Patent Grant
9574200
The present invention, in some embodiments thereof, relates to isolated polypeptides and polynucleotides, nucleic acid constructs comprising same, transgenic plants expressing same and methods of using same for increasing abiotic stress tolerance (ABST), water use efficiency (WUE), yield (e.g., grain quantity and/or quality), biomass, oil content, growth rate, vigor, 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. In addition, chilling may lead to yield losses and lower product quality through the delayed ripening of maize. Excessive light conditions, which occur under clear atmospheric conditions subsequent to cold late summer/autumn night's, can lead to photoinhibition of photosynthesis (disruption of photosynthesis).
Suboptimal nutrient (macro and micro nutrient) affect plant growth and development through the whole plant life cycle. One of the essential macronutrients for the plant is Nitrogen. Nitrogen is responsible for biosynthesis of amino acids and nucleic acids, prosthetic groups, plant hormones, plant chemical defenses, and the like. Nitrogen is often the rate-limiting element in plant growth and all field crops have a fundamental dependence on inorganic nitrogenous fertilizer. Since fertilizer is rapidly depleted from most soil types, it must be supplied to growing crops two or three times during the growing season. Additional important macronutrients are Phosphorous (P) and Potassium (K), which have a direct correlation to yield and general plant tolerance.
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, protein and 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 leaves, 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. 2009/013750 discloses genes, constructs and methods of increasing abiotic stress tolerance, biomass and/or yield in 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. 2007/049275 discloses isolated polypeptides, polynucleotides encoding same, transgenic plants expressing same and methods of using same for increasing plant abiotic stress tolerance and biomass.
WO publication No. 2004/104162 discloses methods of increasing abiotic stress tolerance and/or biomass in plants and plants generated thereby.
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. 2007/020638 discloses methods of increasing abiotic stress tolerance and/or biomass in plants and plants generated thereby.
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. 2010/020941 discloses methods of increasing nitrogen use efficiency, abiotic stress tolerance, yield and biomass in plants and plants generated thereby.
According to an aspect of some embodiments of the present invention there is provided a method of increasing abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, 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:1-473, 783-1272, 1277-4139, 4142, 4146-5508 or 5509, thereby increasing the abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, 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 abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, 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:1-473, 783-1272, 1274, 1275, 1277-4142, and 4146-5509, thereby increasing the abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, 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 abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, 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:474-562, 564-620, 622-750, 752-782, 5510-5939, 5946-6856, 6858-7540, 7543, 7544, 7548-8735 or 8736, thereby increasing the abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, 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 abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, 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:474-782, 5510-5940, 5942, 5943, 5945-6856, 6858-7544, and 7548-8736, thereby increasing the abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, 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 at least 80% identical to SEQ ID NO:1-473, 783-1272, 1277-4139, 4142, 4146-5508 or 5509, wherein the nucleic acid sequence is capable of increasing abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, 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:1-473, 783-1272, 1274, 1275, 1277-4142, and 4146-5509.
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:474-562, 564-620, 622-750, 752-782, 5510-5939, 5946-6856, 6858-7540, 7543, 7544, 7548-8735 or 8736, wherein the amino acid sequence is capable of increasing abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, 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 the amino acid sequence selected from the group consisting of SEQ ID NOs:474-782, 5510-5940, 5942, 5943, 5945-6856, 6858-7544, and 7548-8736.
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:474-562, 564-620, 622-750, 752-782, 5510-5939, 5946-6856, 6858-7540, 7543, 7544, 7548-8735 or 8736, wherein the amino acid sequence is capable of increasing abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, 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:474-782, 5510-5940, 5942, 5943, 5945-6856, 6858-7544, and 7548-8736.
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 some embodiments of the invention, the nucleic acid sequence is as set forth in SEQ ID NO:1-473, 783-1272, 1274, 1275, 1277-4142, 4146-5508 or 5509.
According to some embodiments of the invention, the polynucleotide consists of the nucleic acid sequence selected from the group consisting of SEQ ID NOs:1-473, 783-1272, 1274, 1275, 1277-4142, and 4146-5509.
According to some embodiments of the invention, the nucleic acid sequence encodes an amino acid sequence at least 80% homologous to SEQ ID NO:474-562, 564-620, 622-750, 752-782, 5510-5939, 5946-6856, 6858-7540, 7543, 7544, 7548-8735 or 8736.
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:474-782, 5510-5940, 5942, 5943, 5945-6856, 6858-7544, and 7548-8736.
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 promoter is heterologous to the isolated polynucleotide and/or 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.
Implementation of the method and/or system of embodiments of the invention can involve performing or completing selected tasks manually, automatically, or a combination thereof. Moreover, according to actual instrumentation and equipment of embodiments of the method and/or system of the invention, several selected tasks could be implemented by hardware, by software or by firmware or by a combination thereof using an operating system.
For example, hardware for performing selected tasks according to embodiments of the invention could be implemented as a chip or a circuit. As software, selected tasks according to embodiments of the invention could be implemented as a plurality of software instructions being executed by a computer using any suitable operating system. In an exemplary embodiment of the invention, one or more tasks according to exemplary embodiments of method and/or system as described herein are performed by a data processor, such as a computing platform for executing a plurality of instructions. Optionally, the data processor includes a volatile memory for storing instructions and/or data and/or a non-volatile storage, for example, a magnetic hard-disk and/or removable media, for storing instructions and/or data. Optionally, a network connection is provided as well. A display and/or a user input device such as a keyboard or mouse are optionally provided as well.
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 polypeptides and polynucleotides, nucleic acid constructs comprising the isolated polypeptides, transgenic plants expressing same and methods of using same for increasing abiotic stress tolerance (ABST), water use efficiency (WUE), yield (e.g., grain quantity and/or quality), biomass, oil content, growth rate, vigor, nitrogen use efficiency (NUE) and/or fertilizer use efficiency (FUE) 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 abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, and/or 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 abiotic stress tolerance, yield (e.g., seed yield, oil yield, oil content), biomass, growth rate, vigor, and/or nitrogen use efficiency of a plant. Genes which affect the trait-of-interest were identified based on expression profiles of genes of several Arabidopsis ecotypes and tissues, Tomato, Sorghum, Maize and Barley varieties (Examples 1-8), homology with genes known to affect the trait-of-interest and using digital expression profile in specific tissues and conditions (Tables 1-53, Examples 1-8; polynucleotides SEQ ID NOs:1-274; polypeptides SEQ ID NOs:474-731). Homologous polypeptides and polynucleotides having the same function were also identified (Table 54, Example 10; polynucleotides SEQ ID NOs:783-5509; polypeptides SEQ ID NOs:5510-8736). Transgenic plants over-expressing the identified polynucleotides and polypeptides (Table 55, Example 11) were found to exhibit increased abiotic stress tolerance (e.g., under osmotic stress or salinity stress), nitrogen use efficiency (e.g., root performance), biomass (under stress conditions or normal/standard conditions), growth rate (under stress conditions or normal/standard conditions), and yield (Tables 56-83); Examples 14-15). Altogether, these results suggest the use of the novel polynucleotides and polypeptides of the invention for increasing abiotic stress tolerance, yield (including oil yield, seed yield and oil content), growth rate, biomass, vigor and/or nitrogen use efficiency of a plant.
Thus, according to an aspect of some embodiments of the invention, there is provided method of increasing abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, 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:1-473, 783-1272, 1277-4139, 4142, 4146-5508 or 5509, thereby increasing the abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, and/or nitrogen use efficiency of the plant.
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.
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 vigor. 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 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 abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, 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 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 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:1-473, 783-1272, 1277-4139, 4142, and 4146-5509.
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.
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 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:1-473, 783-1272, 1277-4139, 4142, and 4146-5509.
According to some embodiments of the invention the exogenous polynucleotide is set forth by SEQ ID NO:1-473, 783-1272, 1274, 1275, 1277-4142, 4146-5508 or 5509.
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.
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% homologous to the amino acid sequence selected from the group consisting of SEQ ID NOs: 474-562, 564-620, 622-750, 752-782, 5510-5939, 5946-6856, 6858-7540, 7543, 7544, and 7548-8736.
Homology (e.g., percent homology) can be determined using any homology comparison software, including for example, the BlastP or TBLASTN software of the National Center of Biotechnology Information (NCBI) such as by using default parameters, when starting from a polypeptide sequence; or the tBLASTX algorithm (available via the NCBI) such as by using default parameters, which compares the six-frame conceptual translation products of a nucleotide query sequence (both strands) against a protein sequence database.
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.
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:474-782, 5510-5940, 5942, 5943, 5945-6856, 6858-7544, 7548-8735 or 8736.
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 effect 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, 273, 274, and 473.
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:1-473, 783-1272, 1277-4139, 4142, and 4146-5509.
According to some embodiments of the invention the nucleic acid sequence is capable of increasing abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, and/or nitrogen 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:1-473, 783-1272, 1274, 1275, 1277-4142, and 4146-5509.
According to some embodiments of the invention the isolated polynucleotide is set forth by SEQ ID NO:1-473, 783-1272, 1274, 1275, 1277-4142, 4146-5508 or 5509.
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 NOs: 474-562, 564-620, 622-750, 752-782, 5510-5939, 5946-6856, 6858-7540, 7543, 7544, and 7548-8736.
According to some embodiments of the invention the amino acid sequence is capable of increasing abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, and/or nitrogen 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:474-782, 5510-5940, 5942, 5943, 5945-6856, 6858-7544, and 7548-8736.
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 NOs: 474-562, 564-620, 622-750, 752-782, 5510-5939, 5946-6856, 6858-7540, 7543, 7544, and 7548-8736.
According to some embodiments of the invention, the polypeptide comprising an amino acid sequence selected from the group consisting of SEQ ID NOs:474-782, 5510-5940, 5942, 5943, 5945-6856, 6858-7544, and 7548-8736.
According to some embodiments of the invention, the polypeptide is set forth by SEQ ID NO:474-782, 5510-5940, 5942, 5943, 5945-6856, 6858-7544, 7548-8735 or 8736.
According to 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 of the isolated polynucleotide in a host cell.
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, Brussels 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, barely, 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, 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.
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.
Suitable constitutive promoters include, for example, CaMV 35S promoter (SEQ ID NO:8739; Odell et al., Nature 313:810-812, 1985); Arabidopsis At6669 promoter (SEQ ID NO:8738; see PCT Publication No. WO04081173A2); Arabidopsis new At6669 promoter (SEQ ID NO:8741); maize Ubi 1 (Christensen et al., Plant Sol. Biol. 18:675-689, 1992); rice actin (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 (de Pater et al, Plant J November; 2(6):837-44, 1992); ubiquitin (Christensen et al, Plant Mol. Biol. 18: 675-689, 1992); 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 [such as described, for example, by 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], 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:8740), 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), 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, etal., Plant Mol. Biol. 19: 873-876, 1992)], endosperm specific promoters [e.g., wheat LMW and HMW, glutenin-1 (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), 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. Nati. 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), apetala-3], and root promoters such as the ROOTP promoter [SEQ ID NO: 8742].
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, N.Y.
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.
Since processes which increase abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, and/or nitrogen use efficiency 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 abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, and/or nitrogen use efficiency.
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 than 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, high temperature, heavy metal toxicity, anaerobiosis, nutrient deficiency, nutrient excess, atmospheric pollution and UV irradiation.
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., abiotic stress tolerance, yield, biomass, growth rate, vigor, oil content, fiber yield, fiber quality, and/or nitrogen 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.
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 overexpres sing 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:
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://WorldWide 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.
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.
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 transcriptom 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 nitrogen use efficiency, abiotic stress tolerance, yield, growth rate and the like).
The present inventors have identified polynucleotides which upregulation of expression thereof can increase abiotic stress tolerance (ABST), water use efficiency (WUE), yield, oil content, growth rate, vigor, biomass, nitrogen use efficiency (NUE), and fertilizer use efficiency (FUE) of a plant.
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 ABST, increased yield, growth rate, vigor, biomass, oil content, WUE, NUE and FUE of a plant.
