273 et al. note that “most studies on water stress signaling have focused on salt stress primarily because plant responses to salt and drought are closely related and the mechanisms overlap”. Many examples of similar responses and pathways to this set of stresses have been documented. For example, the CBF transcription factors have been shown to condition resistance to salt, freezing and drought (Kasuga et al. (1999) Nature Biotech. 17: 287-291). The Arabidopsis rd29B gene is induced in response to both salt and dehydration stress, a process that is mediated largely through an ABA signal transduction process (Uno et al. (2000) Proc. Natl. Acad. Sci. USA 97: 11632-11637), resulting in altered activity of transcription factors that bind to an upstream element within the rd29B promoter. In Mesembryanthemum crystallinum (ice plant), Patharker and Cushman have shown that a calcium-dependent protein kinase (McCDPK1) is induced by exposure to both drought and salt stresses (Patharker and Cushman (2000) Plant J. 24: 679-691). The stress-induced kinase was also shown to phosphorylate a transcription factor, presumably altering its activity, although transcript levels of the target transcription factor are not altered in response to salt or drought stress. Similarly, Saijo et al. demonstrated that a rice salt/drought-induced calmodulin-dependent protein kinase (OsCDPK7) conferred increased salt and drought tolerance to rice when overexpressed (Saijo et al. (2000) Plant J. 23: 319-327).
Exposure to dehydration invokes similar survival strategies in plants as does freezing stress (see, for example, Yelenosky (1989) Plant Physiol 89: 444-451) and drought stress induces freezing tolerance (see, for example, Siminovitch et al. (1982) Plant Physiol 69: 250-255; and Guy et al. (1992) Planta 188: 265-270). In addition to the induction of cold-acclimation proteins, strategies that allow plants to survive in low water conditions may include, for example, reduced surface area, or surface oil or wax production. In another example increased solute content of the plant prevents evaporation and water loss due to heat, drought, salinity, osmoticum, and the like therefore providing a better plant tolerance to the above stresses.
It will be appreciated that some pathways involved in resistance to one stress (as described above), will also be involved in resistance to other stresses, regulated by the same or homologous genes. Of course, the overall resistance pathways are related, not identical, and therefore not all genes controlling resistance to one stress will control resistance to the other stresses. Nonetheless, if a gene conditions resistance to one of these stresses, it would be apparent to one skilled in the art to test for resistance to these related stresses. Methods of assessing stress resistance are further provided in the Examples section which follows.
As used herein the phrase “water use efficiency (WUE)” refers to the level of organic matter produced per unit of water consumed by the plant, i.e., the dry weight of a plant in relation to the plant's water use, e.g., the biomass produced per unit transpiration.
As used herein the phrase “fertilizer use efficiency” refers to the metabolic process(es) which lead to an increase in the plant's yield, biomass, vigor, and growth rate per fertilizer unit applied. The metabolic process can be the uptake, spread, absorbent, accumulation, relocation (within the plant) and use of one or more of the minerals and organic moieties absorbed by the plant, such as nitrogen, phosphates and/or potassium.
As used herein the phrase “fertilizer-limiting conditions” refers to growth conditions which include a level (e.g., concentration) of a fertilizer applied which is below the level needed for normal plant metabolism, growth, reproduction and/or viability.
As used herein the phrase “nitrogen use efficiency (NUE)” refers to the metabolic process(es) which lead to an increase in the plant's yield, biomass, vigor, and growth rate per nitrogen unit applied. The metabolic process can be the uptake, spread, absorbent, accumulation, relocation (within the plant) and use of nitrogen absorbed by the plant.
As used herein the phrase “nitrogen-limiting conditions” refers to growth conditions which include a level (e.g., concentration) of nitrogen (e.g., ammonium or nitrate) applied which is below the level needed for normal plant metabolism, growth, reproduction and/or viability.
Improved plant NUE and FUE is translated in the field into either harvesting similar quantities of yield, while implementing less fertilizers, or increased yields gained by implementing the same levels of fertilizers. Thus, improved NUE or FUE has a direct effect on plant yield in the field. Thus, the polynucleotides and polypeptides of some embodiments of the invention positively affect plant yield, seed yield, and plant biomass. In addition, the benefit of improved plant NUE will certainly improve crop quality and biochemical constituents of the seed such as protein yield and oil yield.
It should be noted that improved ABST will confer plants with improved vigor also under non-stress conditions, resulting in crops having improved biomass and/or yield e.g., elongated fibers for the cotton industry, higher oil content.
The term “fiber” is usually inclusive of thick-walled conducting cells such as vessels and tracheids and to fibrillar aggregates of many individual fiber cells. Hence, the term “fiber” refers to (a) thick-walled conducting and non-conducting cells of the xylem; (b) fibers of extraxylary origin, including those from phloem, bark, ground tissue, and epidermis; and (c) fibers from stems, leaves, roots, seeds, and flowers or inflorescences (such as those of Sorghum vulgare used in the manufacture of brushes and brooms).
Example of fiber producing plants, include, but are not limited to, agricultural crops such as cotton, silk cotton tree (Kapok, Ceiba pentandra), desert willow, creosote bush, winterfat, balsa, kenaf, roselle, jute, sisal abaca, flax, corn, sugar cane, hemp, ramie, kapok, coir, bamboo, Spanish moss and Agave spp. (e.g. sisal).
As used herein the phrase “fiber quality” refers to at least one fiber parameter which is agriculturally desired, or required in the fiber industry (further described hereinbelow). Examples of such parameters, include but are not limited to, fiber length, fiber strength, fiber fitness, fiber weight per unit length, maturity ratio and uniformity (further described hereinbelow.
Cotton fiber (lint) quality is typically measured according to fiber length, strength and fineness. Accordingly, the lint quality is considered higher when the fiber is longer, stronger and finer.
As used herein the phrase “fiber yield” refers to the amount or quantity of fibers produced from the fiber producing plant.
As used herein the term “increasing” refers to at least about 2%, at least about 3%, at least about 4%, at least about 5%, at least about 10%, at least about 15%, at least about 20%, at least about 30%, at least about 40%, at least about 50%, at least about 60%, at least about 70%, at least about 80%, increase in yield, seed yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of a plant as compared to a native plant [i.e., a plant not modified with the biomolecules (polynucleotide or polypeptides) of the invention, e.g., a non-transformed plant of the same species which is grown under the same (e.g., identical) growth conditions].
The phrase “expressing within the plant an exogenous polynucleotide” as used herein refers to upregulating the expression level of an exogenous polynucleotide within the plant by introducing the exogenous polynucleotide into a plant cell or plant and expressing by recombinant means, as further described herein below.
As used herein “expressing” refers to expression at the mRNA and optionally polypeptide level.
As used herein, the phrase “exogenous polynucleotide” refers to a heterologous nucleic acid sequence which may not be naturally expressed within the plant or which overexpression in the plant is desired. The exogenous polynucleotide may be introduced into the plant in a stable or transient manner, so as to produce a ribonucleic acid (RNA) molecule and/or a polypeptide molecule. It should be noted that the exogenous polynucleotide may comprise a nucleic acid sequence which is identical or partially homologous to an endogenous nucleic acid sequence of the plant.
The term “endogenous” as used herein refers to any polynucleotide or polypeptide which is present and/or naturally expressed within a plant or a cell thereof.
According to some embodiments of the invention, the exogenous polynucleotide of the invention comprises a nucleic acid sequence encoding a polypeptide having an amino acid sequence at least about 80%, at least about 81%, at least about 82%, at least about 83%, at least about 84%, at least about 85%, at least about 86%, at least about 87%, at least about 88%, at least about 89%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99%, or more say 100% homologous to the amino acid sequence selected from the group consisting of SEQ ID NOs: 480-812, 5174-7015, 7017-7021, 7024, 7026-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, 9143-9177.
Homologous sequences include both orthologous and paralogous sequences. The term “paralogous” relates to gene-duplications within the genome of a species leading to paralogous genes. The term “orthologous” relates to homologous genes in different organisms due to ancestral relationship.
One option to identify orthologues in monocot plant species is by performing a reciprocal blast search. This may be done by a first blast involving blasting the sequence-of-interest against any sequence database, such as the publicly available NCBI database which may be found at: Hypertext Transfer Protocol://World Wide Web (dot) ncbi (dot) nlm (dot) nih (dot) gov. If orthologues in rice were sought, the sequence-of-interest would be blasted against, for example, the 28,469 full-length cDNA clones from Oryza sativa Nipponbare available at NCBI. The blast results may be filtered. The full-length sequences of either the filtered results or the non-filtered results are then blasted back (second blast) against the sequences of the organism from which the sequence-of-interest is derived. The results of the first and second blasts are then compared. An orthologue is identified when the sequence resulting in the highest score (best hit) in the first blast identifies in the second blast the query sequence (the original sequence-of-interest) as the best hit. Using the same rational a paralogue (homolog to a gene in the same organism) is found. In case of large sequence families, the ClustalW program may be used [Hypertext Transfer Protocol://World Wide Web (dot) ebi (dot) ac (dot) uk/Tools/clustalw2/index (dot) html], followed by a neighbor-joining tree (Hypertext Transfer Protocol://en (dot) wikipedia (dot) org/wiki/Neighbor-joining) which helps visualizing the clustering.
Homology (e.g., percent homology, identity+similarity) can be determined using any homology comparison software computing a pairwise sequence alignment.
Identity (e.g., percent homology) can be determined using any homology comparison software, including for example, the BlastN software of the National Center of Biotechnology Information (NCBI) such as by using default parameters.
According to some embodiments of the invention, the identity is a global identity, i.e., an identity over the entire amino acid or nucleic acid sequences of the invention and not over portions thereof.
According to some embodiments of the invention, the term “homology” or “homologous” refers to identity of two or more nucleic acid sequences; or identity of two or more amino acid sequences; or the identity of an amino acid sequence to one or more nucleic acid sequence.
According to some embodiments of the invention, the homology is a global homology, i.e., an homology over the entire amino acid or nucleic acid sequences of the invention and not over portions thereof.
The degree of homology or identity between two or more sequences can be determined using various known sequence comparison tools. Following is a non-limiting description of such tools which can be used along with some embodiments of the invention.
Pairwise global alignment was defined by S. B. Needleman and C. D. Wunsch, “A general method applicable to the search of similarities in the amino acid sequence of two proteins” Journal of Molecular Biology, 1970, pages 443-53, volume 48).
For example, when starting from a polypeptide sequence and comparing to other polypeptide sequences, the EMBOSS-6.0.1 Needleman-Wunsch algorithm (available from http://emboss(dot)sourceforge(dot)net/apps/cvs/emboss/apps/needle(dot)htmlcan be used) to find the optimum alignment (including gaps) of two sequences along their entire length—a “Global alignment”. Default parameters for Needleman-Wunsch algorithm (EMBOSS-6.0.1) include: gapopen=10; gapextend=0.5; datafile=EBLOSUM62; brief=YES.
According to some embodiments of the invention, the parameters used with the EMBOSS-6.0.1 tool (for protein-protein comparison) include: gapopen=8; gapextend=2; datafile=EBLOSUM62; brief=YES.
According to some embodiments of the invention, the threshold used to determine homology using the EMBOSS-6.0.1 Needleman-Wunsch algorithm is 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100%.
When starting from a polypeptide sequence and comparing to polynucleotide sequences, the OneModel FramePlus algorithm (Halperin, E., Faigler, S. and Gill-More, R. (1999)—FramePlus: aligning DNA to protein sequences. Bioinformatics, 15, 867-873) (available from http://www(dot)biocceleration(dot)com/Products(dot)html) can be used with following default parameters: model=frame+_p2n.model mode=local.
According to some embodiments of the invention, the parameters used with the OneModel FramePlus algorithm are model=frame+_p2n.model, mode=qglobal.
According to some embodiments of the invention, the threshold used to determine homology using the OneModel FramePlus algorithm is 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100%.
When starting with a polynucleotide sequence and comparing to other polynucleotide sequences the EMBOSS-6.0.1 Needleman-Wunsch algorithm (available from http://emboss(dot)sourceforge(dot)net/apps/cvs/emboss/apps/needle(dot)html) can be used with the following default parameters: (EMBOSS-6.0.1) gapopen=10; gapextend=0.5; datafile=EDNAFULL; brief=YES.
According to some embodiments of the invention, the parameters used with the EMBOSS-6.0.1 Needleman-Wunsch algorithm are gapopen=10; gapextend=0.2; datafile=EDNAFULL; brief=YES.
According to some embodiments of the invention, the threshold used to determine homology using the EMBOSS-6.0.1 Needleman-Wunsch algorithm for comparison of polynucleotides with polynucleotides is 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100%.
According to some embodiment, determination of the degree of homology further requires employing the Smith-Waterman algorithm (for protein-protein comparison or nucleotide-nucleotide comparison).
Default parameters for GenCore 6.0 Smith-Waterman algorithm include: model=sw.model.
According to some embodiments of the invention, the threshold used to determine homology using the Smith-Waterman algorithm is 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100%.
According to some embodiments of the invention, the global homology is performed on sequences which are pre-selected by local homology to the polypeptide or polynucleotide of interest (e.g., 60% identity over 60% of the sequence length), prior to performing the global homology to the polypeptide or polynucleotide of interest (e.g., 80% global homology on the entire sequence). For example, homologous sequences are selected using the BLAST software with the Blastp and tBlastn algorithms as filters for the first stage, and the needle (EMBOSS package) or Frame+ algorithm alignment for the second stage. Local identity (Blast alignments) is defined with a very permissive cutoff—60% Identity on a span of 60% of the sequences lengths because it use as only a filter for the global alignment stage. The default filtering of the Blast package was not utilized (by setting the parameter “-F F”).
In the second stage, homologs were defined based on a global identity of at least 80% to the core gene polypeptide sequence.
According to some embodiments of the invention, two distinct forms for finding the optimal global alignment for protein or nucleotide sequences are used:
1. Between Two Proteins (Following the Blastp Filter):
EMBOSS-6.0.1 Needleman-Wunsch algorithm with the following modified parameters: gapopen=8 gapextend=2. The rest of the parameters are unchanged from the default options listed here:
Standard (Mandatory) Qualifiers:
2. Between a Protein Sequence and a Nucleotide Sequence (Following the tblastn Filter):
GenCore 6.0 OneModel application utilizing the Frame+ algorithm with the following parameters: model=frame+_p2n.model mode=qglobal -q=protein.sequence -db=nucleotide.sequence. The rest of the parameters are unchanged from the default options:
Usage:
According to some embodiments the homology is local homology or local identity.
Local alignments tools include, but are not limited to the BlastP, BlastN, BlastX or TBLASTN software of the National Center of Biotechnology Information (NCBI), FASTA, and the Smith-Waterman algorithm.
A tblastn search allows the comparison between a protein sequence to the six-frame translations of a nucleotide database. It can be a very productive way of finding homologous protein coding regions in unannotated nucleotide sequences such as expressed sequence tags (ESTs) and draft genome records (HTG), located in the BLAST databases est and htgs, respectively.
Default parameters for blastp include: Max target sequences: 100; Expected threshold: e−5; Word size: 3; Max matches in a query range: 0; Scoring parameters: Matrix—BLOSUM62; filters and masking: Filter—low complexity regions.
Local alignments tools, which can be used include, but are not limited to, the tBLASTX algorithm, which compares the six-frame conceptual translation products of a nucleotide query sequence (both strands) against a protein sequence database. Default parameters include: Max target sequences: 100; Expected threshold: 10; Word size: 3; Max matches in a query range: 0; Scoring parameters: Matrix—BLOSUM62; filters and masking: Filter—low complexity regions.
According to some embodiments of the invention, the exogenous polynucleotide of the invention encodes a polypeptide having an amino acid sequence at least about 80%, at least about 81%, at least about 82%, at least about 83%, at least about 84%, at least about 85%, at least about 86%, at least about 87%, at least about 88%, at least about 89%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99%, or more say 100% identical to the amino acid sequence selected from the group consisting of SEQ ID NOs: 480-812, 5174-7015, 7017-7021, 7024, 7026-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, 9143-9177.
According to some embodiments of the invention, the method of increasing yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of a plant, is effected by expressing within the plant an exogenous polynucleotide comprising a nucleic acid sequence encoding a polypeptide at least at least about 80%, at least about 81%, at least about 82%, at least about 83%, at least about 84%, at least about 85%, at least about 86%, at least about 87%, at least about 88%, at least about 89%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99%, or more say 100% identical to the amino acid sequence selected from the group consisting of SEQ ID NOs: 480-812, 5174-7015, 7017-7021, 7024, 7026-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, 9143-9177, thereby increasing the yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of the plant.
According to some embodiments of the invention, the exogenous polynucleotide encodes a polypeptide consisting of the amino acid sequence set forth by SEQ ID NO: 480-812, 5174-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, 9143-9176 or 9177.
According to an aspect of some embodiments of the invention, the method of increasing yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of a plant, is effected by expressing within the plant an exogenous polynucleotide comprising a nucleic acid sequence encoding a polypeptide comprising an amino acid sequence selected from the group consisting of SEQ ID NOs: 480-812, 5174-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, and 9143-9177, thereby increasing the yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of the plant.
According to an aspect of some embodiments of the invention, there is provided a method of increasing yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of a plant, comprising expressing within the plant an exogenous polynucleotide comprising a nucleic acid sequence encoding a polypeptide selected from the group consisting of SEQ ID NOs: 480-812, 5174-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, and 9143-9177, thereby increasing the yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of the plant.
According to some embodiments of the invention, the exogenous polynucleotide encodes a polypeptide consisting of the amino acid sequence set forth by SEQ ID NO: 480-812, 5174-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, 9143-9176 or 9177.
According to some embodiments of the invention the exogenous polynucleotide comprises a nucleic acid sequence which is at least about 80%, at least about 81%, at least about 82%, at least about 83%, at least about 84%, at least about 85%, at least about 86%, at least about 87%, at least about 88%, at least about 89%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99%, e.g., 100% identical to the nucleic acid sequence selected from the group consisting of SEQ ID NOs:1-479, 813-5173, 8511, 8513, 8515, 8517, 8519, 8521, 8523, and 9096-9142.
According to an aspect of some embodiments of the invention, there is provided a method of increasing yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of a plant, comprising expressing within the plant an exogenous polynucleotide comprising a nucleic acid sequence at least about 80%, at least about 81%, at least about 82%, at least about 83%, at least about 84%, at least about 85%, at least about 86%, at least about 87%, at least about 88%, at least about 89%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99%, e.g., 100% identical to the nucleic acid sequence selected from the group consisting of SEQ ID NOs: 1-479, 813-5173, 8511, 8513, 8515, 8517, 8519, 8521, 8523, and 9096-9142, thereby increasing the yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, abiotic stress tolerance, and/or nitrogen use efficiency of the plant.
According to some embodiments of the invention the exogenous polynucleotide is at least about 80%, at least about 81%, at least about 82%, at least about 83%, at least about 84%, at least about 85%, at least about 86%, at least about 87%, at least about 88%, at least about 89%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99%, e.g., 100% identical to the polynucleotide selected from the group consisting of SEQ ID NOs: 1-479, 813-5173, 8511, 8513, 8515, 8517, 8519, 8521, 8523, and 9096-9142.
According to some embodiments of the invention the exogenous polynucleotide is set forth by SEQ ID NO: 1-479, 813-5173, 8511, 8513, 8515, 8517, 8519, 8521, 8523, 9096-9141 or 9142.
According to some embodiments of the invention the exogenous polynucleotide is set forth by the nucleic acid sequence selected from the group consisting of SEQ ID NOs: 1-479, 813-5173, 8511, 8513, 8515, 8517, 8519, 8521, 8523, and 9096-9142.
As used herein the term “polynucleotide” refers to a single or double stranded nucleic acid sequence which is isolated and provided in the form of an RNA sequence, a complementary polynucleotide sequence (cDNA), a genomic polynucleotide sequence and/or a composite polynucleotide sequences (e.g., a combination of the above).
The term “isolated” refers to at least partially separated from the natural environment e.g., from a plant cell.
As used herein the phrase “complementary polynucleotide sequence” refers to a sequence, which results from reverse transcription of messenger RNA using a reverse transcriptase or any other RNA dependent DNA polymerase. Such a sequence can be subsequently amplified in vivo or in vitro using a DNA dependent DNA polymerase.
As used herein the phrase “genomic polynucleotide sequence” refers to a sequence derived (isolated) from a chromosome and thus it represents a contiguous portion of a chromosome.
As used herein the phrase “composite polynucleotide sequence” refers to a sequence, which is at least partially complementary and at least partially genomic. A composite sequence can include some exonal sequences required to encode the polypeptide of the present invention, as well as some intronic sequences interposing therebetween. The intronic sequences can be of any source, including of other genes, and typically will include conserved splicing signal sequences. Such intronic sequences may further include cis acting expression regulatory elements.
Nucleic acid sequences encoding the polypeptides of the present invention may be optimized for expression. Examples of such sequence modifications include, but are not limited to, an altered G/C content to more closely approach that typically found in the plant species of interest, and the removal of codons atypically found in the plant species commonly referred to as codon optimization.
The phrase “codon optimization” refers to the selection of appropriate DNA nucleotides for use within a structural gene or fragment thereof that approaches codon usage within the plant of interest. Therefore, an optimized gene or nucleic acid sequence refers to a gene in which the nucleotide sequence of a native or naturally occurring gene has been modified in order to utilize statistically-preferred or statistically-favored codons within the plant. The nucleotide sequence typically is examined at the DNA level and the coding region optimized for expression in the plant species determined using any suitable procedure, for example as described in Sardana et al. (1996, Plant Cell Reports 15:677-681). In this method, the standard deviation of codon usage, a measure of codon usage bias, may be calculated by first finding the squared proportional deviation of usage of each codon of the native gene relative to that of highly expressed plant genes, followed by a calculation of the average squared deviation. The formula used is: 1 SDCU=n=1 N [(Xn−Yn)/Yn] 2/N, where Xn refers to the frequency of usage of codon n in highly expressed plant genes, where Yn to the frequency of usage of codon n in the gene of interest and N refers to the total number of codons in the gene of interest. A Table of codon usage from highly expressed genes of dicotyledonous plants is compiled using the data of Murray et al. (1989, Nuc Acids Res. 17:477-498).
One method of optimizing the nucleic acid sequence in accordance with the preferred codon usage for a particular plant cell type is based on the direct use, without performing any extra statistical calculations, of codon optimization Tables such as those provided on-line at the Codon Usage Database through the NIAS (National Institute of Agrobiological Sciences) DNA bank in Japan (Hypertext Transfer Protocol://World Wide Web (dot) kazusa (dot) or (dot) jp/codon/). The Codon Usage Database contains codon usage tables for a number of different species, with each codon usage Table having been statistically determined based on the data present in Genbank.
By using the above Tables to determine the most preferred or most favored codons for each amino acid in a particular species (for example, rice), a naturally-occurring nucleotide sequence encoding a protein of interest can be codon optimized for that particular plant species. This is effected by replacing codons that may have a low statistical incidence in the particular species genome with corresponding codons, in regard to an amino acid, that are statistically more favored. However, one or more less-favored codons may be selected to delete existing restriction sites, to create new ones at potentially useful junctions (5′ and 3′ ends to add signal peptide or termination cassettes, internal sites that might be used to cut and splice segments together to produce a correct full-length sequence), or to eliminate nucleotide sequences that may negatively affect mRNA stability or expression.
The naturally-occurring encoding nucleotide sequence may already, in advance of any modification, contain a number of codons that correspond to a statistically-favored codon in a particular plant species. Therefore, codon optimization of the native nucleotide sequence may comprise determining which codons, within the native nucleotide sequence, are not statistically-favored with regards to a particular plant, and modifying these codons in accordance with a codon usage table of the particular plant to produce a codon optimized derivative. A modified nucleotide sequence may be fully or partially optimized for plant codon usage provided that the protein encoded by the modified nucleotide sequence is produced at a level higher than the protein encoded by the corresponding naturally occurring or native gene. Construction of synthetic genes by altering the codon usage is described in for example PCT Patent Application 93/07278.
According to some embodiments of the invention, the exogenous polynucleotide is a non-coding RNA.
As used herein the phrase ‘non-coding RNA” refers to an RNA molecule which does not encode an amino acid sequence (a polypeptide). Examples of such non-coding RNA molecules include, but are not limited to, an antisense RNA, a pre-miRNA (precursor of a microRNA), or a precursor of a Piwi-interacting RNA (piRNA).
Non-limiting examples of non-coding RNA polynucleotides are provided in SEQ ID NOs: 217, 218, 276, 277, 479, 928, 929, 930, 1045, 1876, 2326, 2374, 2375, 2451, 3045, 3046, 3053, 3200, 3208, 3212, 3217, 3223, 3227, 3298, 3394, 3427, 3428, 3463, 3464, 3572, 3573, 3574, 3575, 3581, 4017, 4064, 4065, 4066, 4068, 4071, 4073, 4075, 4076, 4078, 4409, 4413, 4415, 4420, 4422, 4425, 4426, 4428, 4429, 4430, 4439, 4442, 4443, 4461, 4465, 4466, 4470, 4475, 4480, 4481, 4482, 4493, 4496, 4557, 4564, 4568, 4644, 4692, 4693, 4694, 4698, 4699, 4700, 4701, 4702, 4703, 4704, 4705, 4707, 4716, 4722, 4726, 4730, 4736, 4744, 4746, 4747, 4753, 4760, 9100, 9104, 9109, 9112, 9116, 9118, 9124, 9129, 9130, 9133, 9134, and 9135.
Thus, the invention encompasses nucleic acid sequences described hereinabove; fragments thereof, sequences hybridizable therewith, sequences homologous thereto, sequences encoding similar polypeptides with different codon usage, altered sequences characterized by mutations, such as deletion, insertion or substitution of one or more nucleotides, either naturally occurring or man induced, either randomly or in a targeted fashion.
The invention provides an isolated polynucleotide comprising a nucleic acid sequence at least about 80%, at least about 81%, at least about 82%, at least about 83%, at least about 84%, at least about 85%, at least about 86%, at least about 87%, at least about 88%, at least about 89%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99%, e.g., 100% identical to the polynucleotide selected from the group consisting of SEQ ID NOs: 1-479, 813-5173, 8511, 8513, 8515, 8517, 8519, 8521, 8523, and 9096-9142.
According to some embodiments of the invention the nucleic acid sequence is capable of increasing yield, growth rate, vigor, biomass, oil content, fiber yield, fiber quality, nitrogen use efficiency, fertilizer use efficiency, abiotic stress tolerance and/or water use efficiency of a plant.
According to some embodiments of the invention the isolated polynucleotide comprising the nucleic acid sequence selected from the group consisting of SEQ ID NOs: 1-479, 813-5173, 8511, 8513, 8515, 8517, 8519, 8521, 8523, and 9096-9142.
According to some embodiments of the invention the isolated polynucleotide is set forth by SEQ ID NO: 1-479, 813-5173, 8511, 8513, 8515, 8517, 8519, 8521, 8523, 9096-9141 or 9142.
The invention provides an isolated polynucleotide comprising a nucleic acid sequence encoding a polypeptide which comprises an amino acid sequence at least about 80%, at least about 81%, at least about 82%, at least about 83%, at least about 84%, at least about 85%, at least about 86%, at least about 87%, at least about 88%, at least about 89%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99%, or more say 100% homologous to the amino acid sequence selected from the group consisting of SEQ ID NO: 480-812, 5174-7015, 7017-7021, 7024, 7026-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, 9143-9177.
According to some embodiments of the invention the amino acid sequence is capable of increasing yield, growth rate, vigor, biomass, oil content, fiber yield and/or quality, nitrogen use efficiency, fertilizer use efficiency, abiotic stress tolerance and/or water use efficiency of a plant.
The invention provides an isolated polynucleotide comprising a nucleic acid sequence encoding a polypeptide which comprises the amino acid sequence selected from the group consisting of SEQ ID NOs: 480-812, 5174-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, and 9143-9177.
According to an aspect of some embodiments of the invention, there is provided a nucleic acid construct comprising the isolated polynucleotide of the invention, and a promoter for directing transcription of the nucleic acid sequence in a host cell.
The invention provides an isolated polypeptide comprising an amino acid sequence at least about 80%, at least about 81%, at least about 82%, at least about 83%, at least about 84%, at least about 85%, at least about 86%, at least about 87%, at least about 88%, at least about 89%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99%, or more say 100% homologous to an amino acid sequence selected from the group consisting of SEQ ID NO: 480-812, 5174-7015, 7017-7021, 7024, 7026-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, 9143-9177.
According to some embodiments of the invention, the polypeptide comprising an amino acid sequence selected from the group consisting of SEQ ID NOs: 480-812, 5174-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, and 9143-9177.
According to some embodiments of the invention, the polypeptide is set forth by SEQ ID NO: 480-812, 5174-8510, 8512, 8514, 8516, 8518, 8520, 8522, 8524, 9143-9176 or 9177.
The invention also encompasses fragments of the above described polypeptides and polypeptides having mutations, such as deletions, insertions or substitutions of one or more amino acids, either naturally occurring or man induced, either randomly or in a targeted fashion.
The term “plant” as used herein encompasses whole plants, ancestors and progeny of the plants and plant parts, including seeds, shoots, stems, roots (including tubers), and plant cells, tissues and organs. The plant may be in any form including suspension cultures, embryos, meristematic regions, callus tissue, leaves, gametophytes, sporophytes, pollen, and microspores. Plants that are particularly useful in the methods of the invention include all plants which belong to the superfamily Viridiplantae, in particular monocotyledonous and dicotyledonous plants including a fodder or forage legume, ornamental plant, food crop, tree, or shrub selected from the list comprising Acacia spp., Acer spp., Actinidia spp., Aesculus spp., Agathis australis, Albizia amara, Alsophila tricolor, Andropogon spp., Arachis spp, Areca catechu, Astelia fragrans, Astragalus cicer, Baikiaea plurijuga, Betula spp., Brassica spp., Bruguiera gymnorrhiza, Burkea africana, Butea frondosa, Cadaba farinosa, Calliandra spp, Camellia sinensis, Canna indica, Capsicum spp., Cassia spp., Centroema pubescens, Chacoomeles spp., Cinnamomum cassia, Coffea arabica, Colophospermum mopane, Coronillia varia, Cotoneaster serotina, Crataegus spp., Cucumis spp., Cupressus spp., Cyathea dealbata, Cydonia oblonga, Cryptomeria japonica, Cymbopogon spp., Cynthea dealbata, Cydonia oblonga, Dalbergia monetaria, Davallia divaricata, Desmodium spp., Dicksonia squarosa, Dibeteropogon amplectens, Dioclea spp, Dolichos spp., Dorycnium rectum, Echinochloa pyramidalis, Ehraffia spp., Eleusine coracana, Eragrestis spp., Erythrina spp., Eucalypfus spp., Euclea schimperi, Eulalia vi/losa, Pagopyrum spp., Feijoa sellowlana, Fragaria spp., Flemingia spp, Freycinetia banksli, Geranium thunbergii, GinAgo biloba, Glycine javanica, Gliricidia spp, Gossypium hirsutum, Grevillea spp., Guibourtia coleosperma, Hedysarum spp., Hemaffhia altissima, Heteropogon contoffus, Hordeum vulgare, Hyparrhenia rufa, Hypericum erectum, Hypeffhelia dissolute, Indigo incamata, Iris spp., Leptarrhena pyrolifolia, Lespediza spp., Lettuca spp., Leucaena leucocephala, Loudetia simplex, Lotonus bainesli, Lotus spp., Macrotyloma axillare, Malus spp., Manihot esculenta, Medicago saliva, Metasequoia glyptostroboides, Musa sapientum, Nicotianum spp., Onobrychis spp., Ornithopus spp., Oryza spp., Peltophorum africanum, Pennisetum spp., Persea gratissima, Petunia spp., Phaseolus spp., Phoenix canariensis, Phormium cookianum, Photinia spp., Picea glauca, Pinus spp., Pisum sativam, Podocarpus totara, Pogonarthria fleckii, Pogonaffhria squarrosa, Populus spp., Prosopis cineraria, Pseudotsuga menziesii, Pterolobium stellatum, Pyrus communis, Quercus spp., Rhaphiolepsis umbellata, Rhopalostylis sapida, Rhus natalensis, Ribes grossularia, Ribes spp., Robinia pseudoacacia, Rosa spp., Rubus spp., Salix spp., Schyzachyrium sanguineum, Sciadopitys vefficillata, Sequoia sempervirens, Sequoiadendron giganteum, Sorghum bicolor, Spinacia spp., Sporobolus fimbriatus, Stiburus alopecuroides, Stylosanthos humilis, Tadehagi spp, Taxodium distichum, Themeda triandra, Trifolium spp., Triticum spp., Tsuga heterophylla, Vaccinium spp., Vicia spp., Vitis vinifera, Watsonia pyramidata, Zantedeschia aethiopica, Zea mays, amaranth, artichoke, asparagus, broccoli, Brussel sprouts, cabbage, canola, carrot, cauliflower, celery, collard greens, flax, kale, lentil, oilseed rape, okra, onion, potato, rice, soybean, straw, sugar beet, sugar cane, sunflower, tomato, squash tea, maize, wheat, barley, rye, oat, peanut, pea, lentil and alfalfa, cotton, rapeseed, canola, pepper, sunflower, tobacco, eggplant, eucalyptus, a tree, an ornamental plant, a perennial grass and a forage crop. Alternatively algae and other non-Viridiplantae can be used for the methods of the present invention.
According to some embodiments of the invention, the plant used by the method of the invention is a crop plant such as rice, maize, wheat, barley, peanut, potato, sesame, olive tree, palm oil, banana, soybean, sunflower, canola, sugarcane, alfalfa, millet, leguminosae (bean, pea), flax, lupinus, rapeseed, tobacco, poplar and cotton.
According to some embodiments of the invention the plant is a dicotyledonous plant.
According to some embodiments of the invention the plant is a monocotyledonous plant.
According to some embodiments of the invention, there is provided a plant cell exogenously expressing the polynucleotide of some embodiments of the invention, the nucleic acid construct of some embodiments of the invention and/or the polypeptide of some embodiments of the invention.
According to some embodiments of the invention, expressing the exogenous polynucleotide of the invention within the plant is effected by transforming one or more cells of the plant with the exogenous polynucleotide, followed by generating a mature plant from the transformed cells and cultivating the mature plant under conditions suitable for expressing the exogenous polynucleotide within the mature plant.
