Project description:Understanding how DNA sequence variation is translated into variation for complex phenotypes has remained elusive, but is essential for predicting adaptive evolution, selecting agriculturally important animals and crops, and personalized medicine. Here, we quantified genome-wide genetic variation in gene expression in the sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel. We found that a substantial fraction of the Drosophila transcriptome is genetically variable and organized into modules of genetically correlated transcripts, which provide functional context for newly identified novel transcribed regions. We identified regulatory variants for the mean and variance of gene expression, both of which showed oligogenic genetic architecture. Expression quantitative trait loci the mean, but not the variance, of gene expression were concentrated near genes. This comprehensive characterization of transcriptomic diversity and its genetic basis in the DGRP is critically important for a systems understanding of quantitative trait variation.
Project description:The study of natural genetic variation for plant disease resistance responses is a complementary approach to utilizing mutants to elucidate genetic pathways. While some key genes involved in pathways controlling disease resistance, and signaling intermediates such as salicylic acid (SA) and jasmonic acid (JA), have been identified through mutational analyses, the use of genetic variation in natural populations permits the identification of change-of-function alleles, which likely act in a quantitative manner. Whole genome microarrays, such as Affymetrix GeneChips, allow for molecular characterization of the disease response at a genomics level and characterization of differences in gene expression due to natural variation. Differences in the level of gene expression, or expression level polymorphisms (ELPs), can be mapped in a segregating population to identify regulatory quantitative trait loci (expression QTLs, e-QTLs) affecting host resistance responses. We assessed Arabidopsis accessions Bayreuth-0 (Bay-0) and Shahdara (Sha) for natural variation in the response to JA. We treated vegetatively grown plants with either JA or a control solution (Silwet), and harvested the plants 4, 28, or 52 hours after chemical treatment. We present Affymetrix GeneChip microarray expression data for 2 biological replications of the control (Silwet) samples for Bay-0 and Sha. These GeneChips were used to generate genetic markers which allowed the development of high-density haplotype maps of a Bay-0 x Sha RIL population.
Project description:The study of natural genetic variation for plant disease resistance responses is a complementary approach to utilizing mutants to elucidate genetic pathways. While some key genes involved in pathways controlling disease resistance, and signaling intermediates such as salicylic acid (SA) and jasmonic acid (JA), have been identified through mutational analyses, the use of genetic variation in natural populations permits the identification of change-of-function alleles, which likely act in a quantitative manner. Whole genome microarrays, such as Affymetrix GeneChips, allow for molecular characterization of the disease response at a genomics level and characterization of differences in gene expression due to natural variation. Differences in the level of gene expression, or expression level polymorphisms (ELPs), can be mapped in a segregating population to identify regulatory quantitative trait loci (expression QTLs, e-QTLs) affecting host resistance responses. We assessed Arabidopsis accessions Bayreuth-0 (Bay-0) and Shahdara (Sha) for natural variation in the response to SA. We treated vegetatively grown plants with either SA or a control solution (Silwet), and harvested the plants 4, 28, or 52 hours after chemical treatment. We present Affymetrix GeneChip microarray expression data for 2 biological replications of the control (Silwet) samples for Bay-0 and Sha. These GeneChips were used to generate genetic markers which allowed the development of high-density haplotype maps of a Bay-0 x Sha RIL population.
Project description:The study of natural genetic variation for plant disease resistance responses is a complementary approach to utilizing mutants to elucidate genetic pathways. While some key genes involved in pathways controlling disease resistance, and signaling intermediates such as salicylic acid and jasmonic acid, have been identified through mutational analyses, the use of genetic variation in natural populations permits the identification of change-of-function alleles, which likely act in a quantitative manner. Whole genome microarrays, such as Affymetrix GeneChips, allow for molecular characterization of the disease response at a genomics level and characterization of differences in gene expression due to natural variation. Differences in the level of gene expression, or expression level polymorphisms (ELPs), can be mapped in a segregating population to identify regulatory quantitative trait loci (expression QTLs) affecting host resistance responses. In order to identify an appropriate RIL population to map QTL controlling disease resistance responses, we performed a parental survey of 7 different Arabidopsis accessions. We treated vegetatively grown plants with either salicylic acid or a control solution, and harvested the plants at 3 different time points after chemical treatment. We present Affymetrix GeneChip microarray expression data for 3 biological replications of this parental survey
Project description:Soybean is a self-pollinating crop species that has relatively low nucleotide polymorphism rates compared to other crop plant species. Despite the appearance of a low intervarietal nucleotide polymorphism rate, a wide range of heritable phenotypic variation exists. There is even evidence for heritable phenotypic variation among individuals within some varieties. ‘Williams 82,’ the soybean variety used to produce the reference genome sequence, was derived from backcrossing a phytophthora root rot resistance locus from the donor parent ‘Kingwa’ into the recurrent parent ‘Williams.’ To explore the genetic basis of intravarietal variation, we investigated the nucleotide, structural and gene content variation of different Williams 82 individuals. Williams 82 individuals exhibited variation in the number and size of introgressed Kingwa loci. In these regions of genomic heterogeneity, the reference Williams 82 genome sequence consists of a mosaic of Williams and Kingwa haplotypes. Genomic structural variation between Williams and Kingwa was maintained between the Williams 82 individuals within the regions of heterogeneity. Additionally, the regions of heterogeneity exhibited gene content differences between Williams 82 individuals. Collectively, these findings show that genetic heterogeneity in Williams 82 primarily originated from the differential segregation of polymorphic chromosomal regions following the backcross and single-seed descent generations of the breeding process. We conclude that soybean haplotypes can possess a high rate of structural and gene content variation, and the impact of intravarietal genetic heterogeneity may be much greater than previously assumed. This detailed characterization will be useful for interpreting soybean genomic data sets and highlights important considerations for research communities that are utilizing or working towards developing a reference genome sequence.
