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A new mapping method for quantitative trait loci of silkworm.

Authors :
Hai-Ming Xu
Chang-Shuai Wei
Yun-Ting Tang
Zhi-Hong Zhu
Yang-Fu Sima
Xiang-Yang Lou
Source :
BMC Genetics. 2011, Vol. 12 Issue 1, p19-29. 11p.
Publication Year :
2011

Abstract

Background: Silkworm is the basis of sericultural industry and the model organism in insect genetics study. Mapping quantitative trait loci (QTLs) underlying economically important traits of silkworm is of high significance for promoting the silkworm molecular breeding and advancing our knowledge on genetic architecture of the Lepidoptera. Yet, the currently used mapping methods are not well suitable for silkworm, because of ignoring the recombination difference in meiosis between two sexes. Results: A mixed linear model including QTL main effects, epistatic effects, and QTL × sex interaction effects was proposed for mapping QTLs in an F2 population of silkworm. The number and positions of QTLs were determined by F-test and model selection. The Markov chain Monte Carlo (MCMC) algorithm was employed to estimate and test genetic effects of QTLs and QTL × sex interaction effects. The effectiveness of the model and statistical method was validated by a series of simulations. The results indicate that when markers are distributed sparsely on chromosomes, our method will substantially improve estimation accuracy as compared to the normal chiasmate F2 model. We also found that a sample size of hundreds was sufficiently large to unbiasedly estimate all the four types of epistases (i.e., additive-additive, additive-dominance, dominance-additive, and dominance-dominance) when the paired QTLs reside on different chromosomes in silkworm. Conclusion: The proposed method could accurately estimate not only the additive, dominance and digenic epistatic effects but also their interaction effects with sex, correcting the potential bias and precision loss in the current QTL mapping practice of silkworm and thus representing an important addition to the arsenal of QTL mapping tools. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14712156
Volume :
12
Issue :
1
Database :
Academic Search Index
Journal :
BMC Genetics
Publication Type :
Academic Journal
Accession number :
59143844
Full Text :
https://doi.org/10.1186/1471-2156-12-19