Patent Application
20130191936
The present invention belongs to the field of agriculture more particularly to the field of molecular breeding. The invention provides gene expression signatures which are associated with the presence of high energy use efficient plants. These gene expression signatures are breeder tools which can be used for the selection and production of plants which possess a high energy use efficiency. The high energy use efficiency is reflected in a higher tolerance to abiotic stress and also in an increased vigor.
Abiotic stress is defined as the negative impact of non-living factors on the living organisms in a specific environment. The non-living variable must influence the environment beyond its normal range of variation to adversely affect the population performance or individual physiology of the organism in a significant way. Abiotic stress is essentially unavoidable. Abiotic stress affects animals, but plants are especially dependent on environmental factors, so it is particularly constraining. Abiotic stress is the most harmful factor concerning the growth and productivity of crops worldwide. Drought, temperature extremes, and saline soils are the most common abiotic stresses that plants encounter. Globally, approximately 22% of agricultural land is saline and areas under drought are already expanding and this is expected to increase further. Other crops are exposed to multiple stresses, and the manner in which a plant senses and responds to different environmental factors appears to be overlapping. The most obvious detriment concerning abiotic stress involves farming. It has been calculated that abiotic stress causes the most crop loss of any other factor and that most major crops are reduced in their yield by more than 50% from their potential yield. In addition, it has been speculated that this yield reduction will only worsen with the dramatic climate changes expected in the future. Because abiotic stress is widely considered a detrimental effect, the research on this branch of the issue is extensive. When a plant is subjected to abiotic stress, a number of genes is differently expressed, resulting in a changed level of several metabolites and proteins, some of which may be responsible for conferring a certain degree of protection to these stresses. Obviously, a key to progress towards breeding better crops under stress has been to understand the changes in cellular, biochemical and molecular machinery that occur in response to stress. The development of genetically engineered plants by the overexpression or downregulation of selected genes seems to be a viable option to hasten the breeding of “improved” plants but has thus far not generated a significant impact on the generation of crops with an enhanced tolerance to abiotic stress. It is a constant challenge for breeders to improve and to shorten the timelines of the breeding processes. One particular aspect is the ability to select suitable starting material for breeding comprising optimal agronomical traits such as abiotic stress tolerance. The present invention provides an expression signature profile which can be used as a breeder tool for the selection and production of abiotic stress tolerant plants.
The invention relates to methods of finding a gene expression profile (or a gene expression signature which is equivalent wording) characteristic for a plant with a high energy use efficiency. In one embodiment the invention enables the artisan to correlate the gene expression profile of a plant with a high energy use efficiency.
The present invention provides a method for the production of a plant with a high energy use efficiency comprising i) providing a population of plants of the same plant species, ii) obtaining a nucleic acid sample from said plants, iii) determining a gene expression profile of said plants by quantifying the mRNA expression level (mRNA abundance or presence) of at least two genes from Table 1 or genes comprising at least 70% nucleic acid identity with the genes in Table 1 and/or at least 2 genes from Table 2 or genes comprising at least 70% nucleic acid identity with the genes in Table 2 and/or of at least two genes from Tables 25-28 or genes comprising at least 70% nucleic acid identity with the genes in Table 25-28, iv) identifying at least one plant having an at least increased 1.5 fold presence of at least two genes from Table 2 or genes comprising at least 70% nucleic acid identity with the genes in Table 2 with respect to the average expression level (mRNA abundance or presence) of those genes in the plants of said population and/or having an at least decreased 0.66 fold presence of at least two genes from Table 1 or genes comprising at least 70% nucleic acid identity with the genes in Table 1 with respect to the average expression level of those genes in the plants of said population and/or having an at least increased 2.0 fold presence of at least two genes from Tables 25, 26 27 and 28 or genes comprising at least 70% nucleic acid identity with the genes in Tables 25, 26 27 and 28 with respect to the average expression level of those genes of the plants in said population.
In a specific embodiment the population of plants consists of genetically identical plants.
In another specific embodiment the population of plants consists of doubled haploid plants.
In another specific embodiment the population of plants consists of plants which are produced by vegetative reproduction.
In yet another specific embodiment the population of plants consists of inbred plants.
In another embodiment the produced plant from the methods is further crossed with another plant.
In another specific embodiment the produced plant and which is further crossed with another plant are both inbred plants.
In another specific embodiment the produced high energy use efficiency plant is a Brassica oilseed rape, tomato, rice, wheat, cotton, corn or soybean plant.
In a specific embodiment the quantification of the mRNA expression level (i.e. determining the mRNA presence) in the methods is determined by microarray analysis.
In a specific embodiment the quantification of the mRNA expression level in the methods is determined by RT-PCR.
In another specific embodiment the invention provides for a method for producing a population of plants or seeds with a high energy use efficiency comprising selecting a population of plants according to any one of the previous methods.
In another embodiment the invention provides for a method for increasing harvest yield comprising the steps of producing a population of plants or seeds according to the previous method, growing said plants or seeds in a field and producing a harvest from said plants or seeds.
A method for producing a hybrid plant or hybrid seed with high energy use efficiency comprising selecting a population of plants with high energy use efficiency for at least one parent inbred plant, crossing plants of said population with another inbred plant, isolating hybrid seed from said cross, and optionally, grow hybrid plants from said seed.
In another embodiment the invention provides a kit comprising the necessary tools for carrying out the method of the invention.
In another embodiment the invention provides a method for obtaining a biological or chemical compound which is capable of generating a plant with high energy use efficiency comprising i) providing a population of plants of the same plant species, ii) treating a subset of the plants of said population with one or more biological or chemical compounds, iii) obtaining a nucleic acid sample from said treated and untreated plants, iv) determining a gene expression profile of said treated and untreated plants by quantifying the mRNA expression level (mRNA presence) of at least two genes from Table 1 or genes comprising at least 70% nucleic acid identity with the genes in Table 1 and/or at least 2 genes from Table 2 or genes comprising at least 70% nucleic acid identity with the genes in Table 2, and/or of at least two genes from Table 25-28 or genes comprising at least 70% nucleic acid identity with the genes in Table 25-28 iv) identifying a compound which results in an at least increased 1.5 fold presence of the mRNA of at least two genes from Table 2 or genes comprising at least 70% nucleic acid identity with the genes in Table 2 in a plant from said population with respect to the expression level of said genes untreated plants of said population and/or which results in an at least decreased 0.66 fold presence of the mRNA of at least two genes from Table 1 or genes comprising at least 70% nucleic acid identity with the genes in Table 1 in said plant from said population with respect to the expression level (mRNA presence) of said genes in untreated plants in said population and/or which results in an at least 2.0 fold presence of the mRNA of said at least two genes from Table 25-28 or genes comprising at least 70% nucleic acid identity with the genes in Table 25-28 in said plant from said population with respect to the average expression level (mRNA presence) of said genes untreated plants in said.