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 data.
In order to produce a high throughput correlation analysis, the present inventors utilized a Tomato 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 Toamto genes and transcripts. In order to define correlations between the levels of RNA expression with ABST, yield components or vigor related parameters various plant characteristics of 18 different Tomato varieties were analyzed. Among them, 10 varieties 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].
Correlation of Tomato Varieties Across Ecotype Grown Under 50% Irrigation Conditions
Experimental Procedures
Growth procedure—Tomato variety was grown under normal conditions (4-6 Liters/m2 per day) until flower stage. At this time, irrigation was reduced to 50% compared to normal conditions.
RNA Extraction—Two tissues at different developmental stages [flower and leaf], representing different plant characteristics, were sampled and RNA was extracted as described above. For convenience, each micro-array expression information tissue type has received a Set ID as summarized in Table 1 below.
Tomato yield components and vigor related parameters under 50% water irrigation assessment—10 Tomato varieties in 3 repetitive blocks (named A, B, and C,), each containing 6 plants per plot were grown at net house. Plants were phenotyped on a daily basis following the standard descriptor of tomato (Table 2, below). Harvest was conducted while 50% of the fruits were red (mature). Plants were separated to the vegetative part and fruits, of them, 2 nodes were analyzed for additional inflorescent parameters such as size, number of flowers, and inflorescent weight. Fresh weight of all vegetative material was measured. Fruits were separated to colors (red vs. green) and in accordance with the fruit size (small, medium and large). 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 2, hereinbelow.
Fruit weight (Grams)—At the end of the experiment [when 50% of the fruit were ripe (red)] all fruits from plots within blocks A-C were collected. The total fruits were counted and weighted. The average fruits weight was calculated by dividing the total fruit weight by the number of fruits.
Plant vegetative weight (grams)—At the end of the experiment [when 50% of the fruit were ripe (red)] all plants from plots within blocks A-C were collected. Fresh weight was measured (grams).
Inflorescence weight (grams)—At the end of the experiment [when 50% of the fruits were ripe (red)] two Inflorescence from plots within blocks A-C were collected. The Inflorescence weight (gr.) and number of flowers per inflorescence were counted.
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.
Water Use Efficiency (WUE)—can be determined as the biomass produced per unit transpiration. To analyze WUE, leaf relative water content was measured in control and transgenic plants. Fresh weight (FW) was immediately recorded; then leaves were soaked for 8 hours in distilled water at room temperature in the dark, and the turgid weight (TW) was recorded. Total dry weight (DW) was recorded after drying the leaves at 60° C. to a constant weight. Relative water content (RWC) was calculated according to the following Formula I [(FW−DW)/(TW−DW)×100] as described above.
Plants that maintain high relative water content (RWC) compared to control lines were considered more tolerant to drought than those exhibiting reduced relative water content
Experimental Results
10 different Tomato varieties were grown and characterized for 27 parameters as described above. The average for each of the measured parameter was calculated using the JMP software and values are summarized in Tables 3, 4 and 5 below. Subsequent correlation analysis between the various transcriptom sets (Table 1) and the average parameters was conducted, and results were integrated to the database.
Correlation of early vigor traits across collection of Tomato ecotypes under high salinity concentration—Ten Tomato 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: Tomato seeds were sown in trays filled with a mix of vermiculite and peat in a 1:1 ratio. Following germination, the trays were transferred for the high salinity to 100 mM NaCl solution or to the normal growth solution [full Hogland; KNO3—0.808 grams/liter, MgSO4—0.12 grams/liter, KH2 PO4 —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].
RNA Extraction—All 10 selected Tomato varieties were sample per each treatment. Two tissues [leaves and flowers] growing at 50% irrigation or under Normal conditions were sampled and RNA was extracted as described above.
Tomato vigor related parameters under 100 mM NaCl—following 5 weeks of growing, plant were harvested and analyzed for leaf number, plant height, and plant weight. Next, analyzed data was saved to text files and processed using the JMP statistical analysis software (SAS institute).
Data parameters collected are summarize in Table 7, hereinbelow.
Experimental Results
10 different Tomato varieties were grown and characterized for 3 parameters as described above. The average for each of the measured parameter was calculated using the JMP software and values are summarized in Tables 8 below. Subsequent correlation analysis between the various transcriptom sets (Table 6) and the average parameters, was conducted. Follow, results were integrated to the database.
In order to produce a high throughput correlation analysis, 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 and yield components or vigor related parameters, various plant characteristics of 17 different sorghum varieties were analyzed. Among them, 10 varieties 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].
Correlation of Sorghum Varieties Across Ecotype Grown Under Severe Drought Conditions
Experimental Procedures
17 Sorghum varieties were grown in 3 repetitive plots, in field. Briefly, the growing protocol was as follows: sorghum seeds were sown in soil and grown under normal condition until around 35 days from sowing, around V8 (Last leaf visible, but still rolled up, ear beginning to swell). At this point, irrigation was stopped, and severe drought stress was developed. In order to define correlations between the levels of RNA expression with drought, yield components or vigor related parameters, the 17 different sorghum varieties were analyzed. Among them, 10 varieties 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].
RNA extraction—All 10 selected Sorghum varieties were sample per each treatment. Plant tissues [Flag leaf and Flower meristem] growing under severe drought stress and plants grown under Normal conditions were sampled and RNA was extracted as described above. For convenience, each micro-array expression information tissue type has received a Set ID as summarized in Table 11 below. Data parameters collected are summarize in Table 12, hereinbelow.
Sorghum transcriptom experimental sets
Data parameters collected are summarize in Table 12, hereinbelow.
Sorghum correlated parameters (vectors)
Grain per plant (gr.)—At the end of the experiment (Inflorescence were dry) all spikes from plots within blocks A-C were collected. 5 Inflorescence were separately threshed and grains were weighted, all addition Inflorescence were threshed together and weighted as well. The average weight per Inflorescence was calculated by dividing the total grain weight by number of total Inflorescence per plot, or in case of 5 inflorescence, by weight by the total grain number by 5.
Plant height—Plant were characterize for height during groin period in 6 time Points. In each measure, plants were measured for its height using measuring tape. Height was measured from ground level to top of the longest leaf.
Inflorescence weight (gr.)—At the end of the experiment (when Inflorescence were dry) five Inflorescence from plots within blocks A-C were collected. The Inflorescence were weighted (gr.).
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.
Vegetative dry weight and inflorescence—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 Inflorescence weight of each plot was separated, measured and divided by the number of Inflorescence.
Dry weight=total weight of the vegetative portion above ground (excluding roots) after drying at 70° C. in oven for 48 hours;
Harvest Index (for Sorghum)—The harvest index is calculated using Formula V.
Harvest Index=Average grain dry weight per Inflorescence/(Average vegetative dry weight per Inflorescence+Average Inflorescence dry weight) Formula V:
Experimental Results
16 different sorghum varieties were grown and characterized for 49 parameters as described above. The average for each of the measured parameter was calculated using the JMP software and values are summarized in Tables 13-18 below. Subsequent correlation analysis between the various transcriptom sets (Table 11) and the average parameters, was conducted. Follow, results were integrated to the database.
Sorghum vigor related parameters under 100 mM NaCl and low temperature (8-10° 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) solution, low temperature (8-10° C.) or at Normal growth solution [full Hogland; KNO3—0.808 grams/liter, MgSO4—0.12 grams/liter, KH2 PO4 —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].
RNA extraction—All 10 selected Sorghum varieties were sample per each treatment. Two tissues [leaves and roots] growing at 100 mM NaCl, low temperature (8-10° C.) or under Normal conditions were sampled and RNA was extracted as described above.
Sorghum correlated parameters (vectors)
Experimental Results
10 different Sorghum varieties were grown and characterized for 25 parameters as described above (Table 19). The average for each of the measured parameter was calculated using the JMP software and values are summarized in Tables 20-22 below. Subsequent correlation analysis between the various transcriptom sets (Table 11) and the average parameters (Tables 20-22), was conducted (Tables 23 and 24). Follow, results were integrated to the database.
Sorghum accessions, addition measured parameters
Tables 23 and 24 hereinbelow, provide correlation analysis between the characterized parameters (as described above in Examples 2 and 3) and the tissue transcriptom.
In order to produce a high throughput correlation analysis between plant phenotype and gene expression level, the present inventors utilized a maize 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 maize genes and transcripts. In order to define correlations between the levels of RNA expression with yield and NUE 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].
Correlation of Maize Hybrids Across Ecotypes Grown Under Regular Growth Conditions
Experimental Procedures
12 Maize hybrids were grown in 3 repetitive plots, in field. Maize seeds were planted and plants were grown in the field using commercial fertilization and irrigation protocols. In order to define correlations between the levels of RNA expression with NUE and yield components or vigor related parameters, the 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].
Analyzed sorghum tissues—All 10 selected maize hybrids were sample per each treatment. Plant tissues [Flag leaf, Flower meristem, Grain, Cobs, Internodes] growing under Normal 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 25 below.
The following parameters were collected using digital imaging system:
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 5 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 5 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.
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.)—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 average grain weight per ear was calculated by dividing the total grain weight by number of total 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 Formula II (described above).
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 Inflorescence were dry) all vegetative material from plots within blocks A-C were collected.
Dry weight=total weight of the vegetative portion above ground (excluding roots) after drying at 70° C. in oven for 48 hours;
Harvest Index (HI) (Maize)—The harvest index was calculated using Formula VI.
Harvest Index=Average grain dry weight per Ear/(Average vegetative dry weight per Ear+Average Ear dry weight) Formula VI:
Percent Filled Ear [%]—it was calculated as the percentage of the Ear area with grains out of the total ear.
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.
Experimental Results
12 different maize hybrids were grown and characterized for different parameters: The average for each of the measured parameter was calculated using the JMP software (Tables 27-88) and a subsequent correlation analysis was performed (Tables 29-30). Results were then 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 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
Analyzed Barley tissues—Five tissues at different developmental stages [meristem, flower, booting spike, stem, flag leaf], 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 31 below.
Barley yield components and vigor related parameters assessment—25 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 32, 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).
Grains per spike—At the end of the experiment (50% of the spikes were dry) all spikes from plots within blocks A-D are collected. The total number of grains from 5 spikes that were manually threshed was counted. The average grain per spike is calculated by dividing the total grain number by the number of spikes.
Grain average size (cm)—At the end of the experiment (50% of the spikes were dry) all spikes from plots within blocks A-D are collected. 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.
Grain average weight (mgr)—At the end of the experiment (50% of the spikes were dry) all spikes from plots within blocks A-D are collected. 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.
Grain yield per spike (gr)—At the end of the experiment (50% of the spikes were dry) all spikes from plots within blocks A-D are collected. 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.
Spike length analysis—At the end of the experiment (50% of the spikes were dry) all spikes from plots within blocks A-D are collected. The five chosen spikes per plant were measured using measuring tape excluding the awns.
Spike number analysis—At the end of the experiment (50% of the spikes were dry) all spikes from plots within blocks A-D are collected. The spikes per plant were counted.
Growth habit scoring—At the 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 the 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 the 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 the 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.
Harvest Index (for Barley)—The harvest index is calculated using Formula XVI.
Harvest Index=Average spike dry weight per plant/(Average vegetative dry weight per plant+Average spike dry weight per plant) Formula XVI:
Experimental Results
13 different Barley accessions were grown and characterized for 13 parameters as described above. The average for each of the measured parameter was calculated using the JMP software and values are summarized in Tables 34 and 35 below. Subsequent correlation analysis between the various transcriptom sets (Table 31) and the average parameters, was conducted (Tables 36 and 37). 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 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
Analyzed Arabidopsis tissues—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 above. Each micro-array expression information tissue type has received a Set ID as summarized Table 38 below.
Arabidopsis transcriptom experimental sets
Arabidopsis yield components and vigor related parameters under different nitrogen fertilization levels assessment—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 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 39, 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.
An 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 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, Rosette diameter and area.