According to some embodiments of the invention, the transformation is effected by introducing to the plant cell a nucleic acid construct which includes the exogenous polynucleotide of some embodiments of the invention and at least one promoter for directing transcription of the exogenous polynucleotide in a host cell (a plant cell). Further details of suitable transformation approaches are provided hereinbelow.
As mentioned, the nucleic acid construct according to some embodiments of the invention comprises a promoter sequence and the isolated polynucleotide of the invention.
According to some embodiments of the invention, the isolated polynucleotide is operably linked to the promoter sequence.
A coding nucleic acid sequence is “operably linked” to a regulatory sequence (e.g., promoter) if the regulatory sequence is capable of exerting a regulatory effect on the coding sequence linked thereto.
As used herein, the term “promoter” refers to a region of DNA which lies upstream of the transcriptional initiation site of a gene to which RNA polymerase binds to initiate transcription of RNA. The promoter controls where (e.g., which portion of a plant) and/or when (e.g., at which stage or condition in the lifetime of an organism) the gene is expressed.
According to some embodiments of the invention, the promoter is heterologous to the isolated polynucleotide and/or to the host cell.
Any suitable promoter sequence can be used by the nucleic acid construct of the present invention. Preferably the promoter is a constitutive promoter, a tissue-specific, or an abiotic stress-inducible promoter.
According to some embodiments of the invention, the promoter is a plant promoter, which is suitable for expression of the exogenous polynucleotide in a plant cell.
Suitable constitutive promoters include, for example, CaMV 35S promoter [SEQ ID NO: 8525 (pQFNC); SEQ ID NO: 8526 (PJJ 35S from Brachypodium); SEQ ID NO:8527 (Odell et al., Nature 313:810-812, 1985)], Arabidopsis At6669 promoter (SEQ ID NO:8528; see PCT Publication No. WO04081173A2 or the new At6669 promoter (SEQ ID NO:8529); maize Ubi 1 (maize polyubiquitin-1, SEQ ID NO:8530; Christensen et al., Plant Sol. Biol. 18:675-689, 1992; Taylor et al., Plant Cell Rep 12:491-495, 1993); rice actin 1 (SEQ ID NO:8531, McElroy et al., Plant Cell 2:163-171, 1990); pEMU (Last et al., Theor. Appl. Genet. 81:581-588, 1991); CaMV 19S (Nilsson et al., Physiol. Plant 100:456-462, 1997); GOS2 (SEQ ID NO:8532, de Pater et al, Plant J November; 2(6):837-44, 1992); Ubi 1 promoter (SEQ ID NO:8533); RBCS promoter (SEQ ID NO:8534); Rice cyclophilin (Bucholz et al, Plant Mol Biol. 25(5):837-43, 1994); Maize H3 histone (Lepetit et al, Mol. Gen. Genet. 231: 276-285, 1992); Actin 2 (An et al, Plant J. 10(1); 107-121, 1996) and Synthetic Super MAS (Ni et al., The Plant Journal 7: 661-76, 1995). Other constitutive promoters include those in U.S. Pat. Nos. 5,659,026, 5,608,149; 5,608,144; 5,604,121; 5,569,597; 5,466,785; 5,399,680; 5,268,463; and 5,608,142.
Suitable tissue-specific promoters include, but not limited to, leaf-specific promoters [e.g., AT5G06690 (Thioredoxin) (high expression, SEQ ID NO:8535), AT5G61520 (AtSTP3) (low expression, SEQ ID NO:8536) described in Buttner et al 2000 Plant, Cell and Environment 23, 175-184, or the promoters described in Yamamoto et al., Plant J. 12:255-265, 1997; Kwon et al., Plant Physiol. 105:357-67, 1994; Yamamoto et al., Plant Cell Physiol. 35:773-778, 1994; Gotor et al., Plant J. 3:509-18, 1993; Orozco et al., Plant Mol. Biol. 23:1129-1138, 1993; and Matsuoka et al., Proc. Natl. Acad. Sci. USA 90:9586-9590, 1993; as well as Arabidopsis STP3 (AT5G61520) promoter (Buttner et al., Plant, Cell and Environment 23:175-184, 2000)], seed-preferred promoters [e.g., Napin (originated from Brassica napus which is characterized by a seed specific promoter activity; Stuitje A. R. et. al. Plant Biotechnology Journal 1 (4): 301-309; SEQ ID NO:8537 from seed specific genes (Simon, et al., Plant Mol. Biol. 5. 191, 1985; Scofield, et al., J. Biol. Chem. 262: 12202, 1987; Baszczynski, et al., Plant Mol. Biol. 14: 633, 1990), rice PG5a (U.S. Pat. No. 7,700,835), early seed development Arabidopsis BAN (SEQ ID NO:8538, US 2009/0031450 A1), late seed development Arabidopsis ABI3 (SEQ ID NO:8539) (Ng et al., Plant Molecular Biology 54: 25-38, 2004), Brazil Nut albumin (Pearson' et al., Plant Mol. Biol. 18: 235-245, 1992), legumin (Ellis, et al. Plant Mol. Biol. 10: 203-214, 1988), Glutelin (rice) (Takaiwa, et al., Mol. Gen. Genet. 208: 15-22, 1986; Takaiwa, et al., FEBS Letts. 221: 43-47, 1987), Zein (Matzke et al Plant Mol Biol, 143).323-32 1990), napA (Stalberg, et al, Planta 199: 515-519, 1996), Wheat SPA (Albanietal, Plant Cell, 9: 171-184, 1997), sunflower oleosin (Cummins, et al., Plant Mol. Biol. 19: 873-876, 1992)], endosperm specific promoters [e.g., wheat LMW and HMW, glutenin-1 (Thomas and Flavell, The Plant Cell 2:1171-1180, 1990; Mol Gen Genet 216:81-90, 1989; NAR 17:461-2), wheat a, b and g gliadins (EMBO3:1409-15, 1984), Barley ltrl promoter, barley B1, C, D hordein (Theor Appl Gen 98:1253-62, 1999; Plant J 4:343-55, 1993; Mol Gen Genet 250:750-60, 1996), Barley DOF (Mena et al, The Plant Journal, 116(1): 53-62, 1998), Biz2 (EP99106056.7), Barley SS2 (Guerin and Carbonero Plant Physiology 114: 1 55-62, 1997), wheat Tarp60 (Kovalchuk et al., Plant Mol Biol 71:81-98, 2009), barley D-hordein (D-Hor) and B-hordein (B-Hor) (Agnelo Furtado, Robert J. Henry and Alessandro Pellegrineschi (2009)], Synthetic promoter (Vicente-Carbajosa et al., Plant J. 13: 629-640, 1998), rice prolamin NRP33, rice -globulin Glb-1 (Wu et al, Plant Cell Physiology 39(8) 885-889, 1998), rice alpha-globulin REB/OHP-1 (Nakase et al. Plant Mol. Biol. 33: 513-S22, 1997), rice ADP-glucose PP (Trans Res 6:157-68, 1997), maize ESR gene family (Plant J 12:235-46, 1997), sorgum gamma-kafirin (PMB 32:1029-35, 1996)], embryo specific promoters [e.g., rice OSH1 (Sato et al, Proc. Natl. Acad. Sci. USA, 93: 8117-8122), KNOX (Postma-Haarsma of al, Plant Mol. Biol. 39:257-71, 1999), rice oleosin (Wu et at, J. Biochem., 123:386, 1998)], and flower-specific promoters [e.g., AtPRP4, chalene synthase (chsA) (Van der Meer, et al., Plant Mol. Biol. 15, 95-109, 1990), LAT52 (Twell et al Mol. Gen Genet. 217:240-245; 1989), Arabidopsis apetala-3 (Tilly et al., Development. 125:1647-57, 1998), Arabidopsis APETALA 1 (AT1G69120, AP1) (SEQ ID NO:8540) (Hempel et al., Development 124:3845-3853, 1997)], and root promoters [e.g., the ROOTP promoter [SEQ ID NO: 8541]; rice ExpB5 and barley ExpB1 promoters (Won et al. Mol. Cells 30: 369-376, 2010); arabidopsis monoterpene synthase (AT3G25820) promoter (Chen et al., Plant Phys 135:1956-66, 2004); arabidopsis Pho1 promoter (SEQ ID NO:8542, Hamburger et al., Plant Cell. 14: 889-902, 2002), which is also slightly induced Pi stress].
Suitable abiotic stress-inducible promoters include, but not limited to, salt-inducible promoters such as RD29A (Yamaguchi-Shinozalei et al., Mol. Gen. Genet. 236:331-340, 1993); drought-inducible promoters such as maize rab17 gene promoter (Pla et. al., Plant Mol. Biol. 21:259-266, 1993), maize rab28 gene promoter (Busk et. al., Plant J. 11:1285-1295, 1997) and maize Ivr2 gene promoter (Pelleschi et. al., Plant Mol. Biol. 39:373-380, 1999); heat-inducible promoters such as heat tomato hsp80-promoter from tomato (U.S. Pat. No. 5,187,267).
The nucleic acid construct of some embodiments of the invention can further include an appropriate selectable marker and/or an origin of replication. According to some embodiments of the invention, the nucleic acid construct utilized is a shuttle vector, which can propagate both in E. coli (wherein the construct comprises an appropriate selectable marker and origin of replication) and be compatible with propagation in cells. The construct according to the present invention can be, for example, a plasmid, a bacmid, a phagemid, a cosmid, a phage, a virus or an artificial chromosome.
The nucleic acid construct of some embodiments of the invention can be utilized to stably or transiently transform plant cells. In stable transformation, the exogenous polynucleotide is integrated into the plant genome and as such it represents a stable and inherited trait. In transient transformation, the exogenous polynucleotide is expressed by the cell transformed but it is not integrated into the genome and as such it represents a transient trait.
There are various methods of introducing foreign genes into both monocotyledonous and dicotyledonous plants (Potrykus, I., Annu. Rev. Plant. Physiol., Plant. Mol. Biol. (1991) 42:205-225; Shimamoto et al., Nature (1989) 338:274-276).
The principle methods of causing stable integration of exogenous DNA into plant genomic DNA include two main approaches:
(i) Agrobacterium-mediated gene transfer: Klee et al. (1987) Annu. Rev. Plant Physiol. 38:467-486; Klee and Rogers in Cell Culture and Somatic Cell Genetics of Plants, Vol. 6, Molecular Biology of Plant Nuclear Genes, eds. Schell, J., and Vasil, L. K., Academic Publishers, San Diego, Calif. (1989) p. 2-25; Gatenby, in Plant Biotechnology, eds. Kung, S. and Arntzen, C. J., Butterworth Publishers, Boston, Mass. (1989) p. 93-112.
(ii) Direct DNA uptake: Paszkowski et al., in Cell Culture and Somatic Cell Genetics of Plants, Vol. 6, Molecular Biology of Plant Nuclear Genes eds. Schell, J., and Vasil, L. K., Academic Publishers, San Diego, Calif. (1989) p. 52-68; including methods for direct uptake of DNA into protoplasts, Toriyama, K. et al. (1988) Bio/Technology 6:1072-1074. DNA uptake induced by brief electric shock of plant cells: Zhang et al. Plant Cell Rep. (1988) 7:379-384. Fromm et al. Nature (1986) 319:791-793. DNA injection into plant cells or tissues by particle bombardment, Klein et al. Bio/Technology (1988) 6:559-563; McCabe et al. Bio/Technology (1988) 6:923-926; Sanford, Physiol. Plant. (1990) 79:206-209; by the use of micropipette systems: Neuhaus et al., Theor. Appl. Genet. (1987) 75:30-36; Neuhaus and Spangenberg, Physiol. Plant. (1990) 79:213-217; glass fibers or silicon carbide whisker transformation of cell cultures, embryos or callus tissue, U.S. Pat. No. 5,464,765 or by the direct incubation of DNA with germinating pollen, DeWet et al. in Experimental Manipulation of Ovule Tissue, eds. Chapman, G. P. and Mantell, S. H. and Daniels, W. Longman, London, (1985) p. 197-209; and Ohta, Proc. Natl. Acad. Sci. USA (1986) 83:715-719.
The Agrobacterium system includes the use of plasmid vectors that contain defined DNA segments that integrate into the plant genomic DNA. Methods of inoculation of the plant tissue vary depending upon the plant species and the Agrobacterium delivery system. A widely used approach is the leaf disc procedure which can be performed with any tissue explant that provides a good source for initiation of whole plant differentiation. See, e.g., Horsch et al. in Plant Molecular Biology Manual A5, Kluwer Academic Publishers, Dordrecht (1988) p. 1-9. A supplementary approach employs the Agrobacterium delivery system in combination with vacuum infiltration. The Agrobacterium system is especially viable in the creation of transgenic dicotyledonous plants.
There are various methods of direct DNA transfer into plant cells. In electroporation, the protoplasts are briefly exposed to a strong electric field. In microinjection, the DNA is mechanically injected directly into the cells using very small micropipettes. In microparticle bombardment, the DNA is adsorbed on microprojectiles such as magnesium sulfate crystals or tungsten particles, and the microprojectiles are physically accelerated into cells or plant tissues.
Following stable transformation plant propagation is exercised. The most common method of plant propagation is by seed. Regeneration by seed propagation, however, has the deficiency that due to heterozygosity there is a lack of uniformity in the crop, since seeds are produced by plants according to the genetic variances governed by Mendelian rules. Basically, each seed is genetically different and each will grow with its own specific traits. Therefore, it is preferred that the transformed plant be produced such that the regenerated plant has the identical traits and characteristics of the parent transgenic plant. Therefore, it is preferred that the transformed plant be regenerated by micropropagation which provides a rapid, consistent reproduction of the transformed plants.
Micropropagation is a process of growing new generation plants from a single piece of tissue that has been excised from a selected parent plant or cultivar. This process permits the mass reproduction of plants having the preferred tissue expressing the fusion protein. The new generation plants which are produced are genetically identical to, and have all of the characteristics of, the original plant. Micropropagation allows mass production of quality plant material in a short period of time and offers a rapid multiplication of selected cultivars in the preservation of the characteristics of the original transgenic or transformed plant. The advantages of cloning plants are the speed of plant multiplication and the quality and uniformity of plants produced.
Micropropagation is a multi-stage procedure that requires alteration of culture medium or growth conditions between stages. Thus, the micropropagation process involves four basic stages: Stage one, initial tissue culturing; stage two, tissue culture multiplication; stage three, differentiation and plant formation; and stage four, greenhouse culturing and hardening. During stage one, initial tissue culturing, the tissue culture is established and certified contaminant-free. During stage two, the initial tissue culture is multiplied until a sufficient number of tissue samples are produced to meet production goals. During stage three, the tissue samples grown in stage two are divided and grown into individual plantlets. At stage four, the transformed plantlets are transferred to a greenhouse for hardening where the plants' tolerance to light is gradually increased so that it can be grown in the natural environment.
According to some embodiments of the invention, the transgenic plants are generated by transient transformation of leaf cells, meristematic cells or the whole plant.
Transient transformation can be effected by any of the direct DNA transfer methods described above or by viral infection using modified plant viruses.
Viruses that have been shown to be useful for the transformation of plant hosts include CaMV, Tobacco mosaic virus (TMV), brome mosaic virus (BMV) and Bean Common Mosaic Virus (BV or BCMV). Transformation of plants using plant viruses is described in U.S. Pat. No. 4,855,237 (bean golden mosaic virus; BGV), EP-A 67,553 (TMV), Japanese Published Application No. 63-14693 (TMV), EPA 194,809 (BV), EPA 278,667 (BV); and Gluzman, Y. et al., Communications in Molecular Biology: Viral Vectors, Cold Spring Harbor Laboratory, New York, pp. 172-189 (1988). Pseudovirus particles for use in expressing foreign DNA in many hosts, including plants are described in WO 87/06261.
According to some embodiments of the invention, the virus used for transient transformations is avirulent and thus is incapable of causing severe symptoms such as reduced growth rate, mosaic, ring spots, leaf roll, yellowing, streaking, pox formation, tumor formation and pitting. A suitable avirulent virus may be a naturally occurring avirulent virus or an artificially attenuated virus. Virus attenuation may be effected by using methods well known in the art including, but not limited to, sub-lethal heating, chemical treatment or by directed mutagenesis techniques such as described, for example, by Kurihara and Watanabe (Molecular Plant Pathology 4:259-269, 2003), Gal-on et al. (1992), Atreya et al. (1992) and Huet et al. (1994).
Suitable virus strains can be obtained from available sources such as, for example, the American Type culture Collection (ATCC) or by isolation from infected plants. Isolation of viruses from infected plant tissues can be effected by techniques well known in the art such as described, for example by Foster and Tatlor, Eds. “Plant Virology Protocols: From Virus Isolation to Transgenic Resistance (Methods in Molecular Biology (Humana Pr), Vol 81)”, Humana Press, 1998. Briefly, tissues of an infected plant believed to contain a high concentration of a suitable virus, preferably young leaves and flower petals, are ground in a buffer solution (e.g., phosphate buffer solution) to produce a virus infected sap which can be used in subsequent inoculations.
Construction of plant RNA viruses for the introduction and expression of non-viral exogenous polynucleotide sequences in plants is demonstrated by the above references as well as by Dawson, W. O. et al., Virology (1989) 172:285-292; Takamatsu et al. EMBO J. (1987) 6:307-311; French et al. Science (1986) 231:1294-1297; Takamatsu et al. FEBS Letters (1990) 269:73-76; and U.S. Pat. No. 5,316,931.
When the virus is a DNA virus, suitable modifications can be made to the virus itself. Alternatively, the virus can first be cloned into a bacterial plasmid for ease of constructing the desired viral vector with the foreign DNA. The virus can then be excised from the plasmid. If the virus is a DNA virus, a bacterial origin of replication can be attached to the viral DNA, which is then replicated by the bacteria. Transcription and translation of this DNA will produce the coat protein which will encapsidate the viral DNA. If the virus is an RNA virus, the virus is generally cloned as a cDNA and inserted into a plasmid. The plasmid is then used to make all of the constructions. The RNA virus is then produced by transcribing the viral sequence of the plasmid and translation of the viral genes to produce the coat protein(s) which encapsidate the viral RNA.
In one embodiment, a plant viral polynucleotide is provided in which the native coat protein coding sequence has been deleted from a viral polynucleotide, a non-native plant viral coat protein coding sequence and a non-native promoter, preferably the subgenomic promoter of the non-native coat protein coding sequence, capable of expression in the plant host, packaging of the recombinant plant viral polynucleotide, and ensuring a systemic infection of the host by the recombinant plant viral polynucleotide, has been inserted. Alternatively, the coat protein gene may be inactivated by insertion of the non-native polynucleotide sequence within it, such that a protein is produced. The recombinant plant viral polynucleotide may contain one or more additional non-native subgenomic promoters. Each non-native subgenomic promoter is capable of transcribing or expressing adjacent genes or polynucleotide sequences in the plant host and incapable of recombination with each other and with native subgenomic promoters. Non-native (foreign) polynucleotide sequences may be inserted adjacent the native plant viral subgenomic promoter or the native and a non-native plant viral subgenomic promoters if more than one polynucleotide sequence is included. The non-native polynucleotide sequences are transcribed or expressed in the host plant under control of the subgenomic promoter to produce the desired products.
In a second embodiment, a recombinant plant viral polynucleotide is provided as in the first embodiment except that the native coat protein coding sequence is placed adjacent one of the non-native coat protein subgenomic promoters instead of a non-native coat protein coding sequence.
In a third embodiment, a recombinant plant viral polynucleotide is provided in which the native coat protein gene is adjacent its subgenomic promoter and one or more non-native subgenomic promoters have been inserted into the viral polynucleotide. The inserted non-native subgenomic promoters are capable of transcribing or expressing adjacent genes in a plant host and are incapable of recombination with each other and with native subgenomic promoters. Non-native polynucleotide sequences may be inserted adjacent the non-native subgenomic plant viral promoters such that the sequences are transcribed or expressed in the host plant under control of the subgenomic promoters to produce the desired product.
In a fourth embodiment, a recombinant plant viral polynucleotide is provided as in the third embodiment except that the native coat protein coding sequence is replaced by a non-native coat protein coding sequence.
The viral vectors are encapsidated by the coat proteins encoded by the recombinant plant viral polynucleotide to produce a recombinant plant virus. The recombinant plant viral polynucleotide or recombinant plant virus is used to infect appropriate host plants. The recombinant plant viral polynucleotide is capable of replication in the host, systemic spread in the host, and transcription or expression of foreign gene(s) (exogenous polynucleotide) in the host to produce the desired protein.
Techniques for inoculation of viruses to plants may be found in Foster and Taylor, eds. “Plant Virology Protocols: From Virus Isolation to Transgenic Resistance (Methods in Molecular Biology (Humana Pr), Vol 81)”, Humana Press, 1998; Maramorosh and Koprowski, eds. “Methods in Virology” 7 vols, Academic Press, New York 1967-1984; Hill, S. A. “Methods in Plant Virology”, Blackwell, Oxford, 1984; Walkey, D. G. A. “Applied Plant Virology”, Wiley, New York, 1985; and Kado and Agrawa, eds. “Principles and Techniques in Plant Virology”, Van Nostrand-Reinhold, New York.
In addition to the above, the polynucleotide of the present invention can also be introduced into a chloroplast genome thereby enabling chloroplast expression.
A technique for introducing exogenous polynucleotide sequences to the genome of the chloroplasts is known. This technique involves the following procedures. First, plant cells are chemically treated so as to reduce the number of chloroplasts per cell to about one. Then, the exogenous polynucleotide is introduced via particle bombardment into the cells with the aim of introducing at least one exogenous polynucleotide molecule into the chloroplasts. The exogenous polynucleotides selected such that it is integratable into the chloroplast's genome via homologous recombination which is readily effected by enzymes inherent to the chloroplast. To this end, the exogenous polynucleotide includes, in addition to a gene of interest, at least one polynucleotide stretch which is derived from the chloroplast's genome. In addition, the exogenous polynucleotide includes a selectable marker, which serves by sequential selection procedures to ascertain that all or substantially all of the copies of the chloroplast genomes following such selection will include the exogenous polynucleotide. Further details relating to this technique are found in U.S. Pat. Nos. 4,945,050; and 5,693,507 which are incorporated herein by reference. A polypeptide can thus be produced by the protein expression system of the chloroplast and become integrated into the chloroplast's inner membrane.
For expression of a polypeptide-of-interest in a specific plant tissue or organelle, a signal peptide may be added to the coding sequence of the polypeptide. For example, a signal peptide for expression in a chloroplast of Arabidopsis is provided in SEQ ID NO:9178 (nucleic acid sequence) and SEQ ID NO:9179 (amino acid sequence). The sequence of the signal peptide may be introduced upstream of the coding sequence, e.g., by replacing the codon of the initiator methionine. For further description see Examples 1 and 12 of the Examples section which follows.
Since processes which increase yield, oil content, yield, seed yield, fiber yield, fiber quality, fiber length, growth rate, biomass, vigor, nitrogen use efficiency, fertilizer use efficiency, and/or abiotic stress tolerance of a plant can involve multiple genes acting additively or in synergy (see, for example, in Quesda et al., Plant Physiol. 130:951-063, 2002), the present invention also envisages expressing a plurality of exogenous polynucleotides in a single host plant to thereby achieve superior effect on yield, oil content, yield, seed yield, fiber yield, fiber quality, fiber length, growth rate, biomass, vigor, nitrogen use efficiency, fertilizer use efficiency, and/or abiotic stress tolerance of the plant.
Expressing a plurality of exogenous polynucleotides in a single host plant can be effected by co-introducing multiple nucleic acid constructs, each including a different exogenous polynucleotide, into a single plant cell. The transformed cell can then be regenerated into a mature plant using the methods described hereinabove.
Alternatively, expressing a plurality of exogenous polynucleotides in a single host plant can be effected by co-introducing into a single plant-cell a single nucleic-acid construct including a plurality of different exogenous polynucleotides. Such a construct can be designed with a single promoter sequence which can transcribe a polycistronic messenger RNA including all the different exogenous polynucleotide sequences. To enable co-translation of the different polypeptides encoded by the polycistronic messenger RNA, the polynucleotide sequences can be inter-linked via an internal ribosome entry site (IRES) sequence which facilitates translation of polynucleotide sequences positioned downstream of the IRES sequence. In this case, a transcribed polycistronic RNA molecule encoding the different polypeptides described above will be translated from both the capped 5′ end and the two internal IRES sequences of the polycistronic RNA molecule to thereby produce in the cell all different polypeptides. Alternatively, the construct can include several promoter sequences each linked to a different exogenous polynucleotide sequence.
The plant cell transformed with the construct including a plurality of different exogenous polynucleotides, can be regenerated into a mature plant, using the methods described hereinabove.
Alternatively, expressing a plurality of exogenous polynucleotides in a single host plant can be effected by introducing different nucleic acid constructs, including different exogenous polynucleotides, into a plurality of plants. The regenerated transformed plants can then be cross-bred and resultant progeny selected for superior abiotic stress tolerance, water use efficiency, fertilizer use efficiency, growth, biomass, yield and/or vigor traits, using conventional plant breeding techniques.
According to some embodiments of the invention, the method further comprising growing the plant expressing the exogenous polynucleotide under the abiotic stress.
Non-limiting examples of abiotic stress conditions include, salinity, drought, water deprivation, excess of water (e.g., flood, waterlogging), etiolation, low temperature (e.g., cold stress), high temperature, heavy metal toxicity, anaerobiosis, nutrient deficiency, nutrient excess, atmospheric pollution and UV irradiation.
According to some embodiments of the invention, the method further comprising growing the plant expressing the exogenous polynucleotide under fertilizer limiting conditions (e.g., nitrogen-limiting conditions). Non-limiting examples include growing the plant on soils with low nitrogen content (40-50% Nitrogen of the content present under normal or optimal conditions), or even under sever nitrogen deficiency (0-10% Nitrogen of the content present under normal or optimal conditions).
Thus, the invention encompasses plants exogenously expressing the polynucleotide(s), the nucleic acid constructs and/or polypeptide(s) of the invention.
Once expressed within the plant cell or the entire plant, the level of the polypeptide encoded by the exogenous polynucleotide can be determined by methods well known in the art such as, activity assays, Western blots using antibodies capable of specifically binding the polypeptide, Enzyme-Linked Immuno Sorbent Assay (ELISA), radio-immuno-assays (RIA), immunohistochemistry, immunocytochemistry, immunofluorescence and the like.
Methods of determining the level in the plant of the RNA transcribed from the exogenous polynucleotide are well known in the art and include, for example, Northern blot analysis, reverse transcription polymerase chain reaction (RT-PCR) analysis (including quantitative, semi-quantitative or real-time RT-PCR) and RNA-in situ hybridization.
The sequence information and annotations uncovered by the present teachings can be harnessed in favor of classical breeding. Thus, sub-sequence data of those polynucleotides described above, can be used as markers for marker assisted selection (MAS), in which a marker is used for indirect selection of a genetic determinant or determinants of a trait of interest (e.g., biomass, growth rate, oil content, yield, abiotic stress tolerance, water use efficiency, nitrogen use efficiency and/or fertilizer use efficiency). Nucleic acid data of the present teachings (DNA or RNA sequence) may contain or be linked to polymorphic sites or genetic markers on the genome such as restriction fragment length polymorphism (RFLP), microsatellites and single nucleotide polymorphism (SNP), DNA fingerprinting (DFP), amplified fragment length polymorphism (AFLP), expression level polymorphism, polymorphism of the encoded polypeptide and any other polymorphism at the DNA or RNA sequence.
Examples of marker assisted selections include, but are not limited to, selection for a morphological trait (e.g., a gene that affects form, coloration, male sterility or resistance such as the presence or absence of awn, leaf sheath coloration, height, grain color, aroma of rice); selection for a biochemical trait (e.g., a gene that encodes a protein that can be extracted and observed; for example, isozymes and storage proteins); selection for a biological trait (e.g., pathogen races or insect biotypes based on host pathogen or host parasite interaction can be used as a marker since the genetic constitution of an organism can affect its susceptibility to pathogens or parasites).
The polynucleotides and polypeptides described hereinabove can be used in a wide range of economical plants, in a safe and cost effective manner.
Plant lines exogenously expressing the polynucleotide or the polypeptide of the invention are screened to identify those that show the greatest increase of the desired plant trait.
Thus, according to an additional embodiment of the present invention, there is provided a method of evaluating a trait of a plant, the method comprising: (a) expressing in a plant or a portion thereof the nucleic acid construct of some embodiments of the invention; and (b) evaluating a trait of a plant as compared to a wild type plant of the same type (e.g., a plant not transformed with the claimed biomolecules); thereby evaluating the trait of the plant.
According to an aspect of some embodiments of the invention there is provided a method of growing a crop comprising seeding seeds and/or planting plantlets of a plant transformed with the exogenous polynucleotide of the invention, e.g., the polynucleotide which encodes the polypeptide of some embodiments of the invention, wherein the plant is derived from plants selected for at least one trait selected from the group consisting of increased abiotic stress tolerance, increased nitrogen use efficiency, increased biomass, increased growth rate, increased vigor, increased yield and increased fiber yield or quality as compared to a non-transformed plant.
The effect of the transgene (the exogenous polynucleotide encoding the polypeptide) on abiotic stress tolerance can be determined using known methods such as detailed below and in the Examples section which follows.
Abiotic stress tolerance—Transformed (i.e., expressing the transgene) and non-transformed (wild type) plants are exposed to an abiotic stress condition, such as water deprivation, suboptimal temperature (low temperature, high temperature), nutrient deficiency, nutrient excess, a salt stress condition, osmotic stress, heavy metal toxicity, anaerobiosis, atmospheric pollution and UV irradiation.
Salinity tolerance assay—Transgenic plants with tolerance to high salt concentrations are expected to exhibit better germination, seedling vigor or growth in high salt. Salt stress can be effected in many ways such as, for example, by irrigating the plants with a hyperosmotic solution, by cultivating the plants hydroponically in a hyperosmotic growth solution (e.g., Hoagland solution), or by culturing the plants in a hyperosmotic growth medium [e.g., 50% Murashige-Skoog medium (MS medium)]. Since different plants vary considerably in their tolerance to salinity, the salt concentration in the irrigation water, growth solution, or growth medium can be adjusted according to the specific characteristics of the specific plant cultivar or variety, so as to inflict a mild or moderate effect on the physiology and/or morphology of the plants (for guidelines as to appropriate concentration see, Bernstein and Kafkafi, Root Growth Under Salinity Stress In: Plant Roots, The Hidden Half 3rd ed. Waisel Y, Eshel A and Kafkafi U. (editors) Marcel Dekker Inc., New York, 2002, and reference therein).
For example, a salinity tolerance test can be performed by irrigating plants at different developmental stages with increasing concentrations of sodium chloride (for example 50 mM, 100 mM, 200 mM, 400 mM NaCl) applied from the bottom and from above to ensure even dispersal of salt. Following exposure to the stress condition the plants are frequently monitored until substantial physiological and/or morphological effects appear in wild type plants. Thus, the external phenotypic appearance, degree of wilting and overall success to reach maturity and yield progeny are compared between control and transgenic plants.
Quantitative parameters of tolerance measured include, but are not limited to, the average wet and dry weight, growth rate, leaf size, leaf coverage (overall leaf area), the weight of the seeds yielded, the average seed size and the number of seeds produced per plant. Transformed plants not exhibiting substantial physiological and/or morphological effects, or exhibiting higher biomass than wild-type plants, are identified as abiotic stress tolerant plants.
Osmotic tolerance test—Osmotic stress assays (including sodium chloride and mannitol assays) are conducted to determine if an osmotic stress phenotype was sodium chloride-specific or if it was a general osmotic stress related phenotype. Plants which are tolerant to osmotic stress may have more tolerance to drought and/or freezing. For salt and osmotic stress germination experiments, the medium is supplemented for example with 50 mM, 100 mM, 200 mM NaCl or 100 mM, 200 mM NaCl, 400 mM mannitol.
Drought tolerance assay/osmoticum assay—Tolerance to drought is performed to identify the genes conferring better plant survival after acute water deprivation. To analyze whether the transgenic plants are more tolerant to drought, an osmotic stress produced by the non-ionic osmolyte sorbitol in the medium can be performed. Control and transgenic plants are germinated and grown in plant-agar plates for 4 days, after which they are transferred to plates containing 500 mM sorbitol. The treatment causes growth retardation, then both control and transgenic plants are compared, by measuring plant weight (wet and dry), yield, and by growth rates measured as time to flowering.
Conversely, soil-based drought screens are performed with plants overexpressing the polynucleotides detailed above. Seeds from control Arabidopsis plants, or other transgenic plants overexpressing the polypeptide of the invention are germinated and transferred to pots. Drought stress is obtained after irrigation is ceased accompanied by placing the pots on absorbent paper to enhance the soil-drying rate. Transgenic and control plants are compared to each other when the majority of the control plants develop severe wilting. Plants are re-watered after obtaining a significant fraction of the control plants displaying a severe wilting. Plants are ranked comparing to controls for each of two criteria: tolerance to the drought conditions and recovery (survival) following re-watering.
Cold stress tolerance—To analyze cold stress, mature (25 day old) plants are transferred to 4° C. chambers for 1 or 2 weeks, with constitutive light. Later on plants are moved back to greenhouse. Two weeks later damages from chilling period, resulting in growth retardation and other phenotypes, are compared between both control and transgenic plants, by measuring plant weight (wet and dry), and by comparing growth rates measured as time to flowering, plant size, yield, and the like.
Heat stress tolerance—Heat stress tolerance is achieved by exposing the plants to temperatures above 34° C. for a certain period. Plant tolerance is examined after transferring the plants back to 22° C. for recovery and evaluation after 5 days relative to internal controls (non-transgenic plants) or plants not exposed to neither cold or heat stress.
Water use efficiency—can be determined as the biomass produced per unit transpiration. To analyze WUE, leaf relative water content can be measured in control and transgenic plants. Fresh weight (FW) is immediately recorded; then leaves are soaked for 8 hours in distilled water at room temperature in the dark, and the turgid weight (TW) is recorded. Total dry weight (DW) is recorded after drying the leaves at 60° C. to a constant weight. Relative water content (RWC) is calculated according to the following Formula I:
RWC=[(FW−DW)/(TW−DW)]×100 Formula I
Fertilizer use efficiency—To analyze whether the transgenic plants are more responsive to fertilizers, plants are grown in agar plates or pots with a limited amount of fertilizer, as described, for example, in Yanagisawa et al (Proc Natl Acad Sci USA. 2004; 101:7833-8). The plants are analyzed for their overall size, time to flowering, yield, protein content of shoot and/or grain. The parameters checked are the overall size of the mature plant, its wet and dry weight, the weight of the seeds yielded, the average seed size and the number of seeds produced per plant. Other parameters that may be tested are: the chlorophyll content of leaves (as nitrogen plant status and the degree of leaf verdure is highly correlated), amino acid and the total protein content of the seeds or other plant parts such as leaves or shoots, oil content, etc. Similarly, instead of providing nitrogen at limiting amounts, phosphate or potassium can be added at increasing concentrations. Again, the same parameters measured are the same as listed above. In this way, nitrogen use efficiency (NUE), phosphate use efficiency (PUE) and potassium use efficiency (KUE) are assessed, checking the ability of the transgenic plants to thrive under nutrient restraining conditions.