In another embodiment the invention provides a gene expression profile indicative for high energy use efficiency comprising the expression level of at least two genes from Table 1 or genes comprising at least 70% nucleic acid identity with the genes in Table 1 and/or at least 2 genes from Table 2 or genes comprising at least 70% nucleic acid identity with the genes in Table 2 and/or at least 2 genes from Table 25-28 or genes comprising at least 70% nucleic acid identity with the genes in Table 25-28.
In another embodiment the gene expression profile is used in any of the previous methods.
To facilitate the understanding of this invention a number of terms are defined below. Terms defined herein (unless otherwise specified) have meanings as commonly understood by a person of ordinary skill in the areas relevant to the present invention. As used in this specification and its appended claims, terms such as “a”, “an” and “the” are not intended to refer to only a singular entity, but include the general class of which a specific example may be used for illustration, unless the context dictates otherwise. The terminology herein is used to describe specific embodiments of the invention, but their usage does not delimit the invention, except as outlined in the claims.
In a first embodiment the invention provides for a technical method for the production of a plant with a high energy use efficiency comprising i) providing a population of plants of the same plant species, ii) obtaining a nucleic acid sample from said plants, iii) determining a gene expression profile by quantifying the mRNA expression level (mRNA presence) of at least two genes from Table 1 or genes comprising at least 70% nucleic acid identity with the genes in Table 1 and/or at least 2 genes from Table 2 or genes comprising at least 70% nucleic acid identity with the genes in Table 2 and/or of at least two genes from Tables 25, 26 27 and 28 (SEQ ID NO 147-353) or genes comprising at least 70% nucleic acid identity with the genes in Table 25, 26, 27 and 28, iv) identifying at least one plant having an at least increased 1.5 fold presence of the mRNA of at least two genes from Table 2 or genes comprising at least 70% nucleic acid identity with the genes in Table 2 with respect to the average expression level (mRNA presence) of said genes in the plants of said population and/or having an at least decreased 0.66 fold presence of the mRNA of at least two genes from Table 1 or genes comprising at least 70% nucleic acid identity with the genes in Table 1 with respect to the average expression level (mRNA presence) of said genes in the plants of said population and/or having at least increased 2.0 fold presence of at the mRNA of least two genes from Tables 25, 26 27 and 28 or genes comprising at least 70% nucleic acid identity with the genes in Tables 25, 26 27 and 28 with respect to the average expression level (mRNA presence) of said genes in the plants of said population.
The terms “increase,” “elevate,” “raise,” and grammatical equivalents when used in reference to the level of mRNA expression (presence) of a gene in a first nucleic sample relative to a second sample, mean that the quantity of the mRNA expression in the first sample is higher than in the second sample by an amount that is statistically significant using a statistical method of analysis. Thus, an “at least increased 1.5 or 2.0 fold presence” as used herein, corresponds to a fold change in expression level with respect to a control value that is equal to or higher than 1.5 or 2.0 respectively.
The terms “reduce,” “inhibit,” “diminish,” “suppress,” “decrease,” and grammatical equivalents when used in reference to the level of mRNA expression (presence) of a gene in a first nucleic sample relative to a second sample, mean that the quantity of the mRNA expression in the first sample is lower than in the second sample by an amount that is statistically significant using a statistical method of analysis. Thus, an “at least decreased 0.66 fold presence” as used herein, corresponds to a fold change in expression level with respect to a control value that is equal to or lower than 0.6667. This can also be said to be an at least a 1.5 fold reduction (i.e. a fold reduction that is equal to or higher than 1.5).
A “gene expression profile” includes but is not limited to gene expression profiles as generally understood in the art. A gene expression profile of high energy use efficient plants selected from a population of plants of the same species contains a number of genes differentially expressed in comparison to the average of energy use efficiency of the plants present in said population (see Table 1 for the genes which are downregulated in the high energy use efficient plants compared to the average energy use efficiency of the plants present in the population of plants of the same plant species and Table 2 for the genes which are upregulated in the high energy use efficient plants compared to the average energy use efficiency of the plants present in the population of plants of the same plant species). A gene that appears in a gene expression profile, whether by upregulation or downregulation is said to be a member of the gene expression profile. For example, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes can be selected from Table I for an optimum signature for a high energy use efficient plant and/or at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes can be selected from Table 2 and/or at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes can be selected from Tables 25-28 for an optimum signature for a high energy use efficient plant. A further refinement of the gene expression profile by the identification of coexpression networks is presented in the example section.
Thus in another embodiment the quantification of the mRNA expression profile can be carried out with at least 2 genes or genes comprising at least 70% nucleic acid identity with the genes in Table 3 or Table 4 or Table 5 or Table 6 or Table 7 and/or with at least 2 genes or genes comprising at least 70% nucleic acid identity with the genes in Table 8 or Table 9 or Table 10 or Table 11 or Table 12 or Table 13 or Table 14 or Table 15 or Table 16 or Table 17 or Table 18 or Table 19 or Table 20 or Table 21 and/or with at least two genes or genes comprising at least 70% nucleic acid identity with the genes in Table 25, 26, 27 and 28 Quantification of the mRNA expression profile can also be carried out with at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes or member genes with at least 70% nucleotide sequence identity with the above genes.
In yet another embodiment, quantification of the mRNA expression profile can be carried out with at least two genes or genes comprising at least 70% nucleic acid identity with the genes that have been identified in the coexpression networks of both the HV110 and the HV112 hybrids with respect to control line 115 (genes that were significantly upregulated by at least 2.0 fold), i.e. the genes comprising the nucleotide sequence of SEQ ID NO's: 148, 149, 150, 151, 153, 155, 157, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 174, 175, 176, 178, 180, 181, 182, 183, 184, 185, 188, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 204, 205, 207, 209, 210, 211, 212, 214, 216, 218, 221, 221, 222, 224, 226, 227, 228, 229, 233, 234, 235, 236, 237, 238, 240, 241, 242, 243, 246, 247, 249, 250, 251, 253, 254, 255, 256, 261, 262, 263, 266, 267, 269, 270, 323, 272, 273, 274, 275, 276, 277, 278, 279, 280, 283, 284, 285, 286, 287, 288, 289, 291, 292, 294, 295, 297, 298, 299, 300, 301, 302, 303, 305, 306, 307, 308, 309, 311, 312, 313, 315, 318, 319, 321, 322, 324. Quantification of the mRNA expression profile can also be carried out with at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes or member genes with at least 70% nucleotide sequence identity with the above genes.
