摘要
Advances on methods for mapping quantitative trait loci (QTL) are firstly summarized. Then, some new methods, including mapping multiple QTL, fine mapping of QTL, and mapping QTL for dynamic traits, are mainly described. Finally, some future prospects are proposed, including how to dig novel genes in the germplasm resource, map expression QTL (eQTL) by the use of all markers, phenotypes and micro-array data, identify QTL using genetic mating designs and detect viability loci. The purpose is to direct plant geneticists to choose a suitable method in the inheritance analysis of quantitative trait and in search of novel genes in germplasm resource so that more potential genetic information can be uncovered.
Advances on methods for mapping quantitative trait loci （QTL） are firstly summarized. Then, some new methods, including mapping multiple QTL, fine mapping of QTL, and mapping QTL for dynamic traits, are mainly described. Finally, some future prospects are proposed, including how to dig novel genes in the germplasm resource, map expression QTL （eQTL） by the use of all markers, phenotypes and micro-array data, identify QTL using genetic mating designs and detect viability loci. The purpose is to direct plant geneticists to choose a suitable method in the inheritance analysis of quantitative trait and in search of novel genes in germplasm resource so that more potential genetic information can be uncovered.
基金
This work was supported by the National Natural Science Foundation of China(Grant No.30470998)
Jiangsu Natural Science Foundation(Grant No.BK2005087)
Program for Changjiang Scholars and Innovative Research Team in University,Program for New Centary Excellent Talent in University(Grant No.NCET-05-0489)
973 Program(Grant No.2006CB101708)
the Scientific Research Foundation for the Returned 0versears Chinese Scholars,State Education and Personnel Ministry,and the Talented Foundation of Nanjing Agriculture University.
关键词
定量特征轨迹
参量估计
效应
极大可能性算法
贝叶斯定理法
quantitative trait locus, parameter estimation, effect,maximum likelihood method, Bayesian method
