E-TABM-126 - Transcription profiling of 211 Arabidopsis recombinant inbred lines treated with Silwet solution to identify regulatory quantitative trait loci

Status
Released on 11 April 2007, last updated on 2 May 2014
Organism
Arabidopsis thaliana
Samples (422)
Array (1)
Protocols (9)
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. We present Affymetrix GeneChip microarray expression data for 2 biological replications of the control (Silwet) samples for 63 RILs, plus replicated Bay-0 and Sha control samples grown at the same time as the RILs. These GeneChips representing 63 RILs, along with the GeneChips in Accession E-TABM-62 which represent an additional 148 RILs, form a 211 RIL dataset from which we mapped eQTLs.
Experiment types
transcription profiling by array, compound treatment, strain or line
Contact
Citations
Global eQTL Mapping Reveals the Complex Genetic Architecture of Transcript Level Variation in Arabidopsis. Marilyn A.L. West, Kyunga Kim, Daniel J. Kliebenstein, Hans van Leeuwen, Richard W. Michelmore, R.W. Doerge, Dina A. St.Clair.
Linking metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways. Wentzell AM, Rowe HC, Hansen BG, Ticconi C, Halkier BA, Kliebenstein DJ. :1687-1701 (2007), Europe PMC 17941713
MIAME
PlatformsProtocolsVariablesProcessedRaw
Files
Investigation descriptionE-TABM-126.idf.txt
Sample and data relationshipE-TABM-126.sdrf.txt
Processed data (1)E-TABM-126.processed.1.zip
Array designA-AFFY-2.adf.txt
Links