While not intending to limit the invention to a particular explanation of the occurrence of a specific gene expression signature associated with high energy use efficient plants, it appears that several genes with mitochondrial function such as genes of the respiratory chain are transcriptionally upregulated in high energy efficient plant in addition to the upregulation of the transcription of a number of ribosomal genes and upregulation of transcription of genes involved in chloroplast function.
Thus, in even yet another embodiment, quantification of the mRNA expression profile can be carried out with at least two genes or genes comprising at least 70% nucleic acid identity with the genes that have been found to be significantly upregulated in HV110 or HV112 vs. control line 115 using the agilent (at least 1.5 fold) or combimatrix (at least 2.0 fold) array and that are involved in mitochondria, translation or chloroplasts, i.e. the genes comprising SEQ ID NO's 66, 69, 78, 80, 81, 82, 84, 87, 89, 90, 91, 92, 93, 96, 101, 104, 105, 107, 113, 116, 117, 119, 121, 122, 123, 127, 128, 129, 131, 132, 133, 134, 148, 157, 161, 162, 176, 177, 182, 192, 201, 207, 209, 211, 212, 224, 226, 228, 231, 235, 236, 238, 249, 250, 254, 258, 260, 266, 267, 269, 274, 276, 279, 280, 284, 286, 291, 292, 296, 297, 299, 300, 301, 302, 303, 306, 308, 309, 311, 313, 316, 321, 323, 324, 329, 330, 331, 335, 339, 343, 344, 353. Quantification of the mRNA expression profile can also be carried out with at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes or member genes with at least 70% nucleotide sequence identity with the above genes.
In an even further embodiment, quantification of the mRNA expression profile can be carried out with at least two genes or genes comprising at least 70% nucleic acid identity with the genes that have been found to be significantly upregulated (at least 2.0 fold) in both HV110 and HV112 vs. control line 115 and that are involved in mitochondria, translation or chloroplasts, i.e. the genes comprising SEQ ID NO's 148, 157, 161, 162, 176, 182, 192, 201, 207, 209, 211, 212, 224, 226, 228, 235, 236, 238, 249, 250, 254, 266, 267, 269, 274, 276, 279, 280, 284, 286, 292, 297, 299, 300, 301, 302, 303, 306, 308, 309, 311, 313, 321, 324. Quantification of the mRNA expression profile can also be carried out with at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes or member genes with at least 70% nucleotide sequence identity with the above genes.
In a further embodiment, quantification of the mRNA expression profile can be carried out with the above described genes that have been found to be significantly upregulated with respect to the control line by at least 2.0 fold, by at least 3.0 fold, by at least 4.0 fold, by at least 5.0 fold, by at least 10 fold, or by at least 25 fold (i.e. wherein the fold change in expression is equal to or higher than 2.0, 3.0, 4.0, 5.0, 10 or 25 respectively) and/or that have been found to be significantly downregulated by at least 1.5 fold, by at least 2.0 fold, or by at least 2.5 fold (i.e. wherein the fold change in expression is equal to or below 0.6667, 0.5 or 0.4 respectively).
The nucleic acid sample is obtained from the plant in a manner which allows further cultivation of said sampled individual plants, e.g. by isolating a tissue sample or explant from individual plants of said population. In one embodiment, the nucleic acid sample is obtained from a leaf. In a particular embodiment the nucleic acid sample is obtained from leaf 3 or leaf 4, at the 3- or 4 leaf stage.
“Expression level” as used herein, refers to the net mRNA presence or abundance, i.e. taking into account the rate of mRNA synthesis and the rate of mRNA degradation.
The average expression level (mRNA presence) of a gene in a population of plants can be determined by adding the expression levels of the individual plants and dividing that by the number of plants of the population, or by pooling the nucleic acid samples of all plants of the population and then determine the expression level of the gene in the pooled nucleic acid sample. A gene expression profile may be “determined,” without limitation, by means of DNA microarray analysis, PCR, quantitative RT-PCR, etc. These are referred to herein collectively as “nucleic-acid based: determinations or assays. Alternatively, methods as multiplexed immunofluorescence microscopy or flow cytometry may be used.
Gene expression profiles may be “compared” by any of a variety of statistical analytic procedures including, without limitation, the use of GeneSpring 7.2 software (Silicon Genetics, Redwood City, Calif.) according to the manufacturer's instructions.
The aforementioned methods for examining gene sets employ a number of well-known methods in molecular biology, to which references are made herein. A gene is a heritable chemical code resident in, for example, a cell, virus, or bacteriophage that an organism reads (decodes, decrypts, transcribes) as a template for ordering the structures of biomolecules that an organism synthesizes to impart regulated function to the organism. Chemically, a gene is a heteropolymer comprised of subunits (“nucleotides”) arranged in a specific sequence. In cells, such heteropolymers are deoxynucleic acids (“DNA”) or ribonucleic acids (“RNA”). DNA forms long strands. Characteristically, these strands occur in pairs. The first member of a pair is not identical in nucleotide sequence to the second strand, but complementary. The tendency of a first strand to bind in this way to a complementary second strand (the two strands are said to “anneal” or “hybridize”), together with the tendency of individual nucleotides to line up against a single strand in a complementarily ordered manner accounts for the replication of DNA. Experimentally, nucleotide sequences selected for their complementarity can be made to anneal to a strand of DNA containing one or more genes. A single such sequence can be employed to identify the presence of a particular gene by attaching itself to the gene. This so-called “probe” sequence is adapted to carry with it a “marker” that the investigator can readily detect as evidence that the probe struck a target.
Alternatively, such sequences can be delivered in pairs selected to hybridize with two specific sequences that bracket a gene sequence. A complementary strand of DNA then forms between the “primer pair.” In one well-known method, the “polymerase chain reaction” or “PCR,” the formation of complementary strands can be made to occur repeatedly in an exponential amplification. A specific nucleotide sequence so amplified is referred to herein as the “amplicon” of that sequence. “Quantitative PCR” or “qPCR” herein refers to a version of the method that allows the artisan not only to detect the presence of a specific nucleic acid sequence but also to quantify how many copies of the sequence are present in a sample, at least relative to a control. As used herein, “qRTPCR” may refer to “quantitative real-time PCR,” used interchangeably with “qPCR” as a technique for quantifying the amount of a specific DNA sequence in a sample. However, if the context so admits, the same abbreviation may refer to “quantitative reverse transcriptase PCR,” a method for determining the amount of messenger RNA present in a sample. Since the presence of a particular messenger RNA in a cell indicates that a specific gene is currently active (being expressed) in the cell, this quantitative technique finds use, for example, in gauging the level of expression of a gene. Collectively, the genes of an organism constitute its genome.