Vegetative growth rate: the relative growth rate (RGR) of leaf blade area (Formula VIII), leaf number (Formula IX), rosette area (Formula X), rosette diameter (Formula XI), plot coverage (Formula XII) and Petiole Relative Area (XIII) are calculated as follows:
Relative growth rate of leaf blade area=Regression coefficient of leaf area along time course. Formula VIII:
Relative growth rate of plant leaf number=Regression coefficient of plant leaf number along time course. Formula IX:
Relative growth rate of rosette area=Regression coefficient of rosette area along time course. Formula X:
Relative growth rate of rosette diameter=Regression coefficient of rosette diameter along time course. Formula XI:
Relative growth rate of plot coverage=Regression coefficient of plot. Formula XII:
Petiole Relative Area=[(Leaf blade*Leaf number)/Rosette. Formula XIII:
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—The harvest index was calculated using Formula IV as described above.
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 [g]/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 %.
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 and values are summarized in Table 40 below. Subsequent correlation analysis between the various transcriptom sets (Table 38) and the measured parameters was conducted (Tables 41 and 42 below). Following are the results integrated to the database.
To produce a high throughput correlation analysis comparing between plant phenotype and gene expression level, 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 above. Each micro-array expression information tissue type has received a Set ID as summarized in Table 43 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 P43.0 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
Vegetative growth rate analysis—was calculated according to Formulas VIII-XIII above. The analysis was ended with the appearance of overlapping plants.
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 XV.
Seed Oil yield=Seed yield per plant(gr)*Oil % in seed. Formula XV:
Harvest Index (seed)—The harvest index was calculated using Formula IV (described above).
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 45 and 46 below.
Tables 47 and 48 provide the correlation analyses.
In order to conduct high throughput gene expression correlation analysis, the present inventors used cotton oligonucleotide microarray, designed and produced by
“Comparative Evolutionary Genomics of Cotton” [Hypertext Transfer Protocol (http)://cottonevolution (dot) info/). This Cotton Oligonucleotide Microarray is composed of 12,006 Integrated DNA Technologies (IDT) oligonucleotides derived from an assembly of more than 180,000 Gossypium ESTs sequenced from 30 cDNA libraries. For additional details see PCT/IL2005/000627 and PCT/IL2007/001590 which are fully incorporated herein by reference.
In order to define correlations between the levels of RNA expression and fiber length, fibers from 8 different cotton lines were analyzed. These fibers were selected showing very good fiber quality and high lint index (Pima types, originating from other cotton species, namely G. barbadense), different levels of quality and lint indexes from various G. hirsutum lines: good quality and high lint index (Acala type), and poor quality and short lint index (Tamcot type, and old varieties). A summary of the fiber length of the different lines is provided in Table 50.
Experimental Procedures
RNA extraction—Fiber development stages, representing different fiber characteristics, at 5, 10 and 15 DPA were sampled and RNA was extracted as described above.
Fiber length assessment—Fiber length of the selected cotton lines was 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 World Wide Web (dot) cottoninc (dot) com/ClassificationofCotton/?Pg=4#Length].
Experimental Results
Eight different cotton lines were grown, and their fiber length was measured. The fibers UHM values are summarized in Table 50 hereinbelow. The R square was calculated for each of the genes.
Based on the above described bioinformatics and experimental tools, the present inventors have identified 217 which exhibit a major impact on abiotic stress tolerance, plant yield, oil content, growth rate, vigor, biomass, growth rate, 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 53, hereinbelow.
brachypodium
brachypodium
brachypodium
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
arabidopsis
arabidopsis
arabidopsis
arabidopsis
arabidopsis
arabidopsis
arabidopsis
arabidopsis
arabidopsis
arabidopsis
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
brachypodium
sorghum
sorghum
brachypodium
sorghum
sorghum
brachypodium
brachypodium
brachypodium
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
sorghum
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 homologs: 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 ortholog genes of the genes affecting ABST, WUE, yield (e.g., seed yield, oil yield, biomass, grain quantity and/or quality), oil content, growth rate, vigor, NUE and FUE (presented in Table 53, Example 9 above), 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 to construct 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.
Methods for searching and identifying homologues of yield and improved agronomic traits such as ABS tolerance and FUE related polypeptides or polynucleotides are well within the realm of the skilled artisan. The search and identification of homologous genes involves the screening of sequence information available, for example, in public databases, which include but are not limited to 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 (orthologue) 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), Wheat (Triticum aestivum)
The above-mentioned analyses for sequence homology is preferably 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), PR (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 and polypeptides described in Table 53 above have been identified from the databases using BLAST software using the Blastp and tBlastn algorithms. The query nucleotide and polypeptide sequences are described in Table 53 above (polynucleotide SEQ ID NOs: 1-217, and 218-274; polypeptide SEQ ID NOs:474-689, and 690-731) and the identified homologues are provided in Table 54, below.
brachypodium|09v1|TMPLAF000939T1
leymus|gb166|EG375693
pseudoroegneria|gb167|FF342766
pseudoroegneria|gb167|FF342146
brachypodium|09v1|DV476207
brachypodium|gb169|BE500339
cenchrus|gb166|EB653436
sorghum|gb161.crp|BG051887
brachypodium|gb169|BF485087
brachypodium|09v1|DV471918
brachypodium|gb169|AF022915
sorghum|09v1|SB09G023310
sorghum|gb161.crp|AW037050
pseudoroegneria|gb167|FF342690
leymus|gb166|EG386152
leymus|gb166|EG393155
lolium|10v1|AU246926
leymus|gb166|EG380193
arabidopsis|gb165|AT2G32150
brachypodium|09v1|DV488004
brachypodium|gb169|BE421729
sorghum|09v1|SB04G035550
sorghum|gb161.crp|BG411926
sorghum|09v1|SB04G035630
sorghum|gb161.crp|AW360697
brachypodium|09v1|GT811044
brachypodium|gb169|BE425568
brachypodium|09v1|BRADI1G47000
sorghum|gb161.crp|BQ528947
sorghum|09v1|SB10G005920
brachypodium|gb169|CRPBD005242
sorghum|09v1|TMPLBM380723T1
citrus|gb166|BQ624759
lotus|09v1|BI417308
lotus|gb157.2|BI417308
arabidopsis|gb165|AT4G30440
aquilegia|10v1|DR925021
nasturtium|10v1|SRR032558S0298847
cenchrus|gb166|EB653325
brachypodium|09v1|DV475195
leymus|gb166|EG374982
brachypodium|gb169|BE425783
sorghum|09v1|SB02G026280
sorghum|gb161.crp|AW677026
sorghum|09v1|SB01G031210
cenchrus|gb166|BM084651
brachypodium|09v1|DV469218
cenchrus|gb166|EB655101
brachypodium|09v1|DV472385
brachypodium|gb169|BE421885
leymus|gb166|EG392526
pseudoroegneria|gb167|FF345077
sorghum|09v1|SB05G020410
petunia|gb171|EB174978
medicago|gb157.2|BG647589
papaya|gb165|EX251993
medicago|09v1|AW683787
medicago|gb157.2|AW683787
medicago|09v1|AW684008
cacao|gb167|CA796637
papaya|gb165|EX252008
jatropha|09v1|FM890538
papaya|gb165|AY387588
medicago|09v1|LLBG452648
medicago|gb157.2|BG452648
cichorium|gb171|EH690049
papaya|gb165|EX252058
cacao|gb167|CU476839
petunia|gb171|CV295560
citrus|gb166|BQ623443
ipomoea|gb157.2|BJ558237
coffea|10v1|DV675045
brachypodium|gb169|BE416704
brachypodium|09v1|DV479869
brachypodium|09v1|DV478705
brachypodium|gb169|BE591380
sorghum|09v1|SB02G025930
sorghum|gb161.crp|AW283712
sorghum|09v1|SB07G022430
sorghum|09v1|SB07G022430
sorghum|gb161.crp|AW287657
sorghum|gb161.crp|AW287657
cenchrus|gb166|EB655013
brachypodium|09v1|DV480172
brachypodium|gb169|BE421446
brachypodium|09v1|DV469301
brachypodium|gb169|BE637762
leymus|gb166|EG386154
brachypodium|09v1|DV479518
brachypodium|gb169|BE704541
leymus|gb166|EG384069
brachypodium|09v1|GT776617
brachypodium|gb169|BE445505
sorghum|09v1|SB04G027460
sorghum|09v1|SB09G001020
sorghum|gb161.crp|AI723995
brachypodium|09v1|DV487916
brachypodium|gb169|BF202199
coffea|10v1|DV691567
brachypodium|09v1|DV484814
brachypodium|gb169|AF022914
brachypodium|09v1|GT862474
brachypodium|09v1|GT862474
brachypodium|09v1|DV470791
brachypodium|gb169|BQ801920
pseudoroegneria|gb167|FF357868
arabidopsis|gb165|AT3G58510
brachypodium|09v1|GT845006
