QTL Identification

Abstract

Many important agronomic traits, such as crop yield and stress tolerance, are controlled by polygenes, each with subtle effects and influenced by the environment. Such characteristics are referred to as quantitative traits and the segregating loci as quantitative trait loci (QTLs). As quantitative traits do not segregate into discrete classes, one cannot use standard Mendelian genetic practices to study them. In the past 30 years, a new approach to understanding the genetics of quantitative traits has developed, using molecular linkage maps and populations with linkage disequilibrium. To map and tag a QTL, one needs a segregating population(s) in which linkage disequilibrium exists, a set of molecular markers, and statistical tools. Many plant species are ideally suited for quantitative trait analysis because they have short generation times and many progeny, and controlled crosses can be made in which linkage disequilibrium is known. Annual, self-pollinated species (e.g., Rice, Arabidopsis, Tomato) are best suited for QTL studies. More problematic things are outcrossing perennial species (e.g., many tree species and most animal species), in which controlled crosses are either not possible or impractical, and generation times are longer. New methods (often referred to as association genetics) are emerging that allow researchers to locate and characterize QTLs in natural populations using empirical knowledge of linkage disequilibrium and high-throughput DNA marker analysis. The importance of meta-quantitative trait loci (MQTLs) is increasing because of their role in identifying genes linked to QTL regions. They also aid marker-assisted selection (MAS) in association with statistical analyses. Recently, integrated data for use in meta-analyses of QTLs have become available in plant genome databases and have been analyzed using QTL/microarray, expression-QTL (eQTL), and MQTL methods. In this section, the requirements and methods for identifying and characterizing QTLs using the traditional approach of controlled crosses will be discussed. The information on QTL mapping will be used in MAS in plant breeding. We also discuss the current status of MQTL research and describe the general procedures using a case study to identify MQTL genes related to abiotic stresses in rice.