For the purpose of this invention, the “sequence identity” of two related nucleotide or amino acid sequences, expressed as a percentage, refers to the number of positions in the two optimally aligned sequences which have identical residues (×100) divided by the number of positions compared. A gap, i.e., a position in an alignment where a residue is present in one sequence but not in the other is regarded as a position with non-identical residues. The alignment of the two sequences is performed by the Needleman and Wunsch algorithm (Needleman and Wunsch (1970) J Mol. Biol. 48: 443-453) The computer-assisted sequence alignment above, can be conveniently performed using standard software program such as GAP which is part of the Wisconsin Package Version 10.1 (Genetics Computer Group, Madision, Wis., USA) using the default scoring matrix with a gap creation penalty of 50 and a gap extension penalty of 3. Sequences are indicated as “essentially similar” when such sequence have a sequence identity of at least about 75%, particularly at least about 80%, more particularly at least about 85%, quite particularly about 90%, especially about 95%, more especially about 100%, quite especially are identical. It is clear than when RNA sequences are the to be essentially similar or have a certain degree of sequence identity with DNA sequences, thymine (T) in the DNA sequence is considered equal to uracil (U) in the RNA sequence.
Thus, at least 70% nucleic acid identity, as used herein, refers to 70%-100%, 75%-100%, 80%-100%, 85%-100%, 90%-100%, 95%-100%, 96%-100%, 97-100%, 98%-100% or 99-100% nucleic acid sequence identity with respect to another nucleic acid sequence.
In another aspect, the invention is embodied in a kit useful for detecting the gene expression profile of the invention. To effectively detect a gene expression profile which is characteristic for a plant with a high energy use efficiency or a population of plants with a high energy efficiency the gene expression (mRNa presence) of at least two, at least three, at least four, at least five or more genes depicted in Table I and/or at least two, at least three, at least four, at least five or more genes depicted in Table II, and/or at least two, at least three, at least four, at least five or more genes depicted in Table 25-28 is measured. A kit to carry out a PCR analysis, preferably a multiplex PCR analysis such as a multiplex RT-PCR analysis comprises primers, buffers, polynucleotides and a thermostable DNA polymerase.
In another embodiment, the kit measures the expression level of at least 2 genes or genes comprising at least 70% nucleic acid identity with the genes in Table 3 or Table 4 or Table 5 or Table 6 or Table 7 and/or with at least 2 genes or genes comprising at least 70% nucleic acid identity with the genes in Table 8 or Table 9 or Table 10 or Table 11 or Table 12 or Table 13 or Table 14 or Table 15 or Table 16 or Table 17 or Table 18 or Table 19 or Table 20 or Table 21. The kit measures the expression level of at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes or member genes with at least 70% nucleotide sequence identity with the above genes. The kit can also measures the expression level of at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes or member genes with at least 70% nucleotide sequence identity with the above genes.
In yet another embodiment, the kit measures the expression level of at least two genes or genes comprising at least 70% nucleic acid identity with the genes that have been identified in the coexpression networks of both the HV110 and the HV112 hybrids with respect to control line 115 (genes that were significantly upregulated by at least 2.0 fold, as indicated above). The kit can also measures the expression level of at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes or member genes with at least 70% nucleotide sequence identity with the above genes.
In even yet another embodiment, the kit measures the expression level of at least two genes or genes comprising at least 70% nucleic acid identity with the genes that have been to be significantly upregulated in HV110 or HV112 vs control line 115 using the agilent (at least 1.5 fold) or combimatrix (at least 2.0 fold) array and that are involved in mitochondria, translation or chloroplasts (as indicated above). The kit can also measures the expression level of at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes or member genes with at least 70% nucleotide sequence identity with the above genes.
In an even further embodiment, the kit measures the expression level of at least two genes or genes comprising at least 70% nucleic acid identity with the genes that have been to be significantly upregulated (at least 2.0 fold) in both HV110 and HV112 vs control line 115 and that are involved in mitochondria, translation or chloroplasts (as indicated above). The kit can also measures the expression level of at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes or member genes with at least 70% nucleotide sequence identity with the above genes.
In another embodiment, the kit can measure the expression level the above described genes that have been found to be significantly upregulated with respect to the control line by at least 2.0 fold, by at least 3.0 fold, by at least 4.0 fold, by at least 5.0 fold, by at least 10 fold, or by at least 25 fold (i.e. wherein the fold change in expression is equal to or higher than 2.0, 3.0, 4.0, 5.0, 10 or 25 respectively) and/or that have been found to be significantly downregulated by at least 1.5 fold, by at least 2.0 fold, or by at least 2.5 fold (i.e. wherein the fold change in expression is equal to or below 0.6667, 0.5 or 0.4 respectively).
In a particular embodiment based on the identified gene expression profile it is possible to determine a corresponding protein expression profile. A protein expression profile can conveniently be detected by the use of specific antibodies directed against the differentially expressed protein products.
In a particular embodiment the starting population of plants is of the same plant species or of the same plant variety. In another particular embodiment the population of plants is genetically identical.
As used herein “a population of genetically identical plants” is a population of plants, wherein the individual plants are true breeding, i.e. show little or no variation at the genome nucleotide sequence level, at least for the genetic factors which are underlying the quantitative trait, particularly genetic factors underlying high energy use efficiency and low cellular respiration rate. Genetically uniform plants may be inbred plants but may also be a population of genetically identical plants such as doubled haploid plants. Doubled haploid plants are plants obtained by spontaneous or induced doubling of the haploid genome in haploid plant cell lines (which may be produced from gametes or precursor cells thereof such as microspores). Through the chromosome doubling, complete homozygous plants can be produced in one generation and all progeny plants of a selfed doubled haploid plant are substantially genetically identical (safe the rare mutations, deletions or genome rearrangements). Other genetically uniform plants are obtained by vegetal reproduction or multiplication such as e.g. in potato, sugarcane, trees including poplars or eucalyptus trees.
“Creating propagating material”, as used herein, relates to any means know in the art to produce further plants, plant parts or seeds and includes inter alia vegetative reproduction methods (e.g. air or ground layering, division, (bud) grafting, micropropagation, stolons or runners, storage organs such as bulbs, corms, tubers and rhizomes, striking or cutting, twin-scaling), sexual reproduction (crossing with another plant) and asexual reproduction (e.g. apomixis, somatic hybridization).
As used herein, “energy use efficiency (EUE)” is the quotient of the “energy content” and “cellular respiration”. High energy use efficiency can be achieved in plants when the energy content of the cells of the plant remains about equal to that of control plants, but when such energy content is achieved by a lower cellular respiration.