sorghum|09v1|SB02G030210
sorghum|gb161.crp|AW282915
pseudoroegneria|gb167|FF344208
brachypodium|09v1|DV469420
brachypodium|09v1|DV475244
brachypodium|gb169|BE415626
leymus|gb166|AB161676
pseudoroegneria|gb167|FF340236
nasturtium|10v1|GH164512
leymus|gb166|AB161677
orobanche|10v1|SRR023189S0012323
triphysaria|10v1|SRR023500S0003316
triphysaria|10v1|SRR023500S0037696
cryptomeria|gb166|BJ937299
eucalyptus|gb166|CD668637
liriodendron|gb166|CK747388
lotus|09v1|CB828766
lotus|gb157.2|CB828766
medicago|09v1|BE323170
medicago|gb157.2|BE323170
cryptomeria|gb166|BB940612
cryptomeria|gb166|BP173716
citrus|gb166|CB610761
citrus|gb166|CX635312
salvia|10v1|CV163287
nasturtium|10v1|SRR032558S0000444
cichorium|gb171|EL369595
eucalyptus|gb166|CD668872
sorghum|09v1|SB0G003060
sorghum|gb161.crp|CD231944
rhizophora|10v1|SRR005792S0007548
salvia|10v1|SRR014553S0009878
bruguiera|gb166|BP940238
catharanthus|gb166|EG560916
cenchrus|gb166|BM084728
artemisia|10v1|ES582125
artemisia|gb164|ES582125
sorghum|09v1|SB03G011700
sorghum|gb161.crp|AW564566
artemisia|10v1|GW331462
ginseng|10v1|GR873554
sorghum|09v1|SB09G003050
heritiera|10v1|SRR005794S0002184
jatropha|09v1|GO246525
brachypodium|09v1|DV482704
brachypodium|gb169|BE413132
citrus|gb166|CB290651
gerbera|09v1|AJ750828
ginseng|10v1|GR874639
tragopogon|10v1|SRR020205S0037758
nuphar|gb166|CD475184
medicago|09v1|LLCO512569
centaurea|gb166|EH738262
prunus|gb167|BU040273
prunus|gb167|CB819364
pseudoroegneria|gb167|FF348619
brachypodium|09v1|GT809811
brachypodium|gb169|BE413647
cenchrus|gb166|EB654815
sorghum|09v1|SB09G022810
sorghum|gb161.crp|BE356560
leymus|gb166|EG375667
pseudoroegneria|gb167|FF352847
brachypodium|09v1|DV478766
brachypodium|gb169|BG418029
sorghum|gb161.crp|AW679903
sorghum|09v1|SB10G027540
papaya|gb165|EX275064
medicago|09v1|AW775623
prunus|gb167|AJ823322
lotus|09v1|AV420653
medicago|gb157.2|AW775623
sorghum|09v1|SB03G033040
sorghum|gb161.crp|AW331066
brachypodium|09v1|DV469255
brachypodium|gb169|BE406587
brachypodium|09v1|DV470077
sorghum|gb161.crp|BM325428
sorghum|09v1|SB03G043730
sorghum|gb161.crp|AW677963
brachypodium|09v1|GT814580
brachypodium|gb169|BE591738
brachypodium|09v1|TMPLOS01G68810T1
brachypodium|09v1|GT772015
brachypodium|09v1|DV478709
sorghum|09v1|SB03G043780
brachypodium|09v1|DV486036
sorghum|09v1|SB03G043810
sorghum|gb161.crp|AW745048
brachypodium|09v1|DV474202
sorghum|09v1|SB04G021410
sorghum|gb161.crp|BE345738
brachypodium|09v1|GT767992
brachypodium|gb169|BE406876
leymus|gb166|EG393183
sorghum|09v1|SB04G027590
sorghum|gb161.crp|AI920758
pseudoroegneria|gb167|FF346705
brachypodium|09v1|GT792040
brachypodium|gb169|BE445674
sorghum|gb161.crp|AW091473
sorghum|09v1|SB10G007760
pseudoroegneria|gb167|FF341263
leymus|gb166|EG374932
sorghum|09v1|SB01G047500
sorghum|gb161.crp|AW621098
brachypodium|09v1|DV469506
brachypodium|gb169|DT715392
brachypodium|gb169|CA679165
brachypodium|09v1|GT778632
sorghum|09v1|SB02G032360
brachypodium|09v1|SRR031795S0049444
brachypodium|gb169|BE488380
cenchrus|gb166|EB653342
pseudoroegneria|gb167|FF343851
sorghum|gb161.crp|BE594723
sorghum|09v1|SB01G021890
sorghum|gb161.crp|AA979985
brachypodium|09v1|DV475368
brachypodium|gb169|BE403608
cenchrus|gb166|EB657433
citrus|gb166|CB292297
cacao|gb167|CF974396
eschscholzia|10v1|CD476664
petunia|gb171|DY395574
papaya|gb165|EX245895
cycas|gb166|CB088840
prunus|gb167|BU039320
ipomoea|gb157.2|BJ553883
triphysaria|gb164|EY179701
nasturtium|10v1|SRR032558S0011340
triphysaria|10v1|EY179701
aquilegia|10v1|DR926102
aquilegia|gb157.3|DR926102
petunia|gb171|FN001638
nasturtium|10v1|SRR032558S0012367
salvia|10v1|SRR014553S0011018
sorghum|09v1|SB05G022890
lotus|09v1|LLAF000387
lotus|gb157.2|AF000387
medicago|09v1|AW684320
medicago|gb157.2|AW684320
sorghum|gb161.crp|AI621789
medicago|09v1|LLAW287978
medicago|gb157.2|AW287978
arabidopsis|gb165|AT5G28840
artemisia|10v1|EY051556
artemisia|gb164|EY051556
centaurea|gb166|EH738056
cichorium|gb171|EH675975
tragopogon|10v1|SRR020205S0000342
brachypodium|09v1|DV472085
brachypodium|gb169|BE412805
lolium|10v1|AU246974
physcomitrella|10v1|AW145217
physcomitrella|gb157|AW145217
physcomitrella|10v1|BJ176425
gerbera|09v1|AJ753310
coffea|10v1|DV685976
physcomitrella|10v1|BJ172060
marchantia|gb166|BJ840495
cenchrus|gb166|EB657377
sorghum|09v1|SB01G017460
sorghum|gb161.crp|BE345577
brachypodium|09v1|DV478084
brachypodium|gb169|BF293509
leymus|gb166|EG377220
sorghum|09v1|SB01G017060
sorghum|gb161.crp|BE355313
brachypodium|09v1|DV472183
brachypodium|gb169|BE490826
brachypodium|gb169|AF083344
brachypodium|09v1|SRR031797S0356808
brachypodium|09v1|GT777326
sorghum|09v1|SB03G034390
sorghum|gb161.crp|CD204325
brachypodium|gb169|AV934943
lotus|09v1|BW598183
arabidopsis|gb165|AT1G74310
artemisia|10v1|EF549583
artemisia|10v1|EY034318
artemisia|10v1|EY039119
artemisia|10v1|EY042941
artemisia|10v1|EY043355
artemisia|10v1|EY053904
artemisia|10v1|EY053905
artemisia|10v1|EY054470
artemisia|10v1|EY055002
artemisia|10v1|EY058090
artemisia|10v1|EY059748
artemisia|10v1|EY094034
artemisia|10v1|EY112179
artemisia|10v1|GW328652
artemisia|10v1|GW328923
artemisia|10v1|GW328962
artemisia|10v1|GW329063
artemisia|10v1|GW329182
artemisia|10v1|GW329192
artemisia|10v1|GW329412
artemisia|10v1|GW330388
artemisia|10v1|GW331835
artemisia|10v1|SRR019254S0000375
artemisia|10v1|SRR019254S0000380
artemisia|10v1|SRR019254S0000431
artemisia|10v1|SRR019254S0000460
artemisia|10v1|SRR019254S0000626
artemisia|10v1|SRR019254S0001178
artemisia|10v1|SRR019254S0001487
artemisia|10v1|SRR019254S0001518
artemisia|10v1|SRR019254S0003786
artemisia|10v1|SRR019254S0004038
artemisia|10v1|SRR019254S0004262
artemisia|10v1|SRR019254S0005211
artemisia|10v1|SRR019254S0005860
artemisia|10v1|SRR019254S0005963
artemisia|10v1|SRR019254S0006055
artemisia|10v1|SRR019254S0008243
artemisia|10v1|SRR019254S0008256
artemisia|10v1|SRR019254S0009721
artemisia|10v1|SRR019254S0011742
artemisia|10v1|SRR019254S0012498
artemisia|10v1|SRR019254S0013446
artemisia|10v1|SRR019254S0013783
artemisia|10v1|SRR019254S0015995
artemisia|10v1|SRR019254S0017378
artemisia|10v1|SRR019254S0019913
artemisia|10v1|SRR019254S0020607
artemisia|10v1|SRR019254S0022185
artemisia|10v1|SRR019254S0022238
artemisia|10v1|SRR019254S0024032
artemisia|10v1|SRR019254S0024180
artemisia|10v1|SRR019254S0025912
artemisia|10v1|SRR019254S0026259
artemisia|10v1|SRR019254S0029317
artemisia|10v1|SRR019254S0029360
artemisia|10v1|SRR019254S0030218
artemisia|10v1|SRR019254S0030358
artemisia|10v1|SRR019254S0032259
artemisia|10v1|SRR019254S0051179
artemisia|10v1|SRR019254S0052017
artemisia|10v1|SRR019254S0061794
artemisia|10v1|SRR019254S0069114
artemisia|10v1|SRR019254S0074817
artemisia|10v1|SRR019254S0076339
artemisia|10v1|SRR019254S0079662
artemisia|10v1|SRR019254S0105221
artemisia|10v1|SRR019254S0114141
artemisia|10v1|SRR019254S0120013
artemisia|10v1|SRR019254S0127473
artemisia|10v1|SRR019254S0130786
artemisia|10v1|SRR019254S0140955
artemisia|10v1|SRR019254S0143768
artemisia|10v1|SRR019254S0147045
artemisia|10v1|SRR019254S0266839
artemisia|10v1|SRR019254S0270614
artemisia|10v1|SRR019254S0279002
artemisia|10v1|SRR019254S0387282
artemisia|10v1|SRR019254S0579805
artemisia|10v1|SRR019546S0035668
artemisia|10v1|SRR019546S0183437
artemisia|10v1|SRR019550S0048076
artemisia|10v1|SRR019550S0262313
artemisia|10v1|SRR019550S0292384
brachypodium|09v1|GT779131
eschscholzia|10v1|CD481738
eschscholzia|10v1|SRR014116S0018648
gerbera|09v1|AJ750671
gerbera|09v1|AJ751622
gerbera|09v1|AJ752458
gerbera|09v1|AJ752576
gerbera|09v1|AJ752839
gerbera|09v1|AJ752885
gerbera|09v1|AJ752992
ginseng|10v1|GR871062
heritiera|10v1|SRR005795S0006089
ipomoea|gb157.2|CB330711
jatropha|09v1|FM887562
jatropha|09v1|GT228453
lolium|10v1|AU247171
lolium|10v1|X79715
lotus|09v1|BE122552
lotus|09v1|CB828743
lotus|09v1|CRPLJ031736
lotus|09v1|CRPLJ032446
medicago|09v1|AL366317
medicago|09v1|LLCO514535
nasturtium|10v1|GH167522
nasturtium|10v1|SRR032558S0008057
nasturtium|10v1|SRR032558S0034910
nasturtium|10v1|SRR032558S0046943
nasturtium|10v1|SRR032558S0089537
nasturtium|10v1|SRR032558S0209453
nasturtium|10v1|SRR032558S0317266
nasturtium|10v1|SRR032562S0059705
orobanche|10v1|SRR023189S0000081
orobanche|10v1|SRR023189S0000767
orobanche|10v1|SRR023189S0001936
orobanche|10v1|SRR023189S0004131
orobanche|10v1|SRR023189S0004660
orobanche|10v1|SRR023189S0006888
orobanche|10v1|SRR023189S0009928
orobanche|10v1|SRR023189S0011568
orobanche|10v1|SRR023189S0013200
orobanche|10v1|SRR023189S0014259
orobanche|10v1|SRR023189S0014732
orobanche|10v1|SRR023189S0015759
orobanche|10v1|SRR023189S0016379
orobanche|10v1|SRR023189S0022127
orobanche|10v1|SRR023189S0032223
orobanche|10v1|SRR023189S0032511
orobanche|10v1|SRR023189S0046559
orobanche|10v1|SRR023189S0052369
orobanche|10v1|SRR023189S0105273
physcomitrella|10v1|DC934350
physcomitrella|10v1|FC374737
physcomitrella|10v1|FC381484
physcomitrella|10v1|FC411388
physcomitrella|10v1|XM001751677
physcomitrella|10v1|XM001766297
physcomitrella|10v1|XM001768151
physcomitrella|10v1|XM001769639
physcomitrella|10v1|XM001779929
physcomitrella|10v1|XM001783766
rhizophora|10v1|SRR005793S0007192
salvia|10v1|SRR014553S0011349
tragopogon|10v1|SRR020205S0059721