Nitrogen use efficiency—To analyze whether the transgenic plants (e.g., Arabidopsis plants) are more responsive to nitrogen, plant are grown in 0.75-3 mM (nitrogen deficient conditions) or 6-10 mM (optimal nitrogen concentration). Plants are allowed to grow for additional 25 days or until seed production. The plants are then analyzed for their overall size, time to flowering, yield, protein content of shoot and/or grain/seed production. The parameters checked can be the overall size of the plant, wet and dry weight, the weight of the seeds yielded, the average seed size and the number of seeds produced per plant. Other parameters that may be tested are: the chlorophyll content of leaves (as nitrogen plant status and the degree of leaf greenness is highly correlated), amino acid and the total protein content of the seeds or other plant parts such as leaves or shoots and oil content. Transformed plants not exhibiting substantial physiological and/or morphological effects, or exhibiting higher measured parameters levels than wild-type plants, are identified as nitrogen use efficient plants.
Nitrogen use efficiency assay using plantlets—The assay is done according to Yanagisawa-S. et al. with minor modifications (“Metabolic engineering with Dof1 transcription factor in plants: Improved nitrogen assimilation and growth under low-nitrogen conditions” Proc. Natl. Acad. Sci. USA 101, 7833-7838). Briefly, transgenic plants which are grown for 7-10 days in 0.5×MS [Murashige-Skoog] supplemented with a selection agent are transferred to two nitrogen-limiting conditions: MS media in which the combined nitrogen concentration (NH4NO3 and KNO3) was 0.75 mM (nitrogen deficient conditions) or 6-15 mM (optimal nitrogen concentration). Plants are allowed to grow for additional 30-40 days and then photographed, individually removed from the Agar (the shoot without the roots) and immediately weighed (fresh weight) for later statistical analysis. Constructs for which only T1 seeds are available are sown on selective media and at least 20 seedlings (each one representing an independent transformation event) are carefully transferred to the nitrogen-limiting media. For constructs for which T2 seeds are available, different transformation events are analyzed. Usually, 20 randomly selected plants from each event are transferred to the nitrogen-limiting media allowed to grow for 3-4 additional weeks and individually weighed at the end of that period. Transgenic plants are compared to control plants grown in parallel under the same conditions. Mock-transgenic plants expressing the uidA reporter gene (GUS) under the same promoter or transgenic plants carrying the same promoter but lacking a reporter gene are used as control.
Nitrogen Determination—The procedure for N (nitrogen) concentration determination in the structural parts of the plants involves the potassium persulfate digestion method to convert organic N to NO3− (Purcell and King 1996 Argon. J. 88:111-113, the modified Cd− mediated reduction of NO3− to NO2− (Vodovotz 1996 Biotechniques 20:390-394) and the measurement of nitrite by the Griess assay (Vodovotz 1996, supra). The absorbance values are measured at 550 nm against a standard curve of NaNO2. The procedure is described in details in Samonte et al. 2006 Agron. J. 98:168-176.
Germination tests—Germination tests compare the percentage of seeds from transgenic plants that could complete the germination process to the percentage of seeds from control plants that are treated in the same manner. Normal conditions are considered for example, incubations at 22° C. under 22-hour light 2-hour dark daily cycles. Evaluation of germination and seedling vigor is conducted between 4 and 14 days after planting. The basal media is 50% MS medium (Murashige and Skoog, 1962 Plant Physiology 15, 473-497).
Germination is checked also at unfavorable conditions such as cold (incubating at temperatures lower than 10° C. instead of 22° C.) or using seed inhibition solutions that contain high concentrations of an osmolyte such as sorbitol (at concentrations of 50 mM, 100 mM, 200 mM, 300 mM, 500 mM, and up to 1000 mM) or applying increasing concentrations of salt (of 50 mM, 100 mM, 200 mM, 300 mM, 500 mM NaCl).
The effect of the transgene on plant's vigor, growth rate, biomass, yield and/or oil content can be determined using known methods.
Plant Vigor—The plant vigor can be calculated by the increase in growth parameters such as leaf area, fiber length, rosette diameter, plant fresh weight and the like per time.
Growth rate—The growth rate can be measured using digital analysis of growing plants. For example, images of plants growing in greenhouse on plot basis can be captured every 3 days and the rosette area can be calculated by digital analysis. Rosette area growth is calculated using the difference of rosette area between days of sampling divided by the difference in days between samples.
Evaluation of growth rate can be done by measuring plant biomass produced, rosette area, leaf size or root length per time (can be measured in cm2 per day of leaf area).
Relative growth area can be calculated using Formula II.
Relative growth rate area=Regression coefficient of area along time course Formula II
Thus, the relative growth area rate is in units of 1/day and length growth rate is in units of 1/day.
Seed yield—Evaluation of the seed yield per plant can be done by measuring the amount (weight or size) or quantity (i.e., number) of dry seeds produced and harvested from 8-16 plants and divided by the number of plants.
For example, the total seeds from 8-16 plants can be collected, weighted using e.g., an analytical balance and the total weight can be divided by the number of plants. Seed yield per growing area can be calculated in the same manner while taking into account the growing area given to a single plant. Increase seed yield per growing area could be achieved by increasing seed yield per plant, and/or by increasing number of plants capable of growing in a given area.
In addition, seed yield can be determined via the weight of 1000 seeds. The weight of 1000 seeds can be determined as follows: seeds are scattered on a glass tray and a picture is taken. Each sample is weighted and then using the digital analysis, the number of seeds in each sample is calculated.
The 1000 seeds weight can be calculated using formula III:
1000 Seed Weight=number of seed in sample/sample weight×1000 Formula III
The Harvest Index can be calculated using Formula IV
Harvest Index=Average seed yield per plant/Average dry weight Formula IV
Grain protein concentration—Grain protein content (g grain protein m−2) is estimated as the product of the mass of grain N (g grain N m−2) multiplied by the N/protein conversion ratio of k-5.13 (Mosse 1990, supra). The grain protein concentration is estimated as the ratio of grain protein content per unit mass of the grain (g grain protein kg−1 grain).
Fiber length—Fiber length can be measured using fibrograph. The fibrograph system was used to compute length in terms of “Upper Half Mean” length. The upper half mean (UHM) is the average length of longer half of the fiber distribution. The fibrograph measures length in span lengths at a given percentage point (Hypertext Transfer Protocol://World Wide Web (dot) cottoninc (dot) com/ClassificationofCotton/?Pg=4# Length).
According to some embodiments of the invention, increased yield of corn may be manifested as one or more of the following: increase in the number of plants per growing area, increase in the number of ears per plant, increase in the number of rows per ear, number of kernels per ear row, kernel weight, thousand kernel weight (1000-weight), ear length/diameter, increase oil content per kernel and increase starch content per kernel.
As mentioned, the increase of plant yield can be determined by various parameters. For example, increased yield of rice may be manifested by an increase in one or more of the following: number of plants per growing area, number of panicles per plant, number of spikelets per panicle, number of flowers per panicle, increase in the seed filling rate, increase in thousand kernel weight (1000-weight), increase oil content per seed, increase starch content per seed, among others. An increase in yield may also result in modified architecture, or may occur because of modified architecture.
Similarly, increased yield of soybean may be manifested by an increase in one or more of the following: number of plants per growing area, number of pods per plant, number of seeds per pod, increase in the seed filling rate, increase in thousand seed weight (1000-weight), reduce pod shattering, increase oil content per seed, increase protein content per seed, among others. An increase in yield may also result in modified architecture, or may occur because of modified architecture.
Increased yield of canola may be manifested by an increase in one or more of the following: number of plants per growing area, number of pods per plant, number of seeds per pod, increase in the seed filling rate, increase in thousand seed weight (1000-weight), reduce pod shattering, increase oil content per seed, among others. An increase in yield may also result in modified architecture, or may occur because of modified architecture.
Increased yield of cotton may be manifested by an increase in one or more of the following: number of plants per growing area, number of bolls per plant, number of seeds per boll, increase in the seed filling rate, increase in thousand seed weight (1000-weight), increase oil content per seed, improve fiber length, fiber strength, among others. An increase in yield may also result in modified architecture, or may occur because of modified architecture.
Oil content—The oil content of a plant can be determined by extraction of the oil from the seed or the vegetative portion of the plant. Briefly, lipids (oil) can be removed from the plant (e.g., seed) by grinding the plant tissue in the presence of specific solvents (e.g., hexane or petroleum ether) and extracting the oil in a continuous extractor. Indirect oil content analysis can be carried out using various known methods such as Nuclear Magnetic Resonance (NMR) Spectroscopy, which measures the resonance energy absorbed by hydrogen atoms in the liquid state of the sample [See for example, Conway T F. and Earle F R., 1963, Journal of the American Oil Chemists' Society; Springer Berlin/Heidelberg, ISSN: 0003-021X (Print) 1558-9331 (Online)]; the Near Infrared (NI) Spectroscopy, which utilizes the absorption of near infrared energy (1100-2500 nm) by the sample; and a method described in WO/2001/023884, which is based on extracting oil a solvent, evaporating the solvent in a gas stream which forms oil particles, and directing a light into the gas stream and oil particles which forms a detectable reflected light.
Thus, the present invention is of high agricultural value for promoting the yield of commercially desired crops (e.g., biomass of vegetative organ such as poplar wood, or reproductive organ such as number of seeds or seed biomass).
Any of the transgenic plants described hereinabove or parts thereof may be processed to produce a feed, meal, protein or oil preparation, such as for ruminant animals.
The transgenic plants described hereinabove, which exhibit an increased oil content can be used to produce plant oil (by extracting the oil from the plant).
The plant oil (including the seed oil and/or the vegetative portion oil) produced according to the method of the invention may be combined with a variety of other ingredients. The specific ingredients included in a product are determined according to the intended use. Exemplary products include animal feed, raw material for chemical modification, biodegradable plastic, blended food product, edible oil, biofuel, cooking oil, lubricant, biodiesel, snack food, cosmetics, and fermentation process raw material. Exemplary products to be incorporated to the plant oil include animal feeds, human food products such as extruded snack foods, breads, as a food binding agent, aquaculture feeds, fermentable mixtures, food supplements, sport drinks, nutritional food bars, multi-vitamin supplements, diet drinks, and cereal foods.
According to some embodiments of the invention, the oil comprises a seed oil.
According to some embodiments of the invention, the oil comprises a vegetative portion oil (oil of the vegetative portion of the plant).
According to another embodiment of the present invention, there is provided a food or feed comprising the plants or a portion thereof of the present invention.
According to some embodiments of the invention, the plant cell forms a part of a plant.
As used herein the term “about” refers to ±10%.
The terms “comprises”, “comprising”, “includes”, “including”, “having” and their conjugates mean “including but not limited to”.
The term “consisting of” means “including and limited to”.
The term “consisting essentially of” means that the composition, method or structure may include additional ingredients, steps and/or parts, but only if the additional ingredients, steps and/or parts do not materially alter the basic and novel characteristics of the claimed composition, method or structure.
As used herein, the singular form “a”, “an” and “the” include plural references unless the context clearly dictates otherwise. For example, the term “a compound” or “at least one compound” may include a plurality of compounds, including mixtures thereof.
Throughout this application, various embodiments of this invention may be presented in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the invention. Accordingly, the description of a range should be considered to have specifically disclosed all the possible subranges as well as individual numerical values within that range. For example, description of a range such as from 1 to 6 should be considered to have specifically disclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numbers within that range, for example, 1, 2, 3, 4, 5, and 6. This applies regardless of the breadth of the range.
Whenever a numerical range is indicated herein, it is meant to include any cited numeral (fractional or integral) within the indicated range. The phrases “ranging/ranges between” a first indicate number and a second indicate number and “ranging/ranges from” a first indicate number “to” a second indicate number are used herein interchangeably and are meant to include the first and second indicated numbers and all the fractional and integral numerals therebetween.
As used herein the term “method” refers to manners, means, techniques and procedures for accomplishing a given task including, but not limited to, those manners, means, techniques and procedures either known to, or readily developed from known manners, means, techniques and procedures by practitioners of the chemical, pharmacological, biological, biochemical and medical arts.
It is appreciated that certain features of the invention, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the invention, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable subcombination or as suitable in any other described embodiment of the invention. Certain features described in the context of various embodiments are not to be considered essential features of those embodiments, unless the embodiment is inoperative without those elements.
Various embodiments and aspects of the present invention as delineated hereinabove and as claimed in the claims section below find experimental support in the following examples.
Reference is now made to the following examples, which together with the above descriptions illustrate some embodiments of the invention in a non limiting fashion.
Generally, the nomenclature used herein and the laboratory procedures utilized in the present invention include molecular, biochemical, microbiological and recombinant DNA techniques. Such techniques are thoroughly explained in the literature. See, for example, “Molecular Cloning: A laboratory Manual” Sambrook et al., (1989); “Current Protocols in Molecular Biology” Volumes I-III Ausubel, R. M., ed. (1994); Ausubel et al., “Current Protocols in Molecular Biology”, John Wiley and Sons, Baltimore, Md. (1989); Perbal, “A Practical Guide to Molecular Cloning”, John Wiley & Sons, New York (1988); Watson et al., “Recombinant DNA”, Scientific American Books, New York; Birren et al. (eds) “Genome Analysis: A Laboratory Manual Series”, Vols. 1-4, Cold Spring Harbor Laboratory Press, New York (1998); methodologies as set forth in U.S. Pat. Nos. 4,666,828; 4,683,202; 4,801,531; 5,192,659 and 5,272,057; “Cell Biology: A Laboratory Handbook”, Volumes I-III Cellis, J. E., ed. (1994); “Current Protocols in Immunology” Volumes I-III Coligan J. E., ed. (1994); Stites et al. (eds), “Basic and Clinical Immunology” (8th Edition), Appleton & Lange, Norwalk, Conn. (1994); Mishell and Shiigi (eds), “Selected Methods in Cellular Immunology”, W. H. Freeman and Co., New York (1980); available immunoassays are extensively described in the patent and scientific literature, see, for example, U.S. Pat. Nos. 3,791,932; 3,839,153; 3,850,752; 3,850,578; 3,853,987; 3,867,517; 3,879,262; 3,901,654; 3,935,074; 3,984,533; 3,996,345; 4,034,074; 4,098,876; 4,879,219; 5,011,771 and 5,281,521; “Oligonucleotide Synthesis” Gait, M. J., ed. (1984); “Nucleic Acid Hybridization” Hames, B. D., and Higgins S. J., eds. (1985); “Transcription and Translation” Hames, B. D., and Higgins S. J., Eds. (1984); “Animal Cell Culture” Freshney, R. I., ed. (1986); “Immobilized Cells and Enzymes” IRL Press, (1986); “A Practical Guide to Molecular Cloning” Perbal, B., (1984) and “Methods in Enzymology” Vol. 1-317, Academic Press; “PCR Protocols: A Guide To Methods And Applications”, Academic Press, San Diego, Calif. (1990); Marshak et al., “Strategies for Protein Purification and Characterization—A Laboratory Course Manual” CSHL Press (1996); all of which are incorporated by reference as if fully set forth herein. Other general references are provided throughout this document. The procedures therein are believed to be well known in the art and are provided for the convenience of the reader. All the information contained therein is incorporated herein by reference.
General Experimental and Bioinformatics Methods
RNA extraction—Tissues growing at various growth conditions (as described below) were sampled and RNA was extracted using TRIzol Reagent from Invitrogen [Hypertext Transfer Protocol://World Wide Web (dot) invitrogen (dot) com/content (dot)cfm?pageid=469]. Approximately 30-50 mg of tissue was taken from samples. The weighed tissues were ground using pestle and mortar in liquid nitrogen and resuspended in 500 μl of TRIzol Reagent. To the homogenized lysate, 100 μl of chloroform was added followed by precipitation using isopropanol and two washes with 75% ethanol. The RNA was eluted in 30 μl of RNase-free water. RNA samples were cleaned up using Qiagen's RNeasy minikit clean-up protocol as per the manufacturer's protocol (QIAGEN Inc, CA USA). For convenience, each micro-array expression information tissue type has received an expression Set ID.
Correlation analysis—was performed for selected genes according to some embodiments of the invention, in which the characterized parameters (measured parameters according to the correlation IDs) were used as “x axis” for correlation with the tissue transcriptome, which was used as the “Y axis”. For each gene and measured parameter a correlation coefficient “R” was calculated (using Pearson correlation) along with a p-value for the significance of the correlation. When the correlation coefficient (R) between the levels of a gene's expression in a certain tissue and a phenotypic performance across ecotypes/variety/hybrid is high in absolute value (between 0.5-1), there is an association between the gene (specifically the expression level of this gene) the phenotypic characteristic (e.g., improved yield, growth rate, nitrogen use efficiency, abiotic stress tolerance and the like).
The present inventors have identified polynucleotides which expression thereof in plants can increase yield, fiber yield, fiber quality, growth rate, vigor, biomass, growth rate, oil content, abiotic stress tolerance (ABST), fertilizer use efficiency (FUE) such as nitrogen use efficiency (NUE), and water use efficiency (WUE) of a plant, as follows.
All nucleotide sequence datasets used here were originated from publicly available databases or from performing sequencing using the Solexa technology (e.g. Barley and Sorghum). Sequence data from 100 different plant species was introduced into a single, comprehensive database. Other information on gene expression, protein annotation, enzymes and pathways were also incorporated.
Major databases used include:
Genomes
Expressed EST and mRNA Sequences were Extracted from the Following Databases:
Protein and Pathway Databases
Microarray Datasets were Downloaded from:
QTL and SNPs Information
Database assembly—was performed to build a wide, rich, reliable annotated and easy to analyze database comprised of publicly available genomic mRNA, ESTs DNA sequences, data from various crops as well as gene expression, protein annotation and pathway data QTLs, and other relevant information.
Database assembly is comprised of a toolbox of gene refining, structuring, annotation and analysis tools enabling to construct a tailored database for each gene discovery project. Gene refining and structuring tools enable to reliably detect splice variants and antisense transcripts, generating understanding of various potential phenotypic outcomes of a single gene. The capabilities of the “LEADS” platform of Compugen LTD for analyzing human genome have been confirmed and accepted by the scientific community [see e.g., “Widespread Antisense Transcription”, Yelin, et al. (2003) Nature Biotechnology 21, 379-85; “Splicing of Alu Sequences”, Lev-Maor, et al. (2003) Science 300 (5623), 1288-91; “Computational analysis of alternative splicing using EST tissue information”, Xie H et al. Genomics 2002], and have been proven most efficient in plant genomics as well.
EST clustering and gene assembly—For gene clustering and assembly of organisms with available genome sequence data (arabidopsis, rice, castorbean, grape, brachypodium, poplar, soybean, sorghum) the genomic LEADS version (GANG) was employed. This tool allows most accurate clustering of ESTs and mRNA sequences on genome, and predicts gene structure as well as alternative splicing events and anti-sense transcription.
For organisms with no available full genome sequence data, “expressed LEADS” clustering software was applied.
Gene annotation—Predicted genes and proteins were annotated as follows: Blast search [Hypertext Transfer Protocol://blast (dot) ncbi (dot) nlm (dot) nih (dot) gov/Blast (dot) cgi] against all plant UniProt [Hypertext Transfer Protocol://World Wide Web (dot) uniprot (dot) org/] sequences was performed. Open reading frames of each putative transcript were analyzed and longest ORF with higher number of homologues was selected as predicted protein of the transcript. The predicted proteins were analyzed by InterPro [Hypertext Transfer Protocol://World Wide Web (dot) ebi (dot) ac (dot) uk/interpro/].
Blast against proteins from AraCyc and ENZYME databases was used to map the predicted transcripts to AraCyc pathways.
Predicted proteins from different species were compared using blast algorithm [Hypertext Transfer Protocol://World Wide Web (dot) ncbi (dot) nlm (dot) nih (dot) gov /Blast (dot) cgi] to validate the accuracy of the predicted protein sequence, and for efficient detection of orthologs.
Gene expression profiling—Several data sources were exploited for gene expression profiling, namely microarray data and digital expression profile (see below). According to gene expression profile, a correlation analysis was performed to identify genes which are co-regulated under different development stages and environmental conditions and associated with different phenotypes.
Publicly available microarray datasets were downloaded from TAR and NCBI GEO sites, renormalized, and integrated into the database. Expression profiling is one of the most important resource data for identifying genes important for yield.
A digital expression profile summary was compiled for each cluster according to all keywords included in the sequence records comprising the cluster. Digital expression, also known as electronic Northern Blot, is a tool that displays virtual expression profile based on the EST sequences forming the gene cluster. The tool provides the expression profile of a cluster in terms of plant anatomy (e.g., the tissue/organ in which the gene is expressed), developmental stage (the developmental stages at which a gene can be found) and profile of treatment (provides the physiological conditions under which a gene is expressed such as drought, cold, pathogen infection, etc). Given a random distribution of ESTs in the different clusters, the digital expression provides a probability value that describes the probability of a cluster having a total of N ESTs to contain X ESTs from a certain collection of libraries. For the probability calculations, the following is taken into consideration: a) the number of ESTs in the cluster, b) the number of ESTs of the implicated and related libraries, c) the overall number of ESTs available representing the species. Thereby clusters with low probability values are highly enriched with ESTs from the group of libraries of interest indicating a specialized expression.
Recently, the accuracy of this system was demonstrated by Portnoy et al., 2009 (Analysis Of The Melon Fruit Transcriptome Based On 454 Pyrosequencing) in: Plant & Animal Genomes XVII Conference, San Diego, Calif. Transcriptomic analysis, based on relative EST abundance in data was performed by 454 pyrosequencing of cDNA representing mRNA of the melon fruit. Fourteen double strand cDNA samples obtained from two genotypes, two fruit tissues (flesh and rind) and four developmental stages were sequenced. GS FLX pyrosequencing (Roche/454 Life Sciences) of non-normalized and purified cDNA samples yielded 1,150,657 expressed sequence tags, that assembled into 67,477 unigenes (32,357 singletons and 35,120 contigs). Analysis of the data obtained against the Cucurbit Genomics Database [Hypertext Transfer Protocol://World Wide Web (dot) icugi (dot) org/] confirmed the accuracy of the sequencing and assembly. Expression patterns of selected genes fitted well their qRT-PCR (quantitative reverse transcription-polymerase chain reaction) data.
Overall, 228 genes (SEQ ID NOs: 1-277 and 8511, 8513, 8515, 8517, 8519, 8521 and 8523 for polynucleotides and SEQ ID NOs: 480-733, 8512, 8514, 8516, 8518, 8520, 8522 and 8524 for polypeptides) were identified to have a major impact on plant yield, growth rate, vigor, biomass, growth rate, oil content, fiber quality, fiber yield, abiotic stress tolerance, nitrogen use efficiency, water use efficiency and fertilizer use efficiency when expression thereof is increased in plants. The identified genes, their curated polynucleotide and polypeptide sequences, as well as their updated sequences according to Genbank database are summarized in Table 1, hereinbelow.
brachypodium|09v1|DV477501
brachypodium|09v1|DV485542
brachypodium|09v1|GT773244
brachypodium|09v1|GT805233
brachypodium|09v1|GT827944
sorghum|09v1|CD204441
sorghum|09v1|SB01G007070
sorghum|09v1|SB01G008550
sorghum|09v1|SB01G017160
sorghum|09v1|SB01G019510
sorghum|09v1|SB01G023260
sorghum|09v1|SB01G028930
sorghum|09v1|SB01G031740
sorghum|09v1|SB01G034070
sorghum|09v1|SB01G036360
sorghum|09v1|SB01G045110
sorghum|09v1|SB01G047160
sorghum|09v1|SB02G003520
sorghum|09v1|SB02G005780
sorghum|09v1|SB02G020880
sorghum|09v1|SB02G031600
sorghum|09v1|SB02G034560
sorghum|09v1|SB02G042910
sorghum|09v1|SB02G043760
sorghum|09v1|SB03G003100
sorghum|09v1|SB03G020183
sorghum|09v1|SB03G034280
sorghum|09v1|SB03G038270
sorghum|09v1|SB06G025710
sorghum|09v1|SB04G006450
sorghum|09v1|SB05G002380
sorghum|09v1|SB06G020280
sorghum|09v1|SB06G020440
sorghum|09v1|SB06G021190
sorghum|09v1|SB07G004900
sorghum|09v1|SB07G024936
sorghum|09v1|SB07G025570
sorghum|09v1|SB07G026090
sorghum|09v1|SB08G004193
sorghum|09v1|SB08G004400
sorghum|09v1|SB09G002700
sorghum|09v1|SB09G003280
sorghum|09v1|SB09G005930
sorghum|09v1|SB09G023380
sorghum|09v1|SB09G026280
sorghum|09v1|SB09G027995
sorghum|09v1|SB09G029480
sorghum|09v1|SB09G029660
sorghum|09v1|SB10G006950
sorghum|09v1|SB10G023320
sorghum|09v1|SB10G028690
sorghum|09v1|SLXL50035388D1
brachypodium|09v1|SRR031797S0088390
sorghum|09v1|SB03G035130
sorghum|09v1|SB04G006860
sorghum|09v1|SB10G008610
brachypodium|09v1|DV469171
brachypodium|09v1|GT773244
brachypodium|09v1|GT805233
brachypodium|09v1|GT827944
sorghum|09v1|CD204441
sorghum|09v1|SB01G008550
sorghum|09v1|SB01G028930
sorghum|09v1|SB02G003520
sorghum|09v1|SB02G005780
sorghum|09v1|SB02G020880
sorghum|09v1|SB03G047535
sorghum|09v1|SB04G006450
sorghum|09v1|SB07G004900
sorghum|09v1|SB08G004193
sorghum|09v1|SB09G023380
sorghum|09v1|SB09G029480
sorghum|09v1|SLXL50035388D1
brachypodium|09v1|SRR031797S0088390
sorghum|09v1|SB10G008610
brachypodium|09v1|DV469171
sorghum|09v1|SB08G004193
sorghum|09v1|SB08G004193
The concepts of orthology and paralogy have recently been applied to functional characterizations and classifications on the scale of whole-genome comparisons. Orthologs and paralogs constitute two major types of homologues: The first evolved from a common ancestor by specialization, and the latter are related by duplication events. It is assumed that paralogs arising from ancient duplication events are likely to have diverged in function while true orthologs are more likely to retain identical function over evolutionary time.
To further investigate and identify putative orthologs of the genes affecting plant yield, oil yield, oil content, seed yield, growth rate, vigor, biomass, fiber yield, fiber quality, abiotic stress tolerance, and fertilizer use efficiency (FUE) genes and/or nitrogen use efficiency, all sequences were aligned using the BLAST (Basic Local Alignment Search Tool). Sequences sufficiently similar were tentatively grouped. These putative orthologs were further organized under a Phylogram—a branching diagram (tree) assumed to be a representation of the evolutionary relationships among the biological taxa. Putative ortholog groups were analyzed as to their agreement with the phylogram and in cases of disagreements these ortholog groups were broken accordingly.
Expression data was analyzed and the EST libraries were classified using a fixed vocabulary of custom terms such as developmental stages (e.g., genes showing similar expression profile through development with up regulation at specific stage, such as at the seed filling stage) and/or plant organ (e.g., genes showing similar expression profile across their organs with up regulation at specific organs such as seed). The annotations from all the ESTs clustered to a gene were analyzed statistically by comparing their frequency in the cluster versus their abundance in the database, allowing the construction of a numeric and graphic expression profile of that gene, which is termed “digital expression”. The rationale of using these two complementary methods with methods of phenotypic association studies of QTLs, SNPs and phenotype expression correlation is based on the assumption that true orthologs are likely to retain identical function over evolutionary time. These methods provide different sets of indications on function similarities between two homologous genes, similarities in the sequence level -identical amino acids in the protein domains and similarity in expression profiles.
The search and identification of homologous genes involves the screening of sequence information available, for example, in public databases such as the DNA Database of Japan (DDBJ), Genbank, and the European Molecular Biology Laboratory Nucleic Acid Sequence Database (EMBL) or versions thereof or the MIPS database. A number of different search algorithms have been developed, including but not limited to the suite of programs referred to as BLAST programs. There are five implementations of BLAST, three designed for nucleotide sequence queries (BLASTN, BLASTX, and TBLASTX) and two designed for protein sequence queries (BLASTP and TBLASTN) (Coulson, Trends in Biotechnology: 76-80, 1994; Birren et al., Genome Analysis, I: 543, 1997). Such methods involve alignment and comparison of sequences. The BLAST algorithm calculates percent sequence identity and performs a statistical analysis of the similarity between the two sequences. The software for performing BLAST analysis is publicly available through the National Centre for Biotechnology Information. Other such software or algorithms are GAP, BESTFIT, FASTA and TFASTA. GAP uses the algorithm of Needleman and Wunsch (J. Mol. Biol. 48: 443-453, 1970) to find the alignment of two complete sequences that maximizes the number of matches and minimizes the number of gaps.
The homologous genes may belong to the same gene family. The analysis of a gene family may be carried out using sequence similarity analysis. To perform this analysis one may use standard programs for multiple alignments e.g. Clustal W. A neighbour-joining tree of the proteins homologous to the genes in this invention may be used to provide an overview of structural and ancestral relationships. Sequence identity may be calculated using an alignment program as described above. It is expected that other plants will carry a similar functional gene (ortholog) or a family of similar genes and those genes will provide the same preferred phenotype as the genes presented here. Advantageously, these family members may be useful in the methods of the invention. Example of other plants are included here but not limited to, barley (Hordeum vulgare), Arabidopsis (Arabidopsis thaliana), maize (Zea mays), cotton (Gossypium), Oilseed rape (Brassica napus), Rice (Oryza sativa), Sugar cane (Saccharum officinarum), Sorghum (Sorghum bicolor), Soybean (Glycine max), Sunflower (Helianthus annuus), Tomato (Lycopersicon esculentum), and Wheat (Triticum aestivum).
The above-mentioned analyses for sequence homology can be carried out on a full-length sequence, but may also be based on a comparison of certain regions such as conserved domains. The identification of such domains, would also be well within the realm of the person skilled in the art and would involve, for example, a computer readable format of the nucleic acids of the present invention, the use of alignment software programs and the use of publicly available information on protein domains, conserved motifs and boxes. This information is available in the PRODOM (Hypertext Transfer Protocol://World Wide Web (dot) biochem (dot) ucl (dot) ac (dot) uk/bsm/dbbrowser/protocol/prodomqry (dot) html), PIR (Hypertext Transfer Protocol://pir (dot) Georgetown (dot) edu/) or Pfam (Hypertext Transfer Protocol://World Wide Web (dot) sanger (dot) ac (dot) uk/Software/Pfam/) database. Sequence analysis programs designed for motif searching may be used for identification of fragments, regions and conserved domains as mentioned above. Preferred computer programs include, but are not limited to, MEME, SIGNALSCAN, and GENESCAN.
A person skilled in the art may use the homologous sequences provided herein to find similar sequences in other species and other organisms. Homologues of a protein encompass, peptides, oligopeptides, polypeptides, proteins and enzymes having amino acid substitutions, deletions and/or insertions relative to the unmodified protein in question and having similar biological and functional activity as the unmodified protein from which they are derived. To produce such homologues, amino acids of the protein may be replaced by other amino acids having similar properties (conservative changes, such as similar hydrophobicity, hydrophilicity, antigenicity, propensity to form or break a-helical structures or 3-sheet structures). Conservative substitution tables are well known in the art (see for example Creighton (1984) Proteins. W.H. Freeman and Company). Homologues of a nucleic acid encompass nucleic acids having nucleotide substitutions, deletions and/or insertions relative to the unmodified nucleic acid in question and having similar biological and functional activity as the unmodified nucleic acid from which they are derived.
Polynucleotides and polypeptides with significant homology to the identified genes described in Table 1 (Example 1 above) were identified from the databases using BLAST software with the Blastp and tBlastn algorithms as filters for the first stage, and the needle (EMBOSS package) or Frame+ algorithm alignment for the second stage. Local identity (Blast alignments) was defined with a very permissive cutoff—60% Identity on a span of 60% of the sequences lengths because it use as only a filter for the global alignment stage. The default filtering of the Blast package was not utilized (by setting the parameter “-F F”).
In the second stage, homologs were defined based on a global identity of at least 80% to the core gene polypeptide sequence.
Two distinct forms for finding the optimal global alignment for protein or nucleotide sequences were used in this application:
1. Between two proteins (following the blastp filter):
EMBOSS-6.0.1 Needleman-Wunsch algorithm with the following modified parameters: gapopen=8 gapextend=2. The rest of the parameters were unchanged from the default options described hereinabove.