The energy use efficiency can be determined by determining the cellular respiration and determining the NAD(P)H content in the isolated sample and dividing the NAD(P)H content by the respiration to determine the energy use efficiency. The energy use efficiency can also be determined by measuring the ascorbate or ascorbic acid content of the plant or by measuring the respiratory chain complex I activity in said sample.
“Cellular respiration” refers to the use of oxygen as an electron acceptor and can conveniently be quantified by measuring the electron transport through the mitochondrial respiratory chain e.g. by measuring the capacity of the tissue sample to reduce 2,3,5 triphenyltetrazolium chloride (TTC). Although it is believed that for the purpose of the assays defined here, TTC is the most suited substrate, other indicator molecules, such as MTT (3-(4,5-dimethylthiazol-2-yl)-2,5 diphenyl-2H-tetrazolium), can be used to measure the electron flow in the mitochondrial electron transport chain (see Musser and Oseroff, 1994 Photochemistry and Photobiology 59, pp 621-626). TTC reduction occurs at the end of the mitochondrial respiratory chain at complex IV. Therefore, TTC reduction reflects the total electron flow through the mitochondrial respiratory chain, including the alternative oxidative respiratory pathway. The electrons enter the mitochondrial electron transport chain through complex I, complex II, and the internal and external alternative NAD(P)H dehydrogenases. A suitable TTC reduction assay has been described by De Block and De Brouwer, 2002 (Plant Physiol. Biochem. 40, 845-852).
The “energy content” of cells of a plant refers to the amount of molecules usually employed to store energy such as ATP, NADH and NADPH. The energy content of a sample can conveniently be determined by measuring the NAD(P)H content of the sample. A suitable assay has been described by Nakamura et al. 2003. (Quantification of intracellular NAD(P)H can monitor an imbalance of DNA single strand break repair in base excision repair deficient cells in real time. Nucl. Acids Res. 31, 17 e104).
Plants or subpopulations of plants should be selected wherein the energy use efficiency is at least as good as the energy use efficiency determined for the control plants, preferably is higher than the energy use efficiency of control plants. Although it is believed that there is no particular upper limit for energy use efficiency, it has been observed that subpopulations or plants can be obtained with an energy use efficiency which is about 5% to about 15%, particularly about 10% higher than the energy use efficiency of control plants. As used herein, control plants or control population are a population of plants which are genetically uniform but which have not been subjected to the reiterative selection for plants with a higher energy use efficiency.
Plants or subpopulations of plants can initially be selected for a cellular respiration which is lower than the cellular respiration determined for the control plants. Typically, plants with a high energy use efficiency have cellular respiration rate which is between 85 and 95% of the cellular respiration rate of control plants. It has been observed that it is usually feasible to subject a population with lower respiration rates to an additional cycle of selection yielding a population of plants with even lower respiration rates, wherein however the energy content level is also declined. Such selected population of plants have a yield potential which is not better than a population of unselected control plants and the yield may even be worse in particular circumstances. Selection of populations with too low cellular respiration, particularly when accompanied with a decline in energy content level is not beneficial. Respiration rates below 75% of the respiration rate of control plants, particularly combined with energy contents below 75% of the energy content of control plants should preferably be avoided.
It has been observed that selected populations with a high energy use efficiency are also characterized by an increased respiratory chain complex I activity compared to control plants and by an increased ascorbic acid content compared to control plants. These characteristics could serve as an alternative or supplementary marker to select plants or (sub)populations of plants with increased energy use efficiency. Ascorbate content can be quantified using the reflectometric ascorbic acid test from Merck (Darmstadt, Germany). Complex I activity can be quantified using the MitoProfile Dipstick Assay kit for complex I activity of MitoSciences (Eugene, Oreg., USA).
It has been observed that the selected subpopulation was more tolerant to adverse abiotic conditions than the unselected control plants. Accordingly, the invention also provides a method for producing a population of plants or seeds with increased tolerance to adverse abiotic conditions by selection plants or populations of plants according to the methods described herein. As used herein “adverse abiotic conditions” include drought, water deficiency, hypoxic or anoxic conditions, flooding, high or low suboptimal temperatures, high salinicity, low nutrient level, high ozone concentrations, high or low light concentrations and the like. It has also been observed that the selected plants have a higher yield (or have a yield improvement). Thus, the wording ‘a plant with a high energy use efficiency’ is equivalent to the wording ‘a plant tolerant to abiotic stress and having an improved yield’. It is understood that the tolerance to abiotic stress and improved yield is with respect to the average of the abiotic stress tolerance and yield of the plants of the population from which the plant was selected.
Interplanting, as used herein refers to the mixed planting of parent plants of which seeds and/or progeny plants are to be obtained.
In a particular embodiment the method for the production of a plant with a high energy use efficiency may be applied to both parent lines and if hybrid production involves male sterility necessitating the use of a maintainer line for maintaining the female parent.
The invention also provides selected plants or populations of plants with high energy use efficiency as can be obtained through the selection methods herein described. Such plants are characterized by a low cellular respiration (lower than the cellular respiration of control plants as herein defined) and at least one of the following characteristics: ascorbic acid higher than control plants; NAD(P)H content higher than control plants; respiratory chain complex I activity higher than control plants; and photorespiration lower than control plants.
The methods and means described herein are believed to be suitable for all plant cells and plants, gymnosperms and angiosperms, both dicotyledonous and monocotyledonous plant cells and plants including but not limited to Arabidopsis, alfalfa, barley, bean, corn or maize, cotton, flax, oat, pea, rape, rice, rye, safflower, sorghum, soybean, sunflower, tobacco and other Nicotiana species, including Nicotiana benthamiana, wheat, asparagus, beet, broccoli, cabbage, carrot, cauliflower, celery, cucumber, eggplant, lettuce, onion, oilseed rape, pepper, potato, pumpkin, radish, spinach, squash, tomato, zucchini, almond, apple, apricot, banana, blackberry, blueberry, cacao, cherry, coconut, cranberry, date, grape, grapefruit, guava, kiwi, lemon, lime, mango, melon, nectarine, orange, papaya, passion fruit, peach, peanut, pear, pineapple, pistachio, plum, raspberry, strawberry, tangerine, walnut and watermelon Brassica vegetables, sugarcane, vegetables (including chicory, lettuce, tomato), Lemnaceae (including species from the genera Lemna, Wolffiella, Spirodela, Landoltia, Wolffia) and sugarbeet.