tragopogon|10v1|SRR020205S0133874
triphysaria|10v1|CB815020
triphysaria|10v1|DR171915
triphysaria|10v1|EX999454
triphysaria|10v1|EY151225
triphysaria|10v1|SRR023500S0026363
triphysaria|10v1|SRR023500S0047657
amborella|gb166|CK766783
amborella|gb166|FD441330
antirrhinum|gb166|AJ558339
antirrhinum|gb166|AJ558802
antirrhinum|gb166|AJ559512
antirrhinum|gb166|AJ787885
antirrhinum|gb166|AJ790005
antirrhinum|gb166|AJ791274
antirrhinum|gb166|AJ799867
arabidopsis|gb165|AT1G07660
arabidopsis|gb165|AT1G07820
arabidopsis|gb165|AT3G45930
arabidopsis|gb165|AT3G46320
arabidopsis|gb165|AT3G53730
arabidopsis|gb165|AT5G59690
arabidopsis|gb165|BP850938
artemisia|10v1|SRR019254S0004605
artemisia|gb164|EF549583
artemisia|gb164|EY032843
artemisia|10v1|EY064628
artemisia|10v1|EY035013
artemisia|10v1|EY037977
artemisia|10v1|SRR019254S0006003
artemisia|gb164|EY043355
artemisia|10v1|SRR019254S0020909
artemisia|10v1|EY050092
artemisia|gb164|EY050092
artemisia|10v1|SRR019254S0044441
basilicum|10v1|DY329949
basilicum|gb157.3|DY329949
brachypodium|09v1|DV488531
brachypodium|gb169|AL829713
brachypodium|09v1|SRR031796S0015969
brachypodium|gb169|BE398313
brachypodium|09v1|GT777837
brachypodium|gb169|BE399369
brachypodium|09v1|DV469193
brachypodium|gb169|BE399555
brachypodium|09v1|DV470129
brachypodium|gb169|BE399592
brachypodium|09v1|DV477960
brachypodium|gb169|BE400757
brachypodium|09v1|GT763632
brachypodium|gb169|BE403687
brachypodium|09v1|DV471468
brachypodium|gb169|BE413182
brachypodium|09v1|GT767460
brachypodium|gb169|BE415858
brachypodium|09v1|BRADI4G30960
brachypodium|gb169|BE417523
brachypodium|09v1|SRR031795S0025245
brachypodium|gb169|BM377866
brachypodium|09v1|GT814284
brachypodium|gb169|CA032073
bruguiera|gb166|BP945440
cacao|gb167|CA794917
cacao|gb167|CA796173
cacao|gb167|CU471543
cacao|gb167|CU471645
cacao|gb167|CU471805
cacao|gb167|CU472042
cacao|gb167|CU475022
catharanthus|gb166|EG556351
catharanthus|gb166|FD415203
cenchrus|gb166|BM084286
cenchrus|gb166|EB652615
cenchrus|gb166|EB653521
cenchrus|gb166|EB654271
centaurea|gb166|EH741190
centaurea|gb166|EH760516
cichorium|gb171|EH700759
cichorium|gb171|EH701323
cichorium|gb171|EH702007
cichorium|gb171|EH705029
cichorium|gb171|EL365514
citrus|gb166|BQ623154
citrus|gb166|BQ623438
citrus|gb166|CB611039
citrus|gb166|CF417550
coffea|10v1|DV673331
coffea|gb157.2|BQ448811
coffea|10v1|DV664293
coffea|gb157.2|DV664293
coffea|10v1|DV675511
coffea|gb157.2|DV675511
coffea|10v1|EE193937
coffea|gb157.2|EE193937
cryptomeria|gb166|BP175287
cryptomeria|gb166|BW994999
cryptomeria|gb166|BW995093
cycas|gb166|CB089451
cycas|gb166|CB090291
cycas|gb166|CB090429
cycas|gb166|CB090486
cycas|gb166|CB090617
cynara|gb167|GE590379
cynara|gb167|GE592628
cynara|gb167|GE600719
eucalyptus|gb166|AJ627789
eucalyptus|gb166|AY263810
eucalyptus|gb166|CD668212
ipomoea|gb157.2|BJ553415
ipomoea|gb157.2|BJ553690
ipomoea|gb157.2|BJ555300
ipomoea|gb157.2|BJ556362
ipomoea|gb157.2|BJ556445
ipomoea|gb157.2|BJ558611
ipomoea|gb157.2|BJ560747
ipomoea|gb157.2|EE875704
leymus|gb166|EG386168
liriodendron|gb166|CK753794
liriodendron|gb166|FD489954
lotus|09v1|AW163944
lotus|09v1|AW719271
lotus|gb157.2|AW719271
lotus|09v1|BW597052
lotus|09v1|CB828182
medicago|09v1|AA660565
medicago|gb157.2|AA660565
medicago|09v1|AJ389014
medicago|gb157.2|AJ389014
medicago|09v1|LLAJ498325
medicago|09v1|LLAL366664
medicago|09v1|AL371855
medicago|gb157.2|AL371855
medicago|gb157.2|AL374021
medicago|09v1|AL378431
medicago|09v1|AL379622
medicago|09v1|AL374021
medicago|gb157.2|AL380165
medicago|09v1|AW208199
medicago|gb157.2|AW208199
nuphar|gb166|CD473517
nuphar|gb166|CD474514
nuphar|gb166|CD475677
nuphar|gb166|CK745661
nuphar|gb166|CK767296
papaya|gb165|EX276160
papaya|gb165|EX278412
papaya|gb165|EX283624
petunia|gb171|DC241756
prunus|gb167|AJ873312
prunus|gb167|FC865249
pseudoroegneria|gb167|FF346105
pseudoroegneria|gb167|FF365552
pseudoroegneria|gb167|FF365632
senecio|gb170|DY658928
senecio|gb170|DY659560
senecio|gb170|DY662328
senecio|gb170|DY662897
senecio|gb170|SRR006592S0002545
tamarix|gb166|CD151503
tamarix|gb166|CF198776
tamarix|gb166|EG970851
tamarix|gb166|EG971166
thellungiella|gb167|BY809845
thellungiella|gb167|EC599850
triphysaria|10v1|BM357139
triphysaria|10v1|BM357221
triphysaria|gb164|BM357221
triphysaria|gb164|DR170904
triphysaria|10v1|CB815232
triphysaria|10v1|EX991298
triphysaria|10v1|EX994401
triphysaria|10v1|EX999992
triphysaria|10v1|EX999279
triphysaria|10v1|EY011518
triphysaria|10v1|EY019376
triphysaria|10v1|EY018118
zamia|gb166|DY030802
zamia|gb166|DY032938
zamia|gb166|FD767578
triphysaria|10v1|BM357495
cichorium|gb171|EH698983
artemisia|10v1|SRR019254S0012318
artemisia|10v1|SRR019254S0027665
artemisia|10v1|SRR019254S0111269
nasturtium|10v1|SRR032558S0010849
antirrhinum|gb166|AJ792433
eschscholzia|10v1|SRR014116S0001279
orobanche|10v1|SRR023189S0057009
triphysaria|10v1|SRR023500S0028707
basilicum|10v1|DY336248
artemisia|10v1|GW329205
artemisia|10v1|SRR019254S0020910
artemisia|10v1|SRR019254S0048488
artemisia|10v1|SRR019546S0001094
artemisia|10v1|SRR019550S0074110
jatropha|09v1|GH295594
lotus|09v1|BW594671
lotus|09v1|LLGO012754
medicago|09v1|LLCO512253
medicago|09v1|LLCO513425
nasturtium|10v1|GH163637
nasturtium|10v1|SRR032558S0007001
nasturtium|10v1|SRR032558S0014888
nasturtium|10v1|SRR032558S0126068
orobanche|10v1|SRR023189S0015197
orobanche|10v1|SRR023189S0032180
orobanche|10v1|SRR023189S0073604
physcomitrella|10v1|XM001768153
physcomitrella|10v1|XM001782794
rhizophora|10v1|SRR005793S0017626
tragopogon|10v1|SRR020205S0007187
amborella|gb166|CK763863
antirrhinum|gb166|AJ799109
artemisia|gb164|EY053904
basilicum|10v1|DY323944
cenchrus|gb166|EB654992
cenchrus|gb166|EB665044
cynara|gb167|GE589503
cynara|gb167|GE601275
marchantia|gb166|AU081695
marchantia|gb166|AU081848
marchantia|gb166|BJ849115
medicago|gb157.2|AJ498325
ostreococcus|gb162|XM001415987
ostreococcus|gb162|XM001420298
petunia|gb171|AY650011
petunia|gb171|FN003085
petunia|gb171|FN003987
tamarix|gb166|EG971827
triphysaria|gb164|BM357139
artemisia|10v1|SRR019254S0005641
artemisia|10v1|SRR019254S0085816
gerbera|09v1|AJ753834
artemisia|gb164|EY035013
artemisia|gb164|EY037977
artemisia|gb164|EY056079
cryptomeria|gb166|AU299923
cynara|gb167|GE596075
medicago|gb157.2|AL379622
petunia|gb171|CV296942
petunia|gb171|FN008035
pseudoroegneria|gb167|FF366172
zinnia|gb171|AU290856
artemisia|10v1|SRR019254S0090211
artemisia|10v1|SRR019254S0022227
artemisia|10v1|SRR019254S0216912
orobanche|10v1|SRR023495S0084187
volvox|gb162|BU645998
volvox|gb162|CBGZ25401FWD
volvox|gb162|MDLJGIVOLCA1102100
volvox|gb162|MDLJGIVOLCA1102370
volvox|gb162|MDLJGIVOLCA155291
volvox|gb162|MDLJGIVOLCA155542
volvox|gb162|MDLJGIVOLCA156769
volvox|gb162|MDLJGIVOLCA163165
volvox|gb162|MDLJGIVOLCA188140
zinnia|gb171|DV017431
artemisia|10v1|SRR019546S0127820
artemisia|10v1|SRR019547S0487952
artemisia|10v1|SRR019550S0086000
gerbera|09v1|AJ755846
amborella|gb166|FD427255
ipomoea|gb157.2|DV034788
volvox|gb162|MDLJGIVOLCA1103472
volvox|gb162|MDLJGIVOLCA1108939
basilicum|gb157.3|DY336248
nasturtium|10v1|SRR032563S0097524
basilicum|gb157.3|DY323944
artemisia|10v1|SRR019254S0002617
senecio|gb170|DY663617
triphysaria|gb164|EX999279
eucalyptus|gb166|CD668166
triphysaria|gb164|EY019376
artemisia|10v1|SRR019254S0011984
artemisia|10v1|SRR019254S0031076
artemisia|10v1|SRR019552S0240607
liriodendron|gb166|FD495606
medicago|09v1|LLAJ500188
medicago|gb157.2|AJ500188
artemisia|10v1|SRR019254S0542206
rhizophora|10v1|SRR005793S0076222
centaurea|gb166|EH741518
triphysaria|gb164|EY011518
triphysaria|gb164|EY133021
ginseng|10v1|GR871574
medicago|gb157.2|AL366664
artemisia|10v1|SRR019254S0003873
artemisia|10v1|SRR019254S0123773
artemisia|10v1|SRR019254S0145628
orobanche|10v1|SRR023189S0034388
cacao|gb167|CU472310
triphysaria|gb164|EX994401
zinnia|gb171|DV017189
zinnia|gb171|DV017366
zinnia|gb171|DV017419
senecio|gb170|DY661591
ipomoea|gb157.2|EE881854
salvia|10v1|SRR014553S0015933
tragopogon|10v1|SRR020205S0178366
cacao|gb167|CU469633
artemisia|10v1|EY056079
heritieral|10v1|SRR005795S0031594
bruguiera|gb166|BP939745
tamarix|gb166|EG969617
volvox|gb162|AW676472
volvox|gb162|MDLJGIVOLCA178755
artemisia|10v1|SRR019254S0032901
eschscholzia|10v1|CD480997
cacao|gb167|CU614547
papaya|gb165|EX272338
artemisia|10v1|SRR019254S0030053
ipomoea|gb157.2|DV036726
artemisia|10v1|SRR019550S0172069
arabidopsis|gb165|AT2G28740
medicago|gb157.2|AL378431
triphysaria|gb164|BE574792
pseudoroegneria|gb167|FF366170
eucalyptus|gb166|CT981403
triphysaria|gb164|EY015990
artemisia|10v1|SRR019254S0032449
medicago|09v1|LLEL563523
medicago|gb157.2|AL366317
triphysaria|gb164|BM357495
artemisia|10v1|SRR019254S0000755
cacao|gb167|CU472080
cenchrus|gb166|EB661022
eucalyptus|gb166|CD668068
prunus|gb167|CB819033
medicago|gb157.2|AL380016
artemisia|10v1|EY032843
artemisia|10v1|SRR019254S0041967
nuphar|gb166|CD474059
lotus|gb157.2|CN825630
lotus|gb157.2|BW597052
triphysaria|gb164|EY005632
cenchrus|gb166|EB672104
gerbera|09v1|AJ753672
artemisia|gb164|EY034318
artemisia|gb164|EY048377
triphysaria|gb164|EX999992
triphysaria|gb164|EX988310
artemisia|10v1|SRR019254S0057308
gerbera|09v1|AJ753690
tragopogon|10v1|SRR020205S0080113
cycas|gb166|EX921626
