The genetic dissection of quantitative traits in crops

被引:66
作者
Semagn, Kassa [1 ]
Bjornstad, Asmund [2 ]
Xu, Yunbi [3 ]
机构
[1] Int Maize & Wheat Improvement Ctr, Nairobi, Kenya
[2] Norwegian Univ Life Sci, Dept Plant & Environm Sci, As, Norway
[3] Int Maize & Wheat Improvement Ctr, Mexico City, DF, Mexico
关键词
association mapping; linkage disequilibrium; markers assisted selection; molecular breeding; molecular markers; quantitative trait; QTL mapping; QTL analysis; FUSARIUM HEAD BLIGHT; MARKER-ASSISTED INTROGRESSION; SINGLE NUCLEOTIDE POLYMORPHISMS; MORPHOLOGICAL SHAPE DIFFERENCE; BULKED SEGREGANT ANALYSIS; CYST-NEMATODE RESISTANCE; SIMPLE REGRESSION METHOD; NEAR-ISOGENIC LINES; MAIZE INBRED LINES; LINKAGE DISEQUILIBRIUM;
D O I
10.2225/vol13-issue5-fulltext-14
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Most traits of interest in plant breeding show quantitative inheritance, which complicate the breeding process since phenotypic performances only partially reflects the genetic values of individuals. The genetic variation of a quantitative trait is assumed to be controlled by the collective effects of quantitative trait loci (QTLs), epistasis (interaction between QTLs), the environment, and interaction between QTL and environment. Exploiting molecular markers in breeding involve finding a subset of markers associated with one or more QTLs that regulate the expression of complex traits. Many QTL mapping studies conducted in the last two decades identified QTLs that generally explained a significant proportion of the phenotypic variance, and therefore, gave rise to an optimistic assessment of the prospects of markers assisted selection. Linkage analysis and association mapping are the two most commonly used methods for QTL mapping. This review provides an overview of the two QTL mapping methods, including mapping population type and size, phenotypic evaluation of the population, molecular profiling of either the entire or a subset of the population, marker-trait association analysis using different statistical methods and software as well as the future prospects of using markers in crop improvement.
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页数:45
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