In yet another embodiment the invention provides for a method for obtaining a biological or chemical compound which is capable of generating a plant with high energy use efficiency comprising a) providing a population of plants of the same plant species, b) treating a subset of the plants of said population with a biological or chemical compound, c) obtaining a nucleic acid sample from said plants of said population, iv) determining a gene expression profile by quantifying the mRNA expression level (mRNA presence) of at least two genes from Table 1 or genes comprising at least 70% nucleic acid identity with the genes in Table 1 and/or at least 2 genes from Table 2 or genes comprising at least 70% nucleic acid identity with the genes in Table 2, and/or of at least two genes from Tables 25, 26 27 and 28 (SEQ ID NO 147-353) or genes comprising at least 70% nucleic acid identity with the genes in Table 25, 26, 27 and 28 and d) identifying a compound which when applied to a plant results in an at least increased 1.5 fold presence of at the mRNA of least two genes from Table 2 or genes comprising at least 70% nucleic acid identity with the genes in Table 2 in said plant from said population with respect to the expression level (mRNA presence) of said genes in untreated plants of said population and/or results in an at least decreased 0.66 fold presence of the mRNA of at least two genes from Table 1 or genes comprising at least 70% nucleic acid identity with the genes in Table 1 in said plant from said population with respect to the expression level (mRNA presence) of said genes in untreated plants of said population, and/or results in an at least increased 2.0 fold presence of the mRNA of at least two genes from Tables 25, 26 27 and 28 or genes comprising at least 70% nucleic acid identity with the genes in Tables 25, 26 27 and 28 in a plant from said population with respect to the expression level (mRNA presence) of said genes in untreated plants of said population.
In step (b) any biological or chemical compound may be contacted with the plants or plant parts. It is also envisaged that a plurality of different compounds can be contacted in parallel with plants or plant parts. Preferably each test compound is brought into physical contact with one or more individual plants. Contact can also be attained by various means, such as spraying, spotting, brushing, applying solutions or solids to the soil, to the gaseous phase around the plants or plant parts, dipping, etc. The test compounds may be solid, liquid, semi-solid or gaseous. The test compounds can be artificially synthesized compounds or natural compounds, such as proteins, protein fragments, volatile organic compounds, plant or animal or microorganism extracts, metabolites, sugars, fats or oils, microorganisms such as viruses, bacteria, fungi, etc. In a preferred embodiment the biological compound comprises or consists of one or more microorganisms, or one or more plant extracts or volatiles (e.g. plant headspace compositions). The microorganisms are preferably selected from the group consisting of: bacteria, fungi, mycorrhizae, nematodes and/or viruses. It is especially preferred and evident that the microorganisms are non-pathogenic to plants, or at least to the plant species used in the method. Especially preferred are bacteria which are non-pathogenic root colonizing bacteria and/or fungi, such as Mycorrhizae. Mixtures of two, tree or more compounds may also be applied to start with, and a mixture which shows an effect on priming can then be separated into components which are retested in the method. Using mixtures, also synergistically acting compounds can be identified, i.e. compounds which provide a stronger priming effect together than the sum of their individual priming effect. Preferably compositions are liquid or solid (e.g. powders) and can be applied to the soil, seeds or seedlings or to the aerial parts of the plant.
In another embodiment in the method for obtaining a biological or chemical compound, the quantification of the mRNA expression profile can be carried out with at least 2 genes or genes comprising at least 70% nucleic acid identity with the genes in Table 3 or Table 4 or Table 5 or Table 6 or Table 7 and/or with at least 2 genes or genes comprising at least 70% nucleic acid identity with the genes in Table 8 or Table 9 or Table 10 or Table 11 or Table 12 or Table 13 or Table 14 or Table 15 or Table 16 or Table 17 or Table 18 or Table 19 or Table 20 or Table 21.
In yet another embodiment, in the method for obtaining a biological or chemical compound, the quantification of the mRNA expression profile can be carried out with at least two genes or genes comprising at least 70% nucleic acid identity with the genes that have been identified in the coexpression networks of both the HV110 and the HV112 hybrids with respect to control line 115 (genes that were significantly upregulated by at least 2.0 fold, as indicated above).
In even yet another embodiment, in the method for obtaining a biological or chemical compound, the quantification of the mRNA expression profile can be carried out with at least two genes or genes comprising at least 70% nucleic acid identity with the genes that have been found to be significantly upregulated in HV110 or HV112 vs control line 115 using the agilent (at least 1.5 fold) or combimatrix (at least 2.0 fold) array and that are involved in mitochondria, translation or chloroplasts (as indicated above).
In an even further embodiment in the method for obtaining a biological or chemical compound, quantification of the mRNA expression profile can be carried out with at least two genes or genes comprising at least 70% nucleic acid identity with the genes that have been found to be significantly upregulated (at least 2.0 fold) in both HV110 and HV112 vs control line 115 and that are involved in mitochondria, translation or chloroplasts (as indicated above).
In another embodiment, in the method for obtaining a biological or chemical compound, quantification of the mRNA expression profile can be carried out with the above described genes that have been found to be significantly upregulated with respect to the control line by at least 2.0 fold, by at least 3.0 fold, by at least 4.0 fold, by at least 5.0 fold, by at least 10 fold, or by at least 25 fold (i.e. wherein the fold change in expression is equal to or higher than 2.0, 3.0, 4.0, 5.0, 10 or 25 respectively) and/or that have been found to be significantly downregulated by at least 1.5 fold, by at least 2.0 fold, or by at least 2.5 fold (i.e. wherein the fold change in expression is equal to or below 0.6667, 0.5 or 0.4 respectively).
In yet another embodiment the invention provides a gene expression profile indicative for high energy use efficiency in plants comprises the expression level of at least two genes from Table 1 or genes comprising at least 70% nucleic acid identity with the genes in Table 1 and/or at least 2 genes from Table 2 or genes comprising at least 70% nucleic acid identity with the genes in Table 2 and/or of at least two genes from Tables 25-28 (SEQ ID NO 147-353) or genes comprising at least 70% nucleic acid identity with the genes in Tables 25-28. In a particular embodiment the gene expression profile consists of at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes or member genes with at least 70% nucleotide sequence identity selected from Table 1 and/or at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes from Table 2 or member genes with at least 70% nucleotide sequence identity and/or 2 and/or of at least two genes from Tables 25-28 or genes comprising at least 70% nucleic acid identity with the genes in Tables 25-28. In another particular embodiment the gene expression profile indicative for high energy use efficiency comprises the expression level of at least 2 genes or genes comprising at least 70% nucleic acid identity with the genes in Table 3 or Table 4 or Table 5 or Table 6 or Table 7 and/or with at least 2 genes or genes comprising at least 70% nucleic acid identity with the genes in Table 8 or Table 9 or Table 10 or Table 11 or Table 12 or Table 13 or Table 14 or Table 15 or Table 16 or Table 17 or Table 18 or Table 19 or Table 20 or Table 21. In yet another embodiment, the gene expression profile consists of at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes or member genes with at least 70% nucleotide sequence identity with the genes that have been identified in the coexpression networks of both the HV110 and the HV112 hybrids with respect to control line 115 (genes that were significantly upregulated by at least 2.0 fold, as indicated above). In even yet another embodiment, the gene expression profile consists of at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes or member genes with at least 70% nucleotide sequence identity with the genes that have been found to be significantly upregulated in HV110 or HV112 vs control line 115 using the agilent (at least 1.5 fold) or combimatrix (at least 2.0 fold) array and that are involved in mitochondria, translation or chloroplasts (as indicated above). In an even further embodiment, the gene expression profile consists of at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 member genes or member genes with at least 70% nucleotide sequence identity with the genes that have been found to be significantly upregulated (at least 2.0 fold) in both HV110 and HV112 vs control line 115 and that are involved in mitochondria, translation or chloroplasts (as indicated above).