cryptomeria|gb166|BY890130
lotus|gb157.2|CB828182
triphysaria|gb164|CB815232
ipomoea|gb157.2|CJ744369
artemisia|gb164|EY039119
artemisia|gb164|EY063572
citrus|gb166|EY743876
cryptomeria|gb166|BY884124
ipomoea|gb157.2|CB330659
triphysaria|gb164|EY020033
triphysaria|gb164|EX998942
lolium|10v1|SRR029314S0011890
orobanche|10v1|SRR023495S0014175
triphysaria|10v1|SRR023500S0019032
cichorium|gb171|EH703474
arabidopsis|gb165|AT5G59970
ipomoea|gb157.2|CJ738107
lotus|gb157.2|AW163944
triphysaria|gb164|EX991298
jatropha|09v1|FM888435
triphysaria|gb164|EY012083
citrus|gb166|EY825373
ipomoea|gb157.2|CB330950
artemisia|10v1|SRR019551S0085700
sorghum|09v1|SB01G000950
sorghum|gb161.crp|BF585848
cenchrus|gb166|EB669873
sorghum|09v1|SB02G030950
sorghum|gb161.crp|AI657275
sorghum|09v1|SB01G039250
sorghum|gb161.crp|AI396033
sorghum|09v1|SB01G039240
sorghum|gb161.crp|AI444702
cenchrus|gb166|EB652626
gerbera|09v1|AJ752939
brachypodium|09v1|DV488718
brachypodium|gb169|BE401791
brachypodium|gb169|BI960263
sorghum|09v1|SB09G001520
sorghum|gb161.crp|AW287442
liriodendron|gb166|DT579867
prunus|gb167|DY646167
lotus|09v1|BG661990
lotus|gb157.2|BG661990
gerbera|09v1|AJ753301
citrus|gb166|BQ624783
medicago|09v1|BF643805
artemisia|10v1|EY031915
artemisia|10v1|EY075725
artemisia|10v1|GW328612
artemisia|10v1|GW329305
artemisia|10v1|SRR019254S0011741
artemisia|10v1|SRR019254S0001774
artemisia|gb164|EY031915
artemisia|10v1|SRR019254S0002410
artemisia|gb164|EY055445
lotus|09v1|BI418493
lotus|gb157.2|BI418493
cynara|gb167|GE588632
cichorium|gb171|EH704900
gerbera|09v1|AJ756141
cenchrus|gb166|EB656997
artemisia|10v1|SRR019254S0013055
medicago|gb157.2|BF643805
orobanche|10v1|SRR023189S0002180
lotus|09v1|LLAW719911
lotus|gb157.2|AW719911
pseudoroegneria|gb167|FF340751
eschscholzia|10v1|CD480726
centaurea|gb166|EL932239
coffea|10v1|DV673276
ginseng|10v1|DV554362
brachypodium|gb169|BE398477
brachypodium|09v1|DV475962
brachypodium|gb169|BE400244
medicago|09v1|BE239402
medicago|gb157.2|BE239402
artemisia|10v1|GW329229
jatropha|09v1|GT228525
orobanche|10v1|SRR023189S0007626
antirrhinum|gb166|AJ568652
bruguiera|gb166|BP941111
papaya|gb165|EX255877
tragopogon|10v1|SRR020205S0003365
cacao|gb167|EH057782
artemisia|10v1|SRR019254S0011939
cichorium|gb171|EH698455
brachypodium|09v1|SRR031795S0043037
cynara|gb167|GE588059
nasturtium|10v1|SRR032558S0003969
medicago|09v1|AL384067
medicago|gb157.2|AL384067
nuphar|gb166|CD473263
nuphar|gb166|CD474301
nuphar|gb166|CD475325
pseudoroegneria|gb167|FF342758
tamarix|gb166|CF199999
senecio|gb170|DY658597
brachypodium|09v1|SRR031797S0022709
cichorium|gb171|EH682187
ginseng|10v1|DV555645
orobanche|10v1|SRR023189S0008983
tragopogon|10v1|SRR020205S0018059
catharanthus|gb166|EG558535
catharanthus|gb166|EG562453
catharanthus|gb166|FD416131
centaurea|gb166|EH753053
artemisia|10v1|SRR019254S0001113
jatropha|09v1|GT229311
nasturtium|10v1|SRR032558S0000657
nasturtium|10v1|SRR032558S0008269
orobanche|10v1|SRR023189S0017978
medicago|09v1|AL377356
medicago|09v1|BF519200
orobanche|10v1|SRR023189S0010876
orobanche|10v1|SRR023189S0028654
basilicum|10v1|DY323812
basilicum|gb157.3|DY323812
cacao|gb167|EH057760
cichorium|gb171|DT212229
medicago|gb157.2|AW574007
triphysaria|10v1|BM356994
triphysaria|10v1|DR173737
triphysaria|gb164|EY137032
heritiera|10v1|SRR005795S0031964
artemisia|10v1|EY082330
artemisia|10v1|EY084850
artemisia|10v1|SRR019254S0007700
artemisia|10v1|SRR019254S0012643
artemisia|10v1|EY039776
artemisia|gb164|EY082330
artemisia|gb164|EY084850
ipomoea|gb157.2|BJ554819
orobanche|10v1|SRR023189S0001029
sorghum|09v1|SB09G022690
sorghum|gb161.crp|AW681166
ginseng|10v1|DV553422
centaurea|gb166|EL930888
centaurea|gb166|EL934894
artemisia|10v1|SRR019254S0007762
medicago|09v1|AL376385
orobanche|10v1|SRR023189S0000458
orobanche|10v1|SRR023189S0014080
triphysaria|10v1|DR176290
antirrhinum|gb166|AJ558758
antirrhinum|gb166|AJ568035
liriodendron|gb166|CK748317
medicago|gb157.2|AL376384
petunia|gb171|CV300217
senecio|gb170|DY658035
triphysaria|gb164|BM356994
triphysaria|gb164|EY129294
triphysaria|gb164|EY136702
triphysaria|gb164|BE574777
triphysaria|gb164|EX999662
artemisia|10v1|EY082130
artemisia|10v1|GW328287
artemisia|10v1|GW328462
artemisia|10v1|SRR019254S0000360
artemisia|10v1|SRR019254S0003074
artemisia|10v1|SRR019254S0042995
artemisia|10v1|SRR019254S0094458
artemisia|10v1|SRR019254S0000494
artemisia|gb164|EY082130
gerbera|09v1|AJ754996
cynara|gb167|GE592728
brachypodium|09v1|GT797969
brachypodium|gb169|BE400172
pseudoroegneria|gb167|FF345930
leymus|gb166|EG378703
medicago|09v1|AW256724
medicago|gb157.2|AW256724
nasturtium|10v1|SRR032558S0007563
brachypodium|09v1|DV477522
leymus|gb166|EG388830
pseudoroegneria|gb167|FF340314
sorghum|09v1|SB02G003590
sorghum|gb161.crp|BE366228
brachypodium|09v1|DV476934
brachypodium|gb169|BE424014
sorghum|09v1|SB02G042750
sorghum|gb161.crp|BI096623
brachypodium|09v1|GT790399
sorghum|gb161.crp|AI491551
pseudoroegneria|gb167|FF340152
sorghum|09v1|SB09G004290
cenchrus|gb166|EB652891
brachypodium|09v1|DV477815
catharanthus|gb166|EG561166
pseudoroegneria|gb167|FF343982
lolium|10v1|ES699035
leymus|gb166|EG374681
citrus|gb166|BQ623150
jatropha|09v1|GT229173
amborella|gb166|CD483554
cacao|gb167|CA795583
papaya|gb165|EX262198
coffea|10v1|DV678801
coffea|gb157.2|DV678801
papaya|gb165|EX275159
jatropha|09v1|FM892996
nasturtium|10v1|GH163808
prunus|gb167|AJ827102
prunus|gb167|CB822575
ipomoea|gb157.2|BJ556879
orobanche|10v1|SRR023189S0004601
citrus|gb166|CB293637
eucalyptus|gb166|CT982220
triphysaria|10v1|BM356765
triphysaria|10v1|BM356862
triphysaria|10v1|EX990668
ipomoea|gb157.2|BJ553202
eschscholzia|10v1|CD478146
nasturtium|10v1|SRR032558S0018850
arabidopsis|gb165|AT5G27850
centaurea|gb166|EH737450
cryptomeria|gb166|BW993132
cynara|gb167|GE586442
ipomoea|gb157.2|CB330344
liriodendron|gb166|CK766210
petunia|gb171|DY396235
triphysaria|gb164|BM356862
gerbera|09v1|AJ750626
lotus|09v1|BW595275
arabidopsis|gb165|AT3G05590
lotus|09v1|LLCN825309
lotus|gb157.2|CN825309
senecio|gb170|DY658757
thellungiella|gb167|BQ079245
eschscholzia|10v1|CD477064
coffea|10v1|DV666712
physcomitrella|10v1|BJ158142
physcomitrella|10v1|BJ185019
bruguiera|gb166|BP938752
cichorium|gb171|EH701900
lotus|09v1|LLAW720439
triphysaria|gb164|BM356765
physcomitrella|gb157|BJ158142
triphysaria|10v1|EY014546
physcomitrella|gb157|AW126838
physcomitrella|gb157|BG362299
orobanche|10v1|SRR023189S0022111
physcomitrella|10v1|AW126838
physcomitrella|10v1|BG362299
tragopogon|10v1|SRR020205S0015140
tragopogon|10v1|SRR020205S0106933
centaurea|gb166|EH738805
centaurea|gb166|EH739466
cichorium|gb171|DT213052
cynara|gb167|GE588262
ipomoea|gb157.2|CJ737673
petunia|gb171|CV295039
petunia|gb171|CV299987
thellungiella|gb167|BY803938
ginseng|10v1|CN848661
physcomitrella|10v1|AW126801
liriodendron|gb166|DT580181
zamia|gb166|DY031019
physcomitrella|gb157|AW126801
salvia|10v1|CV164239
salvia|10v1|SRR014553S0002907
tragopogon|10v1|SRR020205S0018138
artemisia|10v1|EY032066
artemisia|gb164|EY032066
artemisia|10v1|EY056461
artemisia|gb164|EY056461
basilicum|10v1|DY321729
cichorium|gb171|EH683001
cycas|gb166|CB088957
medicago|09v1|AW684723
medicago|gb157.2|AW684723
cynara|gb167|GE588021
medicago|09v1|LLAW256698
medicago|gb157.2|AW256698
salvia|10v1|FE536981
antirrhinum|gb166|AJ558493
antirrhinum|gb166|AJ788113
artemisia|gb164|EY033512
basilicum|gb157.3|DY321729
marchantia|gb166|C96610
medicago|09v1|BE249407
medicago|gb157.2|BE249407
artemisia|10v1|EY033512
triphysaria|gb164|BM356434
triphysaria|gb164|EY126952
triphysaria|10v1|EY133632
triphysaria|gb164|EY133632
ginseng|10v1|CN848265
petunia|gb171|DC244521
triphysaria|10v1|EY126952
triphysaria|10v1|BM356434
sorghum|gb161.crp|CF481271
sorghum|09v1|CF481271
leymus|gb166|EG384787
brachypodium|gb169|BE412637
brachypodium|09v1|DV472699
sorghum|09v1|SB05G023240
sorghum|09v1|SB05G023240
sorghum|gb161.crp|BE363468
sorghum|gb161.crp|BE363468
brachypodium|09v1|SRR031795S0000152
brachypodium|gb169|BG262952
sorghum|gb161.crp|BI098059
sorghum|09v1|SB05G000860
lotus|09v1|BW594599
medicago|09v1|BE325764
medicago|gb157.2|BE325764
medicago|09v1|AW257191
cichorium|gb171|EH676540
petunia|gb171|AM489763
petunia|gb171|PETTRNSFB
coffea|10v1|DV664667
coffea|gb157.2|DV664667
ipomoea|gb157.2|BJ555139
antirrhinum|gb166|AY306142
prunus|gb167|BU039561
papaya|gb165|EX248886
cacao|gb167|CU475790
antirrhinum|gb166|AY306140
antirrhinum|gb166|AY306141
triphysaria|10v1|SRR023501S0006880
nasturtium|10v1|SRR032558S0070643
citrus|gb166|CB290298
lotus|09v1|AY770397
lotus|gb157.2|AY770397
nasturtium|10v1|SRR032558S0103587
cichorium|gb171|EH686695
medicago|09v1|CRPMT000849
citrus|gb166|CB293061
liriodendron|gb166|DT580890
liriodendron|gb166|CO998849
eschscholzia|10v1|CD476730
nasturtium|10v1|GH163469
nasturtium|10v1|SRR032558S0000854
nasturtium|10v1|SRR032558S0006059
citrus|gb166|CF417897
aquilegia|10v1|DR937723
aquilegia|gb157.3|DR937723
cacao|gb167|CU473741
cichorium|gb171|DT212028
prunus|gb167|BU046232
artemisia|10v1|EY045818
lotus|09v1|LLBG662143
medicago|09v1|AA660688
medicago|gb157.2|AA660688
papaya|gb165|AM903981
prunus|gb167|BU039863
coffea|10v1|DV665562
coffea|gb157.2|DV665562
cacao|gb167|EH057828