Project description:The study of natural genetic variation for plant disease resistance responses is a complementary approach to utilizing mutants to elucidate genetic pathways. While some key genes involved in pathways controlling disease resistance, and signaling intermediates such as salicylic acid (SA) and jasmonic acid (JA), have been identified through mutational analyses, the use of genetic variation in natural populations permits the identification of change-of-function alleles, which likely act in a quantitative manner. Whole genome microarrays, such as Affymetrix GeneChips, allow for molecular characterization of the disease response at a genomics level and characterization of differences in gene expression due to natural variation. Differences in the level of gene expression, or expression level polymorphisms (ELPs), can be mapped in a segregating population to identify regulatory quantitative trait loci (expression QTLs, eQTLs) affecting host resistance responses. We surveyed recombinant inbred lines (RILs) from a population derived from a cross of inbred Arabidopsis accessions Bayreuth-0 (Bay-0) and Shahdara (Sha) in order to map eQTLs controlling ELPs. We treated vegetatively grown plants with either SA or a control solution (Silwet), and harvested the plants 28 hours after chemical treatment. Here we present Affymetrix GeneChip microarray expression data for 8 biological replications of the control (Silwet) samples for Bay-0 and Sha.
Project description:The study of natural genetic variation for plant disease resistance responses is a complementary approach to utilizing mutants to elucidate genetic pathways. While some key genes involved in pathways controlling disease resistance, and signaling intermediates such as salicylic acid (SA) and jasmonic acid (JA), have been identified through mutational analyses, the use of genetic variation in natural populations permits the identification of change-of-function alleles, which likely act in a quantitative manner. Whole genome microarrays, such as Affymetrix GeneChips, allow for molecular characterization of the disease response at a genomics level and characterization of differences in gene expression due to natural variation. Differences in the level of gene expression, or expression level polymorphisms (ELPs), can be mapped in a segregating population to identify regulatory quantitative trait loci (expression QTLs, e-QTLs) affecting host resistance responses. We assessed Arabidopsis accessions Bayreuth-0 (Bay-0) and Shahdara (Sha) for natural variation in the response to SA. We treated vegetatively grown plants with either SA or a control solution (Silwet), and harvested the plants 4, 28, or 52 hours after chemical treatment. We present Affymetrix GeneChip microarray expression data for 2 biological replications of the SA-treated samples for Bay-0 and Sha. The GeneChip microarray expression data for the control (Silwet-treated) samples was submitted as E-TABM-61. Normalized data is not provided here as the normalization step was included in the data statistical analsyses - for more information please contact the experiment provider.
Project description:The study of natural genetic variation for plant disease resistance responses is a complementary approach to utilizing mutants to elucidate genetic pathways. While some key genes involved in pathways controlling disease resistance, and signaling intermediates such as salicylic acid (SA) and jasmonic acid (JA), have been identified through mutational analyses, the use of genetic variation in natural populations permits the identification of change-of-function alleles, which likely act in a quantitative manner. Whole genome microarrays, such as Affymetrix GeneChips, allow for molecular characterization of the disease response at a genomics level and characterization of differences in gene expression due to natural variation. Differences in the level of gene expression, or expression level polymorphisms (ELPs), can be mapped in a segregating population to identify regulatory quantitative trait loci (expression QTLs, e-QTLs) affecting host resistance responses. We assessed Arabidopsis accessions Bayreuth-0 (Bay-0) and Shahdara (Sha) for natural variation in the response to JA. We treated vegetatively grown plants with either JA or a control solution (Silwet), and harvested the plants 4, 28, or 52 hours after chemical treatment. We present Affymetrix GeneChip microarray expression data for 2 biological replications of the JA-treated samples for Bay-0 and Sha. The GeneChip microarray expression data for the control (Silwet) samples was submitted as E-TABM-60. Normalized data is not provided here as the normalization step was included in the data statistical analsyses - for more information please contact the experiment provider.
Project description:The study of natural genetic variation for plant disease resistance responses is a complementary approach to utilizing mutants to elucidate genetic pathways. While some key genes involved in pathways controlling disease resistance, and signaling intermediates such as salicylic acid (SA) and jasmonic acid (JA), have been identified through mutational analyses, the use of genetic variation in natural populations permits the identification of change-of-function alleles, which likely act in a quantitative manner. Whole genome microarrays, such as Affymetrix GeneChips, allow for molecular characterization of the disease response at a genomics level and characterization of differences in gene expression due to natural variation. Differences in the level of gene expression, or expression level polymorphisms (ELPs), can be mapped in a segregating population to identify regulatory quantitative trait loci (expression QTLs, e-QTLs) affecting host resistance responses. We surveyed recombinant inbred lines (RILs) from a population derived from a cross of inbred Arabidopsis accessions Bayreuth-0 (Bay-0) and Shahdara (Sha) in order to map e-QTLs controlling ELPs. We treated vegetatively grown plants with either SA or a control solution (Silwet), and harvested the plants 28 hours after chemical treatment. We present Affymetrix GeneChip microarray expression data for 2 biological replications of the control (Silwet) samples for 148 RILs, plus replicated Bay-0 and Sha control samples grown at the same time as the RILs. These GeneChips were used to develop genetic markers and derive high-density haplotypes for the RILs