QTL Analysis and Genetic Architecture of Complex Traits

Abstract

The essence of quantitative genetics is to understand the genetic basis and architecture of quantitative trait variation within and between populations. With the availability of dense genome-wide molecular markers, it is now possible to map many biologically or medically important quantitative trait loci (QTL) into genome positions for further study. Early study in QTL mapping analysis was mainly concerned with accurate and robust localization of individual QTL. More recently, research (at least in experimental populations) has been shifted to the inference of overall genetic architecture of complex traits, which may include the number, positions, effects, interaction and pleiotropy of QTL. Statistically, there are many challenges for this inference and for the justification of inferred genetic structure. The talk will be concentrated on the recent development of statistical methodology to infer the genetic architecture of complex traits, particularly on multiple traits in multiple environments. A few mapping examples in Drosophila and maize will be used to illustrate capabilities and also limitations of the current methodology. The talk will also briefly discuss the connection of QTL mapping analysis with microarray gene expression data for the inference of gene expression regulatory structure.