2. Between a protein sequence and a nucleotide sequence (following the tblastn filter):
GenCore 6.0 OneModel application utilizing the Frame+ algorithm with the following parameters: model=frame+_p2n.model mode=qglobal -q=protein.sequence -db=nucleotide.sequence. The rest of the parameters are unchanged from the default options described hereinabove. The query polypeptide sequences were SEQ ID NOs: 480-733, 8512, 8514, 8516, 8518, 8520, 8522 and 8524 (which are encoded by the polynucleotides SEQ ID NOs:1-277 and 8511, 8513, 8515, 8517, 8519, 8521 and 8523, shown in Table 1 above) and the identified orthologous and homologous sequences having at least 80% global sequence identity are provided in Table 2, below. These homologous genes are expected to increase plant yield, seed yield, oil yield, oil content, growth rate, fiber yield, fiber quality, biomass, vigor, ABST and/or NUE of a plant.
leymus|gb166|EG375994_P1
brachypodium|09v1|DV470933
brachypodium|12v1|BRADI5G22570T2_P1
brachypodium|09v1|SRR031795S0031948
brachypodium|12v1|BRADI3G57530_P1
sorghum|09v1|SB04G034630
sorghum|12v1|SB04G034630_P1
leymus|gb166|EG377887_P1
brachypodium|09v1|DV475357
brachypodium|12v1|BRADI1G53920_P1
sorghum|09v1|SB02G006500
sorghum|12v1|SB02G006500_P1
leymus|gb166|EG394965_P1
leymus|gb166|EG384174_P1
brachypodium|12v1|BRADI3G55570_P1
sorghum|12v1|SB04G037460_P1
brachypodium|09v1|CRPBD006396
brachypodium|09v1|CRPBD004062
pseudoroegneria|gb167|FF357444
leymus|gb166|EG374930_P1
sorghum|09v1|SB01G022490
sorghum|12v1|SB01G022490_P1
brachypodium|12v1|BRADI1G07560_P1
leymus|gb166|EG397836_P1
brachypodium|09v1|DV475654
lolium|10v1|EB709728_T1
sorghum|12v1|SB10G030100_P1
brachypodium|09v1|GT764798
brachypodium|12v1|BRADI1G35150T2_P1
sorghum|09v1|SB10G030100
sorghum|09v1|SB03G035010
sorghum|12v1|SB03G035010_P1
cenchrus|gb166|EB654148_P1
sorghum|09v1|SB10G030970
sorghum|12v1|SB10G030970_P1
brachypodium|09v1|DV477985
brachypodium|12v1|BRADI3G60790_P1
sorghum|09v1|SB04G038510
sorghum|12v1|SB04G038510_P1
pseudoroegneria|gb167|FF344261
sorghum|09v1|SB06G019430
sorghum|12v1|SB06G019430_P1
sorghum|09v1|SB02G023690
sorghum|12v1|SB02G023690_P1
sorghum|09v1|SB06G032600
sorghum|12v1|SB06G032600_P1
cynodon|10v1|ES292366_P1
leymus|gb166|EG394000_P1
brachypodium|09v1|GT808574
brachypodium|12v1|BRADI5G25860_P1
sorghum|09v1|SB07G024200
sorghum|12v1|SB07G024200_P1
sorghum|09v1|SB07G024210
sorghum|12v1|SB07G024210_P1
brachypodium|09v1|DV471443
brachypodium|12v1|BRADI4G38510_P1
cynodon|10v1|ES292982_P1
leymus|gb166|EG375129_P1
pseudoroegneria|gb167|FF350081
leymus|gb166|EG377276_P1
amorphophallus|11v2|SRR089351X113366_P1
distylium|11v1|SRR065077X101573_P1
pseudoroegneria|gb167|FF347130
phalaenopsis|11v1|SRR125771.1033372_T1
chelidonium|11v1|SRR084752X100908_P1
chelidonium|11v1|SRR084752X101815_P1
aristolochia|10v1|SRR039082S0070766_P1
brachypodium|09v1|DV474207
brachypodium|12v1|BRADI3G42800T6_P1
nuphar|gb166|CK747559_P1
humulus|11v1|GD242898_P1
phalaenopsis|11v1|SRR125771.1004556_P1
sarracenia|11v1|SRR192669.103979_P1
tabernaemontana|11v1|SRR098689X11504_P1
ginseng|10v1|CN848206_P1
pseudotsuga|10v1|SRR065119S0005295
abies|11v2|SRR098676X106955_T1
phyla|11v2|SRR099035X104155_P1
aristolochia|10v1|SRR039082S0135731_P1
cacao|10v1|CF972749_P1
cyamopsis|10v1|EG977006_P1
cycas|gb166|CB089948_P1
ginseng|10v1|EW712050_P1
leymus|gb166|CN466494_P1
liriodendron|gb166|CK753392_P1
nuphar|gb166|CD474021_P1
sorghum|09v1|SB03G040550
sorghum|12v1|SB03G040550_P1
zamia|gb166|DY031878
eschscholzia|11v1|CK750888_P1
amorphophallus|11v2|SRR089351X100060_T1
primula|11v1|SRR098679X104520_T1
tabernaemontana|11v1|SRR098689X122189_P1
citrus|gb166|CB304385
bupleurum|11v1|SRR301254.11858_P1
catharanthus|11v1|EG562566_P1
cedrus|11v1|SRR065007X109999_P1
olea|11v1|SRR014463.11312_P1
platanus|11v1|SRR096786X120035_P1
pteridium|11v1|SRR043594X105469_P1
sarracenia|11v1|SRR192669.101116_P1
thalictrum|11v1|SRR096787X103466_P1
cryptomeria|gb166|BJ937459_P1
medicago|09v1|LLES610908
medicago|12v1|ES610908_P1
papaya|gb165|EX249851_P1
eschscholzia|11v1|CK766388_P1
catharanthus|11v1|EG558011_T1
amsonia|11v1|SRR098688X104577_P1
cephalotaxus|11v1|SRR064395X151698_P1
eschscholzia|11v1|CD477238_P1
eschscholzia|11v1|CD478319_P1
eucalyptus|11v2|CU396236_P1
fagopyrum|11v1|SRR063689X107500_P1
fraxinus|11v1|SRR058827.117586_P1
olea|11v1|SRR014463.18658_P1
scabiosa|11v1|SRR063723X10991_P1
antirrhinum|gb166|AJ560015_P1
basilicum|10v1|DY325036_P1
catharanthus|gb166|EG558011
cenchrus|gb166|EB654688_P1
eucalyptus|11v1|CU396236
heritiera|10v1|SRR005794S0003479_P1
lolium|10v1|AU249969_P1
petunia|gb171|CV298098_P1
podocarpus|10v1|SRR065014S0012085_P1
thellungiella|gb167|DN774728
fraxinus|11v1|SRR058827.142875_T1
coffea|10v1|DV663604_P1
euonymus|11v1|SRR070038X114371_P1
euonymus|11v1|SRR070038X190637_P1
primula|11v1|SRR098679X113048_P1
tripterygium|11v1|SRR098677X110207_P1
utricularia|11v1|SRR094438.102473_T1
cenchrus|gb166|BQ479113_P1
leymus|gb166|EG376201_P1
momordica|10v1|SRR071315S0005611_P1
nasturtium|10v1|SRR032558S0007114
nasturtium|11v1|SRR032558.101084_P1
orobanche|10v1|SRR023189S0001673_P1
petunia|gb171|CV294332_P1
petunia|gb171|CV299939_P1
sequoia|10v1|SRR065044S0003631
taxus|10v1|SRR032523S0015691
thellungiella|gb167|DN774951
amsonia|11v1|SRR098688X106132_P1
vinca|11v1|SRR098690X102336_P1
vinca|11v1|SRR098690X107812_P1
valeriana|11v1|SRR099039X101941_P1
valeriana|11v1|SRR099039X111375_P1
cucurbita|11v1|SRR091276X105908_T1
curcuma|10v1|DY394111_T1
aquilegia|10v1|DR919077_P1
cucurbita|11v1|FG227425_P1
cucurbita|11v1|SRR091276X104899_P1
euonymus|11v1|SRR070038X130859_P1
fagopyrum|11v1|SRR063703X113606_P1
humulus|11v1|ES654690_P1
olea|11v1|SRR014463.20541_P1
plantago|11v2|SRR066373X100572_P1
pteridium|11v1|GW575187_P1
tripterygium|11v1|SRR098677X111812_P1
antirrhinum|gb166|AJ789157_P1
aquilegia|10v2|DR919077
aquilegia|10v2|DR921801
lotus|09v1|AW719561_P1
marchantia|gb166|BJ841118_P1
marchantia|gb166|C96032_P1
pseudoroegneria|gb167|FF340018
salvia|10v1|CV168785
aquilegia|10v1|DR925946_P1
cirsium|11v1|SRR346952.115429_P1
cucurbita|11v1|SRR091276X104110_P1
euonymus|11v1|SRR070038X106585_P1
euonymus|11v1|SRR070038X127546_P1
fraxinus|11v1|SRR058827.101271_P1
platanus|11v1|SRR096786X10321_P1
aquilegia|10v2|DR925946
arabidopsis|10v1|AT5G22440_P1
cynara|gb167|GE597248_P1
fescue|gb161|DT685613_P1
nasturtium|10v1|GH162041
nasturtium|11v1|GH162041_P1
taxus|10v1|SRR032523S0003326
phyla|11v2|SRR099037X193979_T1
cannabis|12v1|GR221542_P1
vinca|11v1|SRR098690X100190_P1
cryptomeria|gb166|BP174254_T1
salvia|10v1|SRR014553S0014817
cannabis|12v1|EW701238_P1
fagopyrum|11v1|SRR063689X108738_P1
amaranthus|10v1|SRR039411S0000047_P1
cichorium|gb171|DT213592_P1
eschscholzia|10v1|CK750888
antirrhinum|gb166|AJ789134_T1
amborella|12v2|CK757481_P1
arnica|11v1|SRR099034X106235_P1
arnica|11v1|SRR099034X117709_P1
cirsium|11v1|SRR346952.1020901_P1
epimedium|11v1|SRR013502.10782_P1
eucalyptus|11v2|DR410017_P1
trigonella|11v1|SRR066194X109093_P1
brachypodium|09v1|DV475206
brachypodium|12v1|BRADI2G55600_P1
centaurea|gb166|EH755136_P1
eucalyptus|11v1|DR410017
medicago|09v1|AA660463
medicago|12v1|AA660463_P1
medicago|09v1|LLBG644354
thellungiella|gb167|EC599536
tragopogon|10v1|SRR020205S0005773
tragopogon|10v1|SRR020205S0054300
triphysaria|10v1|BE574961
fraxinus|11v1|SRR058827.149429_T1
amborella|12v2|CK754386_P1
ambrosia|11v1|GR935615_P1
ambrosia|11v1|SRR346935.197056_P1
ambrosia|11v1|SRR346935.207821_P1
ambrosia|11v1|SRR346943.100852_P1
ambrosia|11v1|SRR346943.103647_P1
ambrosia|11v1|SRR346943.104242_P1
arnica|11v1|SRR099034X102057_P1
cirsium|11v1|DV175371_P1
cirsium|11v1|SRR346952.100637_P1
flaveria|11v1|SRR149229.100897_P1
flaveria|11v1|SRR149229.105912_P1
flaveria|11v1|SRR149229.106781_P1
flaveria|11v1|SRR149229.106867_P1
flaveria|11v1|SRR149229.112923_P1
flaveria|11v1|SRR149229.416813_P1
flaveria|11v1|SRR149232.102816_P1
flaveria|11v1|SRR149232.115803_P1
flaveria|11v1|SRR149232.115954_P1
flaveria|11v1|SRR149232.120376_P1
centaurea|gb166|EH726717_P1
centaurea|gb166|EH729121_P1
cichorium|gb171|DT211948_P1
cynara|gb167|GE585793_P1
gerbera|09v1|AJ752617_P1
parthenium|10v1|GW776856_P1
triphysaria|10v1|BM356583
medicago|12v1|AL366013_P1
prunus|10v1|CB819399
plantago|11v2|SRR066373X105277_P1
cacao|10v1|CU484457_T1
ambrosia|11v1|SRR346935.167042_T1
ambrosia|11v1|SRR346943.459404_T1
arnica|11v1|SRR099034X109759_T1
flaveria|11v1|SRR149229.447389_T1
amborella|gb166|CK757481
ambrosia|11v1|SRR346935.155011_P1
epimedium|11v1|SRR013502.10210_P1
thalictrum|11v1|SRR096787X107013_P1
trigonella|11v1|SRR066194X100308_P1
arabidopsis|10v1|AT1G08360_P1
arabidopsis|10v1|AT2G27530_P1
cichorium|gb171|DT211200_P1
cynara|gb167|GE589205_P1
lotus|09v1|BF177566_P1
medicago|09v1|AW698717
medicago|12v1|AJ389005_P1
parthenium|10v1|GW779249_P1
sequoia|10v1|SRR065044S0005324
euphorbia||11v1|BE095315_P1
fagopyrum|11v1|SRR063689X100987_P1
flaveria|11v1|SRR149232.135928_P1
catharanthus|gb166|EG562566
hevea||10v1|EC602536_P1
jatropha||09v1|FM892483_P1
triphysaria|10v1|BE574747
ambrosia|11v1|SRR346935.124048_T1
flaveria|11v1|SRR149241.2888_T1
gerbera|09v1|AJ752767_T1
lotus|09v1|LLBW598038_T1
ambrosia|11v1|SRR346947.105064_T1
ambrosia|11v1|SRR346943.102888_T1
cephalotaxus|11v1|SRR064395X116623_P1
fagopyrum|11v1|SRR063703X113882_T1
flaveria|11v1|SRR149244.11798_P1
fraxinus|11v1|SRR058827.114519_T1
silene|11v1|GH293964_P1
ceratodon||10v1|SRR074890S0000846_P1
physcomitrella||10v1|AW126854_P1
artemisia||10v1|EY043816_P1
guizotia|10v1|GE552355_T1
basilicum|10v1|DY336374_P1
prunus|10v1|CB822822
euphorbia||11v1|SRR098678X101209_P1
amborella|gb166|CK762906
physcomitrella||10v1|Z98058_P1
sarracenia|11v1|SRR192669.11631_P1
artemisia||10v1|EY044623_T1
physcomitrella||10v1|AW497015_P1
parthenium|10v1|GW780345_P1
euphorbia||11v1|SRR098678X101198_P1
silene|11v1|SRR096785X100437_P1
medicago|09v1|AL366014
eschscholzia|10v1|CK766388
ambrosia|11v1|SRR346935.5183_T1
flaveria|11v1|SRR149241.110115_P1
sorghum|12v1|SB04G030700_P1
sorghum|09v1|SB04G030700
brachypodium|09v1|GT783994
brachypodium|12v1|BRADI3G52620_P1
sorghum|09v1|SB04G031540
sorghum|12v1|SB04G031540_P1
sorghum|12v1|SB06G025390_P1
sorghum|09v1|SB02G035940
sorghum|12v1|SB02G035940_P1
sorghum|09v1|SB03G025740
sorghum|12v1|SB03G025740_P1
brachypodium|09v1|GT758302
brachypodium|12v1|BRADI2G41500_P1
sorghum|09v1|SB07G019240
sorghum|12v1|SB07G019240_P1
brachypodium|09v1|GT772760
brachypodium|12v1|BRADI3G35000_P1
cynodon|10v1|ES291891_P1
sorghum|09v1|SB08G005300
sorghum|12v1|SB08G005300_P1
fescue|gb161|DT683395_P1
fescue|gb161|DT696789_P1
lolium|10v1|AU246931_P1
leymus|gb166|CD809087_P1
pseudoroegneria|gb167|FF340056
brachypodium|09v1|DV475775
brachypodium|12v1|BRADI4G40780_P1
sorghum|09v1|SB09G028990
sorghum|12v1|SB09G028990_P1
sorghum|09v1|SB02G026450
sorghum|12v1|SB02G026450_P1
sorghum|09v1|SB02G039350
sorghum|09v1|SB05G004540
sorghum|09v1|SB08G001140
sorghum|12v1|SB08G001140_T1
sorghum|09v1|SB05G002590
sorghum|12v1|SB05G002590_P1
sorghum|09v1|SB10G024430
sorghum|12v1|SB10G024430_P1
sorghum|09v1|SB10G001000
sorghum|12v1|SB10G001000_P1
cynodon|10v1|ES293242_P1
pseudoroegneria|gb167|FF352787
brachypodium|09v1|DV478300
brachypodium|12v1|BRADI1G50180_P1
nasturtium|10v1|SRR032558S0002326
nasturtium|11v1|SRR032558.11557_P1
amaranthus|10v1|SRR039411S0053406_P1
citrus|gb166|AB011799
fagopyrum|11v1|SRR063689X101291_T1
coffea|10v1|DV672822_P1
eucalyptus|11v2|CT980471_P1
arabidopsis|10v1|AT2G35520_P1
aristolochia|10v1|FD750442_P1
eucalyptus|11v1|CT980471
momordica|10v1|SRR071315S0004489_P1
papaya|gb165|EX259202_P1
aquilegia|10v2|JGIAC001698
bupleurum|11v1|SRR301254.10188_P1
bupleurum|11v1|SRR301254.103177_P1
bupleurum|11v1|SRR301254.116549_P1
cucurbita|11v1|SRR091276X112807_T1
cucurbita|11v1|SRR091276X116524_T1
cucurbita|11v1|SRR091276X130274XX1_T1
fagopyrum|11v1|SRR063703X10184_T1
euonymus|11v1|SRR070038X105435_P1
fagopyrum|11v1|SRR063689X100301_P1
fagopyrum|11v1|SRR063703X102261_P1
humulus|11v1|GD242916_P1
phalaenopsis|11v1|SRR125771.100895_P1
arabidopsis|10v1|AT1G32210_P1
cyamopsis|10v1|EG984797_P1
cichorium|gb171|EL365522_T1
centaurea|gb166|EH715505_P1
senecio|gb170|SRR006592S0005216
euonymus|11v1|SRR070038X134639_P1
phalaenopsis|11v1|SRR125771.1011736_P1
plantago|11v2|AM156929_P1
cucurbita|11v1|SRR091276X109664_T1
prunus|10v1|BU047738
heritiera|10v1|SRR005795S0011088_P1
bupleurum|11v1|SRR301254.22559_P1
tragopogon|10v1|SRR020205S0030697
olea|11v1|SRR014463.48353_P1
scabiosa|11v1|SRR063723X100675_P1
valeriana|11v1|SRR099039X102388_P1
heritiera|10v1|SRR005794S0000485_P1
petunia|gb171|AY227437_P1
platanus|11v1|SRR096786X201688_T1
tamarix|gb166|EH050677
amorphophallus|11v2|SRR089351X106271_P1
amorphophallus|11v2|SRR089351X109124_P1
cannabis|12v1|SOLX00017739_P1
lotus|09v1|LLCB829384_P1
eschscholzia|11v1|CD478253_T1
sarracenia|11v1|SRR192669.102986_T1
triphysaria|10v1|EY131424
tabernaemontana|11v1|SRR098689X101117_P1
vinca|11v1|SRR098690X222500_P1
flaveria|11v1|SRR149229.10081_P1
flaveria|11v1|SRR149229.230770_P1
flaveria|11v1|SRR149232.118105_P1
flaveria|11v1|SRR149232.123588_P1
flaveria|11v1|SRR149229.105886_P1
fraxinus|11v1|SRR058827.103870_P1
phyla|11v2|SRR099037X116212_P1
euphorbia||11v1|BP961349_P1
antirrhinum|gb166|AJ559287_P1
silene|11v1|SRR096785X105699_T1
prunus|10v1|MDU68560
cirsium|11v1|SRR346952.118405_P1
arnica|11v1|SRR099034X119762_P1
cirsium|11v1|SRR346952.101479_P1
cirsium|11v1|SRR346952.1015198_P1
flaveria|11v1|SRR149232.113067_P1
flaveria|11v1|SRR149232.176507_P1
flaveria|11v1|SRR149244.165800_P1
utricularia|11v1|SRR094438.104568_P1
artemisia||10v1|EY036948_T1
cynara|gb167|GE590262_P1
ginseng|10v1|DV554463_P1
euphorbia||11v1|BP953547_P1
olea|11v1|SRR014463.1314_P1
phyla|11v2|SRR099035X134712_P1
salvia|10v1|CV162894
salvia|10v1|SRR014553S0008302
triphysaria|10v1|EY016755
acacia|10v1|GR480985_T1
catharanthus|11v1|EG562088_P1
ambrosia|11v1|SRR346935.378400_P1
ambrosia|11v1|SRR346943.158491_P1
phyla|11v2|SRR099037X119521_T1
triphysaria|10v1|EY157452
ambrosia|11v1|SRR346943.100571_T1
cichorium|gb171|EH706520_P1
cynara|gb167|GE586619_P1
aquilegia|10v2|JGIAC000753
gerbera|09v1|AJ751921_P1
sarracenia|11v1|SRR192669.101455_P1
sarracenia|11v1|SRR192669.115702_P1
amborella|12v2|CK763832_T1
amborella|gb166|CK763832
medicago|09v1|BF637130
medicago|12v1|BF637130_P1
tamarix|gb166|EG970118
sorghum|09v1|SB03G045180
sorghum|12v1|SB03G045180_P1
brachypodium|12v1|BRADI2G60090T2_P1
brachypodium|09v1|GT820385
sorghum|09v1|SB01G008860
sorghum|12v1|SB01G008860_P1
brachypodium|09v1|DV473285
brachypodium|12v1|BRADI1G09460_P1
fescue|gb161|DT680982_P1
sorghum|09v1|SB10G000380
sorghum|12v1|SB10G000380_P1
sorghum|09v1|SB04G027340
sorghum|12v1|SB04G027340_P1
pseudoroegneria|gb167|FF355079
brachypodium|12v1|BRADI3G58600_P1
brachypodium|09v1|DV483604
sorghum|12v1|SB03G025990_P1
sorghum|09v1|SB03G025990
brachypodium|12v1|BRADI2G41830_P1
brachypodium|09v1|GT802010
sorghum|09v1|SB10G002480
sorghum|12v1|SB10G002480_T1
cynodon|10v1|ES305015_T1
brachypodium|09v1|DV479696
brachypodium|12v1|BRADI1G51530_T1
leymus|gb166|EG379612_T1
sorghum|09v1|SB01G029740
sorghum|12v1|SB01G029740_T1
cynodon|10v1|ES303046_P1
sorghum|09v1|SB01G032750
sorghum|12v1|SB01G032750_P1
brachypodium|09v1|GT777927
brachypodium|12v1|BRADI1G60090_P1
sorghum|09v1|SB04G006360
sorghum|12v1|SB04G006360_P1
sorghum|09v1|SB03G041910
sorghum|12v1|SB03G041910_P1
sorghum|09v1|SB06G032890
sorghum|12v1|SB06G032890_P1
brachypodium|09v1|GT778319
brachypodium|12v1|BRADI5G26120_P1
sorghum|09v1|SB04G002980
sorghum|12v1|SB04G002980_P1
brachypodium|09v1|GT772136
brachypodium|12v1|BRADI3G03270_P1
leymus|gb166|EG381321_T1
sorghum|09v1|SB01G011650
sorghum|12v1|SB01G011650_P1
sorghum|09v1|SB01G009660
sorghum|12v1|SB01G009660_P1
brachypodium|09v1|GT764665
brachypodium|12v1|BRADI1G10250_P1
cynodon|10v1|ES293189_P1
pseudoroegneria|gb167|FF344761
sorghum|09v1|SB03G030040
sorghum|12v1|SB03G030040_P1
brachypodium|09v1|TMPLOS01G46950T1
sorghum|12v1|SB10G006300_P1
sorghum|09v1|SB10G006280
sorghum|12v1|SB10G006280_P1
sorghum|12v1|SB10G006290_P1
sorghum|09v1|SB10G006290
cynodon|10v1|ES293072_P1
brachypodium|09v1|GT758287
brachypodium|12v1|BRADI3G22980_P1
sorghum|09v1|SB10G006270
sorghum|12v1|SB10G006270_T1
sorghum|09v1|SB09G026770
sorghum|12v1|SB09G026770_P1
sorghum|09v1|SB06G020520
sorghum|12v1|SB06G020520_P1
brachypodium|09v1|DV489073
brachypodium|12v1|BRADI5G13700_P1
sorghum|09v1|SB01G015780
sorghum|12v1|SB01G015780_P1
sorghum|12v1|SB04G017430_P1
sorghum|09v1|SB04G017430
cenchrus|gb166|EB655382_P1
brachypodium|12v1|BRADI3G43137_P1
euonymus|11v1|HS011083_T1
leymus|gb166|EG391468_P1
pseudoroegneria|gb167|FF339860_P1
fescue|gb161|CK802837_P1
sorghum|12v1|BG357441_P1
sorghum|09v1|SB01G047550
sorghum|09v1|SB01G001060
sorghum|12v1|SB01G001060_P1
sorghum|09v1|SB09G030810
sorghum|12v1|SB09G030810_P1
cynodon|10v1|ES293199_P1
brachypodium|09v1|GT804298
brachypodium|12v1|BRADI2G14260_P1
leymus|gb166|EG391342_P1
cucurbita|11v1|SRR091276X120709_P1
platanus|11v1|SRR096786X130411_P1
platanus|11v1|SRR096786X355108_P1
trigonella|11v1|SRR066194X157903_P1
coffea|10v1|DV712995_P1
amsonia|11v1|SRR098688X38847_P1
phalaenopsis|11v1|SRR125771.1149762_P1
amborella|gb166|CK755640
cacao|10v1|CU504428_P1
citrus|gb166|CF504147
coffea|10v1|EE191840_P1
heritiera|10v1|SRR005794S0000480_P1
bupleurum|11v1|SRR301254.139455_P1
bupleurum|11v1|SRR301254.15817_P1
eucalyptus|11v2|ES592357_P1
fagopyrum|11v1|SRR063689X105178_P1
medicago|12v1|BQ144100_P1
sarracenia|11v1|SRR192669.112573_P1
utricularia|11v1|SRR094438.103235_P1
antirrhinum|gb166|AJ559733_P1
aquilegia|10v2|JGIAC023381
eucalyptus|11v1|ES592357
jatropha||09v1|FM891742_P1
salvia|10v1|FE536863
amorphophallus|11v2|SRR089351X119533_P1
catharanthus|11v1|EG557252_P1
eucalyptus|11v2|ES588366_P1
euonymus|11v1|SRR070038X161992_P1
euonymus|11v1|SRR070038X427194_P1
euonymus|11v1|SRR070038X545766_P1
nasturtium|11v1|GH167276_P1
tabernaemontana|11v1|SRR098689X130803_P1
acacia|10v1|FS586254_P1
eucalyptus|11v1|ES588366
nasturtium|10v1|GH167276
cirsium|11v1|SRR346952.1006577_P1
cirsium|11v1|SRR346952.1063347_P1
cirsium|11v1|SRR346952.106494_P1
euonymus|11v1|SRR070038X316257_P1
plantago|11v2|SRR066373X134434_P1
tripterygium|11v1|SRR098677X236783_P1
vinca|11v1|SRR098690X147661_P1
centaurea|gb166|EH739616_P1
centaurea|gb166|EH742668_P1
cichorium|gb171|EL371031_P1
cynara|gb167|GE591637_P1
hevea||10v1|EC600278_P1
triphysaria|10v1|EY125732
cannabis|12v1|SOLX00063103_P1
cirsium|11v1|SRR346952.125654_P1
flaveria|11v1|SRR149229.21124_P1
humulus|11v1|SRR098683X111685_P1
olea|11v1|SRR014464.32155_P1
aristolochia|10v1|SRR039082S0054216_P1
artemisia||10v1|SRR019254S0103015_P1
cynara|gb167|GE590619_P1
lotus|09v1|AU251384_P1
zinnia|gb171|AU307714
momordica|10v1|SRR071315S0102256_P1
ambrosia|11v1|SRR346943.132542_T1
flaveria|11v1|SRR149232.381162_T1
ambrosia|11v1|SRR346943.120806_P1
euphorbia||11v1|DV119892_P1
euphorbia||11v1|SRR098678X107103_P1
flaveria|11v1|SRR149229.317100_P1
flaveria|11v1|SRR149232.156175_P1
artemisia||10v1|EY064441_P1
zostera|10v1|SRR057351S0102941
valeriana|11v1|SRR099039X175201_P1
primula|11v1|SRR098679X61753_P1
arabidopsis|10v1|AT1G65700_P1
lotus|09v1|AV426525_P1
papaya|gb165|EX252216_P1
sequoia|10v1|SRR065044S0138565
sorghum|09v1|SB07G007750
sorghum|12v1|SB07G007750_P1
brachypodium|09v1|DV474658
brachypodium|12v1|BRADI3G18920_P1
sorghum|09v1|SB04G022140
sorghum|12v1|SB04G022140_P1
brachypodium|09v1|DV469217
brachypodium|12v1|BRADI3G45260_P1
sorghum|09v1|SB01G027790
sorghum|12v1|SB01G027790_P1
cynodon|10v1|ES297680_P1
brachypodium|09v1|DV479530
brachypodium|12v1|BRADI3G34557_P1
pseudoroegneria|gb167|FF339930
fescue|gb161|DT701118_P1
sorghum|09v1|SB06G021810
sorghum|12v1|SB06G021810_P1
brachypodium|09v1|DV485200
brachypodium|12v1|BRADI5G14910_P1
pseudoroegneria|gb167|FF350465
sorghum|09v1|SB10G025050
sorghum|12v1|SB10G025050_P1
brachypodium|09v1|DV476163
brachypodium|12v1|BRADI1G30330_P1
sorghum|12v1|SB03G010320_P1
sorghum|09v1|SB03G010320
sorghum|12v1|SB10G029300_P1
sorghum|09v1|SB10G029300
sorghum|09v1|SB01G043220
sorghum|12v1|SB01G043220_P1
brachypodium|09v1|GT767056
brachypodium|12v1|BRADI1G39090_P1
brachypodium|12v1|BRADI2G26420_T1
brachypodium|09v1|SRR031797S0049352
tripterygium|11v1|SRR098677Xl00547_P1
citrus|gb166|CB304914
euonymus|11v1|SRR070038X115804_P1
euphorbia||11v1|BG317307_P1
euonymus|11v1|SRR070038X112478_P1
eucalyptus|11v2|ES590324_P1
ambrosia|11v1|SRR346935.104108_T1
catharanthus|11v1|EG555556_P1
tabernaemontana|11v1|SRR098689X100220_P1
eucalyptus|11v1|ES590324
ambrosia|11v1|SRR346935.307154_T1
flaveria|11v1|SRR149229.102721_P1
triphysaria|10v1|EX988156
cichorium|gb171|EH675116_P1
tragopogon|10v1|SRR020205S0004863
amsonia|11v1|SRR098688X107521_P1
triphysaria|10v1|DR173475
artemisia||10v1|EY036781_P1
citrus|gb166|CF506647
coffea|10v1|DV675662_P1
momordica|10v1|SRR071315S0009397_P1
nasturtium|10v1|GH162060
nasturtium|11v1|GH162060_T1
prunus|10v1|CN993152
cirsium|11v1|SRR346952.1017142_P1
ambrosia|11v1|SRR346935.65560_T1
flaveria|11v1|SRR149229.231079XX2_T1
cirsium|11v1|SRR346952.162014_P1
valeriana|11v1|SRR099039X10437_P1
vinca|11v1|SRR098690X110682_P1
aristolochia|10v1|SRR039082S0101548_P1
amorphophallus|11v2|SRR089351X108628_T1
trigonella|11v1|SRR066194X122711_P1
arabidopsis|10v1|AT5G26360_P1
amborella|12v2|SRR038634.26959_P1
orobanche|10v1|SRR023189S0002940_P1
phalaenopsis|11v1|SRR125771.1000872_T1
medicago|09v1|LLAW684643
eschscholzia|11v1|CK751932_P1
chelidonium|11v1|SRR084752X114234_T1
vinca|11v1|SRR098690X123290_P1
aquilegia|10v2|DR926350
abies|11v2|SRR098676X124250_T1
ambrosia|11v1|SRR346935.126014_P1
pseudotsuga|10v1|SRR065119S0004989
silene|11v1|SRR096785X110757_P1
zostera|10v1|SRR057351S0000590
zostera|10v1|AM767310
phyla|11v2|SRR099035X100113_P1
podocarpus|10v1|SRR065014S0030106_P1
sciadopitys|10v1|SRR065035S0022639
euonymus|11v1|SRR070038X118006_T1
cynara|gb167|GE577561_T1
flaveria|11v1|SRR149229.376402XX1_T1
distylium|11v1|SRR065077X111648_P1
sorghum|09v1|SB04G037820
sorghum|12v1|SB04G037820_P1
pseudoroegneria|gb167|FF356910
euonymus|11v1|SRR070038X108680_P1
ambrosia|11v1|SRR346943.236458_T1
ambrosia|11v1|SRR346935.121691_T1
triphysaria|10v1|EX999372
sorghum|09v1|SB03G044840
sorghum|12v1|SB03G044840_P1
sorghum|09v1|SB01G041310
sorghum|12v1|SB01G041310_P1
brachypodium|09v1|DV482321
brachypodium|12v1|BRADI1G68310_P1
sorghum|09v1|SB03G030390
sorghum|12v1|SB03G030390_P1
brachypodium|09v1|DV486637
brachypodium|12v1|BRADI2G45840_P1
sorghum|09v1|SB08G015570
sorghum|12v1|SB08G015570_P1
cynodon|10v1|ES294929_P1
sorghum|09v1|SB02G040990
sorghum|12v1|SB02G040990_P1
cenchrus|gb166|EB658585_P1
sorghum|09v1|SB03G037640
sorghum|12v1|SB03G037640_P1
brachypodium|09v1|GT761626
brachypodium|12v1|BRADI2G21510_P1
platanus|11v1|SRR096786X124431_P1
tripterygium|11v1|SRR098677X100363_P1
euonymus|11v1|SRR070038X215578_P1
platanus|11v1|SRR096786X131437_P1
phalaenopsis|11v1|CK857600_P1
phalaenopsis|11v1|CK858273_P1
citrus|gb166|CB304559
olea|11v1|SRR014463.10628_P1
ambrosia|11v1|SRR346935.264705_P1
aquilegia|10v1|DT745261_P1
cucurbita|11v1|FG227439_P1
euonymus|11v1|SRR070038X120289_P1
gerbera|09v1|AJ758761_P1
tragopogon|10v1|SRR020205S0020529
zostera|10v1|SRR057351S0008909
chelidonium|11v1|SRR084752X117011_T1
amborella|12v2|SRR038634.8195_P1
amorphophallus|11v2|SRR089351X325197_P1
cucurbita|11v1|SRR091276X113571_P1
phyla|11v2|SRR099037X118182_P1
aquilegia|10v2|DT745261
cichorium|gb171|DT214124_P1
aristolochia|10v1|SRR039085S0175270_T1
amsonia|11v1|SRR098688X109897_P1
arnica|11v1|SRR099034X105811_P1
arnica|11v1|SRR099034X112592XX2_P1
catharanthus|11v1|EG557339_P1
eschscholzia|11v1|SRR014116.104619_P1
eschscholzia|11v1|SRR014116.127866_P1
basilicum|10v1|DY336625_P1
centaurea|gb166|EH711172_P1
centaurea|gb166|EH714679_P1
coffea|10v1|DQ124065_P1
liriodendron|gb166|CK759778_P1
petunia|gb171|CV300555_P1
prunus|10v1|CB823004
ambrosia|11v1|SRR346935.124143_T1
cirsium|11v1|SRR346952.1000620_T1
tabernaemontana|11v1|SRR098689X112460_P1
tabernaemontana|11v1|SRR098689X112536_P1
vinca|11v1|SRR098690X120702_P1
senecio|gb170|CO553167
cannabis|12v1|JK493807_P1
fagopyrum|11v1|SRR063689X100335_P1
flaveria|11v1|SRR149229.121715_P1
flaveria|11v1|SRR149229.18262_P1
flaveria|11v1|SRR149232.226868_P1
sarracenia|11v1|SRR192669.102682_P1
antirrhinum|gb166|AJ559235_P1
cacao|10v1|CU577695_P1
zostera|10v1|AM768788
fagopyrum|11v1|SRR063689X103805_P1
fagopyrum|11v1|SRR063689X141652_P1
silene|11v1|GH293083_P1
vinca|11v1|SRR098690X103571_P1
cacao|10v1|CU485045_P1
ginseng|10v1|CN846008_P1
lotus|09v1|BI419229_P1
nasturtium|10v1|SRR032558S0004295
nasturtium|11v1|SRR032558.115231_P1
orobanche|10v1|SRR023189S0003207_P1
taxus|10v1|SRR032523S0026069
flaveria|11v1|SRR149229.10776_T1
cephalotaxus|11v1|SRR064395X102481_P1
eucalyptus|11v2|CB967808_P1
euphorbia||11v1|BP961149_P1
phyla|11v2|SRR099035X135361_P1
plantago|11v2|SRR066373X101438_P1
trigonella|11v1|SRR066194X106460_P1
eucalyptus|11v1|CB967808
medicago|09v1|LLAW685471
medicago|12v1|AW685471_P1
nasturtium|10v1|GH162890
nasturtium|11v1|GH162890_P1
sciadopitys|10v1|SRR065035S0020951
tamarix|gb166|EG970613
cedrus|11v1|SRR065007X105181_P1
euphorbia||11v1|DV123915_P1
podocarpus|10v1|SRR065014S0002788_P1
abies|11v2|SRR098676X108000_P1
distylium|11v1|SRR065077X10715_P1
euphorbia||11v1|SRR098678X105123_P1
valeriana|11v1|SRR099039X102057_P1
sequoia|10v1|SRR065044S0008978
triphysaria|10v1|EY020960
ambrosia|11v1|SRR346935.193248_P1
cephalotaxus|11v1|SRR064395X117699_P1
pseudotsuga|10v1|SRR065119S0002247
pteridium|11v1|SRR043594X105305_P1
arabidopsis|10v1|AT2G27020_P1
pseudoroegneria|gb167|FF351474
thellungiella|gb167|DN779086
catharanthus|gb166|EG557339
momordica|10v1|SRR071315S0001940_P1
triphysaria|10v1|EY138636
ambrosia|11v1|SRR346935.195528_P1
acacia|10v1|FS583849_P1
cynara|gb167|GE592900_P1
fraxinus|11v1|SRR058827.100577_P1
marchantia|gb166|C95781_P1
antirrhinum|gb166|AJ568496_T1
utricularia|11v1|SRR094438.101641_T1
sorghum|09v1|SB03G046760
sorghum|12v1|SB03G046760_P1
sorghum|09v1|SB07G024120
sorghum|12v1|SB07G024120_P1
cynodon|10v1|ES293660_P1
sorghum|09v1|SB03G027650
sorghum|12v1|SB03G027650_P1
sorghum|12v1|SB12V1CRP050477_P1
leymus|gb166|EG375712_P1
leymus|gb166|EG378713_P1
leymus|gb166|EG377756_P1
brachypodium|09v1|DV474047
brachypodium|12v1|BRADI2G43230_P1
sorghum|09v1|SB02G003270
sorghum|12v1|SB02G003270_P1
brachypodium|09v1|GT794739
brachypodium|12v1|BRADI1G57360_P1
leymus|gb166|EG402765_T1
sorghum|09v1|SB02G036640
sorghum|12v1|SB02G036640_P1
brachypodium|09v1|SRR031797S0060563
brachypodium|12v1|BRADI1G24360_T1
sorghum|09v1|SB01G009950
sorghum|12v1|SB01G009950_P1
sorghum|09v1|SB08G019430
sorghum|12v1|SB08G019430_P1
sorghum|09v1|SB02G006130
sorghum|12v1|SB02G006130_P1
brachypodium|09v1|DV487106
brachypodium|12v1|BRADI1G54360_P1
sorghum|09v1|SB01G004360
sorghum|12v1|SB01G004360_P1
brachypodium|09v1|SRR031797S0002191
brachypodium|12v1|BRADI1G04720_P1
sorghum|09v1|SB03G040920
sorghum|12v1|SB03G040920_P1
brachypodium|09v1|GT784099
brachypodium|12v1|BRADI2G56050_P1
sorghum|09v1|SB02G033900
sorghum|12v1|SB02G033900_P1
brachypodium|12v1|BRADI1G26950_P1
brachypodium|09v1|DV472875
sorghum|12v1|AW287172_T1
sorghum|12v1|AW287172_T1
brachypodium|12v1|BDPRD12V1011015_T1
brachypodium|12v1|BDPRD12V1011015_T1
brachypodium|09v1|CRPBD011704
sorghum|09v1|AW282689
lotus|09v1|GFXAP002983X34_P1
medicago|09v1|GFXNC003119X7
prunus|10v1|CN854620
brachypodium|09v1|CRPBD026436
brachypodium|12v1|BDCRP12V1055702_P1
coffea|10v1|GFXEF044213X25_P1
sorghum|09v1|SB05G018990
