scholarly journals A quantitative trait locus on Bos taurus autosome 17 explains a large proportion of the genetic variation in de novo synthesized milk fatty acids

2014 ◽  
Vol 97 (11) ◽  
pp. 7276-7285 ◽  
Author(s):  
S.I. Duchemin ◽  
M.H.P.W. Visker ◽  
J.A.M. Van Arendonk ◽  
H. Bovenhuis
2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Tim Martin Knutsen ◽  
Hanne Gro Olsen ◽  
Valeria Tafintseva ◽  
Morten Svendsen ◽  
Achim Kohler ◽  
...  

2014 ◽  
Vol 97 (2) ◽  
pp. 1139-1149 ◽  
Author(s):  
Aniek C. Bouwman ◽  
Marleen H.P.W. Visker ◽  
JohanA.M. van Arendonk ◽  
Henk Bovenhuis

Genetics ◽  
2008 ◽  
Vol 180 (3) ◽  
pp. 1645-1660 ◽  
Author(s):  
Luis-Miguel Chevin ◽  
Frédéric Hospital

2019 ◽  
Vol 110 (7) ◽  
pp. 880-891 ◽  
Author(s):  
Jinhui Shi ◽  
Jiankang Wang ◽  
Luyan Zhang

Abstract Multiparental advanced generation intercross (MAGIC) populations provide abundant genetic variation for use in plant genetics and breeding. In this study, we developed a method for quantitative trait locus (QTL) detection in pure-line populations derived from 8-way crosses, based on the principles of inclusive composite interval mapping (ICIM). We considered 8 parents carrying different alleles with different effects. To estimate the 8 genotypic effects, 1-locus genetic model was first built. Then, an orthogonal linear model of phenotypes against marker variables was established to explain genetic effects of the locus. The linear model was estimated by stepwise regression and finally used for phenotype adjustment and background genetic variation control in QTL mapping. Simulation studies using 3 genetic models demonstrated that the proposed method had higher detection power, lower false discovery rate (FDR), and unbiased estimation of QTL locations compared with other methods. Marginal bias was observed in the estimation of QTL effects. An 8-parental recombinant inbred line (RIL) population previously reported in cowpea and analyzed by interval mapping (IM) was reanalyzed by ICIM and genome-wide association mapping implemented in software FarmCPU. The results indicated that ICIM identified more QTLs explaining more phenotypic variation than did IM; ICIM provided more information on the detected QTL than did FarmCPU; and most QTLs identified by IM and FarmCPU were also detected by ICIM.


2009 ◽  
Vol 92 (2) ◽  
pp. 758-764 ◽  
Author(s):  
G. Rincón ◽  
A. Islas-Trejo ◽  
J. Casellas ◽  
Y. Ronin ◽  
M. Soller ◽  
...  

2012 ◽  
Vol 30 (2) ◽  
pp. 1163-1179 ◽  
Author(s):  
Xianzhi Wang ◽  
Guo-Liang Jiang ◽  
Marci Green ◽  
Roy A. Scott ◽  
David L. Hyten ◽  
...  

Author(s):  
Andrew P. Hendry

This chapter focuses on common empirical methods for studying the genetics of adaptation: quantitative genetics, quantitative trait locus (QTL) linkage mapping, association mapping, genome scans, gene expression, and candidate genes. It addresses various aspects of adaptation, speciation, and eco-evolutionary dynamics. The key questions include examining how much additive genetic variation exists in fitness-related traits, to what extent nonadditive genetic variation (dominance and epistasis) influences phenotypic variation, how many loci are involved in adaptation and how large their effects are, to what extent the adaptation of independent populations to similar environments involves parallel/convergent genetic changes, whether adaptation to changing environments is driven mainly by new mutations or by standing genetic variation, and to what extent the ecological effects of individuals transmitted among generations are.


2019 ◽  
Vol 7 (3) ◽  
pp. 350-359 ◽  
Author(s):  
Shouling Xu ◽  
Yunchao Zheng ◽  
Yang Liu ◽  
Xiaohao Guo ◽  
Yuanyuan Tan ◽  
...  

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