Statistical approaches in QTL mapping and molecular breeding for complex traits

被引:14
作者
Xu HaiMing [1 ]
Zhu Jun [1 ]
机构
[1] Zhejiang Univ, Coll Agr & Biotechnol, Inst Bioinformat, Hangzhou 310058, Zhejiang, Peoples R China
来源
CHINESE SCIENCE BULLETIN | 2012年 / 57卷 / 21期
关键词
complex traits; QTL mapping; epistasis; environment interaction; crop breeding; MARKER-ASSISTED SELECTION; X ENVIRONMENT INTERACTION; GENETIC ARCHITECTURE; DEVELOPMENTAL BEHAVIOR; PLANT HEIGHT; MULTIPLE ENVIRONMENTS; GENERAL FRAMEWORK; YIELD COMPONENTS; RESISTANCE GENES; TILLER NUMBER;
D O I
10.1007/s11434-012-5107-1
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Most of the important agronomic traits in crops, such as yield and quality, are complex traits affected by multiple genes with gene x gene interaction as well as gene x environment interaction. Understanding the genetic architecture of complex traits is a long-term task for quantitative geneticists and plant breeders who wish to design efficient breeding programs. Conventionally, the genetic properties of traits can be revealed by partitioning the total variation into variation components caused by specific genetic effects. With recent advances in molecular genotyping and high-throughput technology, the unraveling of the genetic architecture of complex traits by analyzing quantitative trait locus (QTL) has become possible. The improvement of complex traits has also been achieved by pyramiding individual QTL. In this review, we describe some statistical methods for QTL mapping that can be used to analyze QTL x QTL interaction and QTL x environment interaction, and discuss their applications in crop breeding for complex traits.
引用
收藏
页码:2637 / 2644
页数:8
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