sorghum|12v1|SB05G018990_P1
sorghum|09v1|SB07G029170
sorghum|12v1|SB07G029170_P1
brachypodium|09v1|DV475291
brachypodium|12v1|BRADI3G38580_P1
sorghum|09v1|SB07G029165
sorghum|12v1|SB07G029165_P1
sorghum|09v1|SB09G025090
sorghum|12v1|SB09G025090_P1
sorghum|12v1|SB10G026520_P1
sorghum|12v1|CN139880_T1
sorghum|09v1|SB10G026510
sorghum|12v1|SB05G017110_P1
sorghum|09v1|SB05G017110
sorghum|09v1|SB06G017360
sorghum|12v1|SB06G017360_P1
brachypodium|09v1|GT777348
brachypodium|12v1|BRADI3G30670_P1
sorghum|09v1|SB02G038200
sorghum|12v1|SB02G038200_P1
sorghum|09v1|SB01G038960
sorghum|12v1|SB01G038960_P1
sorghum|12v1|SB06G022540_P1
sorghum|09v1|SB06G022530
sorghum|09v1|SB03G027120
sorghum|12v1|SB03G027120_P1
sorghum|09v1|SB04G024620
sorghum|12v1|SB04G024620_P1
brachypodium|09v1|GT768950
brachypodium|12v1|BRADI5G18230_P1
brachypodium|09v1|GT815201
brachypodium|12v1|BRADI4G29160_P1
brachypodium|12v1|SRR031797.131015_T1
cacao|10v1|CU539770_T1
prunus|10v1|BU041739
amorphophallus|11v2|SRR089351X156162_P1
aristolochia|10v1|SRR039082S0005698_T1
aquilegia|10v2|DR921454
euphorbia||11v1|BP955632XX2_T1
sorghum|09v1|SB09G021150
sorghum|12v1|SB09G021150_P1
sorghum|09v1|SB08G006420
sorghum|12v1|SB08G006420_P1
sorghum|12v1|SB03G002950_P1
sorghum|09v1|BE600472
sorghum|12v1|BE600472_P1
sorghum|12v1|SB10G029540_P1
sorghum|09v1|SB10G029540
brachypodium|12v1|BRADI5G13680_P1
sorghum|09v1|SB10G006400
sorghum|12v1|SB12V1CRP127261_T1
sorghum|12v1|SB03G020184_P1
brachypodium|09v1|CRPBD020464
brachypodium|09v1|CRPBD020464
brachypodium|12v1|SOLX00012727_T1
brachypodium|12v1|SOLX00012727_T1
brachypodium|12v1|SRR031797.122789_P1
brachypodium|12v1|SRR031797.122789_P1
brachypodium|09v1|CRPBD021288
brachypodium|09v1|CRPBD021288
aristolochia|10v1|GFXAF528920X1_T1
aristolochia|10v1|GFXAF528920X1_T1
eucalyptus|11v2|CT980503_P1
eucalyptus|11v2|CT980503_P1
brachypodium|09v1|GFXEU325680X7
brachypodium|09v1|GFXEU325680X7
cannabis|12v1|MDCRP043432_P1
cannabis|12v1|MDCRP043432_P1
cannabis|12v1|SOLX00002586_T1
cannabis|12v1|SOLX00002586_T1
amborella|12v2|SRR038634.9338_P1
amborella|12v2|SRR038634.9338_P1
amborella|12v2|GFXAJ506156X4_T1
sorghum|12v1|SB03G012590_P1
sorghum|09v1|SB08G005500
sorghum|12v1|SB08G005500_P1
cynodon|10v1|ES294980_P1
fescue|gb161|DT680081_P1
leymus|gb166|CD808800_P1
leymus|gb166|EG374703_P1
pseudoroegneria|gb167|FF342518
cenchrus|gb166|EB661653_P1
sorghum|09v1|SB10G027860
sorghum|12v1|SB10G027860_P1
cynodon|10v1|ES294067_P1
fagopyrum|11v1|SRR063689X106965_P1
fagopyrum|11v1|SRR063703X102206_P1
cynodon|10v1|ES291885_P1
brachypodium|09v1|DV480073
brachypodium|12v1|BRADI1G33240_P1
bupleurum|11v1|SRR301254.100076XX1_P1
bupleurum|11v1|SRR301254.100467_P1
bupleurum|11v1|SRR301254.10098_P1
bupleurum|11v1|SRR301254.10148_P1
bupleurum|11v1|SRR301254.102821_P1
bupleurum|11v1|SRR301254.117013_P1
eucalyptus|11v2|CT980761_P1
eucalyptus|11v1|CT980761
bupleurum|11v1|SRR301254.147563_T1
vinca|11v1|SRR098690X122147_P1
fraxinus|11v1|SRR058827.100960_T1
phyla|11v2|SRR099038X42348_P1
arabidopsis|10v1|AT1G15270_P1
ginseng|10v1|GR873071_P1
vinca|11v1|SRR098690X184375_P1
fescue|gb161|DT699350_P1
lolium|10v1|AU249250_P1
fraxinus|11v1|SRR058827.132445_T1
amorphophallus|11v2|SRR089351X100345_P1
phyla|11v2|SRR099037X11804_P1
bruguiera|gb166|BP939355_P1
coffea|10v1|DV667153_P1
salvia|10v1|SRR014553S0002535
triphysaria|10v1|DR171571
triphysaria|10v1|SRR023500S0007334
zostera|10v1|AM766369
phalaenopsis|11v1|SRR125771.1002229XX1_T1
euphorbia||11v1|DV119597_P1
fraxinus|11v1|SRR058827.100992XX1_P1
fraxinus|11v1|SRR058827.105740_P1
fraxinus|11v1|SRR058827.109819_P1
fraxinus|11v1|SRR058827.112998_P1
fraxinus|11v1|SRR058827.130969_P1
olea|11v1|GO244557XX1_P1
olea|11v1|SRR014463.10998_P1
plantago|11v2|SRR066373X102021_P1
primula|11v1|SRR098679X13011_P1
antirrhinum|gb166|AJ559847_P1
cirsium|11v1|SRR346952.1008085_T1
cirsium|11v1|SRR346952.1008892_T1
fraxinus|11v1|SRR058827.100487_T1
cucurbita|11v1|SRR091276X105643_T1
abies|11v2|SRR098676X103278_P1
amsonia|11v1|SRR098688X122830_P1
cucurbita|11v1|SRR091276X101559_P1
distylium|11v1|SRR065077X107460XX1_P1
euonymus|11v1|SRR070038X102260_P1
euonymus|11v1|SRR070038X141304_P1
nasturtium|11v1|GH163719_P1
phyla|11v2|SRR099038X76130_P1
trigonella|11v1|SRR066194X100086_P1
valeriana|11v1|SRR099039X147982_P1
valeriana|11v1|SRR099040X71022_P1
basilicum|10v1|DY322210_P1
basilicum|10v1|DY325883_P1
citrus|gb166|BQ623463
cycas|gb166|EX927396_P1
medicago|09v1|AW698603
medicago|12v1|AW698603_P1
nasturtium|10v1|GH163719
triphysaria|10v1|SRR023500S0063788
sarracenia|11v1|SRR192669.100650_T1
bupleurum|11v1|SRR301254.104289XX1_T1
cephalotaxus|11v1|SRR064395X101889_T1
ambrosia|11v1|SRR346935.190011_P1
ambrosia|11v1|SRR346935.432767_P1
ambrosia|11v1|SRR346943.139663_P1
cirsium|11v1|SRR346952.261183_P1
cirsium|11v1|SRR349641.110690_P1
cirsium|11v1|SRR349641.123007_P1
plantago|11v2|AJ843980_P1
artemisia||10v1|EY037715_P1
artemisia||10v1|EY055263_P1
artemisia||10v1|SRR019254S0009767_P1
artemisia||10v1|SRR019254S0088250_P1
artemisia||10v1|SRR019550S0004626_P1
centaurea|gb166|EH739812_P1
cichorium|gb171|DT212035_P1
cynara|gb167|GE595140_P1
gerbera|09v1|AJ750498_P1
gerbera|09v1|AJ750942_P1
lolium|10v1|SRR029311S0016269_P1
petunia|gb171|CV296824_P1
tragopogon|10v1|SRR020205S0037348
tragopogon|10v1|SRR020205S0060119
triphysaria|10v1|EX982507
arnica|11v1|SRR099034X549516_T1
epimedium|11v1|SRR013506.42109_T1
cannabis|12v1|EW701093_P1
chelidonium|11v1|SRR084752X10734_P1
humulus|11v1|ES654110_P1
platanus|11v1|SRR096786X118170_P1
sarracenia|11v1|SRR192669.100480_P1
sarracenia|11v1|SRR192669.127001_P1
sarracenia|11v1|SRR192669.140494_P1
tripterygium|11v1|SRR098677X101722_P1
utricularia|11v1|SRR094438.147614_P1
cryptomeria|gb166|BP174151_P1
gnetum|10v1|SRR064399S0012509_P1
heritiera|10v1|SRR005795S0009522_P1
podocarpus|10v1|SRR065014S0043830_P1
sciadopitys|10v1|SRR065035S0001739
tamarix|gb166|CF200182
thellungiella|gb167|BY814668
catharanthus|11v1|EG557229_P1
euphorbia||11v1|BP959954_P1
flaveria|11v1|SRR149229.103149_P1
flaveria|11v1|SRR149229.141868_P1
flaveria|11v1|SRR149241.71553_P1
olea|11v1|SRR014463.10408_P1
catharanthus|gb166|EG557229
orobanche|10v1|SRR023495S0003009_P1
tamarix|gb166|EG967706
amborella|12v2|SRR038634.18378_T1
cedrus|11v1|SRR065007X104650_T1
cucurbita|11v1|SRR091276X103882_T1
cucurbita|11v1|SRR091276X113394_T1
cucurbita|11v1|SRR091276X134114_T1
cucurbita|11v1|SRR091276X278302_T1
euonymus|11v1|SRR070038X121832_T1
euonymus|11v1|SRR070038X177346_T1
phyla|11v2|SRR099035X175078_T1
sarracenia|11v1|SRR192669.117747_T1
scabiosa|11v1|SRR063723X101722_T1
thalictrum|11v1|SRR096787X100350_T1
hevea||10v1|CB376964_T1
jatropha||09v1|GO247022_T1
liriodendron|gb166|CK745299_T1
lotus|09v1|LLBW595688_T1
orobanche|10v1|SRR023189S0005134_T1
prunus|10v1|BU042914
pseudotsuga|10v1|SRR065119S0000572
salvia|10v1|SRR014553S0005217
ceratodon||10v1|SRR074893S0834293_T1
sequoia|10v1|SRR065044S0003578
cichorium|gb171|FL679916_T1
sarracenia|11v1|SRR192669.353196_T1
orobanche|10v1|SRR023189S0000941_P1
physcomitrella||10v1|AW477225_P1
sorghum|09v1|SB07G025450
sorghum|12v1|SB07G025450_P1
sorghum|09v1|SB06G032040
sorghum|12v1|SB06G032040_P1
brachypodium|09v1|DV469647
brachypodium|12v1|BRADI1G19830_P1
pseudoroegneria|gb167|FF360551
coffea|10v1|DV663567_P1
catharanthus|11v1|EG557262_P1
tabernaemontana|11v1|SRR098689X208821_P1
catharanthus|gb166|EG557262
antirrhinum|gb166|AJ558624_P1
nuphar|gb166|ES731316_P1
olea|11v1|SRR014463.24625_P1
aquilegia|10v2|DT747028
aristolochia|10v1|SRR039082S0056492_P1
orobanche|10v1|SRR023189S0011635_P1
vinca|11v1|SRR098690X154197_P1
chelidonium|11v1|SRR084752X100611_P1
humulus|11v1|EX516220_P1
cacao|10v1|CU493627_P1
euphorbia||11v1|DV127349_P1
cirsium|11v1|SRR346952.1037943_P1
phyla|11v2|SRR099037X115792_P1
platanus|11v1|SRR096786X101972_P1
bupleurum|11v1|SRR301254.171937_P1
cirsium|11v1|SRR346952.1029416_P1
cucurbita|11v1|FG227637XX1_P1
flaveria|11v1|SRR149229.120871_P1
flaveria|11v1|SRR149229.257301_P1
flaveria|11v1|SRR149241.26086_P1
phalaenopsis|11v1|SRR125771.1013792_P1
silene|11v1|SRR096785X10886_P1
centaurea|gb166|EH715632_P1
triphysaria|10v1|EY129481
momordica|10v1|SRR071315S0003440_T1
eschscholzia|11v1|SRR014116.137043_P1
triphysaria|10v1|EY006476
arnica|11v1|SRR099034X136477_P1
euonymus|11v1|SRR070038X166437_P1
euphorbia||11v1|BP956101_P1
flaveria|11v1|SRR149244.104981_P1
phyla|11v2|SRR099035X111531_P1
sarracenia|11v1|SRR192669.110514_P1
acacia|10v1|FS584802_P1
centaurea|gb166|EH779021_P1
petunia|gb171|CV295259_P1
prunus|10v1|BU044840
salvia|10v1|CV163987
heritiera|10v1|SRR005795S0009606_T1
cucurbita|11v1|SRR091276X112632_P1
euonymus|11v1|SRR070038X145995_P1
sarracenia|11v1|SRR192669.105920_P1
lotus|09v1|AV411597_P1
flaveria|11v1|SRR149229.183404_T1
primula|11v1|SRR098679X165172_P1
ambrosia|11v1|SRR346935.236909_P1
ambrosia|11v1|SRR346946.102089_P1
eucalyptus|11v2|SRR001659X125325_P1
trigonella|11v1|SRR066194X135604_P1
artemisia||10v1|EY075435_P1
cichorium|gb171|EH691297_P1
tragopogon|10v1|SRR020205S0006671
ambrosia|11v1|SRR346935.125104_T1
flaveria|11v1|SRR149229.44212_T1
eucalyptus|11v2|SRR001658X10263_P1
eucalyptus|11v1|SRR001659X109109
euonymus|11v1|SRR070038X220716_T1
cichorium|gb171|EL359267_P1
citrus|gb166|CF829290
eucalyptus|11v1|SRR001659X100605
nasturtium|10v1|GH169509
nasturtium|11v1|GH169509_P1
bupleurum|11v1|SRR301254.158856_T1
guizotia|10v1|GE558322_T1
cenchrus|gb166|EB654414_P1
ambrosia|11v1|SRR346935.379251_P1
eucalyptus|11v2|SRR001659X100605_P1
valeriana|11v1|SRR099039X158087_P1
curcuma|10v1|DY386428_P1
nasturtium|10v1|SRR032558S0015778
trigonella|11v1|SRR066194X158071_P1
arabidopsis|10v1|AT5G54750_P1
cycas|gb166|EX809532_P1
medicago|09v1|AI974266
medicago|12v1|AI974266_P1
eschscholzia|11v1|SRR014116.52507_P1
rhizophora|10v1|SRR005793S0004856
thellungiella|gb167|BY829428
rhizophora|10v1|SRR005793S0039343
abies|11v2|SRR098676X10670_P1
cynodon|10v1|ES296622_P1
flaveria|11v1|SRR149232.114650_T1
cynara|gb167|GE592458_P1
medicago|09v1|DW015568
medicago|12v1|DW015568_P1
vinca|11v1|SRR098690X119056_P1
gnetum|10v1|SRR064399S0040420_P1
podocarpus|10v1|SRR065014S0089867_P1
cryptomeria|gb166|BY881835_P1
sciadopitys|10v1|SRR065035S0003976
cephalotaxus|11v1|SRR064395X108699_P1
taxus|10v1|SRR032523S0001250
zostera|10v1|AM767777
sorghum|09v1|SB04G007110
sorghum|12v1|SB04G007110_P1
sorghum|12v1|SB03G029180_P1
sorghum|09v1|SB03G029170
sorghum|12v1|SB03G029170_T1
brachypodium|09v1|DV471640
brachypodium|12v1|BRADI2G44856_T1
sorghum|09v1|SB03G006340
sorghum|12v1|SB03G006340_P1
sorghum|09v1|SB10G007165
sorghum|12v1|SB10G007165_P1
brachypodium|09v1|SRR031797S0079359
brachypodium|12v1|BRADI4G23600T2_P1
sorghum|09v1|SB05G005680
sorghum|12v1|SB05G005680_P1
sorghum|09v1|SB04G004200
sorghum|12v1|SB04G004200_P1
eucalyptus|11v2|SRR001660X10716_P1
eucalyptus|11v1|SRR001660X10716
prunus|10v1|BU039281
cacao|10v1|CGD0027220_P1
aquilegia|10v2|DT762298
arabidopsis|10v1|AT5G63960_P1
sorghum|09v1|SB01G017170
sorghum|12v1|SB01G017170_P1
brachypodium|09v1|DV486633
brachypodium|12v1|BRADI3G28580_P1
brachypodium|12v1|BRADI3G23230_P1
brachypodium|09v1|DV471548
brachypodium|09v1|DV471651
brachypodium|12v1|BRADI1G61240_P1
brachypodium|12v1|BRADI1G61230T2_P1
brachypodium|09v1|GT775205
brachypodium|12v1|BRADI1G63460_P1
brachypodium|09v1|DV470400
brachypodium|12v1|BRADI1G72490_P1
brachypodium|09v1|DV481080
brachypodium|12v1|BRADI1G54650_P1
brachypodium|09v1|DV478121
brachypodium|12v1|BRADI4G36880_P1
brachypodium|09v1|GT808814
brachypodium|12v1|BRADI1G16810_P1
sorghum|09v1|SB01G037810
sorghum|12v1|SB01G037810_P1
brachypodium|09v1|GT833085
brachypodium|12v1|BRADI1G64780_P1
brachypodium|12v1|SOLX00061016_T1
brachypodium|12v1|SOLX00061016_T1
brachypodium|12v1|BRADI2G49540_P1
brachypodium|09v1|GT864163
brachypodium|12v1|GT864163_T1
sorghum|09v1|SB08G001260
sorghum|12v1|SB08G001260_P1
brachypodium|09v1|GT762130
brachypodium|12v1|BRADI4G43300_P1
pseudoroegneria|gb167|FF345192
leymus|gb166|EG388433_P1
brachypodium|09v1|CRPBD006459
brachypodium|12v1|BDPRD12V1000513_T1
brachypodium|12v1|BDPRD12V1002850_T1
brachypodium|12v1|BDPRD12V1002850_T1
brachypodium|12v1|BDPRD12V1002850_T1
brachypodium|09v1|CRPBD010137
brachypodium|12v1|BDCRP12V1047739_T1
brachypodium|09v1|DV473390
brachypodium|12v1|BRADI4G41550_P1
brachypodium|12v1|BRADI2G36470_P1
sorghum|09v1|SB05G010000
sorghum|12v1|SB05G010000_P1
brachypodium|12v1|BRADI2G22320_T1
sorghum|12v1|SB09G026270_P1
sorghum|09v1|SB04G007170
sorghum|12v1|SB04G007170_P1
brachypodium|09v1|DV485498
brachypodium|12v1|BRADI3G07700_P1
leymus|gb166|EG389317_P1
pseudoroegneria|gb167|FF340342
brachypodium|12v1|BRADI1G36830_P1
phalaenopsis|11v1|CK858753_P1
phalaenopsis|11v1|SRR125771.1026916_P1
aristolochia|10v1|FD752980_P1
ambrosia|11v1|SRR346943.112590_P1
olea|11v1|SRR014463.16487_P1
platanus|11v1|SRR096786X101189_P1
amorphophallus|11v2|SRR089351X154410_P1
euonymus|11v1|SRR070038X108655_P1
artemisia||10v1|EY035921_P1
prunus|10v1|BU039992
ambrosia|11v1|SRR346935.102367_P1
ambrosia|11v1|SRR346935.102836_P1
chelidonium|11v1|SRR084752X10130XX1_P1
tabernaemontana|11v1|SRR098689X102019_P1
utricularia|11v1|SRR094438.100168_P1
orobanche|10v1|SRR023189S0024830_P1
catharanthus|11v1|EG558267_P1
citrus|gb166|CB611197
cannabis|12v1|JK495288_P1
flaveria|11v1|SRR149229.100470_P1
flaveria|11v1|SRR149229.126130_P1
flaveria|11v1|SRR149232.108448_P1
phyla|11v2|SRR099035X100142_P1
platanus|11v1|SRR096786X101928_P1
trigonella|11v1|SRR066194X106107_P1
centaurea|gb166|EH726046_P1
lotus|09v1|LLBI418881_P1
nasturtium|10v1|SRR032558S0002899
nasturtium|11v1|SRR032558.102915_P1
nasturtium|10v1|GH168766
nasturtium|11v1|GH168766_P1
arnica|11v1|SRR099034X108350_P1
flaveria|11v1|SRR149229.122029_P1
phyla|11v2|SRR099037X106234_P1
vinca|11v1|SRR098690X124323_P1
arabidopsis|10v1|AT5G19990_P1
medicago|09v1|LLAA660628
medicago|12v1|AA660628_P1
momordica|10v1|SRR071315S0011108_T1
amsonia|11v1|SRR098688X10079_P1
amsonia|11v1|SRR098688X111547_P1
arnica|11v1|SRR099034X108322_P1
cirsium|11v1|SRR346952.1011032XX1_P1
arabidopsis|10v1|AT5G20000_P1
eschscholzia|11v1|CD480449_P1
eucalyptus|11v2|CD668547_P1
euphorbia||11v1|SRR098678X106410_P1
cichorium|gb171|DT212089_P1
coffea|10v1|CF588948_P1
triphysaria|10v1|CB815068
cirsium|11v1|SRR346952.103555_P1
cucurbita|11v1|SRR091276X104784_T1
centaurea|gb166|EH714022_P1
tragopogon|10v1|SRR020205S0013091
aquilegia|10v1|DR912932_P1
cichorium|gb171|EH701464_T1
eschscholzia|11v1|CD481664_P1
flaveria|11v1|SRR149232.14242_P1
vinca|11v1|SRR098690X117569_T1
ambrosia|11v1|SRR346935.120689_P1
distylium|11v1|SRR065077X10332_P1
valeriana|11v1|SRR099039X102285_P1
aquilegia|10v2|DR912932
fescue|gb161|DT683905_P1
plantago|11v2|SRR066373X111867_T1
cephalotaxus|11v1|SRR064395X111026_P1
vinca|11v1|SRR098690X111800_P1
amborella|12v2|FD426294_P1
amborella|12v2|FD432605_P1
cephalotaxus|11v1|SRR064395X14548_P1
brachypodium|09v1|DV469847
zostera|10v1|AM770544
ambrosia|11v1|SRR346943.101350_T1
gnetum|10v1|SRR064399S0017610_P1
marchantia|gb166|BJ852337_P1
taxus|10v1|SRR032523S0001172
ambrosia|11v1|SRR346935.103060_T1
cedrus|11v1|SRR065007X103547_P1
fraxinus|11v1|SRR058827.12308_T1
zostera|10v1|SRR057351S0018576
ceratodon||10v1|AW086694_P1
podocarpus|10v1|SRR065014S0003863_P1
artemisia||10v1|EY114257_P1
ambrosia|11v1|SRR346935.427394_P1
ambrosia|11v1|SRR346943.171955_P1
nuphar|gb166|CD473821_P1
amborella|gb166|FD426360
abies|11v2|SRR098676X104019_P1
silene|11v1|GH292895_P1
pseudotsuga|10v1|SRR065119S0001943
sciadopitys|10v1|SRR065035S0039368
physcomitrella||10v1|BY960531_P1
flaveria|11v1|SRR149229.147122_T1
cryptomeria|gb166|BP175599_P1
cycas|gb166|CB088913_P1
euphorbia||11v1|SRR098678X139562_T1
humulus|11v1|FG346179_P1
pteridium|11v1|GW574939_P1
sequoia|10v1|SRR065044S0002707
silene|11v1|SRR096785X140908_P1
brachypodium|12v1|BRADI1G23510_P1
pseudoroegneria|gb167|FF340042
leymus|gb166|CD809029_P1
fescue|gb161|CK800822_P1
lolium|10v1|AU246424_P1
pseudoroegneria|gb167|FF350119
brachypodium|09v1|GT765667
brachypodium|12v1|BRADI4G35390_P1
cynodon|10v1|ES300861_P1
brachypodium|12v1|BRADI3G02730_P1
brachypodium|09v1|GT765922
leymus|gb166|EG389023_P1
pseudoroegneria|gb167|FF346294
brachypodium|09v1|DV478227
brachypodium|12v1|BRADI1G02960_P1
sorghum|12v1|GFXNC008602X25_P1
lolium|10v1|GFXAM777385X23_T1
brachypodium|12v1|BDPRD12V1004106_T1
brachypodium|12v1|BRADI4G08053_T1
sorghum|12v1|SB0506S002020_P1
brachypodium|12v1|BRADI1G05800_P1
brachypodium|09v1|GFXEU325680X23
brachypodium|12v1|BDCRP12V1063443_T1
brachypodium|12v1|SOLX00008440_T1
pseudoroegneria|gb167|FF350971_T1
brachypodium|12v1|BDCRP12V1040005_P1
amorphophallus|11v2|SRR089351X115215_T1
amborella|12v2|FD428869_T1
arabidopsis|10v1|ATCG00740_T1
tabernaemontana|11v1|SRR098689X10070_T1
vinca|11v1|SRR098690X100243XX2_T1
petunia|gb171|CV300349_P1
catharanthus|11v1|SRR098691X100542_P1
heritiera|10v1|SRR005794S0008515_P1
ginseng|10v1|GFXAY582139X24_P1
silene|11v1|GFXAB189069X7_T1
antirrhinum|gb166|AJ558610_P1
ambrosia|11v1|SRR346935.101008_T1
guizotia|10v1|GE552365_P1
euphorbia||11v1|DV143422_T1
zostera|10v1|AM766297_T1
triphysaria|10v1|DR171572_P1
cannabis|12v1|GR222152_T1
cynara|gb167|GE580888_T1
tripterygium|11v1|SRR098677X118761XX3_T1
amborella|12v2|AMB12V2CRP112003_T1
cannabis|12v1|MDCRP100988_P1
trigonella|11v1|SRR066194X102109_P1
plantago|11v2|SRR066373X101440_T1
lotus|09v1|GFXAP002983X29_P1
fagopyrum|11v1|GFXEU254477X24_T1
tabernaemontana|11v1|SRR098689X115121_T1
jatropha||09v1|GFXFJ695500X22_P1
tripterygium|11v1|SRR098677X100034XX1_P1
medicago|12v1|MTPRD043867_T1
leymus|gb166|DY895747_T1
lotus|09v1|CRPLJ020612_T1
liriodendron|gb166|GFXAF123796X1_P1
brachypodium|12v1|SOLX00058314_P1
brachypodium|09v1|GT763524
brachypodium|12v1|BRADI4G11670_P1
sorghum|09v1|SB03G030830
sorghum|12v1|SB03G030830_P1
brachypodium|09v1|GT792764
brachypodium|12v1|BRADI2G46277_P1
amorphophallus|11v2|SRR089351X105880_P1
sorghum|09v1|SB07G005180
sorghum|12v1|SB07G005180_T1
brachypodium|09v1|DV477678
sorghum|09v1|SB04G037460
brachypodium|09v1|CRPBD010426
brachypodium|12v1|SOLX00039853_T1
brachypodium|12v1|SOLX00039853_T1
brachypodium|12v1|SOLX00039853_T1
brachypodium|12v1|BDPRD12V1000412_P1
brachypodium|12v1|BRADI1G47050_T1
brachypodium|09v1|SRR031797S0149787
sorghum|09v1|SB10G005910
sorghum|12v1|SB10G005910_T1
sorghum|12v1|SB01G002350_T1
sorghum|12v1|SB12V1CRP000248_T1
sorghum|09v1|SB01G002340
sorghum|09v1|SB02G034180
sorghum|12v1|SB02G034180_T1
sorghum|09v1|SB06G020470
sorghum|12v1|SB06G020470_P1
sorghum|12v1|SB10G006400_T1
cannabis|12v1|SOLX00047290_T1
eschscholzia|11v1|CK759888_T1
amborella|12v2|SRR038637.200754_P1
abies|11v2|SRR098676X204510_T1
cannabis|12v1|JK498546_T1
humulus|11v1|SRR098684X111065_T1
amorphophallus|11v2|SRR089351X113896_T1
sequoia|10v1|SRR065044S0195288
taxus|10v1|SRR032523S0026526
platanus|11v1|SRR096786X262173_P1
eucalyptus|11v2|CT986494_T1
guizotia|10v1|GE557732_T1
lotus|09v1|CRPLJ004951_T1
sciadopitys|10v1|SRR065035S0161405
cephalotaxus|11v1|SRR064395X196722_P1
trigonella|11v1|SRR066194X265059_T1
tripterygium|11v1|SRR098677X113789_P1
tripterygium|11v1|SRR098677X225048_P1
cannabis|12v1|JK501057_T1
humulus|11v1|SRR098684X164760_T1
cichorium|gb171|EH700156_T1
pseudotsuga|10v1|SRR065119S0002637
eucalyptus|11v1|CT986494
brachypodium|09v1|GT759895
brachypodium|12v1|BRADI1G46640T2_T1
papaya|gb165|EX256125_T1
cucurbita|11v1|SRR091276X123019_T1
euonymus|11v1|SRR070038X164269_T1
olea|11v1|SRR014464.38760_T1
vinca|11v1|SRR098690X22825_T1
arabidopsis|10v1|AT4G21090_T1
physcomitrella||10v1|AW145591_T1
sorghum|09v1|SB02G003530
sorghum|12v1|SB02G003530_P1
sorghum|12v1|BG048733_T1
sorghum|12v1|SB12V1CUFF43842T1P2_T1
brachypodium|09v1|SRR031795S0021480
brachypodium|12v1|BDCRP12V1033046_T1
brachypodium|09v1|CRPBD020292
sorghum|09v1|SBGWP040163
amborella|12v2|GFXAF235047X1_T1
amborella|12v2|GFXAJ506156X22_T1
platanus|11v1|GFXDQ923116X23_T1
amborella|12v2|SRR038634.10442_T1
amsonia|11v1|SRR098688X100366_T1
aristolochia|10v1|GFXAF528893X1_T1
tragopogon|10v1|SRR020205S0000675
nasturtium|10v1|SRR032558S0003041
medicago|12v1|AW256478_T1
medicago|12v1|AW559313_T1
rhizophora|10v1|SRR005792S0004605
euonymus|11v1|GFXGQ998190X1_T1
sorghum|09v1|SB0506S002020
cucurbita|11v1|SRR091276X10414_T1
prunus|10v1|CN848687_T1
salvia|10v1|FE536543
cannabis|12v1|GR221477_T1
momordica|10v1|SRR071315S0000098_T1
euphorbia||11v1|DV124656_T1
tabernaemontana|11v1|SRR098689X100380_T1
sorghum|12v1|SB06G029270_P1
pseudotsuga|10v1|SRR065119S0049481
cedrus|11v1|SRR065007X112403_T1
abies|11v2|SRR098676X100684_P1
zostera|10v1|AM766384
sorghum|12v1|SB10G025110_P1
sorghum|09v1|SB06G025390
brachypodium|09v1|GT799879
sorghum|09v1|SB01G028150
sorghum|12v1|SB01G028150_P1
sorghum|12v1|SB04G024430_T1
sorghum|09v1|SB06G028430
sorghum|12v1|SB06G028430_P1
sorghum|09v1|SB04G024425
sorghum|12v1|SB01G033630_P1
sorghum|09v1|SB06G025650
sorghum|12v1|SB06G025650_P1
brachypodium|09v1|GT763030
brachypodium|12v1|BRADI2G57087_P1
sorghum|09v1|SB03G012520
sorghum|12v1|SB03G012520_P1
leymus|gb166|EG384632_P1
sorghum|09v1|SB02G027510
sorghum|12v1|SB02G027510_P1
brachypodium|09v1|SRR031795S0043310
brachypodium|12v1|BRADI5G09817_P1
sorghum|12v1|SB01G007170_P1
sorghum|09v1|SB01G007170
sorghum|09v1|SB03G009700
sorghum|12v1|SB03G009700_P1
brachypodium|09v1|DV483417
brachypodium|12v1|BRADI2G08960_P1
fescue|gb161|DT679374_P1
eucalyptus|11v2|CD668810_P1
eucalyptus|11v1|CD668810
amorphophallus|11v2|SRR089351X2550_P1
aquilegia|10v2|DR928227
cacao|10v1|CU476740_P1
aristolochia|10v1|SRR039082S0002761_P1
amorphophallus|11v2|SRR089351X188349_P1
cirsium|11v1|SRR346952.1038670_P1
cannabis|12v1|JK496040_P1
euphorbia||11v1|BI961995_P1
arnica|11v1|SRR099034X100054_P1
cirsium|11v1|SRR346952.206135_P1
centaurea|gb166|EH712147_P1
cirsium|11v1|SRR346952.1011854_P1
tabernaemontana|11v1|SRR098689X114962_P1
flaveria|11v1|SRR149229.56663_P1
humulus|11v1|GD242787_P1
medicago|09v1|AI974575
medicago|12v1|AI974575_P1
cirsium|11v1|SRR346952.145853_P1
catharanthus|11v1|EG558780_P1
vinca|11v1|SRR098690X101115_P1
flaveria|11v1|SRR149229.155880_P1
prunus|10v1|BU042321
sequoia|10v1|SRR065044S0000578
chelidonium|11v1|SRR084752X118599_P1
prunus|10v1|BU573305
cephalotaxus|11v1|SRR064395X100052_P1
medicago|09v1|BE187613
medicago|12v1|BE187613_P1
ambrosia|11v1|SRR346935.136110_P1
amsonia|11v1|SRR098688X100899_P1
eucalyptus|11v2|CD668073_P1
trigonella|11v1|SRR066194X146772_P1
eucalyptus|11v1|CD668073
cichorium|gb171|EH673771_P1
lotus|09v1|CRPLJ011361_P1
taxus|10v1|SRR032523S0008792
catharanthus|11v1|EG560749_P1
eschscholzia|11v1|CK752191_P1
euonymus|11v1|SRR070038X117930_P1
podocarpus|10v1|SRR065014S0001157_P1
phalaenopsis|11v1|HO059358_P1
pseudotsuga|10v1|SRR065119S0006823
ambrosia|11v1|SRR346935.134706_P1
arnica|11v1|SRR099034X101482_P1
cedrus|11v1|SRR065007X104038_P1
flaveria|11v1|SRR149229.11178_P1
phyla|11v2|SRR099035X111448_P1
cacao|10v1|CU500965_P1
arnica|11v1|SRR099034X104265_T1
flaveria|11v1|SRR149229.11815_T1
abies|11v2|SRR098676X100270_P1
amborella|12v2|CK758678_P1
cirsium|11v1|SRR346952.1131212_P1
citrus|gb166|CK665649
eschscholzia|11v1|SRR014116.19395_P1
eucalyptus|11v2|ES592214_P1
phalaenopsis|11v1|SRR125771.1003109_P1
eucalyptus|11v1|ES592214
ambrosia|11v1|SRR346935.11371_T1
vinca|11v1|SRR098690X131031_P1
medicago|09v1|AW257189
medicago|12v1|AW257189_P1
valeriana|11v1|SRR099039X106946_T1
artemisia||10v1|EY111321_T1
artemisia||10v1|EY085219_P1
cacao|10v1|CU473459_P1
ambrosia|11v1|SRR346935.144595_T1
trigonella|11v1|SRR066194X248935_T1
citrus|gb166|CF419828
cynara|gb167|GE577965_P1
trigonella|11v1|SRR066194X168106_P1
nasturtium|10v1|SRR032558S0000067
orobanche|10v1|SRR023189S0019902_P1
ambrosia|11v1|SRR346935.120699_P1
arabidopsis|10v1|AT4G16143_P1
tabernaemontana|11v1|SRR098689X103178XX1_P1
zostera|10v1|SRR057351S0003096_T1
sorghum|09v1|SLXL50313361D1
sorghum|12v1|SB12V1CRP006190_P1
amorphophallus|11v2|SRR089351X107338_T1
sorghum|12v1|GFXEF115542X26_P1
brachypodium|09v1|TMPLOS04G16714T1
brachypodium|09v1|GFXEU325680X24
brachypodium|12v1|BRADI4G37052_P1
lolium|10v1|GFXAM777385X24_P1
amorphophallus|11v2|SRR089351X300894_P1
euonymus|11v1|GFXAY237135X2_T1
eucalyptus|11v2|CT981419_P1
eucalyptus|11v2|GFXAY780259X26_P1
eucalyptus|11v1|GFXAY780259X26
medicago|12v1|BG644701_P1
olea|11v1|SRR014465.6187_P1
ginseng|10v1|GFXAY582139X25_P1
prunus|10v1|CN856608
guizotia|10v1|GE572902_P1
amborella|12v2|FD429846_P1
fagopyrum|11v1|GFXEU254477X25_P1
arabidopsis|10v1|ATCG00065_P1
jatropha||09v1|GFXFJ695500X23_P1
liriodendron|gb166|GFXAF123782X3_P1
zamia|gb166|GFXAF188850X3
sorghum|09v1|SB04G004490
sorghum|12v1|SB04G004490_P1
cenchrus|gb166|EB655195_P1
sorghum|09v1|SB10G025230
sorghum|12v1|SB10G025230_P1
sorghum|09v1|SB10G005880
brachypodium|09v1|GT799154
brachypodium|12v1|BRADI1G47080_P1
sorghum|12v1|SB10G005880_P1
sorghum|09v1|SB01G017340
sorghum|12v1|SB01G017340_P1
sorghum|12v1|SB10G024680_P1
brachypodium|12v1|BRADI1G35600_P1
brachypodium|12v1|BRADI4G08030_P1
brachypodium|09v1|DV473324
brachypodium|09v1|GT779639
brachypodium|12v1|BRADI1G48350_T1
leymus|gb166|EG379262_P1
brachypodium|09v1|DV485204
brachypodium|12v1|BRADI5G14260_P1
leymus|gb166|EG390543_P1
sorghum|09v1|SB02G043130
sorghum|12v1|SB02G043130_P1
sorghum|09v1|SB10G001780
sorghum|12v1|SB10G001780_P1
lolium|10v1|AU247800_P1
fescue|gb161|DT690833_T1
amaranthus|10v1|SRR039411S0011389
phyla|11v2|SRR099035X115605
ginseng|10v1|EC599983
medicago|12v1|MTPRD023600
centaurea|gb166|EH785657
lotus|09v1|CRPLJ011653
phyla|11v2|SRR099037X11582
arnica|11v1|SRR099034X10033
brachypodium|12v1|BDPRD12V1004628
ceratodon||10v1|SRR074891S0680381XX1
tripterygium|11v1|SRR098677X100669XX1
medicago|12v1|MTPRD017482
orobanche|10v1|SRR023189S0001383
artemisia||10v1|SRR019254S0053783
lotus|09v1|CRPLJ040450
tripterygium|11v1|SRR098677X106141
lotus|09v1|CRPLJ003115
conyza|10v1|SRR035294S0015476
eucalyptus|11v2|SRR001659X124697
phyla|11v2|SRR099035X10108
coffea|10v1|CF588735
vinca|11v1|SRR098690X109897XX3
sorghum|12v1|SB12V1CRP123950
lotus|09v1|CRPLJ016207
medicago|12v1|MTPRD016895
lotus|09v1|CRPLJ031511
The output of the functional genomics approach described herein is a set of genes highly predicted to improve yield and/or other agronomic important traits such as growth rate, vigor, oil content, fiber yield and/or quality, biomass, growth rate, abiotic stress tolerance, nitrogen use efficiency, water use efficiency and fertilizer use efficiency of a plant by increasing their expression. Although each gene is predicted to have its own impact, modifying the mode of expression of more than one gene is expected to provide an additive or synergistic effect on the plant yield and/or other agronomic important yields performance. Altering the expression of each gene described herein alone or a set of genes together increases the overall yield and/or other agronomic important traits, hence expects to increase agricultural productivity.
In order to produce a high throughput correlation analysis, the present inventors utilized a Barley oligonucleotide micro-array, produced by Agilent Technologies [Hypertext Transfer Protocol://World Wide Web (dot) chem. (dot) agilent (dot) com/Scripts/PDS (dot) asp?1Page=50879]. The array oligonucleotide represents about 47,500 Barley genes and transcripts. In order to define correlations between the levels of RNA expression and yield or vigor related parameters, various plant characteristics of 25 different Barley accessions were analyzed. Among them, 13 accessions encompassing the observed variance were selected for RNA expression analysis. The correlation between the RNA levels and the characterized parameters was analyzed using Pearson correlation test [Hypertext Transfer Protocol://World Wide Web (dot) davidmlane (dot) com/hyperstat/A34739 (dot) html].
