Methodologies for segregation analysis and QTL mapping in plants.
Most characters of biological interest and economic importance are quantitative traits. To uncover the genetic architecture of quantitative traits, two approaches have become popular in China. One is the establishment of an analytical model for mixed major-gene plus polygenes inheritance and the other the discovery of quantitative trait locus (QTL). Here we review our progress employing these two approaches. First, we proposed joint segregation analysis of multiple generations for mixed major-gene plus polygenes inheritance. Second, we extended the multilocus method of Lander and Green (1987), Jiang and Zeng (1997) to a more generalized approach. Our methodology handles distorted, dominant and missing markers, including the effect of linked segregation distortion loci on the estimation of map distance. Finally, we developed several QTL mapping methods. In the Bayesian shrinkage estimation (BSE) method, we suggested a method to test the significance of QTL effects and studied the effect of the prior distribution of the variance of QTL effect on QTL mapping. To reduce running time, a penalized maximum likelihood method was adopted. To mine novel genes in crop inbred lines generated in the course of normal crop breeding work, three methods were introduced. If a well-documented genealogical history of the lines is available, two-stage variance component analysis and multi-QTL Haseman-Elston regression were suggested; if unavailable, multiple loci in silico mapping was proposed.
Zhang
Yuan-Ming
YM
Section on Statistical Genomics, State Key Laboratory of Crop Genetics and Germplasm Enhancement and National Center for Soybean Improvement, College of Agriculture, Nanjing Agricultural University, Nanjing, 210095, China. soyzhang@njau.edu.cn
Gai
Junyi
J
D002874:Chromosome Mapping / Q000379:methods*; D005799:Genes, Dominant; D017343:Genes, Plant; D005819:Genetic Markers; D006801:Humans; D010944:Plants / Q000235:genetics*; D040641:Quantitative Trait Loci
D005819:Genetic Markers