In another embodiment, the gene expression profile consists of the above described genes that have been found to be significantly upregulated with respect to the control line by at least 1.5 fold, by at least 2.0 fold, by at least 3.0 fold, by at least 4.0 fold, by at least 5.0 fold, by at least 10 fold, or by at least 25 fold (i.e. wherein the fold change in expression is equal to or higher than 2.0, 3.0, 4.0, 5.0, 10 or 25 respectively) and/or that have been found to be significantly downregulated by at least 1.5 fold, by at least 2.0 fold, or by at least 2.5 fold (i.e. wherein the fold change in expression is equal to or below 0.6667, 0.5 or 0.4 respectively).
In another embodiment the herein before defined gene expression profile is used for the production of a plant with a high energy use efficiency according to the methods described herein.
In yet another embodiment the gene expression profile is used in the method for obtaining a biological or chemical compound which is capable of generating a plant with a high energy use efficiency.
The following non-limiting Examples describe methods and means according to the invention. Unless stated otherwise in the Examples, all techniques are carried out according to protocols standard in the art.
Selection of B. napus plants with high energy use efficiency (EUE) and low energy use efficiency (EUE) and yield was performed as described in Hauben et al. (2009) Proc Natl Acad Sci USA November 24; 106(47):20109-14 and in the examples 1 and 2 of the priority application EP09075284 (filed on 1 Jul., 2009), both of which references are incorporated herein by reference.
In short, starting with these selected individual plants with high or low EUE we performed multiple cycles of self-crossing and selection for EUE for the production of isogenic clones. Seeds of the low-EUE clone and the high-EUE clone were up-scaled. As described in Example 2 of the priority application EP09075284 (filed on 1 Jul., 2009) and schematically depicted in FIG. 9 in EP09075284, hereby incorporated by reference, B. napus hybrids were generated with elite parental lines of canola which were selected for high EUE. Two high EUE B. napus hybrid were generated and designated as HV110 and HV112.
We showed that stress testing in growth chambers and the greenhouse revealed that high-EUE B. napus plants have an enhanced tolerance to ozone (4 days, 400 ppb) and heat (10 days, 45° C.) compared with a control B. napus plant (Variety “Simon”) and compared with low-EUE plants. In field trials of three subsequent years it could be demonstrated that these high-EUE plants yield ˜8% higher (kg seeds/ha) than control plants, while these low-EUE plants yield ˜10% less than control plants. In fields with moderate drought stress, the line with the highest EUE had a 20% higher yield than that of the control, while the seed yield of the line with the highest respiration and lowest EUE dropped by 20%.
The transcriptome of the high-EUE B. napus (also designated as the high vigor hybrid line HV110), showing lower respiration levels, was compared to the transcriptome of the B. napus control hybrid line (also designated as B. napus control line 115). This transcriptome analysis was carried out because it was shown that the genome of line HV110 has a decrease in global methylation, which pointed out to an effect on transcription of genes.
Leaf 4 was harvested from four trays, each containing 4 to 5 plants from line HV110 and control line 115. RNA was isolated from individual leafs and used in a pilot cDNA-AFLP experiment, which indicated differences on the transcript level between the HV110 and control line. For each line (3 replicas/line), RNA from leafs harvested from the same tray was pooled, resulting in 3 samples/line for hybridization to microarrays.
In the experiments we used the commercially available 44K array developed by Agilent. This 44K array is a transcriptome-wide Brassica napus microarray. One slide contains 4 identical 44K microarrays. Each microarrays contains 43,803 probes sourced from RefSeq, UniGene, TIGR Plant TA and TIGR Gene Indices.
As an RNA source for hybridization 3 replicas/line were used. The quality report showed an increase in number of signals above background based on absent/present calls. The percentage of probes with a signal above background was 70.26%.
With the microarray 44K data, probe filtering was followed by quantile normalization. Based on P/A calls, the intensities for 27,297 probes were retained and after removal of duplicated probes we ended up with intensities for 26,851 probes. Limma and qvalue packages for R Bioconducter were used for further analysis. Pairwise comparison (t-test) resulted in 865 transcripts with a p value lower than 0.001. After correction for false discovery, we found 174 transcripts to be significantly differential between line HV110 and the control line 115.
Out of 174 differential B. napus transcripts, 61 transcripts are at least more than 0.66 fold down-regulated and 73 transcripts are at least more than 1.5 times up-regulated in the HV110 line. Table 1 depicts the list of genes which are at least 0.66 fold downregulated. Table 2 depicts the list of genes which are at least 1.5 times upregulated.
Chlamydomonas results in disruption of
thaliana] (TAIR: AT1G29640.1)
Subsequently, we used the lists of up- and down-regulated genes (Table I depicts the genes that are at least 0.66 times downregulated in HV110 with respect to the control hybrid line 115, Table II depicts the genes that are at least 1.5 times upregulated in HV110 with respect to the control hybrid line 115) that are differentially expressed in the HV110 line as input list for the web tool CORNET (http://bioinformatics.psb.ugent.be/cornet/). With this tool, co-expression patterns can be visualized. This co-expression is defined by calculating the Pearson correlation between gene expression profiles using precompiled publically available microarray gene expression data sets.
The input list for CORNET after removal of doubles or Brassica IDs without an Arabidopsis homolog is 56 AGI (Arabidopsis Genome Initiative) codes. For 8 AGI codes no reliable probe sets were found according to the CDF file used by CORNET, which results in an input list of 48 AGI codes. The selected arrays (1488 exp in total) include arrays from abiotic stress (256 exp), AtGenExpress All (425 exp), development (135 exp), hormone treatment (140 exp), microarray compendium 2 (111 exp—no bias), stress (abiotic+biotic) (336 exp) and whole plant (85 exp). The selected databases for identification of protein-protein interaction include the Bar, IntAct and TAIR databases. We identified two networks with a Pearson correlation coefficient higher than 0.75. These networks are depicted in Tables 3 and 4.