Experimental Procedures
Five tissues at different developmental stages [meristem, flower, booting spike, and stem], representing different plant characteristics, were sampled and RNA was extracted as described hereinabove under “GENERAL EXPERIMENTAL AND BIOINFORMATICS METHODS”.
For convenience, each micro-array expression information tissue type has received a Set ID as summarized in Table 3 below.
Barley yield components and vigor related parameters assessment—13 Barley accessions in 4 repetitive blocks (named A, B, C, and D), each containing 4 plants per plot were grown at net house. Plants were phenotyped on a daily basis following the standard descriptor of barley (Table 4, below). Harvest was conducted while 50% of the spikes were dry to avoid spontaneous release of the seeds. Plants were separated to the vegetative part and spikes, of them, 5 spikes were threshed (grains were separated from the glumes) for additional grain analysis such as size measurement, grain count per spike and grain yield per spike. All material was oven dried and the seeds were threshed manually from the spikes prior to measurement of the seed characteristics (weight and size) using scanning and image analysis. The image analysis system included a personal desktop computer (Intel P4 3.0 GHz processor) and a public domain program—ImageJ 1.37 (Java based image processing program, which was developed at the U.S. National Institutes of Health and freely available on the internet [Hypertext Transfer Protocol://rsbweb (dot) nih (dot) gov/]. Next, analyzed data was saved to text files and processed using the JMP statistical analysis software (SAS institute).
At the end of the experiment (50% of the spikes were dry) all spikes from plots within blocks A-D were collected, and the following measurements were performed:
(i) Grains per spike—The total number of grains from 5 spikes that were manually threshed was counted. The average grain per spike was calculated by dividing the total grain number by the number of spikes.
(ii) Grain average size (cm)—The total grains from 5 spikes that were manually threshed were scanned and images were analyzed using the digital imaging system. Grain scanning was done using Brother scanner (model DCP-135), at the 200 dpi resolution and analyzed with Image J software. The average grain size was calculated by dividing the total grain size by the total grain number.
(iii) Grain average weight (mgr)—The total grains from 5 spikes that were manually threshed were counted and weight. The average weight was calculated by dividing the total weight by the total grain number.
(iv) Grain yield per spike (gr)—The total grains from 5 spikes that were manually threshed were weight. The grain yield was calculated by dividing the total weight by the spike number.
(v) Spike length analysis—The five chosen spikes per plant were measured using measuring tape excluding the awns.
(vi) Spike number analysis—The spikes per plant were counted.
Additional parameters were measured as follows:
Growth habit scoring—At growth stage 10 (booting), each of the plants was scored for its growth habit nature. The scale that was used was 1 for prostate nature till 9 for erect.
Hairiness of basal leaves—At growth stage 5 (leaf sheath strongly erect; end of tillering), each of the plants was scored for its hairiness nature of the leaf before the last. The scale that was used was 1 for prostate nature till 9 for erect.
Plant height—At harvest stage (50% of spikes were dry), each of the plants was measured for its height using measuring tape. Height was measured from ground level to top of the longest spike excluding awns.
Days to flowering—Each of the plants was monitored for flowering date. Days of flowering was calculated from sowing date till flowering date.
Stem pigmentation—At growth stage 10 (booting), each of the plants was scored for its stem color. The scale that was used was 1 for green till 5 for full purple.
Vegetative dry weight and spike yield—At the end of the experiment (50% of the spikes were dry) all spikes and vegetative material from plots within blocks A-D are collected. The biomass and spikes weight of each plot was separated, measured and divided by the number of plants.
Dry weight=total weight of the vegetative portion above ground (excluding roots) after drying at 70° C. in oven for 48 hours.
Spike yield per plant=total spike weight per plant (gr) after drying at 30° C. in oven for 48 hours.
Experimental Results
13 different Barley accessions were grown and characterized for 12 parameters as described above. The average for each of the measured parameter was calculated using the JMP software and values are summarized in Tables 6 and 7 below. Subsequent correlation analysis between the various transcriptom expression sets (Table 3) and the average parameters was conducted. Follow, results were integrated to the database (Table 8 below).
To produce a high throughput correlation analysis, the present inventors utilized an Arabidopsis thaliana oligonucleotide micro-array, produced by Agilent Technologies [Hypertext Transfer Protocol://World Wide Web (dot) chem. (dot) agilent (dot) com/Scripts/PDS (dot) asp?1Page=50879]. The array oligonucleotide represents about 40,000 A. thaliana genes and transcripts designed based on data from the TIGR ATH1 v.5 database and Arabidopsis MPSS (University of Delaware) databases. To define correlations between the levels of RNA expression and yield, biomass components or vigor related parameters, various plant characteristics of 15 different Arabidopsis ecotypes were analyzed. Among them, nine ecotypes encompassing the observed variance were selected for RNA expression analysis. The correlation between the RNA levels and the characterized parameters was analyzed using Pearson correlation test [Hypertext Transfer Protocol://World Wide Web (dot) davidmlane (dot) com/hyperstat/A34739 (dot) html].
Experimental Procedures
Analyzed Arabidopsis tissues—Five tissues at different developmental stages including root, leaf, flower at anthesis, seed at 5 days after flowering (DAF) and seed at 12 DAF, representing different plant characteristics, were sampled and RNA was extracted as described as described hereinabove under “GENERAL EXPERIMENTAL AND BIOINFORMATICS METHODS”. For convenience, each micro-array expression information tissue type has received a Set ID as summarized in Table 9 below.
Yield components and vigor related parameters assessment—Eight out of the nine Arabidopsis ecotypes were used in each of 5 repetitive blocks (named A, B, C, D and E), each containing 20 plants per plot. The plants were grown in a greenhouse at controlled conditions in 22° C., and the N:P:K fertilizer (20:20:20; weight ratios) [nitrogen (N), phosphorus (P) and potassium (K)] was added. During this time data was collected, documented and analyzed. Additional data was collected through the seedling stage of plants grown in a tissue culture in vertical grown transparent agar plates. Most of chosen parameters were analyzed by digital imaging.
Digital imaging in tissue culture—A laboratory image acquisition system was used for capturing images of plantlets sawn in square agar plates. The image acquisition system consists of a digital reflex camera (Canon EOS 300D) attached to a 55 mm focal length lens (Canon EF-S series), mounted on a reproduction device (Kaiser RS), which included 4 light units (4×150 Watts light bulb) and located in a darkroom.
Digital imaging in greenhouse—The image capturing process was repeated every 3-4 days starting at day 7 till day 30. The same camera attached to a 24 mm focal length lens (Canon EF series), placed in a custom made iron mount, was used for capturing images of larger plants sawn in white tubs in an environmental controlled greenhouse. The white tubs were square shape with measurements of 36×26.2 cm and 7.5 cm deep. During the capture process, the tubs were placed beneath the iron mount, while avoiding direct sun light and casting of shadows. This process was repeated every 3-4 days for up to 30 days.
An image analysis system was used, which consists of a personal desktop computer (Intel P4 3.0 GHz processor) and a public domain program—ImageJ 1.37, Java based image processing program, which was developed at the U.S. National Institutes of Health and is freely available on the internet at Hypertext Transfer Protocol://rsbweb (dot) nih (dot) gov/. Images were captured in resolution of 6 Mega Pixels (3072×2048 pixels) and stored in a low compression JPEG (Joint Photographic Experts Group standard) format. Next, analyzed data was saved to text files and processed using the JMP statistical analysis software (SAS institute).
Leaf analysis—Using the digital analysis leaves data was calculated, including leaf number, area, perimeter, length and width. On day 30, 3-4 representative plants were chosen from each plot of blocks A, B and C. The plants were dissected, each leaf was separated and was introduced between two glass trays, a photo of each plant was taken and the various parameters (such as leaf total area, laminar length etc.) were calculated from the images. The blade circularity was calculated as laminar width divided by laminar length.
Root analysis—During 17 days, the different ecotypes were grown in transparent agar plates. The plates were photographed every 3 days starting at day 7 in the photography room and the roots development was documented (see examples in
Relative growth rate of root coverage=Regression coefficient of root coverage along time course. Formula V
Vegetative growth rate analysis—was calculated according to Formula VI. The analysis was ended with the appearance of overlapping plants.
Relative vegetative growth rate area=Regression coefficient of vegetative area along time course. Formula VI
For comparison between ecotypes the calculated rate was normalized using plant developmental stage as represented by the number of true leaves. In cases where plants with 8 leaves had been sampled twice (for example at day 10 and day 13), only the largest sample was chosen and added to the Anova comparison.
Seeds in siliques analysis—On day 70, 15-17 siliques were collected from each plot in blocks D and E. The chosen siliques were light brown color but still intact. The siliques were opened in the photography room and the seeds were scatter on a glass tray, a high resolution digital picture was taken for each plot. Using the images the number of seeds per silique was determined.
Seeds average weight—At the end of the experiment all seeds from plots of blocks A-C were collected. An average weight of 0.02 grams was measured from each sample, the seeds were scattered on a glass tray and a picture was taken. Using the digital analysis, the number of seeds in each sample was calculated.
Oil percentage in seeds—At the end of the experiment all seeds from plots of blocks A-C were collected. Columbia seeds from 3 plots were mixed grounded and then mounted onto the extraction chamber. 210 ml of n-Hexane (Cat No. 080951 Biolab Ltd.) were used as the solvent. The extraction was performed for 30 hours at medium heat 50° C. Once the extraction has ended the n-Hexane was evaporated using the evaporator at 35° C. and vacuum conditions. The process was repeated twice. The information gained from the Soxhlet extractor (Soxhlet, F. Die gewichtsanalytische Bestimmung des Milchfettes, Polytechnisches J. (Dingler's) 1879, 232, 461) was used to create a calibration curve for the Low Resonance NMR. The content of oil of all seed samples was determined using the Low Resonance NMR (MARAN Ultra-Oxford Instrument) and its MultiQuant software package.
Silique length analysis—On day 50 from sowing, 30 siliques from different plants in each plot were sampled in block A. The chosen siliques were green-yellow in color and were collected from the bottom parts of a grown plant's stem. A digital photograph was taken to determine silique's length.
Dry weight and seed yield—On day 80 from sowing, the plants from blocks A-C were harvested and left to dry at 30° C. in a drying chamber. The biomass and seed weight of each plot was separated, measured and divided by the number of plants. Dry weight=total weight of the vegetative portion above ground (excluding roots) after drying at 30° C. in a drying chamber; Seed yield per plant=total seed weight per plant (gr).
Oil yield—The oil yield was calculated using Formula VII.
Seed Oil yield=Seed yield per plant (gr.)*Oil % in seed. Formula VII
Harvest Index (seed)—The harvest index was calculated using Formula IV (described above): Harvest Index=Average seed yield per plant/Average dry weight.
Experimental Results
Nine different Arabidopsis ecotypes were grown and characterized for 18 parameters (named as vectors).
Arabidopsis correlated parameters (vectors)
The characterized values are summarized in Tables 11 and 12 below.
In order to produce a high throughput correlation analysis, the present inventors utilized an Arabidopsis oligonucleotide micro-array, produced by Agilent Technologies [Hypertext Transfer Protocol://World Wide Web (dot) chem (dot) agilent (dot) com/Scripts/PDS (dot) asp?1Page=50879]. The array oligonucleotide represents about 44,000 Arabidopsis genes and transcripts. To define correlations between the levels of RNA expression with NUE, yield components or vigor related parameters various plant characteristics of 14 different Arabidopsis ecotypes were analyzed. Among them, ten ecotypes encompassing the observed variance were selected for RNA expression analysis. The correlation between the RNA levels and the characterized parameters was analyzed using Pearson correlation test [Hypertext Transfer Protocol://World Wide Web (dot) davidmlane (dot) com/hyperstat/A34739 (dot) html].
Experimental Procedures
Two tissues of plants [leaves and stems] growing at two different nitrogen fertilization levels (1.5 mM Nitrogen or 6 mM Nitrogen) were sampled and RNA was extracted as described hereinabove under “GENERAL EXPERIMENTAL AND BIOINFORMATICS METHODS”. For convenience, each micro-array expression information tissue type has received a Set ID as summarized in Table 13 below.
Assessment of Arabidopsis yield components and vigor related parameters under different nitrogen fertilization levels—10 Arabidopsis accessions in 2 repetitive plots each containing 8 plants per plot were grown at greenhouse. The growing protocol used was as follows: surface sterilized seeds were sown in Eppendorf tubes containing 0.5×Murashige-Skoog basal salt medium and grown at 23° C. under 12-hour light and 12-hour dark daily cycles for 10 days. Then, seedlings of similar size were carefully transferred to pots filled with a mix of perlite and peat in a 1:1 ratio. Constant nitrogen limiting conditions were achieved by irrigating the plants with a solution containing 1.5 mM inorganic nitrogen in the form of KNO3, supplemented with 2 mM CaCl2, 1.25 mM KH2PO4, 1.50 mM MgSO4, 5 mM KCl, 0.01 mM H3BO3 and microelements, while normal irrigation conditions (Normal Nitrogen conditions) was achieved by applying a solution of 6 mM inorganic nitrogen also in the form of KNO3, supplemented with 2 mM CaCl2, 1.25 mM KH2PO4, 1.50 mM MgSO4, 0.01 mM H3BO3 and microelements. To follow plant growth, trays were photographed the day nitrogen limiting conditions were initiated and subsequently every 3 days for about 15 additional days. Rosette plant area was then determined from the digital pictures. ImageJ software was used for quantifying the plant size from the digital pictures [Hypertext Transfer Protocol://rsb (dot) info (dot) nih (dot) gov/ij/] utilizing proprietary scripts designed to analyze the size of rosette area from individual plants as a function of time. The image analysis system included a personal desktop computer (Intel P4 3.0 GHz processor) and a public domain program—ImageJ 1.37 (Java based image processing program, which was developed at the U.S. National Institutes of Health and freely available on the internet [Hypertext Transfer Protocol://rsbweb (dot) nih (dot) gov/]. Next, analyzed data was saved to text files and processed using the JMP statistical analysis software (SAS institute).
Data parameters collected are summarized in Table 14, hereinbelow.
Arabidopsis correlated parameters (vectors)
Assessment of NUE, yield components and vigor-related parameters—Ten Arabidopsis ecotypes were grown in trays, each containing 8 plants per plot, in a greenhouse with controlled temperature conditions for about 12 weeks. Plants were irrigated with different nitrogen concentration as described above depending on the treatment applied. During this time, data was collected documented and analyzed. Most of chosen parameters were analyzed by digital imaging.
Digital Imaging—Greenhouse Assay
An image acquisition system, which consists of a digital reflex camera (Canon EOS 400D) attached with a 55 mm focal length lens (Canon EF-S series) placed in a custom made Aluminum mount, was used for capturing images of plants planted in containers within an environmental controlled greenhouse. The image capturing process is repeated every 2-3 days starting at day 9-12 till day 16-19 (respectively) from transplanting.
The image processing system which was used is described in Example 4 above. Images were captured in resolution of 10 Mega Pixels (3888×2592 pixels) and stored in a low compression JPEG (Joint Photographic Experts Group standard) format. Next, image processing output data was saved to text files and analyzed using the JMP statistical analysis software (SAS institute).
Leaf analysis—Using the digital analysis leaves data was calculated, including leaf number, leaf blade area, plot coverage, Rosette diameter and Rosette area.
Relative growth rate area: The relative growth rate area of the rosette and the leaves was calculated according to Formulas VIII and IX, respectively.
Relative growth rate of rosette area=Regression coefficient of rosette area along time course. Formula VIII
Relative growth rate of plant leaf number=Regression coefficient of plant leaf number along time course. Formula IX
Seed yield and 1000 seeds weight—At the end of the experiment all seeds from all plots were collected and weighed in order to measure seed yield per plant in terms of total seed weight per plant (gr.). For the calculation of 1000 seed weight, an average weight of 0.02 grams was measured from each sample, the seeds were scattered on a glass tray and a picture was taken. Using the digital analysis, the number of seeds in each sample was calculated.
Dry weight and seed yield—At the end of the experiment, plant were harvested and left to dry at 30° C. in a drying chamber. The biomass was separated from the seeds, weighed and divided by the number of plants. Dry weight=total weight of the vegetative portion above ground (excluding roots) after drying at 30° C. in a drying chamber.
Harvest Index (seed)—The harvest index was calculated using Formula IV as described above [Harvest Index=Average seed yield per plant/Average dry weight].
T50 days to flowering—Each of the repeats was monitored for flowering date. Days of flowering was calculated from sowing date till 50% of the plots flowered.
Plant nitrogen level—The chlorophyll content of leaves is a good indicator of the nitrogen plant status since the degree of leaf greenness is highly correlated to this parameter. Chlorophyll content was determined using a Minolta SPAD 502 chlorophyll meter and measurement was performed at time of flowering. SPAD meter readings were done on young fully developed leaf. Three measurements per leaf were taken per plot. Based on this measurement, parameters such as the ratio between seed yield per nitrogen unit [seed yield/N level=seed yield per plant [gr.]/SPAD unit], plant DW per nitrogen unit [DW/N level=plant biomass per plant [gr.]/SPAD unit], and nitrogen level per gram of biomass [N level/DW=SPAD unit/plant biomass per plant (gr.)] were calculated.
Percent of seed yield reduction—measures the amount of seeds obtained in plants when grown under nitrogen-limiting conditions compared to seed yield produced at normal nitrogen levels expressed in percentages (%).
Experimental Results
10 different Arabidopsis accessions (ecotypes) were grown and characterized for 37 parameters as described above. The average for each of the measured parameters was calculated using the JMP software (Table 15 below). Subsequent correlation analysis between the various transcriptom sets (Table 13) and the average parameters were conducted.
In order to produce a high throughput correlation analysis between plant phenotype and gene expression level, the present inventors utilized a sorghum oligonucleotide micro-array, produced by Agilent Technologies [Hypertext Transfer Protocol://World Wide Web (dot) chem. (dot) agilent (dot) com/Scripts/PDS (dot) asp?1Page=50879]. The array oligonucleotide represents about 44,000 Sorghum genes and transcripts. In order to define correlations between the levels of RNA expression with ABST, yield and NUE components or vigor related parameters, various plant characteristics of 17 different sorghum hybrids were analyzed. Among them, 10 hybrids encompassing the observed variance were selected for RNA expression analysis. The correlation between the RNA levels and the characterized parameters was analyzed using Pearson correlation test [Hypertext Transfer Protocol://World Wide Web (dot) davidmlane (dot) com/hyperstat/A34739 (dot) html].
I. Correlation of Sorghum Varieties Across Ecotypes Grown Under Regular Growth Conditions, Severe Drought Conditions and Low Nitrogen Conditions
Experimental Procedures
17 Sorghum varieties were grown in 3 repetitive plots, in field. Briefly, the growing protocol was as follows:
1. Regular growth conditions: sorghum plants were grown in the field using commercial fertilization and irrigation protocols (370 liter per meter2, fertilization of 14 units of 21% urea per entire growth period).
2. Drought conditions: sorghum seeds were sown in soil and grown under normal condition until around 35 days from sowing, around stage V8 (eight green leaves are fully expanded, booting not started yet). At this point, irrigation was stopped, and severe drought stress was developed.
3. Low nitrogen fertilization conditions: sorghum plants were fertilized with 50% less amount of nitrogen in the field than the amount of nitrogen applied in the regular growth treatment. All the fertilizer was applied before flowering.
Analyzed Sorghum tissues—All 10 selected Sorghum hybrids were sample per each treatment. Tissues [Flag leaf, Flower meristem and Flower] from plants growing under normal conditions, severe drought stress and low nitrogen conditions were sampled and RNA was extracted as described above. Each micro-array expression information tissue type has received a Set ID as summarized in Table 16 below.
Sorghum transcriptom expression sets
The following parameters were collected using digital imaging system:
At the end of the growing period the grains were separated from the Plant ‘Head’ and the following parameters were measured and collected:
Average Grain Area (cm2)—A sample of ˜200 grains were weight, photographed and images were processed using the below described image processing system. The grain area was measured from those images and was divided by the number of grains.
(ii) Upper and Lower Ratio Average of Grain Area, width, diameter and perimeter—Grain projection of area, width, diameter and perimeter were extracted from the digital images using open source package imagej (nih). Seed data was analyzed in plot average levels as follows:
Average of all seeds;
Average of upper 20% fraction—contained upper 20% fraction of seeds; and
Average of lower 20% fraction—contained lower 20% fraction of seeds;
Further on, ratio between each fraction and the plot average was calculated for each of the data parameters.
At the end of the growing period 5 ‘Heads’ were, photographed and images were processed using the below described image processing system.
(i) Head Average Area (cm2)—At the end of the growing period 5 ‘Heads’ were photographed and images were processed using the below described image processing system. The ‘Head’ area was measured from those images and was divided by the number of ‘Heads’.
(ii) Head Average Length (cm)—At the end of the growing period 5 ‘Heads’ were photographed and images were processed using the below described image processing system. The ‘Head’ length (longest axis) was measured from those images and was divided by the number of ‘Heads’.
(iii) Head Average Width (cm)—At the end of the growing period 5 ‘Heads’ were photographed and images were processed using the below described image processing system. The ‘Head’ width was measured from those images and was divided by the number of ‘Heads’.
(iiii) Head Average Width (cm)—At the end of the growing period 5 ‘Heads’ were photographed and images were processed using the below described image processing system. The ‘Head’ perimeter was measured from those images and was divided by the number of ‘Heads’.
The image processing system was used, which consists of a personal desktop computer (Intel P4 3.0 GHz processor) and a public domain program—ImageJ 1.37, Java based image processing software, which was developed at the U.S. National Institutes of Health and is freely available on the internet at Hypertext Transfer Protocol://rsbweb (dot) nih (dot) gov/. Images were captured in resolution of 10 Mega Pixels (3888×2592 pixels) and stored in a low compression JPEG (Joint Photographic Experts Group standard) format. Next, image processing output data for seed area and seed length was saved to text files and analyzed using the JMP statistical analysis software (SAS institute).
Additional parameters were collected either by sampling 5 plants per plot or by measuring the parameter across all the plants within the plot.
Total Grain Weight/Head (gr.) (grain yield)—At the end of the experiment (plant ‘Heads’) heads from plots within blocks A-C were collected. 5 heads were separately threshed and grains were weighted, all additional heads were threshed together and weighted as well. The average grain weight per head was calculated by dividing the total grain weight by number of total heads per plot (based on plot). In case of 5 heads, the total grains weight of 5 heads was divided by 5.
FW Head/Plant gram—At the end of the experiment (when heads were harvested) total and 5 selected heads per plots within blocks A-C were collected separately. The heads (total and 5) were weighted (gr.) separately and the average fresh weight per plant was calculated for total (FW Head/Plant gr. based on plot) and for 5 (FW Head/Plant gr. based on 5 plants).
Plant height—Plants were characterized for height during growing period at 5 time points. In each measure, plants were measured for their height using a measuring tape. Height was measured from ground level to top of the longest leaf.