cichorium|gb171|DT211464
medicago|09v1|BE239304
medicago|gb157.2|BE239304
petunia|gb171|CV293104
artemisia|gb164|EY045818
artemisia|10v1|EY084194
artemisia|gb164|EY084194
prunus|gb167|BU039728
jatropha|09v1|GO247020
lotus|09v1|BI420953
lotus|gb157.2|BI420953
arabidopsis|gb165|AT3G13920
cenchrus|gb166|EB653990
medicago|09v1|AW256944
medicago|gb157.2|AW256944
sorghum|09v1|SB10G028940
sorghum|gb161.crp|ZMU73459
brachypodium|09v1|DV470402
brachypodium|gb169|Z21510
lotus|09v1|BP036168
triphysaria|10v1|BE574917
orobanche|10v1|SRR023189S0018945
arabidopsis|gb165|AT1G54270
sorghum|09v1|SB04G003390
sorghum|gb161.crp|ZMU17979
artemisia|gb164|EY063986
leymus|gb166|CD808554
cenchrus|gb166|BM084681
nuphar|gb166|CD474917
triphysaria|10v1|BE574926
triphysaria|gb164|BE574926
cycas|gb166|CB088419
aquilegia|10v1|DR917189
aquilegia|gb157.3|DR917189
triphysaria|10v1|EY006504
physcomitrella|10v1|AW145733
cacao|gb167|CU512667
marchantia|gb166|C96517
physcomitrella|gb157|AW145733
arabidopsis|gb165|AT1G72730
lolium|10v1|AU250857
physcomitrella|10v1|AW477079
physcomitrella|10v1|BG409334
physcomitrella|gb157|AW477079
physcomitrella|gb157|BG409334
centaurea|gb166|EH763543
physcomitrella|10v1|AJ225463
physcomitrella|gb157|AW561235
catharanthus|gb166|EG558000
artemisia|10v1|EY063986
orobanche|10v1|SRR023189S0021240
volvox|gb162|AI670453
ostreococcus|gb162|XM001418935
pseudoroegneria|gb167|FF346170
pseudoroegneria|gb167|FF348025
brachypodium|09v1|DV477130
brachypodium|gb169|BE430022
sorghum|09v1|SB10G020570
sorghum|gb161.crp|AI977976
sorghum|09v1|SB04G009230
sorghum|gb161.crp|AI987556
sorghum|09v1|SB04G001510
sorghum|gb161.crp|BE918485
pseudoroegneria|gb167|FF341367
pseudoroegneria|gb167|FF344192
brachypodium|09v1|GT766551
lolium|10v1|ES699371
arabidopsis|gb165|AT3G07880
sorghum|gb161.crp|BE917776
sorghum|09v1|SB06G029650
leymus|gb166|EG375949
brachypodium|09v1|DV478509
brachypodium|gb169|BE494994
brachypodium|09v1|GFXAM072969X2
sorghum|09v1|SB02G027870
sorghum|gb161.crp|BF507008
sorghum|09v1|SB07G028600
sorghum|gb161.crp|AI372324
thellungiella|gb167|BY818625
arabidopsis|gb165|AT2G38880
citrus|gb166|CB290512
nasturtium|10v1|SRR032558S0015243
medicago|09v1|AL387357
papaya|gb165|EX239264
citrus|gb166|CK740017
nasturtium|10v1|SRR032558S0243931
sorghum|09v1|SB02G038960
sorghum|gb161.crp|SBGWP022909
brachypodium|09v1|GT829942
brachypodium|gb169|BF257470
sorghum|09v1|SB05G002450
sorghum|gb161.crp|BF421813
brachypodium|09v1|GT778679
brachypodium|gb169|BE496864
cichorium|gb171|DT211930
petunia|gb171|CV292888
triphysaria|10v1|DR175232
coffea|10v1|DV665545
tragopogon|10v1|SRR020205S0000615
citrus|gb166|CF507005
coffea|gb157.2|DV665545
lotus|09v1|BP037753
cichorium|gb171|EH673760
artemisia|10v1|EY089946
artemisia|gb164|EY089946
petunia|gb171|CV298273
artemisia|gb164|EY085224
artemisia|10v1|SRR019254S0002302
sorghum|09v1|SLXL50010512D1
petunia|gb171|CV299604
eschscholzia|10v1|SRR014116S0005541
ipomoea|gb157.2|BJ567233
rhizophora|10v1|SRR005792S0001643
rhizophora|10v1|SRR005793S0006109
eucalyptus|gb166|CU396200
leymus|gb166|CD808996
pseudoroegneria|gb167|FF343365
sorghum|gb161.crp|SBGWP053010
ipomoea|gb157.2|BJ566333
salvia|10v1|CV162812
salvia|10v1|CV163214
basilicum|10v1|DY325098
basilicum|gb157.3|DY325098
centaurea|gb166|EL931474
cichorium|gb171|EH685996
zamia|gb166|CB095911
eschscholzia|10v1|SRR014116S0006563
basilicum|gb157.3|DY326229
basilicum|10v1|DY326229
brachypodium|09v1|CRPBD012820
gerbera|09v1|AJ753152
lotus|09v1|BG662143
nasturtium|10v1|SRR032558S0020815
orobanche|10v1|SRR023189S0012423
physcomitrella|10v1|PHPCRP010667
cynara|gb167|GE599288
basilicum|10v1|DY341441
medicago|09v1|AL370119
physcomitrella|10v1|PHPCRP016239
tragopogon|10v1|SRR020205S0006730
amborella|gb166|CO999518
basilicum|gb157.3|DY341441
cichorium|gb171|EH679514
petunia|gb171|CV297073
triphysaria|gb164|DR176592
antirrhinum|gb166|AJ789472
cynara|gb167|GE598198
thellungiella|gb167|BY800754
medicago|09v1|LLAL381370
brachypodium|09v1|DV469797
brachypodium|gb169|BE400316
nuphar|gb166|CD474327
triphysaria|gb164|EY006504
zinnia|gb171|AU305761
ginseng|10v1|GR871242
gerbera|09v1|AJ754459
jatropha|09v1|FM891968
antirrhinum|gb166|AJ559628
rhizophora|10v1|SRR005793S0029492
cacao|gb167|CU583493
senecio|gb170|SRR006594S0009563
salvia|10v1|SRR014553S0018208
cryptomeria|gb166|AU066365
cryptomeria|gb166|BP175684
lotus|gb157.2|BP036168
triphysaria|10v1|EY154847
triphysaria|gb164|EY154847
eucalyptus|gb166|CB967721
thellungiella|gb167|BY825969
tragopogon|10v1|SRR020205S0002992
ipomoea|gb157.2|BJ569764
cacao|gb167|CU476966
brachypodium|09v1|DV482604
brachypodium|gb169|BF474193
brachypodium|gb169|BE426494
brachypodium|09v1|SRR031795S0016784
brachypodium|09v1|SRR031797S0018936
leymus|gb166|EG389112
brachypodium|09v1|SRR031797S0001217
leymus|gb166|EG389322
brachypodium|gb169|BE403306
leymus|gb166|EG374734
brachypodium|09v1|DV469105
brachypodium|gb169|BE426266
sorghum|09v1|SB04G034760
brachypodium|09v1|DV475081
brachypodium|gb169|BE414854
leymus|gb166|EG379378
triphysaria|gb164|DR175232
triphysaria|10v1|DR171145
orobanche|10v1|SRR023189S0001256
lotus|09v1|GO026464
ipomoea|gb157.2|IPBPALA
catharanthus|gb166|AB042520
ipomoea|gb157.2|IPBPAL
cynara|gb167|GFXAM418586X1
artemisia|10v1|EY085223
basilicum|10v1|DY321950
basilicum|gb157.3|DY322602
artemisia|10v1|EY060660
basilicum|10v1|DY321580
jatropha|09v1|GFXDQ883805X1
citrus|gb166|CLU43338
salvia|10v1|CV165552
aquilegia|10v1|DR912258
citrus|gb166|CF832012
prunus|gb167|AF036948
cacao|gb167|CF974594
cynara|gb167|GFXAM418560X1
medicago|09v1|AI737513
citrus|gb166|BE208887
nasturtium|10v1|GH164221
lotus|09v1|AW720528
petunia|gb171|CV294118
lotus|09v1|CB826853
nasturtium|10v1|SRR032558S0014671
triphysaria|10v1|EX991935
coffea|10v1|AF218453
nasturtium|10v1|GH168296
lotus|09v1|BP085550
arabidopsis|gb165|AT2G37040
citrus|gb166|CF417508
lotus|09v1|AB283035
brachypodium|09v1|DV469561
The output of the functional genomics approach described herein is a set of genes highly predicted to improve ABST, yield and/or other agronomic important traits such as growth rate, vigor, biomass, growth rate, oil content, 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 here alone or set of genes together increases the overall yield and/or other agronomic important traits, hence expects to increase agricultural productivity.
To validate their role in improving ABST, yield, growth rate, biomass, vigor, oil content, WUE, NUE and/or FUE selected genes were over-expressed in plants, as follows.
Cloning Strategy
Selected genes from those presented in Examples 4 and 5 hereinabove are cloned into binary vectors for the generation of transgenic plants. For cloning, the full-length open reading frames (ORFs) were identified. EST clusters and in some cases 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.
In order to clone the full-length cDNAs, reverse transcription (RT) followed by polymerase chain reaction (PCR; RT-PCR) is performed on total RNA extracted from leaves, roots or other plant tissues, growing under normal conditions. Total RNA extraction, production of cDNA and PCR amplification is 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 are purified using PCR purification kit (Qiagen)
Usually, 2 sets of primers are prepared for the amplification of each gene, via nested PCR (if required). Both sets of primers are used for amplification on cDNA. In case no product is obtained, a nested PCR reaction is performed. Nested PCR is performed by amplification of the gene using external primers and then using the produced PCR product as a template for a second PCR reaction, where the internal set of primers are used. Alternatively, one or two of the internal primers are used for gene amplification, both in the first and the second PCR reactions (meaning only 2-3 primers were designed for a gene). To facilitate further cloning of the cDNAs, an 8-12 bp extension is added to the 5′ of each internal primer. The primer extension includes an endonuclease restriction site. The restriction sites are selected using two parameters: (a) the restriction 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 direction into the binary vector utilized for transformation.
PCR products are digested with the restriction endonucleases (New England BioLabs Inc) according to the sites designed in the primers. Each digested PCR product is inserted into a high copy vector pBlue-script KS plasmid vector [pBlue-script KS plasmid vector, Hypertext Transfer Protocol://World Wide Web (dot) stratagene (dot) com/manuals/212205 (dot) pdf) or pUC19 (New England BioLabs Inc], or into plasmids originated from these vectors. In case of the high copy vector originated from pBlue-script KS plasmid vector (pGXN or pGXNa), the PCR product is inserted in the high copy plasmid upstream to the NOS terminator (SEQ ID NO:8737) originated from pBI 101.3 binary vector (GenBank Accession No. U12640, nucleotides 4356 to 4693) and downstream to the 35S promoter. In other cases (pKSJ_6669 a or pUC19_pr6669), the At6669 promoter (SEQ ID NO:8741) is already cloned into the pBlue-script KS or pUC19 respectively, so the gene is introduced downstream of the promoter.