We identified two networks with a Pearson correlation coefficient >0.8. These networks are depicted in Tables 5 and 6.
We identified one network with a Pearson correlation coefficient >0.9. This network is depicted in Table 7.
3.2 Transcription Networks for upregulated Genes
The input list for CORNET after removal of doubles or Brassica IDs without an Arabidopsis homolog is 65 AGI codes. For 11 AGI codes no reliable probe sets were found according to the CDF file used by CORNET, which results in an input list of 54 AGI codes. The selected arrays (1488 exp in total) include arrays from abiotic stress (256 exp), AtGenExpress All (425 exp), development (135 exp), hormone treatment (140 exp), microarray compendium 2 (111 exp—no bias), stress (abiotic+biotic) (336 exp) and whole plant (85 exp). The selected databases for identification of protein-protein interaction include the Bar, IntAct and TAIR databases.
We identified five network with a Pearson correlation coefficient higher than 0.70. These networks are depicted in Tables 8, 9, 10 and 11.
We identified four networks with a Pearson correlation coefficient >0.75.
We identified three networks with a Pearson correlation coefficient >0.80. These networks are depicted in Tables 16, 17 and 18.
We identified three networks with a Pearson correlation coefficient >0.90. These networks are depicted in Tables 19, 20 and 21.
RNA was extracted from the same leaf material used for transcript profiling as described in Example 2 to characterize expression characteristics of 4 genes. Specifically, 4 genes were selected from Table 2, i.e. the list of transcripts which are upregulated in the high vigor hybrid line HV110. These four genes, which are depicted in Table 22, encode subunits of the mitochondrial respiratory chain.
First-strand cDNA was prepared from 2.5 mg of total RNA, Superscript II RNaseH Reverse Transcriptase (Invitrogen) and a oligo(dT) 15 primer. Five microliters of a 1:12 diluted first-strand cDNA was used as a template in the subsequent PCR, which was performed on the iCycler iQ (BioRad, Hercules, Calif.) with 200 nM primers and Platinum SYBR green Supermix-UGD (2′) (Invitrogen) in a final volume of 25 ml per reaction, according to manufacturer's instructions. All PCRs were performed at least in triplicate. For each of the selected transcripts, the sequence of the Brassica napus cDNA or EST was used to design gene-specific primers with the Beacon Designer™ software. Two housekeeping genes (BAR and polypyrimidine tract binding protein (PTBP)) were used for normalization of the data.
Brassica napus BNZB Brassica
napus cDNA 5′, mRNA sequence
Gene-specific primers used to quantify six selected transcripts are depicted in table 23.
Table 24 shows the difference in expression level for the 4 genes between the high vigor hybrid line HV110 and the control hybrid line 115.
The transcriptomes of two high-EUE B. napus (also designated as the high vigor hybrid lines (HV110 and HV112), showing lower respiration levels, were compared to the transcriptome of the B. napus control hybrid line (also designated as B. napus control line 115).
Leaf 3 was harvested from five trays, each containing 4 to 5 plants from line HV110, HV112 and control line 115. For each line (3 replicas/line), RNA was isolated from leafs harvested from different trays and pooled, resulting in 3 samples/line for hybridization to microarrays.
The analysis was performed on a high density CombiMatrix 90K Brassica oligonucleotide array produced by the Plant Functional Genomics Center at the University of Verona. The estimated genome coverage of this array is 65% based on homology with Arabidopsis thaliana. This microarray contains 90,500 probes sourced from EST generated by the Brassica Genomics consortium (http://brassicagenomics.ca/ests/).
As an RNA source for hybridization 3 replicas/line were used. Probe filtering was followed by quantile normalization. The intensities for 55,994 probes were retained. Limma and qvalue packages for R Bioconducter were used for further analysis. Pairwise comparison (t-test) resulted in 603 transcripts with a q value lower than 0.05 between line HV110 and the control line 115 and 655 transcripts significantly differential between line HV112 and the control line 115.
Out of the 603 differential transcripts between line HV110 and control line 115, 582 are at least more than 2 fold upregulated and 21 are at least 2 fold downregulated. Out of the 655 transcripts differential between line HV112 and control line 115, 624 are at least 2 fold upregulated and 31 are at least 2 fold down-regulated.
The lists of 2 fold upregulated transcripts in line HV110 and line HV112 were used to build transcriptional networks. The input list for CORNET after removal of doubles or Brassica IDs without an Arabidopsis homolog for line HV110 is 485 AGI codes. For 55 AGI codes no reliable probe sets were found according to the CDF file used by CORNET, which results in an input list of 430 AGI codes. The selected experiments (1488 in total) include arrays from abiotic stress (256 exp), AtGenExpress All (425 exp), development (135 exp), hormone treatment (140 exp), microarray compendium 2 (111 exp—no bias), stress (abiotic+biotic) (336 exp) and whole plant (85 exp). The selected databases for identification of protein-protein interaction include the Bar, IntAct and TAIR databases. We can identify several networks with a Pearson correlation coefficient higher than 0.80. In the largest network, we can identify a cluster of coregulated genes enriched in mitochondrial genes linked to genes involved in translation. Another cluster of coregulated genes from the largest network is enriched in chloroplast-located proteins.
The input list for CORNET after removal of doubles or Brassica IDs without an Arabidopsis homolog for line HV112 is 514 AGI codes. For 63 AGI codes no reliable probe sets were found according to the CDF file used by CORNET, which results in an input list of 451 AGI codes. The selected experiments (1488 in total) include arrays from abiotic stress (256 exp), AtGenExpress All (425 exp), development (135 exp), hormone treatment (140 exp), microarray compendium 2 (111 exp—no bias), stress (abiotic+biotic) (336 exp) and whole plant (85 exp). The selected databases for identification of protein-protein interaction include the Bar, IntAct and TAIR databases. We can identify several networks with a Pearson correlation coefficient higher than 0.80. In the largest network, we can again identify a cluster of coregulated genes enriched in mitochondrial genes linked to genes involved in translation. Another cluster of coregulated genes from the largest network is enriched in chloroplast-located proteins.
thaliana Ras Associated with
thaliana RNA polymerase II
thaliana Glutathione S-
| Number | Date | Country | Kind |
|---|---|---|---|
| 10075588.3 | Oct 2010 | EP | regional |
| 10075750.9 | Dec 2010 | EP | regional |
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/EP2011/004858 | 9/26/2011 | WO | 00 | 3/27/2013 |
| Number | Date | Country | |
|---|---|---|---|
| 61388366 | Sep 2010 | US | |
| 61419022 | Dec 2010 | US |
