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 (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:We performed DNase-seq on 7-day-old seedlings from four A. thaliana accessions: Bur-0, Tsu-0, Bay-0, Est-1 using INTACT constructs (Deal and Henikoff, Developmental Cell, 2010) driven by the UBQ10 promoter. Chromatin accessibility profiling (Dnase I-seq) of 7-day-old seedlings of A. thaliana accessions: Bur-0, Tsu-0, Bay-0 & Est-1 grown in LD conditions (16hr light 22°C, 8hr dark 20°C).
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
Project description:Due to difficulties inherent in designating conservation units for effective species management and conservation, the use of multiple complementary sources of information is required to identify and assess the designation of conservation units based on the degree of variation among populations within a species. In this study, we combined estimates of microsatellite and transcriptomic variation to assess the population structure and potential for adaptive variation of threatened Atlantic salmon, Salmo salar, among rivers in the Bay of Fundy. In general, population structure identified by genetic differentiation was consistent with the patterns of variation in gene expression. Both data sets provided clear indication of strong regional differentiation between rivers located within the inner Bay of Fundy relative to rivers located within the outer Bay of Fundy or the Southern Uplands region. There was also support for more refined population structure; there was some differentiation in both microsatellite and gene expression patterns between salmon from rivers in the two regions of the inner Bay of Fundy: Chignecto Bay and Minas Basin. Consistent patterns apparent in the genetic and transcriptomic dataset indicate that Atlantic salmon populations from the inner and outer Bay of Fundy reflect unique genetic lineages, with some evidence of unique genetic legacies between regions of the inner Bay of Fundy, and even between individual rivers within a region. Consistency of the microarray data across two years helps to validate the use of this technique as a useful tool in assessment of variation among wild populations for species conservation.
Project description:Due to difficulties inherent in designating conservation units for effective species management and conservation, the use of multiple complementary sources of information is required to identify and assess the designation of conservation units based on the degree of variation among populations within a species. In this study, we combined estimates of microsatellite and transcriptomic variation to assess the population structure and potential for adaptive variation of threatened Atlantic salmon, Salmo salar, among rivers in the Bay of Fundy. In general, population structure identified by genetic differentiation was consistent with the patterns of variation in gene expression. Both data sets provided clear indication of strong regional differentiation between rivers located within the inner Bay of Fundy relative to rivers located within the outer Bay of Fundy or the Southern Uplands region. There was also support for more refined population structure; there was some differentiation in both microsatellite and gene expression patterns between salmon from rivers in the two regions of the inner Bay of Fundy: Chignecto Bay and Minas Basin. Consistent patterns apparent in the genetic and transcriptomic dataset indicate that Atlantic salmon populations from the inner and outer Bay of Fundy reflect unique genetic lineages, with some evidence of unique genetic legacies between regions of the inner Bay of Fundy, and even between individual rivers within a region. Consistency of the microarray data across two years helps to validate the use of this technique as a useful tool in assessment of variation among wild populations for species conservation.