Mapping of Quantitative Trait Loci

Abstract

The genomic region associated with the expression of a quantitative trait is referred to as quantitative trait locus (QTL), which may contain one or more genes. QTLs have been grouped into different categories on the basis of their effect size, the effect of environment on their expression, and the manner of their action. QTL mapping is generally based on biparental populations in which the marker genotype and trait phenotype data are analyzed to detect association between the two. A large number of QTL analysis approaches have been proposed based on regression analysis, maximum likelihood parameter estimation, or Bayesian models. Single QTL mapping methods detect single QTL at a time. Multiple QTL mapping combines multiple regression analysis with simple interval mapping to include all the significant QTLs in the genetic model. Composite interval mapping can be extended to deal with data coming from multiple cross populations and for joint analysis of multiple traits. Appropriate experimental designs and QTL analysis methods are available for the detection and estimation of QTL x QTL and QTL x environment interactions. Confirmation of QTL analysis results, i.e., QTL validation, consists of confirmation of marker-QTL association and QTL position in unrelated germplasm and the assessment of effects of the genetic background on QTL expression. Homozygous lines derived from near-isogenic lines (NILs) and intercross recombinant inbred lines have been used for fine mapping of QTL regions. QTL meta-analysis attempts to integrate the results from different QTL studies to determine the “actual” number of QTLs affecting a trait and to reduce the QTL confidence intervals. QTL mapping identifies markers flanking the QTL regions, which can be used for marker-assisted selection in breeding programs. The findings from QTL mapping studies are affected by several factors like genetic properties of QTL, genetic background, size of mapping population, and effect of environment and experimental error.