Title: "Part 1: Functional Genomics of Quantitative Traits: Expression Level Polymorphisms of QTLs Affecting Disease Resistance Pathways in Arabidopsis"

Speaker: R.W. Doerge
Place: Krannert (KRAN) G016; September 12, 2006; Tuesday, 4:30pm


This is a two part lecture dealing with the identification of expression quantitative trait loci (eQTL). The first lecture will set the stage for the second lecture by introducing the general ideas, history, and statistical concepts underlying the location of quantitative trait loci (QTL; regions of any genome associated with a disease or complex trait). The second lecture will introduce novel concepts of combining QTL methodology with microarray technology for the purpose of locating eQTL.

There is increasing interest in understanding the molecular basis of complex traits. Initially, the genetic dissection of quantitative traits involved measurements of gross phenotypes. Most recently, the underlying mechanisms of inheritance have been studied through various approaches that are supported by modern technological and methodological advances, namely quantitative trait locus/loci (QTL) analysis in genetics and gene expression analysis in genomics. Since different technologies and approaches focus on specific pieces of a larger, poorly understood biological system, the challenge is to integrate these different types of information to elucidate the genetic architecture of complex traits. To address one of these challenges we have combined QTL analysis with microarray analysis to characterize the genomic architecture that controls quantitative traits. Using Affymetrix technology and 211 biologically replicated (RIL) individuals from a segregating Arabidopsis population, the transcript variation (i.e., expression level polymorphisms, ELPs) of 22,810 genes, in both control and treatment conditions, provide data for mapping expression QTL (eQTL). Results from our statistical analysis of the entire genome reveal both cis- and trans-eQTL under control conditions. The statistical methodology developed for this type of analysis will be presented for a directed analysis of SA-inducible secretory genes controlled by NPR1. ***This work is funded by NSF Arabidopsis 2010 in collaboration with Drs. Marilyn West, Hans van Leeuwen, Richard Michelmore, and Dina St.Clair University of California, Plant Sciences Dept, Davis CA, and Ms. Kyunga Kim and Mr. Riyan Cheng Purdue University, Department of Statistics, West Lafayette, IN.***

Click here for a full schedule of BIOINFORMATICS SEMINARS, past and present.