E-TABM-61 - Transcription profiling by array of Arabidopsis treated with surfactant 0.02% Silwet L77 for different amounts of time
Released on 1 January 2007, last updated on 1 August 2014
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.
transcription profiling by array, compound treatment, strain or line, time series
Dina St. Clair <firstname.lastname@example.org>, Alexander Kozik, Daniel J. Kliebenstein, Dina A. St Clair, Hans van Leeuwen, Marilyn A.L. West, R W. Doerge, Richard W. Michelmore
High-density haplotyping with microarray-based expression and single feature polymorphism markers in Arabidopsis. Marilyn A.L. West; Hans van Leeuwen; Alexander Kozik; Daniel J. Kliebenstein; R. W. Doerge; Dina A. St.Clair; Richard W. Michelmore. , Europe PMC 16702412