SPAD—Chlorophyll content was determined using a Minolta SPAD 502 chlorophyll meter and measurement was performed 64 days post sowing. SPAD meter readings were done on young fully developed leaf. Three measurements per leaf were taken per plot.
Vegetative fresh weight and heads—At the end of the experiment (when Inflorescence were dry) all Inflorescence and vegetative material from plots within blocks A-C were collected. The biomass and Heads weight of each plot was separated, measured and divided by the number of Heads.
Plant biomass (fresh weight)—At the end of the experiment (when Inflorescence were dry) the vegetative material from plots within blocks A-C were collected. The plants biomass without the Inflorescence were measured and divided by the number of Plants.
FW Heads/(FW Heads+FW Plants)—The total fresh weight of heads and their respective plant biomass were measured at the harvest day. The heads weight was divided by the sum of weights of heads and plants.
Experimental Results
17 different sorghum varieties were grown and characterized for different parameters: The average for each of the measured parameter was calculated using the JMP software (Tables 18-19) and a subsequent correlation analysis between the various transcriptom sets (Table 16) and the average parameters (Tables 17-19), was conducted (Table 20). Results were then integrated to the database.
Sorghum correlated parameters (vectors)
II. Correlation of Sorghum Varieties Across Ecotype Grown Under Salinity Stress and Cold Stress Conditions
Sorghum vigor related parameters under 100 mM NaCl and low temperature (10±2° C.)—Ten Sorghum varieties were grown in 3 repetitive plots, each containing 17 plants, at a net house under semi-hydroponics conditions. Briefly, the growing protocol was as follows: Sorghum seeds were sown in trays filled with a mix of vermiculite and peat in a 1:1 ratio. Following germination, the trays were transferred to the high salinity solution (100 mM NaCl in addition to the Full Hogland solution), low temperature (10±2° C. in the presence of Full Hogland solution) or at Normal growth solution [Full Hogland solution at 28±2° C.].
Full Hogland solution consists of: KNO3—0.808 grams/liter, MgSO4—0.12 grams/liter, KH2PO4—0.172 grams/liter and 0.01% (volume/volume) of ‘Super coratin’ micro elements (Iron-EDDHA [ethylenediamine-N,N′-bis(2-hydroxyphenylacetic acid)]—40.5 grams/liter; Mn—20.2 grams/liter; Zn 10.1 grams/liter; Co 1.5 grams/liter; and Mo 1.1 grams/liter), solution's pH should be 6.5-6.8].
All 10 selected Sorghum varieties were sampled per each treatment. Two tissues [leaves and roots] growing at 100 mM NaCl, low temperature (10±2° C.) or under Normal conditions (full Hogland at a temperature between 28±2° C.) were sampled and RNA was extracted as described hereinabove under “GENERAL EXPERIMENTAL AND BIOINFORMATICS METHODS”.
Sorghum transcriptom expression sets
Sorghum bath/NUE/root
Sorghum bath/NaCl/root
Sorghum bath/Cold/vegetative meristem
Sorghum bath/Normal/vegetative meristem
Sorghum bath/NUE/vegetative meristem
Sorghum bath/NaCl/vegetative meristem
Sorghum bath/Normal/root
Sorghum bath/Cold/root
Experimental Results
10 different Sorghum varieties were grown and characterized for the following parameters: “Leaf number Normal”=leaf number per plant under normal conditions (average of five plants); “Plant Height Normal”=plant height under normal conditions (average of five plants); “Root DW 100 mM NaCl”—root dry weight per plant under salinity conditions (average of five plants); The average for each of the measured parameters was calculated using the JMP software and values are summarized in Table 23 below. Subsequent correlation analysis between the various transcriptom sets and the average parameters were conducted (Table 24). Results were then integrated to the database.
Sorghum correlated parameters (vectors)
Sorghum accessions, measured parameters
To produce a high throughput correlation analysis, the present inventors utilized a Maize oligonucleotide micro-array, produced by Agilent Technologies [Hypertxt Transfer Protocol://World Wide Web (dot) chem. (dot) agilent (dot) com/Scripts/PDS (dot) asp?1Page=50879]. The array oligonucleotide represents about 60K Maize genes and transcripts designed based on data from Public databases (Example 1). To define correlations between the levels of RNA expression and yield, biomass components or vigor related parameters, various plant characteristics of 12 different Maize hybrids were analyzed. Among them, 10 hybrids encompassing the observed variance were selected for RNA expression analysis. The correlation between the RNA levels and the characterized parameters was analyzed using Pearson correlation test [Hypertext Transfer Protocol://World Wide Web (dot) davidmlane (dot) com/hyperstat/A34739 (dot) html].
Experimental Procedures
Four tissues at different developmental stages including Ear (R1-R2), leaf (R1-R2; and V2-V3), Grain from the distal part of the ear (R4-R5), and Internode (upper internode; R1-R2, R3-R4, V6-V8) representing different plant characteristics, were sampled and RNA was extracted as described in “GENERAL EXPERIMENTAL AND BIOINFORMATICS METHODS”. For convenience, each micro-array expression information tissue type has received a Set ID as summarized in Table 25 below.
The following parameters were collected:
Grain Area (cm2)—At the end of the growing period the grains were separated from the ear. A sample of ˜200 grains were weight, photographed and images were processed using the below described image processing system. The grain area was measured from those images and was divided by the number of grains.
Grain Length and Grain width (cm)—At the end of the growing period the grains were separated from the ear. A sample of ˜200 grains were weight, photographed and images were processed using the below described image processing system. The sum of grain lengths/or width (longest axis) was measured from those images and was divided by the number of grains.
Ear Area (cm2)—At the end of the growing period 6 ears were, photographed and images were processed using the below described image processing system. The Ear area was measured from those images and was divided by the number of Ears.
Ear Length and Ear Width (cm)—At the end of the growing period 6 ears were, photographed and images were processed using the below described image processing system. The Ear length and width (longest axis) was measured from those images and was divided by the number of ears.
Filled per Whole Ear—was calculated as the length of the ear with grains out of the total ear.
Percent Filled Ear—At the end of the growing period 6 ears were, photographed and images were processed using the below described image processing system. The percent filled Ear grain was the ear with grains out of the total ear and was measured from those images and was divided by the number of Ears.
The image processing system was used, which consists of a personal desktop computer (Intel P4 3.0 GHz processor) and a public domain program—ImageJ 1.37, Java based image processing software, which was developed at the U.S. National Institutes of Health and is freely available on the internet at Hypertext Transfer Protocol://rsbweb (dot) nih (dot) gov/. Images were captured in resolution of 10 Mega Pixels (3888×2592 pixels) and stored in a low compression JPEG (Joint Photographic Experts Group standard) format. Next, image processing output data for seed area and seed length was saved to text files and analyzed using the JMP statistical analysis software (SAS institute).
Additional parameters were collected either by sampling 6 plants per plot or by measuring the parameter across all the plants within the plot.
Normalized Grain Weight per plant (gr.)(yield)—At the end of the experiment all ears from plots within blocks A-C were collected. 6 ears were separately threshed and grains were weighted, all additional ears were threshed together and weighted as well. The grain weight was normalized using the relative humidity to be 0%. The normalized average grain weight per ear was calculated by dividing the total normalized grain weight by the total number of ears per plot (based on plot). In case of 6 ears, the total grains weight of 6 ears was divided by 6.
Ear FW (gr.)—At the end of the experiment (when ears were harvested) total and 6 selected ears per plots within blocks A-C were collected separately. The plants with (total and 6) were weighted (gr.) separately and the average ear per plant was calculated for total (Ear FW per plot) and for 6 (Ear FW per plant).
Plant height and Ear height—Plants were characterized for height at harvesting. In each measure, 6 plants were measured for their height using a measuring tape. Height was measured from ground level to top of the plant below the tassel. Ear height was measured from the ground level to the place were the main ear is located
Leaf number per plant—Plants were characterized for leaf number during growing period at 5 time points. In each measure, plants were measured for their leaf number by counting all the leaves of 3 selected plants per plot.
Relative Growth Rate—was calculated using regression coefficient of leaf number change a long time course.
SPAD—Chlorophyll content was determined using a Minolta SPAD 502 chlorophyll meter and measurement was performed 64 days post sowing. SPAD meter readings were done on young fully developed leaf. Three measurements per leaf were taken per plot. Data were taken after 46 and 54 days after sowing (DPS).
Dry weight per plant—At the end of the experiment when all vegetative material from plots within blocks A-C were collected, weight and divided by the number of plants.
Ear diameter [cm]—The diameter of the ear at the mid of the ear was measured using a ruler.
Cob diameter [cm]—The diameter of the cob without grains was measured using a ruler.
Kernel Row Number per Ear—The number of rows in each ear was counted.
The average of 6 ears per plot was calculated.
Leaf area index [LAI]=total leaf area of all plants in a plot. Measurement was performed using a Leaf area-meter.
Yield/LAI [kg]-is the ratio between total grain yields and total leaf area index.
Twelve maize varieties were grown, and characterized for parameters, as described above. The average for each parameter was calculated using the JMP software, and values are summarized in Tables 27-28 below. Subsequent correlation between the various transcriptom sets for all or sub set of lines was done by the bioinformatic unit and results were integrated into the database (Table 29 below).
In order to produce a high throughput correlation analysis comparing between plant phenotype and gene expression level, the present inventors utilized a Barley oligonucleotide micro-array, produced by Agilent Technologies [Hypertext Transfer Protocol://World Wide Web (dot) chem. (dot) agilent (dot) com/Scripts/PDS (dot) asp?1Page=50879]. The array oligonucleotide represents about 60K Barley genes and transcripts. In order to define correlations between the levels of RNA expression and yield or vigor related parameters, various plant characteristics of 15 different Barley accessions were analyzed. Among them, 10 accessions encompassing the observed variance were selected for RNA expression analysis. The correlation between the RNA levels and the characterized parameters was analyzed using Pearson correlation test [Hypertext Transfer Protocol://World Wide Web (dot) davidmlane (dot) com/hyperstat/A34739 (dot) html].
Experimental Procedures
Analyzed Barley tissues—Five tissues [leaf, spike, meristem, root tip and adventitious root] tissues at different developmental stages (vegetative stage, reproductive stage), and treatments (drought, low nitrogen (N) and normal conditions), representing different plant characteristics, were sampled and RNA was extracted as described above. Each micro-array expression information tissue type has received a Set ID as summarized in Table 30 below.
Barley yield components and vigor related parameters assessment—15 Barley accessions in 5 repetitive blocks, each containing 5 plants per pot were grown at net house. Three different treatments were applied: plants were regularly fertilized and watered during plant growth until harvesting (as recommended for commercial growth) or under low Nitrogen (80% percent less Nitrogen) or drought stress. Plants were phenotyped on a daily basis following the standard descriptor of barley (Table 31, below). Harvest was conducted while all the spikes were dry. All material was oven dried and the seeds were threshed manually from the spikes prior to measurement of the seed characteristics (weight and size) using scanning and image analysis. The image analysis system included a personal desktop computer (Intel P4 3.0 GHz processor) and a public domain program—ImageJ 1.37 (Java based image processing program, which was developed at the U.S. National Institutes of Health and freely available on the internet [Hypertext Transfer Protocol://rsbweb (dot) nih (dot) gov/]. Next, analyzed data was saved to text files and processed using the JMP statistical analysis software (SAS institute).
Grains number—The total number of grains from all spikes that were manually threshed was counted. No. of grains per plot were counted.
Grain weight (gr.)—At the end of the experiment all spikes of the pots were collected. The total grains from all spikes that were manually threshed were weight. The grain yield was calculated by per plot.
Spike length and width analysis—At the end of the experiment the length and width of five chosen spikes per plant were measured using measuring tape excluding the awns.
Spike number analysis—The spikes per plant were counted.
Plant height—Each of the plants was measured for its height using measuring tape. Height was measured from ground level to top of the longest spike excluding awns at two time points at the Vegetative growth (30 days after sowing) and at harvest.
Spike weight—The biomass and spikes weight of each plot was separated, measured and divided by the number of plants.
Dry weight=total weight of the vegetative portion above ground (excluding roots) after drying at 70° C. in oven for 48 hours at two time points at the Vegetative growth (30 days after sowing) and at harvest.
Root dry weight=total weight of the root portion underground after drying at 70° C. in oven for 48 hours at harvest.
Root/Shoot Ratio—The Root/Shoot Ratio is calculated using Formula X.
Root/Shoot Ratio=total weight of the root at harvest/total weight of the vegetative portion above ground at harvest. Formula X
Total No of tillers—all tillers were counted per plot at two time points at the Vegetative growth (30 days after sowing) and at harvest.
SPAD—Chlorophyll content was determined using a Minolta SPAD 502 chlorophyll meter and measurement was performed at time of flowering. SPAD meter readings were done on young fully developed leaf. Three measurements per leaf were taken per plot.
Root FW (gr.), root length (cm) and No. of lateral roots—3 plants per plot were selected for measurement of root weight, root length and for counting the number of lateral roots formed.
Shoot FW—weight of 3 plants per plot were recorded at different time-points. Relative water content—Fresh weight (FW) of three leaves from three plants each from different seed ID is immediately recorded; then leaves are soaked for 8 hours in distilled water at room temperature in the dark, and the turgid weight (TW) is recorded. Total dry weight (DW) is recorded after drying the leaves at 60° C. to a constant weight. Relative water content (RWC) is calculated according to Formula I above.
Harvest Index (for barley)—The harvest index is calculated using Formula XI.
Harvest Index=Average grain weight per plant/(Average vegetative dry weight per plant+Average grain weight per plant). Formula XI
Relative growth rate: the relative growth rate (RGR) of Plant Height, Spad and number of tillers are calculated as follows:
The relative growth rate of plant height was calculated according to Formula XII.
Relative growth rate of Plant height=Regression coefficient of Plant height along time course. Formula XII
Relative growth rate of SPAD=Regression coefficient of SPAD measurements along time course. Formula XIII
Relative growth rate of Number of tillers=Regression coefficient of Number of tillers along time course. Formula XIV
Experimental Results
15 different Barley accessions were grown and characterized for different parameters as described above. The average for each of the measured parameters was calculated using the JMP software and values are summarized in Tables 32-33 below. Subsequent correlation analysis between the various transcriptom sets and the average parameters was conducted (Table 34). Follow, results were integrated to the database.
In order to produce a high throughput correlation analysis comparing between plant phenotype and gene expression level, the present inventors utilized a brachypodium oligonucleotide micro-array, produced by Agilent Technologies [Hypertext Transfer Protocol://World Wide Web (dot) chem. (dot) agilent (dot) com/Scripts/PDS (dot) asp?1Page=50879]. The array oligonucleotide represents about 60K brachypodium genes and transcripts. In order to define correlations between the levels of RNA expression and yield or vigor related parameters, various plant characteristics of 24 different brachypodium accessions were analyzed. Among them, 22 accessions encompassing the observed variance were selected for RNA expression analysis and comparative genomic hybridization (CGH) analysis.
The correlation between the RNA levels and the characterized parameters was analyzed using Pearson correlation test [Hypertext Transfer Protocol://World Wide Web (dot) davidmlane (dot) com/hyperstat/A34739 (dot) html].
Additional correlation analysis was done by comparing plant phenotype and gene copy number. The correlation between the normalized copy number hybridization signal and the characterized parameters was analyzed using Pearson correlation test [Hypertext Transfer Protocol://World Wide Web (dot) davidmlane (dot) com/hyperstat/A34739 (dot) html].
Experimental Procedures
Analyzed Brachypodium tissues—two tissues [leaf and spike] were sampled and RNA was extracted as described above. Each micro-array expression information tissue type has received a Set ID as summarized in Table 35 below.
Brachypodium transcriptom expression sets
Brachypodium yield components and vigor related parameters assessment—24 brachypodium accessions were grown in 4-6 repetitive plots (8 plant per plot), in a green house. The growing protocol was as follows: brachypodium seeds were sown in plots and grown under normal condition. Plants were continuously phenotyped during the growth period and at harvest (Table 37-38, below). The image analysis system included a personal desktop computer (Intel P4 3.0 GHz processor) and a public domain program—ImageJ 1.37 (Java based image processing program, which was developed at the U.S. National Institutes of Health and freely available on the internet [Hypertext Transfer Protocol://rsbweb (dot) nih (dot) gov/]. Next, analyzed data was saved to text files and processed using the JMP statistical analysis software (SAS institute).
At the end of the growing period the grains were separated from the spikes and the following parameters were measured using digital imaging system and collected:
No. of tillering—all tillers were counted per plant at harvest (mean per plot).
Head number—At the end of the experiment, heads were harvested from each plot and were counted.
Total Grains weight per plot (gr.)—At the end of the experiment (plant ‘Heads’) heads from plots were collected, the heads were threshed and grains were weighted. In addition, the average grain weight per head was calculated by dividing the total grain weight by number of total heads per plot (based on plot).
Highest number of spikelets—The highest spikelet number per head was calculated per plant (mean per plot).
Mean number of spikelets—The mean spikelet number per head was calculated per plot.
Plant height—Each of the plants was measured for its height using measuring tape. Height was measured from ground level to spike base of the longest spike at harvest.
Spikelets weight (gr.)—The biomass and spikes weight of each plot was separated, measured per plot.
Average head weight—calculated by dividing spikelets weight with head number (gr.).
Harvest Index—The harvest index was calculated using Formula XIV (described above).
Spikelets Index—The Spikelets index is calculated using Formula XVII.
Spikelets Index=Average Spikelets weight per plant/(Average vegetative dry weight per plant plus Average Spikelets weight per plant). Formula XVII
Percent Number of heads with spikelets—The number of heads with more than one spikelet per plant were counted and the percent from all heads per plant was calculated.
Total dry mater per plot—Calculated as Vegetative portion above ground plus all the spikelet dry weight per plot.
1000 grain weight—At the end of the experiment all grains from all plots were collected and weighted and the weight of 1000 were calculated.
The following parameters were collected using digital imaging system:
At the end of the growing period the grains were separated from the spikes and the following parameters were measured and collected:
(i) Average Grain Area (cm2)—A sample of ˜200 grains was weighted, photographed and images were processed using the below described image processing system. The grain area was measured from those images and was divided by the number of grains.
(ii) Average Grain Length, perimeter and width (cm)—A sample of ˜200 grains was weighted, photographed and images were processed using the below described image processing system. The sum of grain lengths and width (longest axis) was measured from those images and was divided by the number of grains.
The image processing system was used, which consists of a personal desktop computer (Intel P4 3.0 GHz processor) and a public domain program—ImageJ 1.37, Java based image processing software, which was developed at the U.S. National Institutes of Health and is freely available on the internet at Hypertext Transfer Protocol://rsbweb (dot) nih (dot) gov/. Images were captured in resolution of 10 Mega Pixels (3888×2592 pixels) and stored in a low compression JPEG (Joint Photographic Experts Group standard) format. Next, image processing output data for seed area and seed length was saved to text files and analyzed using the JMP statistical analysis software (SAS institute).
Brachypodium correlated parameters (vectors)
Experimental Results
24 different Brachypodium accessions were grown and characterized for different parameters as described above. The average for each of the measured parameter was calculated using the JMP software and values are summarized in Tables 37-38 below. Subsequent correlation analysis between the various transcriptom sets and the average parameters (Table 39) was conducted. Follow, results were integrated to the database.
In order to produce a high throughput correlation analysis comparing between plant phenotype and gene expression level, the present inventors utilized a foxtail millet oligonucleotide micro-array, produced by Agilent Technologies [Hypertext Transfer Protocol://World Wide Web (dot) chem. (dot) agilent (dot) com/Scripts/PDS (dot) asp?1Page=50879]. The array oligonucleotide represents about 60K foxtail millet genes and transcripts. In order to define correlations between the levels of RNA expression and yield or vigor related parameters, various plant characteristics of 15 different foxtail millet accessions were analyzed. Among them, 11 accessions encompassing the observed variance were selected for RNA expression analysis. The correlation between the RNA levels and the characterized parameters was analyzed using Pearson correlation test [Hypertext Transfer Protocol://World Wide Web (dot) davidmlane (dot) com/hyperstat/A34739 (dot) html].
Experimental Procedures
Analyzed Foxtail millet tissues—three tissues [leaf, flower, and stem] at different developmental stages [time point 1 (TP1) and 2 (TP2)] under normal conditions, representing different plant characteristics, were sampled and RNA was extracted as described above. Each micro-array expression information tissue type has received a Set ID as summarized in Table 40 below.
Foxtail millet yield components and vigor related parameters assessment—14 Foxtail millet accessions in 5 repetitive plots, in the field. Foxtail millet seeds were sown in soil and grown under normal condition in the field. Plants were continuously phenotyped during the growth period and at harvest (Table 42-43, below). The image analysis system included a personal desktop computer (Intel P4 3.0 GHz processor) and a public domain program—ImageJ 1.37 (Java based image processing program, which was developed at the U.S. National Institutes of Health and freely available on the internet [Hypertext Transfer Protocol://rsbweb (dot) nih (dot) gov/]. Next, analyzed data was saved to text files and processed using the JMP statistical analysis software (SAS institute).
The following parameters were collected using digital imaging system:
At the end of the growing period the grains were separated from the Plant ‘Head’ and the following parameters were measured and collected:
(i) Average Grain Area (cm2)—A sample of ˜200 grains was weighted, photographed and images were processed using the below described image processing system. The grain area was measured from those images and was divided by the number of grains.
(ii) Average Grain Length and width (cm)—A sample of ˜200 grains was weighted, photographed and images were processed using the below described image processing system. The sum of grain lengths and width (longest axis) was measured from those images and was divided by the number of grains.
At the end of the growing period 14 ‘Heads’ were photographed and images were processed using the below described image processing system.
(i) Head Average Area (cm2) The ‘Head’ area was measured from those images and was divided by the number of ‘Heads’.
(ii) Head Average Length (mm) The ‘Head’ length (longest axis) was measured from those images and was divided by the number of ‘Heads’.
The image processing system was used, which consists of a personal desktop computer (Intel P4 3.0 GHz processor) and a public domain program—ImageJ 1.37, Java based image processing software, which was developed at the U.S. National Institutes of Health and is freely available on the internet at Hypertext Transfer Protocol://rsbweb (dot) nih (dot) gov/. Images were captured in resolution of 10 Mega Pixels (3888×2592 pixels) and stored in a low compression JPEG (Joint Photographic Experts Group standard) format. Next, image processing output data for seed area and seed length was saved to text files and analyzed using the JMP statistical analysis software (SAS institute).
Additional parameters were collected either by sampling 5 plants per plot or by measuring the parameter across all the plants within the plot.
Total Grain Weight (gr.)—At the end of the experiment (plant ‘Heads’) heads from plots were collected, the heads were threshed and grains were weighted. In addition, the average grain weight per head was calculated by dividing the total grain weight by number of total heads per plot (based on plot).
Head weight and head number—At the end of the experiment, heads were harvested from each plot and were counted and weighted (kg).
Biomass at harvest—At the end of the experiment the vegetative material from plots was weighted.
Dry weight=total weight of the vegetative portion above ground (excluding roots) after drying at 70° C. in oven for 48 hours at harvest.
Total dry mater per plot—Calculated as Vegetative portion above ground plus all the heads dry weight per plot.
Num days to anthesis—Calculated as the number of days from sowing till 50% of the plot arrive anthesis.
Experimental Results
14 different foxtail millet accessions were grown and characterized for different parameters as described above. The average for each of the measured parameter was calculated using the JMP software and values are summarized in Tables 42-43 below. Subsequent correlation analysis between the various transcriptom sets and the average parameters was conducted (Table 44). Follow, results were integrated to the database.
In order to produce a high throughput correlation analysis, the present inventors utilized a Soybean oligonucleotide micro-array, produced by Agilent Technologies [Hypertext Transfer Protocol://World Wide Web (dot) chem. (dot) agilent (dot) com/Scripts/PDS (dot) asp?1Page=50879]. The array oligonucleotide represents about 42,000 Soybean genes and transcripts. In order to define correlations between the levels of RNA expression with yield components or plant architecture related parameters or plant vigor related parameters, various plant characteristics of 29 different Glycine max varieties were analyzed and 12 varieties were further used for RNA expression analysis. The correlation between the RNA levels and the characterized parameters was analyzed using Pearson correlation test.
Correlation of Glycine max Genes' Expression Levels with Phenotypic Characteristics Across Ecotype
Experimental Procedures
29 Soybean varieties were grown in three repetitive plots, in field. Briefly, the growing protocol was as follows: Soybean seeds were sown in soil and grown under normal conditions until harvest. In order to define correlations between the levels of RNA expression with yield components or plant architecture related parameters or vigor related parameters, 12 different Soybean varieties (out of 29 varieties) were analyzed and used for gene expression analyses. Analysis was performed at two pre-determined time periods: at pod set (when the soybean pods are formed) and at harvest time (when the soybean pods are ready for harvest, with mature seeds).
RNA extraction—All 12 selected Soybean varieties were sampled per treatment. Plant tissues [leaf, root, stem, pod, apical meristem, flower buds] growing under normal conditions were sampled and RNA was extracted as described above.
The collected data parameters were as follows:
Main branch base diameter [mm] at pod set—the diameter of the base of the main branch (based diameter) average of three plants per plot.
Fresh weight [gr./plant] at pod set—total weight of the vegetative portion above ground (excluding roots) before drying at pod set, average of three plants per plot.
Dry weight [gr./plant] at pod set—total weight of the vegetative portion above ground (excluding roots) after drying at 70° C. in oven for 48 hours at pod set, average of three plants per plot.
Total number of nodes with pods on lateral branches [value/plant]—counting of nodes which contain pods in lateral branches at pod set, average of three plants per plot.
Number of lateral branches at pod set [value/plant]—counting number of lateral branches at pod set, average of three plants per plot.
Total weight of lateral branches at pod set [gr./plant]—weight of all lateral branches at pod set, average of three plants per plot.
Total weight of pods on main stem at pod set [gr./plant]—weight of all pods on main stem at pod set, average of three plants per plot.
Total number of nodes on main stem [value/plant]—count of number of nodes on main stem starting from first node above ground, average of three plants per plot.
Total number of pods with 1 seed on lateral branches at pod set [value/plant]-count of the number of pods containing 1 seed in all lateral branches at pod set, average of three plants per plot.
Total number of pods with 2 seeds on lateral branches at pod set [value/plant]—count of the number of pods containing 2 seeds in all lateral branches at pod set, average of three plants per plot.
Total number of pods with 3 seeds on lateral branches at pod set [value/plant]—count of the number of pods containing 3 seeds in all lateral branches at pod set, average of three plants per plot.
Total number of pods with 4 seeds on lateral branches at pod set [value/plant]—count of the number of pods containing 4 seeds in all lateral branches at pod set, average of three plants per plot.
Total number of pods with 1 seed on main stem at pod set [value/plant]—count of the number of pods containing 1 seed in main stem at pod set, average of three plants per plot.
Total number of pods with 2 seeds on main stem at pod set [value/plant]-count of the number of pods containing 2 seeds in main stem at pod set, average of three plants per plot.
Total number of pods with 3 seeds on main stem at pod set [value/plant]-count of the number of pods containing 3 seeds in main stem at pod set, average of three plants per plot.
Total number of pods with 4 seeds on main stem at pod set [value/plant]-count of the number of pods containing 4 seeds in main stem at pod set, average of three plants per plot.
Total number of seeds per plant at pod set [value/plant]—count of number of seeds in lateral branches and main stem at pod set, average of three plants per plot.
Total number of seeds on lateral branches at pod set [value/plant]—count of total number of seeds on lateral branches at pod set, average of three plants per plot.
Total number of seeds on main stem at pod set [value/plant]—count of total number of seeds on main stem at pod set, average of three plants per plot.
Plant height at pod set [cm/plant]—total length from above ground till the tip of the main stem at pod set, average of three plants per plot.
Plant height at harvest [cm/plant]—total length from above ground till the tip of the main stem at harvest, average of three plants per plot.
Total weight of pods on lateral branches at pod set [gr./plant]—weight of all pods on lateral branches at pod set, average of three plants per plot.
Ratio of the number of pods per node on main stem at pod set—calculated in formula XVIII, average of three plants per plot.
Total number of pods on main stem/Total number of nodes on main stem, average of three plants per plot. Formula XVIII
Ratio of total number of seeds in main stem to number of seeds on lateral branches—calculated in formula XIX, average of three plants per plot.
Total number of seeds on main stem at pod set/Total number of seeds on lateral branches at pod set. Formula XIX
Total weight of pods per plant at pod set [gr./plant]—weight of all pods on lateral branches and main stem at pod set, average of three plants per plot.
Days till 50% flowering [days]—number of days till 50% flowering for each plot.
Days till 100% flowering [days]—number of days till 100% flowering for each plot.
Maturity [days]—measure as 95% of the pods in a plot have ripened (turned 100% brown). Delayed leaf drop and green stems are not considered in assigning maturity. Tests are observed 3 days per week, every other day, for maturity. The maturity date is the date that 95% of the pods have reached final color. Maturity is expressed in days after August 31 [according to the accepted definition of maturity in USA, Descriptor list for SOYBEAN, Hypertext Transfer Protocol://World Wide Web (dot) ars-grin (dot) gov/cgi-bin/npgs/html/desclist (dot) pl?51].
Seed quality [ranked 1-5]—measure at harvest; a visual estimate based on several hundred seeds. Parameter is rated according to the following scores considering the amount and degree of wrinkling, defective coat (cracks), greenishness, and moldy or other pigment. Rating is 1-very good, 2-good, 3-fair, 4-poor, 5-very poor.
Lodging [ranked 1-5]—is rated at maturity per plot according to the following scores: 1-most plants in a plot are erected; 2-all plants leaning slightly or a few plants down; 3-all plants leaning moderately, or 25%-50% down; 4-all plants leaning considerably, or 50%-80% down; 5-most plants down. Note: intermediate score such as 1.5 are acceptable.
Seed size [gr.]—weight of 1000 seeds per plot normalized to 13% moisture, measure at harvest.
Total weight of seeds per plant [gr./plant]—calculated at harvest (per 2 inner rows of a trimmed plot) as weight in grams of cleaned seeds adjusted to 13% moisture and divided by the total number of plants in two inner rows of a trimmed plot.
Yield at harvest [bushels/hectare]—calculated at harvest (per 2 inner rows of a trimmed plot) as weight in grams of cleaned seeds, adjusted to 13% moisture, and then expressed as bushels per acre.
Experimental Results
Twelve different Soybean varieties (i.e., V00-3636, V03-1754, V06-1365, V06-7487, V07-7840, V07-8022, V07-8309, V07-8393, V07-8515, V07-8782, V04-7750, V05-5973) were grown and characterized for 34 parameters as specified above. The average for each of the measured parameters was calculated using the JMP software and values are summarized in Tables 45-50 below.
To validate their role in improving plant yield, oil content, seed yield, biomass, growth rate, fiber yield, fiber quality, ABST, NUE and/or vigor, selected genes were over-expressed in plants, as follows.
Cloning Strategy
Selected genes from those listed in Examples 1-11 hereinabove are cloned into binary vectors for the generation of transgenic plants. For cloning, the full-length open reading frame (ORF) was first identified. In case of ORF-EST clusters and in some cases already published mRNA sequences were analyzed to identify the entire open reading frame by comparing the results of several translation algorithms to known proteins from other plant species. To clone the full-length cDNAs, reverse transcription (RT) followed by polymerase chain reaction (PCR; RT-PCR) was performed on total RNA extracted from leaves, flowers, siliques or other plant tissues, growing under normal and different treated conditions. Total RNA was extracted as described in “GENERAL EXPERIMENTAL AND BIOINFORMATICS METHODS” above. Production of cDNA and PCR amplification was performed using standard protocols described elsewhere (Sambrook J., E. F. Fritsch, and T. Maniatis. 1989. Molecular Cloning. A Laboratory Manual., 2nd Ed. Cold Spring Harbor Laboratory Press, New York), which are well known to those skilled in the art. PCR products were purified using PCR purification kit (Qiagen). In case where the entire coding sequence was not found, RACE kit from Invitrogen (RACE=Rapid Amplification of cDNA Ends) was used to access the full cDNA transcript of the gene from the RNA samples described above. RACE products were cloned into high copy vector followed by sequencing or directly sequenced.
The information from the RACE procedure was used for cloning of the full length ORF of the corresponding genes.
In case genomic DNA was cloned, the genes were amplified by direct PCR on genomic DNA extracted from leaf tissue using the DNAeasy kit (Qiagen Cat. No. 69104).
Usually, 2 sets of primers were synthesized for the amplification of each gene from a cDNA or a genomic sequence; an external set of primers and an internal set (nested PCR primers). When needed (e.g., when the first PCR reaction does not result in a satisfactory product for sequencing), an additional primer (or two) of the nested PCR primers was used.
To facilitate cloning of the cDNAs/genomic sequences, an 8-12 bp extension was added to the 5′ of each primer. The primer extension includes an endonuclease restriction site. The restriction sites were selected using two parameters: (a). The site does not exist in the cDNA sequence; and (b). The restriction sites in the forward and reverse primers are designed such that the digested cDNA is inserted in the sense formation into the binary vector utilized for transformation.
Each digested PCR product was inserted into a high copy vector pUC19 (New England BioLabs Inc], or into plasmids originating from this vector. In some cases the undigested PCR product is inserted into pCR-Blunt II-TOPO (Invitrogen).
Sequencing of the amplified PCR products was performed, using ABI 377 sequencer (Amersham Biosciences Inc). In some cases, after confirming the sequences of the cloned genes, the cloned cDNA was introduced into a modified pGI binary vector containing the At6669 promoter via digestion with appropriate restriction endonucleases. In any case the insert is followed by single copy of the NOS terminator (SEQ ID NO:8543). The digested products and the linearized plasmid vector were ligated using T4 DNA ligase enzyme (Roche, Switzerland).
High copy plasmids containing the cloned genes were digested with the restriction endonucleases (New England BioLabs Inc) according to the sites designed in the primers and cloned into binary vectors.
Several DNA sequences of the selected genes were synthesized by a commercial supplier GeneArt [Hypertext Transfer Protocol://World Wide Web (dot) geneart (dot) com/]. Synthetic DNA was designed in silico. Suitable restriction enzymes sites were added to the cloned sequences at the 5′ end and at the 3′ end to enable later cloning into the pQFNc binary vector downstream of the At6669 promoter (SEQ ID NO: 8529).