Sequencing of the inserted genes is performed, using the ABI 377 sequencer (Applied Biosystems). In some cases, after confirming the sequences of the cloned genes, the cloned cDNA accompanied/or not with the NOS terminator is introduced into a modified pGI binary vector containing the At6669 promoter via digestion with appropriate restriction endonucleases (the cloned gene replaces the GUI gene). In other cases the cloned cDNA accompanied with the At6669 promoter is introduced into a pGI vector (that does not contain the At6669 promoter). In any case the insert is followed by single copy of the NOS terminator (SEQ ID NO:8737). The digested products and the linearized plasmid vector are ligated using T4 DNA ligase enzyme (Roche, Switzerland).
Several DNA sequences of the selected genes are synthesized by GeneArt [Hypertext Transfer Protocol://World Wide Web (dot) geneart (dot) com/]. Synthetic DNA is designed in silico. Suitable restriction enzymes sites are added to the cloned sequences at the 5′ end and at the 3′ end to enable later cloning into the desired binary vector.
The pPI plasmid vector is constructed by inserting a synthetic poly-(A) signal sequence, originating from pGL3 basic plasmid vector (Promega, GenBank Accession No. U47295; nucleotides 4658-4811) into the HindIII restriction site of the binary vector pBI101.3 (Clontech, GenBank Accession No. U12640). pGI (
The modified pGI vector (pQFN or pQYN_6669) is a modified version of the pGI vector in which the cassette is inverted between the left and right borders so the gene and its corresponding promoter are close to the right border and the NPTII gene is close to the left border.
At6669, the Arabidopsis thaliana promoter sequence (SEQ ID NO:8741) is 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 are analyzed by PCR using the primers covering the insert which are designed to span the introduced promoter and gene. Positive plasmids are identified, isolated and sequenced.
Selected genes cloned by the present inventors are provided in Table 55 below.
Arabidopsis thaliana Kondara
Arabidopsis thaliana Kondara
Sorghum bicolor ND
Brachypodiums distachyon ND
Brachypodiums distachyon ND
Brachypodiums distachyon ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor Monsanto S5
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Sorghum bicolor ND
Brachypodiums distachyon ND
Arabidopsis thaliana Kondara
Arabidopsis thaliana Kondara
Arabidopsis thaliana Kondara
Sorghum bicolor ND
Arabidopsis thaliana Kondara
Arabidopsis thaliana Kondara
Arabidopsis thaliana Kondara
Arabidopsis thaliana Kondara
Arabidopsis thaliana Kondara
Each of the binary vectors described in Example 11 above are used to transform Agrobacterium cells. Two additional binary constructs, having only the At6669 or the 35S promoter or no additional promoter are used as negative controls.
The binary vectors are introduced to Agrobacterium tumefaciens GV301, or LB4404 competent cells (about 109 cells/mL) by electroporation. The electroporation is performed using a MicroPulser electroporator (Biorad), 0.2 cm cuvettes (Biorad) and EC-2 electroporation program (Biorad). The treated cells are 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 are developed on the selective media, are further analyzed by PCR using the primers designed to span the inserted sequence in the pPI plasmid. The resulting PCR products are isolated and sequenced to verify that the correct polynucleotide sequences of the invention are properly introduced to the Agrobacterium cells.
Arabidopsis thaliana Columbia plants (T0 plants) are transformed using the Floral Dip procedure described by Clough and Bent, 1998 (Floral dip: a simplified method for Agrobacterium-mediated transformation of Arabidopsis thaliana. Plant J 16:735-43) and by Desfeux et al., 2000 (Female Reproductive Tissues Are the Primary Target of Agrobacterium-Mediated Transformation by the Arabidopsis Floral-Dip Method. Plant Physiol, July 2000, Vol. 123, pp. 895-904), with minor modifications. Briefly, T0 Plants are sown in 250 ml pots filled with wet peat-based growth mix. The pots are 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 hour light/dark cycles. The T0 plants are ready for transformation six days before anthesis.
Single colonies of Agrobacterium carrying the binary constructs, are generated as described in Example 3 above. Colonies are cultured in LB medium supplemented with kanamycin (50 mg/L) and gentamycin (50 mg/L). The cultures are incubated at 28° C. for 48 hours under vigorous shaking and then centrifuged at 4000 rpm for 5 minutes. The pellets comprising the Agrobacterium cells are re-suspended in a transformation medium containing 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 T0 plants is 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 is immediately placed in a plastic tray, then covered with clear plastic dome to maintain humidity and is kept in the dark at room temperature for 18 hours, to facilitate infection and transformation. Transformed (transgenic) plants are then uncovered and transferred to a greenhouse for recovery and maturation. The transgenic T0 plants are grown in the greenhouse for 3-5 weeks until siliques are brown and dry. Seeds are harvested from plants and kept at room temperature until sowing.
For generating T1 and T2 transgenic plants harboring the genes, seeds collected from transgenic T0 plants are surface-sterilized by soaking in 70% ethanol for 1 minute, followed by soaking in 5% sodium hypochloride and 0.05% triton for 5 minutes. The surface-sterilized seeds are thoroughly washed in sterile distilled water then placed on culture plates containing half-strength Murashige-Skoog (Duchefa); 2% sucrose; 0.8% plant agar; 50 mM kanamycin; and 200 mM carbenicylin (Duchefa). The culture plates are 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 are transferred to a fresh culture plates for another week of incubation. Following incubation the T1 plants are removed from culture plates and planted in growth mix contained in 250 ml pots. The transgenic plants are allowed to grow in a greenhouse to maturity. Seeds harvested from T1 plants are cultured and grown to maturity as T2 plants under the same conditions as used for culturing and growing the T1 plants.
Assay 1: plant growth under osmotic stress [poly (ethylene glycol) (PEG)] in tissue culture conditions—One of the consequences of drought is the induction of osmotic stress in the area surrounding the roots; therefore, in many scientific studies, PEG (e.g., 1.5% PEG) is used to simulate the osmotic stress conditions resembling the high osmolarity found during drought stress.
Surface sterilized seeds are sown in basal media [50% Murashige-Skoog medium (MS) supplemented with 0.8% plant agar as solidifying agent] in the presence of Kanamycin (for selecting only transgenic plants). After sowing, plates are 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 are carefully transferred to plates containing 1.5% PEG: 0.5 MS media or Normal growth conditions (0.5 MS media). 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 independent transformation events are analyzed from each construct. Plants expressing the polynucleotides of the invention are 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 included 4 light units (4×150 Watts light bulb) and located in a darkroom, is used for capturing images of plantlets sawn in agar plates.
The image capturing process is repeated every 3-4 days starting at day 1 till day 10 (see for example the images in
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).
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, XVII and XVIII.
Relative growth rate of leaf area=Regression coefficient of leaf area along time course. Formula XVI:
Relative growth rate of root coverage=Regression coefficient of root coverage along time course. Formula XVII:
Relative growth rate of root length=Regression coefficient of root length along time course. Formula XVIII:
At the end of the experiment, plantlets are removed from the media and weighed for the determination of plant fresh weight. Plantlets are then dried for 24 hours at 60° C., and weighed again to measure plant dry weight for later statistical analysis. Growth rate is determined by comparing the leaf area coverage, root coverage and root length, between each couple of sequential photographs, and results are used to resolve the effect of the gene introduced on plant vigor, under osmotic stress, as well as under optimal conditions. Similarly, the effect of the gene introduced on biomass accumulation, under osmotic stress as well as under optimal conditions, is 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 are examined in replicates.
Statistical analyses—To identify genes conferring significantly improved tolerance to abiotic stresses or enlarged root architecture, the results obtained from the transgenic plants are compared to those obtained from control plants. To identify outperforming genes and constructs, results from the independent transformation events tested are analyzed separately. To evaluate the effect of a gene event over a control the data is analyzed by Student's t-test and the p value is calculated. Results are 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:
The genes presented in Tables 56-59 showed a significant improvement in plant ABST since they produced larger plant biomass (plant fresh and dry weight and leaf area) in T2 generation (Tables 27-28) or T1 generation (Tables 29-30) when grown under osmotic stress conditions, compared to control plants. The genes were cloned under the regulation of a constitutive promoter (At6669; SEQ ID NO:8741). 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 60-61 showed a significant improvement in plant NUE since they produced a larger root biomass (root length and root coverage) when grown under osmotic stress conditions, compared to control plants. Plants producing larger root biomass have better possibilities to absorb larger amount of water from soil. The genes were cloned under the regulation of a constitutive promoter (At6669; SEQ ID NO:8741). 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 root performance. Event with p-value<0.1 was considered statistically significant
The genes listed in Tables 62-65 have improved plant growth rate (growth rate of the leaf area, root coverage and root length) when grown under osmotic stress conditions, compared to control plants. Plants showing fast growth rate show a better plant establishment in soil under osmotic stress conditions. Faster growth was observed when growth rate of leaf area and root length and coverage was measured. The genes were cloned under the regulation of a constitutive promoter (At6669; SEQ ID NO:8741). 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 and the results obtained where positive as well. Event with p-value<0.0.1 was considered statistically significant.
The genes listed in Tables 66-69 improved plant biomass when grown at standard conditions. These genes produced larger plant biomass (plant fresh and dry weight and leaf area) when grown under standard conditions, compared to control plants. Larger plant biomass under this growth conditions indicates the high ability of the plant to better metabolize the nutrients present in the medium. The genes were cloned under the regulation of a constitutive promoter (At6669; SEQ ID NO:8741). 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 and the results obtained where positive as well. Event with p-value<0.1 was considered statistically significant
The genes listed in Tables 70-71 improved plant NUE when grown at standard conditions. These genes produced larger root biomass (root length and root coverage) when grown under standard growth conditions, compared to control plants. Plants producing larger root biomass have better possibilities to absorb larger amount of water from soil. The genes were cloned under the regulation of a constitutive promoter (At6669; SEQ ID NO:8741). 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 resulting in positive results as well. Event with p-value <0.1 was considered statistically significant
The genes listed in Tables 72-73 improved plant growth rate (leaf area, root length and root coverage growth rate) when grown at standard growth conditions. These produced plants that grew faster than control plants when grown under standard growth conditions. Faster growth was observed when growth rate of leaf area and root length and coverage was measured. The genes were cloned under the regulation of a constitutive promoter (At6669; SEQ ID NO:8741). 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 resulting in positive results as well. Event with p-value<0.1 was considered statistically significant
ABS tolerance: Yield and plant growth rate at high salinity concentration under greenhouse conditions (until bolting)—This assay follows the plant biomass formation and the rosette area growth of plants grown in the greenhouse at high salinity irrigation and normal irrigation. Transgenic Arabidopsis seeds were sown in phytogel 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. Half of the plants are irrigated with a salt solution (150 mM NaCl) so as to induce salinity stress (stress conditions). The other half of the plants is irrigated with tap water (normal conditions). All plants are grown in the greenhouse until bolting stage, then harvested (the above ground tissue) and weighted (immediately or following drying in oven at 50° C. for 24 hours). High salinity conditions are achieved by irrigating with a solution containing 150 mM NaCl (“ABS” growth conditions) and compared to regular growth conditions.
Each construct was validated at its T2 generation. Transgenic plants transformed with a construct conformed by an empty vector carrying the AT6669 (SEQ ID NO:8741) promoter and the selectable marker was 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 with no gene at all, under the same promoter were used as control.
The experiment is 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 included 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 16. 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 are 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 is 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, leaf blade area, Petiole Relative Area and leaf petiole length.
Vegetative growth rate: the relative growth rate (RGR) of leaf blade area (Formula VIII), leaf number (Formula IX), rosette area (Formula X), rosette diameter (Formula XI), plot coverage (Formula XII) and Petiole Relative Area (XIII) as described above.
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 genes conferring significantly improved tolerance to abiotic stresses, 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. Data was analyzed using Student's t-test and results are 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:
The genes listed in Tables 74-83 improved plant ABST when grown at high salinity concentration. These genes produced larger plants with a larger photosynthetic area, biomass (fresh weight, dry weight, rosette diameter, rosette area and plot coverage) when grown under high salinity concentration. The genes were cloned under the regulation of a constitutive (At6669; SEQ ID NO:8741). 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
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.
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| Child | 14554076 | US |
