Functional Genomics of Quantitative Traits
We are using Arabidopsis thaliana and a novel combination of functional genomics, statistics, QTL analysis and molecular genetics to explore quantitative differences in the expression of genes involved in resistance to pathogens and that respond to induction by salicylic acid. We are using microarrays to evaluate the differential expression of genes induced by this chemical in a genetically segregating recombinant inbred line (RIL) population and identifying expression level polymorphisms (ELPs, quantitative differences in gene expression). The ELPs are being mapped as expression QTLs (eQTLs) to identify regulatory loci controlling natural variation in gene expression patterns; individual genes will be targeted for further molecular characterization. This project capitalizes on the wide array of genetic tools available in Arabidopsis, including whole-genome microarrays (Affymetrix ATH1 GeneChips) for expression analysis and a fully sequenced genome.
- Our simulation studies of a RIL population subjected to microarray analysis indicated that some of the existing QTL mapping methods will detect eQTLs for ELPs, but there is a limit to their power, suggesting the need for advanced statistical approaches (publication).
- In a factorial experiment, we used GeneChips to evaluate gene expression of seven diverse accessions of Arabidopsis subjected to two treatments (salicylic acid and control) and sampled at three time points. We detected ELPs among the accessions for several thousand genes; this variation in gene expression was associated with sequence diversity across the chromosomes (publication).
- We have used our recently generated GeneChip data from 148 RILs to derive two types of genetic markers, single-feature polymorphism (SFP) markers and gene expression markers (GEMs) and obtain robust high-density haplotypes and linkage maps (publication).
- A statistical approach capable of assessing higher-order a priori defined gene network responses was tested on our GeneChip data from 148 control treated RILs. This analysis detected significant network variation between Arabidopsis accessions Bay-0 and Shahdara, and we were able to identify eQTLs controlling network responses for 18 out of 20 a priori defined gene networks in the Bay-0 x Sha RILs (publication).
- GeneChip data for 211 RILs that were subjected to two treatments (salicylic acid and control) in a large replicated factorial experiment is being used to map eQTLs for ELPs. Under the control treatment, eQTLs were mapped for 69% of the transcripts/e-traits measured on the microarrays. One-third of the quantitatively controlled e-traits were regulated by cis-eQTLs, and many trans-eQTLs mapped to hotspots controlling hundreds to thousands of e-traits (publication).