Binary Vectors Used for Cloning:
The plasmid pPI was constructed by inserting a synthetic poly-(A) signal sequence, originating from pGL3 basic plasmid vector (Promega, Acc No U47295; bp 4658-4811) into the HindIII restriction site of the binary vector pBI101.3 (Clontech, Acc. No. U12640). pGI (pBXYN) is similar to pPI, but the original gene in the backbone, the GUS gene, was replaced by the GUS-Intron gene followed by the NOS terminator (SEQ ID NO:8543) (Vancanneyt. G, et al MGG 220, 245-50, 1990). pGI was used in the past to clone the polynucleotide sequences, initially under the control of 35S promoter [Odell, J T, et al. Nature 313, 810-812 (28 Feb. 1985); SEQ ID NO:8527].
The modified pGI vectors [pQXNc (
At6669, the Arabidopsis thaliana promoter sequence (SEQ ID NO:8529) was inserted in the modified pGI binary vector, upstream to the cloned genes, followed by DNA ligation and binary plasmid extraction from positive E. coli colonies, as described above.
Colonies were analyzed by PCR using the primers covering the insert which were designed to span the introduced promoter and gene. Positive plasmids were identified, isolated and sequenced.
Cloning of Genes with a Signal Peptide which Directs Expression of the Gene in Arabidopsis Plants:
Two genes (LYM670 and LYM721) were found by bioinformatics analysis to have a biological function in the chloroplast of Maize (LYM670) and Sorghum (LYM721). In order to express the genes in the chloroplasts of Arabidopsis plants, a signal peptide which directs expression of a polypeptide into Arabidopsis chloroplast was inserted into the sequence, by replacing the initiator Methionine coding sequence. The Arabidopsis signal peptide that was used is provided by SEQ ID NO: 9179 (MASSMLSSATMVASPAQATMVAPFNGLKSSAAFPATRKANNDITSITSNGGRV NC) and is encoded by SEQ ID NO: 9178 (5′-ATGGCTTCCTCTATGCTCTCTTCCGCTACTATGGTTGCCTCTCCGGCTCAGGC CACTATGGTCGCTCCTTTCAACGGACTTAAGTCCTCCGCTGCCTTCCCAGCC ACCCGCAAGGCTAACAACGACATTACTTCCATCACAAGCAACGGCGGAAGA GTTAACTGC). It should be noted that for expression of this genes in the chloroplast of other target plants, alternative signal peptides may be used, based on the target plants.
In addition, LYM745 gene, which is another chloroplast specific gene, was found to be conserved with a start codon of ACG (on the DNA level) yet with a Methionine as the first amino acid on the protein level. The gene was therefore cloned into a plant with the ACG as the initiation codon (the sequence was chemically synthesized by Gene_Art).
Selected genes cloned by the present inventors are provided in Table 51 below.
Experimental Methods
Production of Agrobacterium Tumefaciens Cells Harboring the Binary Vectors According to Some Embodiments of the Invention—
Each of the binary vectors described in Example 12 above was used to transform Agrobacterium cells. Two additional binary constructs, having only the At6669 or the 35S promoter or no additional promoter were used as negative controls.
The binary vectors were introduced to Agrobacterium tumefaciens GV301, or LB4404 competent cells (about 109 cells/mL) by electroporation. The electroporation was performed using a MicroPulser electroporator (Biorad), 0.2 cm cuvettes (Biorad) and EC-2 electroporation program (Biorad). The treated cells were cultured in LB liquid medium at 28° C. for 3 hours, then plated over LB agar supplemented with gentamycin (50 mg/L; for Agrobacterium strains GV301) or streptomycin (300 mg/L; for Agrobacterium strain LB4404) and kanamycin (50 mg/L) at 28° C. for 48 hours. Agrobacterium colonies, which were developed on the selective media, were further analyzed by PCR using the primers designed to span the inserted sequence in the pPI plasmid. The resulting PCR products were isolated and sequenced to verify that the correct polynucleotide sequences of the invention were properly introduced to the Agrobacterium cells.
Preparation of Arabidopsis Plants for Transformation—
Arabidopsis thaliana var Columbia (T0 plants) were transformed according to the Floral Dip procedure [Clough S J, Bent A F. (1998) Floral dip: a simplified method for Agrobacterium-mediated transformation of Arabidopsis thaliana. Plant J. 16(6): 735-43; and Desfeux C, Clough S J, Bent A F. (2000) Female reproductive tissues are the primary targets of Agrobacterium-mediated transformation by the Arabidopsis floral-dip method. Plant Physiol. 123(3): 895-904] with minor modifications. Briefly, Arabidopsis thaliana Columbia (Col0) T0 plants were sown in 250 ml pots filled with wet peat-based growth mix. The pots were covered with aluminum foil and a plastic dome, kept at 4° C. for 3-4 days, then uncovered and incubated in a growth chamber at 18-24° C. under 16/8 hours light/dark cycles. The T0 plants were ready for transformation six days before anthesis.
Preparation of the Agrobacterium Carrying the Binary Vectors to Transformation into Arabidopsis Plants—
Single colonies of Agrobacterium carrying the binary vectors harboring the genes of some embodiments of the invention were cultured in LB medium supplemented with kanamycin (50 mg/L) and gentamycin (50 mg/L). The cultures were incubated at 28° C. for 48 hours under vigorous shaking and centrifuged at 4000 rpm for 5 minutes. The pellets comprising Agrobacterium cells were resuspended in a transformation medium which contains half-strength (2.15 g/L) Murashige-Skoog (Duchefa); 0.044 μM benzylamino purine (Sigma); 112 μg/L B5 Gambourg vitamins (Sigma); 5% sucrose; and 0.2 ml/L Silwet L-77 (OSI Specialists, CT) in double-distilled water, at pH of 5.7.
Transformation of Arabidopsis Plants with the Agrobacterium—
Transformation of T0 plants was performed by inverting each plant into an Agrobacterium suspension such that the above ground plant tissue is submerged for 3-5 seconds. Each inoculated T0 plant was immediately placed in a plastic tray, then covered with clear plastic dome to maintain humidity and was kept in the dark at room temperature for 18 hours to facilitate infection and transformation. Transformed (transgenic) plants were then uncovered and transferred to a greenhouse for recovery and maturation. The transgenic T0 plants were grown in the greenhouse for 3-5 weeks until siliques are brown and dry, then seeds were harvested from plants and kept at room temperature until sowing.
Generation of T1 and T2 Transgenic Plants—
For generating T1 and T2 transgenic plants harboring the genes, seeds collected from transgenic T0 plants were surface-sterilized by soaking in 70% ethanol for 1 minute, followed by soaking in 5% sodium hypochlorite and 0.05% triton for 5 minutes. The surface-sterilized seeds were thoroughly washed in sterile distilled water then placed on culture plates containing half-strength Murashig-Skoog (Duchefa); 2% sucrose; 0.8% plant agar; 50 mM kanamycin; and 200 mM carbenicylin (Duchefa). The culture plates were incubated at 4° C. for 48 hours then transferred to a growth room at 25° C. for an additional week of incubation. Vital T1 Arabidopsis plants were transferred to a fresh culture plates for another week of incubation. Following incubation the T1 plants were removed from culture plates and planted in growth mix contained in 250 ml pots. The transgenic plants were allowed to grow in a greenhouse to maturity. Seeds harvested from T1 plants were cultured and grown to maturity as T2 plants under the same conditions as used for culturing and growing the T1 plants.
Assay 1: Seed Yield Plant Biomass and Plant Growth Rate Under Normal Greenhouse Conditions—
This assay follows seed yield production, the biomass formation and the rosette area growth of plants grown in the greenhouse at non-limiting nitrogen growth conditions. Transgenic Arabidopsis seeds were sown in agar media supplemented with ½ MS medium and a selection agent (Kanamycin). The T2 transgenic seedlings were then transplanted to 1.7 trays filled with peat and perlite in a 1:1 ratio. The trays were irrigated with a solution containing 6 mM inorganic nitrogen in the form of KNO3 with 1 mM KH2PO4, 1 mM MgSO4, 2 mM CaCl2 and microelements. All plants were grown in the greenhouse until mature seeds. Seeds were harvested, extracted and weighted. The remaining plant biomass (the above ground tissue) was also harvested, and weighted immediately or following drying in oven at 50° C. for 24 hours.
Each construct was validated at its T2 generation. Transgenic plants transformed with a construct conformed by an empty vector carrying the At6669 promoter (SEQ ID NO:8529) and the selectable marker were used as control.
The plants were analyzed for their overall size, growth rate, flowering (flowering time), seed yield, 1,000-seed weight, dry matter and harvest index (HI—seed yield/dry matter). Early flowering time (e.g., a decrease in flowering time as compared to control, e.g., having a negative value) is an important agronomical trait that has a potential to contribute to increase in yield under various environmental conditions. Transgenic plants performance was compared to control plants grown in parallel under the same conditions. Mock-transgenic plants expressing the uidA reporter gene (GUS-Intron) or with no gene at all, under the same promoter were used as control.
The experiment was planned in nested randomized plot distribution. For each gene of the invention three to five independent transformation events were analyzed from each construct.
Digital Imaging—
A laboratory image acquisition system, which consists of a digital reflex camera (Canon EOS 300D) attached with a 55 mm focal length lens (Canon EF-S series), mounted on a reproduction device (Kaiser RS), which includes 4 light units (4×150 Watts light bulb) is used for capturing images of plant samples.
The image capturing process was repeated every 2 days starting from day 1 after transplanting till day 15. Same camera, placed in a custom made iron mount, was used for capturing images of larger plants sawn in white tubs in an environmental controlled greenhouse. The tubs were square shape include 1.7 liter trays. During the capture process, the tubs were placed beneath the iron mount, while avoiding direct sun light and casting of shadows.
An image analysis system was used, which consists of a personal desktop computer (Intel P4 3.0 GHz processor) and a public domain program—ImageJ 1.39 [Java based image processing program which was developed at the U.S. National Institutes of Health and freely available on the internet at Hypertext Transfer Protocol://rsbweb (dot) nih (dot) gov/]. Images were captured in resolution of 10 Mega Pixels (3888×2592 pixels) and stored in a low compression JPEG (Joint Photographic Experts Group standard) format. Next, analyzed data was saved to text files and processed using the JMP statistical analysis software (SAS institute).
Leaf Analysis—
Using the digital analysis leaves data was calculated, including leaf number, rosette area, rosette diameter, and leaf blade area.
Vegetative Growth Rate:
the relative growth rate (RGR) of leaf number [Formula X (described above)], rosette area (Formula IX above), plot coverage (Formula XX below) and harvest index (Formula IV above) were calculated with the indicated formulas.
RGR plot coverage Relative growth rate of plot coverage=Regression coefficient of plot coverage along time course. Formula XX
Seeds Average Weight—
At the end of the experiment all seeds were collected. The seeds were scattered on a glass tray and a picture was taken. Using the digital analysis, the number of seeds in each sample was calculated.
Dry Weight and Seed Yield—
On about day 80 from sowing, the plants were harvested and left to dry at 30° C. in a drying chamber. The biomass and seed weight of each plot were measured and divided by the number of plants in each plot.
Dry weight=total weight of the vegetative portion above ground (excluding roots) after drying at 30° C. in a drying chamber.
Seed yield per plant=total seed weight per plant (gr.).
1000 seed weight (the weight of 1000 seeds) (gr.).
Oil Percentage in Seeds—
At the end of the experiment all seeds from each plot were collected. Seeds from 3 plots were mixed grounded and then mounted onto the extraction chamber. 210 ml of n-Hexane (Cat No. 080951 Biolab Ltd.) were used as the solvent. The extraction was performed for 30 hours at medium heat 50° C. Once the extraction has ended the n-Hexane is evaporated using the evaporator at 35° C. and vacuum conditions. The process was repeated twice. The information gained from the Soxhlet extractor (Soxhlet, F. Die gewichtsanalytische Bestimmung des Milchfettes, Polytechnisches J. (Dingler's) 1879, 232, 461) was used to create a calibration curve for the Low Resonance NMR. The content of oil of all seed samples was determined using the Low Resonance NMR (MARAN Ultra-Oxford Instrument) and its MultiQuant software package.
Silique Length Analysis—
On day 50 from sowing, 30 siliques from different plants in each plot were sampled in block A. The chosen siliques were green-yellow in color and were collected from the bottom parts of a grown plant's stem. A digital photograph was taken to determine silique's length.
Statistical Analyses—
To identify outperforming genes and constructs, results from the independent transformation events tested were analyzed separately. Data was analyzed using Student's t-test and results were considered significant if the p value was less than 0.1. The JMP statistics software package was used (Version 5.2.1, SAS Institute Inc., Cary, N.C., USA).
Tables 52-56 summarize the observed phenotypes of transgenic plants exogenously expressing the gene constructs using the seed maturation (GH-SM) assays under normal conditions. The evaluation of each gene was performed by testing the performance of different number of events. Event with p-value <0.1 was considered statistically significant.
Assay 2: Plant Performance Improvement Measured Until Bolting Stage: Plant Biomass and Plant Growth Rate Under Normal Greenhouse Conditions (GH-SB Assays)
This assay follows the plant biomass formation and the rosette area growth of plants grown in the greenhouse under normal growth conditions. Transgenic Arabidopsis seeds were sown in agar media supplemented with ½ MS medium and a selection agent (Kanamycin). The T2 transgenic seedlings were then transplanted to 1.7 trays filled with peat and perlite in a 1:1 ratio. The trays were irrigated with a solution containing of 6 mM inorganic nitrogen in the form of KNO3 with 1 mM KH2PO4, 1 mM MgSO4, 2 mM CaCl2 and microelements. All plants were grown in the greenhouse until bolting stage. Plant biomass (the above ground tissue) was weight in directly after harvesting the rosette (plant fresh weight [FW]). Following plants were dried in an oven at 50° C. for 48 hours and weighted (plant dry weight [DW]).
Each construct was validated at its T2 generation. Transgenic plants transformed with a construct conformed by an empty vector carrying the 35S promoter and the selectable marker were used as control.
The plants were analyzed for their overall size, growth rate, fresh weight and dry matter. Transgenic plants performance was compared to control plants grown in parallel under the same conditions. Mock-transgenic plants expressing the uidA reporter gene (GUS-Intron) or with no gene at all, under the same promoter were used as control.
The experiment was planned in nested randomized plot distribution. For each gene of the invention three to five independent transformation events were analyzed from each construct.
Digital Imaging—
A laboratory image acquisition system, which consists of a digital reflex camera (Canon EOS 300D) attached with a 55 mm focal length lens (Canon EF-S series), mounted on a reproduction device (Kaiser RS), which includes 4 light units (4×150 Watts light bulb) was used for capturing images of plant samples.
The image capturing process was repeated every 2 days starting from day 1 after transplanting till day 15. Same camera, placed in a custom made iron mount, was used for capturing images of larger plants sawn in white tubs in an environmental controlled greenhouse. The tubs were square shape include 1.7 liter trays. During the capture process, the tubes were placed beneath the iron mount, while avoiding direct sun light and casting of shadows.
An image analysis system was used, which consists of a personal desktop computer (Intel P4 3.0 GHz processor) and a public domain program—ImageJ 1.39 [Java based image processing program which was developed at the U.S. National Institutes of Health and freely available on the internet at Hypertext Transfer Protocol://rsbweb (dot) nih (dot) gov/]. Images were captured in resolution of 10 Mega Pixels (3888×2592 pixels) and stored in a low compression JPEG (Joint Photographic Experts Group standard) format. Next, analyzed data was saved to text files and processed using the JMP statistical analysis software (SAS institute).
Leaf Analysis—
Using the digital analysis leaves data was calculated, including leaf number, rosette area, rosette diameter, and leaf blade area.
Vegetative Growth Rate:
the relative growth rate (RGR) of leaf number (Formula IX, described above), rosette area (Formula VIII described above) and plot coverage (Formula XV, described below) were calculated using the indicated formulas.
RGR plot coverage Relative growth rate of plot coverage=Regression coefficient of plot coverage along time course. Formula XV
Plant Fresh and Dry Weight—
On about day 80 from sowing, the plants were harvested and directly weight for the determination of the plant fresh weight (FW) and left to dry at 50° C. in a drying chamber for about 48 hours before weighting to determine plant dry weight (DW).
Statistical Analyses—
To identify outperforming genes and constructs, results from the independent transformation events tested were analyzed separately. Data was analyzed using Student's t-test and results were considered significant if the p value was less than 0.1. The JMP statistics software package was used (Version 5.2.1, SAS Institute Inc., Cary, N.C., USA).
Experimental Results:
Tables 57-59 summarize the observed phenotypes of transgenic plants expressing the genes constructs using the GH-SB Assays.
The genes listed in Tables 57-59 improved plant performance when grown at normal conditions. These genes produced larger plants with a larger photosynthetic area, biomass (fresh weight, dry weight, rosette diameter, rosette area and plot coverage), relative growth rate, blade relative area and petiole relative area. The genes were cloned under the regulation of a constitutive At6669 promoter (SEQ ID NO:8529). The evaluation of each gene was performed by testing the performance of different number of events. Event with p-value <0.1 was considered statistically significant.
Surface sterilized seeds were sown in basal media [50% Murashige-Skoog medium (MS) supplemented with 0.8% plant agar as solidifying agent] in the presence of Kanamycin (used as a selecting agent). After sowing, plates were transferred for 2-3 days for stratification at 4° C. and then grown at 25° C. under 12-hour light 12-hour dark daily cycles for 7 to 10 days. At this time point, seedlings randomly chosen were carefully transferred to plates containing ½ MS media (15 mM N). For experiments performed in T2 lines, each plate contained 5 seedlings of the same transgenic event, and 3-4 different plates (replicates) for each event. For each polynucleotide of the invention at least four-five independent transformation events were analyzed from each construct. For experiments performed in T1 lines, each plate contained 5 seedlings of 5 independent transgenic events and 3-4 different plates (replicates) were planted. In total, for T1 lines, 20 independent events were evaluated. Plants expressing the polynucleotides of the invention were compared to the average measurement of the control plants (empty vector or GUS reporter gene under the same promoter) used in the same experiment.
Digital Imaging—
A laboratory image acquisition system, which consists of a digital reflex camera (Canon EOS 300D) attached with a 55 mm focal length lens (Canon EF-S series), mounted on a reproduction device (Kaiser RS), which includes 4 light units (4×150 Watts light bulb) and located in a darkroom, was used for capturing images of plantlets sawn in agar plates.
The image capturing process was repeated every 3-4 days starting at day 1 till day 10 (see for example the images in
Seedling Analysis—
Using the digital analysis seedling data was calculated, including leaf area, root coverage and root length.
The relative growth rate for the various seedling parameters was calculated according to the following formulas XVI (RGR leaf area, below), V (RGR root coverage, described above) and XVII (RGR root length, below).
Relative growth rate of leaf area=Regression coefficient of leaf area along time course. Formula XVI
Relative growth rate of root length=Regression coefficient of root length along time course. Formula XVII
At the end of the experiment, plantlets were removed from the media and weighed for the determination of plant fresh weight. Plantlets were then dried for 24 hours at 60° C., and weighed again to measure plant dry weight for later statistical analysis. The fresh and dry weights were provided for each Arabidopsis plant. Growth rate was determined by comparing the leaf area coverage, root coverage and root length, between each couple of sequential photographs, and results were used to resolve the effect of the gene introduced on plant vigor under optimal conditions. Similarly, the effect of the gene introduced on biomass accumulation, under optimal conditions, was determined by comparing the plants' fresh and dry weight to that of control plants (containing an empty vector or the GUS reporter gene under the same promoter). From every construct created, 3-5 independent transformation events were examined in replicates.
Statistical Analyses—
To identify genes conferring significantly improved plant vigor or enlarged root architecture, the results obtained from the transgenic plants were compared to those obtained from control plants. To identify outperforming genes and constructs, results from the independent transformation events tested were analyzed separately. To evaluate the effect of a gene event over a control the data was analyzed by Student's t-test and the p value was calculated. Results were considered significant if p<0.1. The JMP statistics software package was used (Version 5.2.1, SAS Institute Inc., Cary, N.C., USA).
Experimental Results:
Tables 60-62 summarize the observed phenotypes of transgenic plants expressing the gene constructs using the TC -T2 Assays.
The genes presented in Table 60 showed a significant improvement as they produced larger plant biomass (plant fresh and dry weight) in T2 generation when grown under normal growth conditions, compared to control plants. The genes were cloned under the regulation of a constitutive promoter (At6669, SEQ ID NO:8529).
The evaluation of each gene was carried out by testing the performance of different number of events. Some of the genes were evaluated in more than one tissue culture assay. The results obtained in these second experiments were significantly positive as well.
The genes presented in Tables 61-62 show a significant improvement in plant performance since they produced a larger leaf biomass (leaf area) and root biomass (root length and root coverage) (Table 61) and a higher relative growth rate of leaf area, root coverage and root length (Table 62) when grown under normal growth conditions, compared to control plants. Plants producing larger root biomass have better possibilities to absorb larger amount of nitrogen from soil. Plants producing larger leaf biomass have better ability to produce assimilates. The genes were cloned under the regulation of a constitutive promoter (At6669). The evaluation of each gene was performed by testing the performance of different number of events. Some of the genes were evaluated in more than one tissue culture assay. This second experiment confirmed the significant increment in leaf and root performance. Event with p-value <0.1 was considered statistically significant.
Results from T1 Plants
The genes presented in Tables 63-64 showed a significant improvement in plant biomass and root development since they produced a larger leaf and root biomass (leaf area, root length and root coverage) (Table 63), and a higher relative growth rate of leaf area, root coverage and root length (Table 64) when grown under normal growth conditions, compared to control plants. Plants producing larger root biomass have better possibilities to absorb larger amount of nitrogen from soil. Plants producing larger leaf biomass has better ability to produce assimilates). The genes were cloned under the regulation of a constitutive promoter (At6669; SEQ ID NO:8529). The evaluation of each gene was performed by testing the performance of different number of events. Some of the genes were evaluated in more than one tissue culture assay. This second experiment confirmed the significant increment in leaf and root performance. Event with p-value <0.1 was considered statistically significant.
Tables 63-64 summarize the observed phenotypes of transgenic plants expressing the gene constructs using the TC-T1 Assays.
These results demonstrate that the polynucleotides of the invention are capable of improving yield and additional valuable important agricultural traits such as increase of biomass, abiotic stress tolerance, nitrogen use efficiency, yield, vigor, fiber yield and/or quality. Thus, transformed plants showing improved fresh and dry weight demonstrate the gene capacity to improve biomass a key trait of crops for forage and plant productivity; transformed plants showing improvement of seed yield demonstrate the genes capacity to improve plant productivity; transformed plants showing improvement of plot coverage and rosette diameter demonstrate the genes capacity to improve plant drought resistance as they reduce the loss of soil water by simple evaporation and reduce the competition with weeds; hence reduce the need to use herbicides to control weeds. Transformed plants showing improvement of relative growth rate of various organs (leaf and root) demonstrate the gene capacity to promote plant growth and hence shortening the needed growth period and/or alternatively improving the utilization of available nutrients and water leading to increase of land productivity; Transformed plants showing improvement of organ number as demonstrated by the leaf number parameter exhibit a potential to improve biomass yield important for forage crops and improve the plant productivity; Transformed plants showing increased root length and coverage demonstrate the gene capacity to improve drought resistance and better utilization of fertilizers as the roots can reach larger soil volume; Transformed plants showing improvement of leaf petiole relative area and leaf blade area demonstrate the genes capacity to cope with limited light intensities results from increasing the plant population densities and hence improve land productivity.
Although the invention has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art. Accordingly, it is intended to embrace all such alternatives, modifications and variations that fall within the spirit and broad scope of the appended claims.
All publications, patents and patent applications mentioned in this specification are herein incorporated in their entirety by reference into the specification, to the same extent as if each individual publication, patent or patent application was specifically and individually indicated to be incorporated herein by reference. In addition, citation or identification of any reference in this application shall not be construed as an admission that such reference is available as prior art to the present invention. To the extent that section headings are used, they should not be construed as necessarily limiting. In addition, any priority document(s) of this application is/are hereby incorporated herein by reference in its/their entirety.
This application is a division of U.S. patent application Ser. No. 15/979,507 filed on May 15, 2018, which is a division of U.S. patent application Ser. No. 14/239,787 filed on Jun. 9, 2014 which is a National Phase of PCT Patent Application No. PCT/IL2012/050327 having International Filing Date of Aug. 23, 2012, which claims the benefit of priority under 35 USC § 119(e) of U.S. Provisional Patent Application Nos. 61/526,299 filed on Aug. 23, 2011 and 61/585,688 filed on Jan. 12, 2012. The contents of the above applications are all incorporated by reference as if fully set forth herein in their entirety.
| Number | Name | Date | Kind |
|---|---|---|---|
| 6084153 | Good et al. | Jul 2000 | A |
| 6476212 | Lalgudi | Nov 2002 | B1 |
| 7214786 | Kovalic et al. | May 2007 | B2 |
| 8362325 | Troukhan et al. | Jan 2013 | B2 |
| 20020046419 | Choo et al. | Apr 2002 | A1 |
| 20050108791 | Edgerton | May 2005 | A1 |
| 20060141495 | Wu | Jun 2006 | A1 |
| 20060179511 | Chomet et al. | Aug 2006 | A1 |
| 20090087878 | La Rosa et al. | Apr 2009 | A9 |
| 20090199308 | Duff | Aug 2009 | A1 |
| 20110065583 | Kondo et al. | Mar 2011 | A1 |
| 20110214206 | La Rosa et al. | Sep 2011 | A1 |
| 20140289900 | Poraty-Gavra et al. | Sep 2014 | A1 |
| 20180245094 | Poraty-Gavra et al. | Aug 2018 | A1 |
| Number | Date | Country |
|---|---|---|
| WO 2004081173 | Sep 2004 | WO |
| WO 2004104162 | Dec 2004 | WO |
| WO 2004111183 | Dec 2004 | WO |
| WO 2005121364 | Dec 2005 | WO |
| WO 2007020638 | Feb 2007 | WO |
| WO 2007049275 | May 2007 | WO |
| WO 2008075364 | Jun 2008 | WO |
| WO 2008122980 | Oct 2008 | WO |
| WO 2009013750 | Jan 2009 | WO |
| WO 2009083958 | Jul 2009 | WO |
| WO 2009141824 | Nov 2009 | WO |
| WO 2010020941 | Feb 2010 | WO |
| WO 2010049897 | May 2010 | WO |
| WO 2010076756 | Jul 2010 | WO |
| WO 2010100595 | Sep 2010 | WO |
| WO 2010143138 | Dec 2010 | WO |
| WO 2011015985 | Feb 2011 | WO |
| WO 2011080674 | Jul 2011 | WO |
| WO 2011135527 | Nov 2011 | WO |
| WO 2012028993 | Mar 2012 | WO |
| WO 2012085862 | Jun 2012 | WO |
| WO 2012150598 | Nov 2012 | WO |
| WO 2013027223 | Feb 2013 | WO |
| WO 2013078153 | May 2013 | WO |
| WO 2013080203 | Jun 2013 | WO |
| WO 2013098819 | Jul 2013 | WO |
| WO 2013128448 | Sep 2013 | WO |
| WO 2013179211 | Dec 2013 | WO |
| WO 2014033714 | Mar 2014 | WO |
| WO 2014102773 | Jul 2014 | WO |
| WO 2014102774 | Jul 2014 | WO |
| WO 2014188428 | Nov 2014 | WO |
| WO 2015029031 | Mar 2015 | WO |
| WO 2015181823 | Dec 2015 | WO |
| WO 2016030885 | Mar 2016 | WO |
| WO 2017115353 | Jul 2017 | WO |
| Entry |
|---|
| Soderlund et al. (Sequencing, Mapping, and Analysis of 27,455 Maize Full-Length cDNAs. PLOS Genetics. 5:1-13, 2009) (Year: 2009). |
| Montoya-Garcia et al. (Regulation of Acidic Ribosomal Protein Expression and Phosphorylation in Maize. Biochemistry. 41, 10166-10172, 2002) (Year: 2002). |
| Requisition by the Examiner dated Jun. 26, 2020 From the Canadian Intellectual Property Office Re. Application No. 2,845,682. (3 Pages). |
| Clarifications Prior to Substantive Examination dated Aug. 23, 2019 from Argentinean Industrial Property National Institute Re. Application No. P20120103112 and Its English Summary. (6 pages). |
| Examination Report dated Aug. 7, 2017 From the Institute Mexican© de la Propiedad Industrial, IMPI, Direccion Divisional de Patentes Re. Application No. MX/a/2014/002049 and Its Translation Into English. (8 Pages). |
| Examination Report dated Apr. 12, 2019 from Australian Government, IP Australia Re. Application No. 2018201669. (3 pages). |
| Examination Report dated Jan. 12, 2017 From the Australian Government, IP Australia Re. Application No. 2012298157. (3 Pages). |
| Examination Report dated Jun. 12, 2016 From the Institute Mexicano de la Propiedad Industrial, IMPI Re. Application No. MX/a/2014/002049 and Its Translation Into English. |
| Examination Report dated Feb. 14, 2018 From the Institute Mexicano de la Propiedad Industrial, IMPI, Direccion Divisional de Patentes Re. Application No. MX/a/2014/002049 and Its Translation Into English. (6 Pages). |
| Examination Report dated Aug. 15, 2017 From the Australian Government, IP Australia Re. Application No. 2012298157. (9 Pages). |
| Examination Report dated Aug. 22, 2019 from Australian Government, IP Australia Re. Application No. 2018201669. (2 pages). |
| Examination Report dated Nov. 22, 2016 From the Instituto Mexicano de la Propiedad Industrial, IMPI Re. Application No. MX/a/2014/002049 and Its Translation Into English. (13 Pages). |
| International Preliminary Report on Patentability dated Mar. 6, 2014 From the International Bureau of WIPO Re. Application No. PCT/IL2012/050327. |
| International Search Report and the Written Opinion dated Apr. 10, 2013 From the International Searching Authority Re. Application No. PCT/IL2012/050327. |
| Invitation to Pay Additional Fees dated Dec. 31, 2012 From the International Searching Authority Re. Application No. PCT/IL2012/050327. |
| Official Action dated Oct. 4, 2017 From the US Patent and Trademark Office Re. U.S. Appl. No. 14/239,787. (25 pages). |
| Official Action dated Oct. 10, 2018 From the US Patent and Trademark Office Re. U.S. Appl. No. 15/979,507. (38 pages). |
| Official Action dated Mar. 21, 2017 From the US Patent and Trademark Office Re. U.S. Appl. No. 14/239,787. (59 pages. |
| Official Action dated Apr. 29, 2019 From the US Patent and Trademark Office Re. U.S. Appl. No. 15/979,507. (26 pages). |
| Requisition by the Examiner dated May 9, 2019 From the Innovation, Science and Economic Development Canada, Canadian Intellectual Property Office Re. Application No. 2,845,682. (5 Pages). |
| Requisition by the Examiner dated Apr. 24, 2018 From the Innovation, Science and Economic Development Canada, Canadian Intellectual Property Office Re. Application No. 2,845,682. (3 Pages). |
| Restriction Official Action dated Dec. 5, 2016 From the US Patent and Trademark Office Re. U.S. Appl. No. 14/239,787. (7 pages). |
| Restriction Official Action dated Jul. 16, 2018 From the US Patent and Trademark Office Re. U.S. Appl. No. 15/979,507. (6 pages). |
| Burk et al. “A Katanin-Like Protein Regulates Normal Cell Wall Biosynthesis and Cell Elongation”, The Plant Cell, 13(4): 807- 827, Apr. 1, 2001. |
| Kawaura er al. “Triticum Aestivum cDNA Clone: SET2_C15, Cultivar: Chinese Spring”, Database NCBI [Online], GenBank: AK333791.1, Database Accession No. AK333791, Jun. 25, 2009. |
| Sasaki et al. “Katanin [Oryza Sativa Japonica Group]”, Database NCBI [Online], GenBank: BAD87507.1, Database Accession No. BAD87507, Feb. 16, 2008. |
| Sasaki et al. “Vacuolar Protein Sorting Factor 4B-Like [Oryza Sativa Japonica Group]”, Database NCBI [Online], GenBank: BAD73312.1, Database Accession No. BAD73312, Feb. 16, 2008. |
| Sasaki et al. “Vacuolar Protein Sorting Factor 4B-Like [Oryza Sativa Japonica Group]”, Database NCBI [Online], GenBank: BAD73365.1, Database Accession No. BAD73365, Feb. 16, 2008. |
| Soderlund et al. “Sequencing, Mapping, and Analysis of 27,455 Maize Full-Length cDNAs”, PLoS Genetics, 5(11): e1000740-1—e1000740-13, Nov. 2009. |
| Soderlund et al. “Unknown [Zea Mays]”, Database NCBI [Online], GenBank: ACF85066.1, Database Accession No. ACF85066, Jul. 30, 2008. |
| Soderlund et al. “Unknown [Zea Mays]”, Database NCBI [Online], GenBank: ACN28820.1, Database Accession No. ACN28820, Feb. 21, 2009. |
| Stoppin-Mellet et al. “Katanin's Severing Activity Favors Bundling of Cortical Microtubules in Plants”, The Plant Journal, 46(6): 1009-1017, Jun. 1, 2006. |
| The International Brachypodium Initiative “Genome Sequencing and Analysis of the Model Grass Brachypodium Distachyon”, Nature, 463(7282): 763-768, Feb. 11, 2010. |
| Yanagisawa et al. “Metabolic Engineering With Dof1 Transcription Factor in Plants: Improved Nitrogen Assimilation and Growth Under Low-Nitrogen Conditions”, Proc. Natl. Acad. Sci USA, PNAS, 101(20): 7833-7838, May 18, 2004. |
| Technical Examination Report dated Dec. 18, 2020 from the National Institute of Industrial Property of Brazil Re. Application No. P20120103112 with an English Summary. (9 pages). |
| Examination Report dated May 4, 2021 from the Australian Patent Office Re. Application No. 2020202369. (2 pages). |
| Examination Report dated Oct. 8, 2021 from the Australian Patent Office Re. Application No. 2020202369. (6 pages). |
| Requisition by the Examiner dated Sep. 3, 2021 From the Innovation, Science and Economic Development Canada, Canadian Intellectual Property Office Re. Application No. 2,845,682. (3 pages). |
| Number | Date | Country | |
|---|---|---|---|
| 20200048652 A1 | Feb 2020 | US |
| Number | Date | Country | |
|---|---|---|---|
| 61526299 | Aug 2011 | US | |
| 61585688 | Jan 2012 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 15979507 | May 2018 | US |
| Child | 16665132 | US | |
| Parent | 14239787 | US | |
| Child | 15979507 | US |
