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Joint multiple quantitative trait loci mapping for allometries of body compositions and metabolic traits to body weights in broiler

Published online by Cambridge University Press:  09 January 2020

X. Zhou Open the ORCID record for X. Zhou [Opens in a new window] ,
Y. Zhang ,
H. Zhang ,
J. Du ,
J. Ye ,
Y. Xu  and
R. Yang
X. Zhou
Affiliation:
Department of Information and Computing Science, Heilongjiang Bayi Agricultural University, No.5 Xinfeng Road, Gaoxin District, Daqing 163319, People’s Republic of China Bioinformatics Research Laboratory, Heilongjiang Bayi Agricultural University, No.5 Xinfeng Road, Gaoxin District, Daqing 163319, People’s Republic of China
Y. Zhang
Affiliation:
College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, No. 5 Xinfeng Road, Gaoxin District, Daqing 163319, People’s Republic of China
H. Zhang
Affiliation:
Department of Information and Computing Science, Heilongjiang Bayi Agricultural University, No.5 Xinfeng Road, Gaoxin District, Daqing 163319, People’s Republic of China
J. Du
Affiliation:
Research Centre for Aquatic Biotechnology, Chinese Academy of Fishery Sciences, No. 150 Qingta west Road, Fengtai District, Beijing 100141, People’s Republic of China
J. Ye
Affiliation:
Department of Information and Computing Science, Heilongjiang Bayi Agricultural University, No.5 Xinfeng Road, Gaoxin District, Daqing 163319, People’s Republic of China Bioinformatics Research Laboratory, Heilongjiang Bayi Agricultural University, No.5 Xinfeng Road, Gaoxin District, Daqing 163319, People’s Republic of China
Y. Xu
Affiliation:
Department of Information and Computing Science, Heilongjiang Bayi Agricultural University, No.5 Xinfeng Road, Gaoxin District, Daqing 163319, People’s Republic of China Bioinformatics Research Laboratory, Heilongjiang Bayi Agricultural University, No.5 Xinfeng Road, Gaoxin District, Daqing 163319, People’s Republic of China
R. Yang*
Affiliation:
Research Centre for Aquatic Biotechnology, Chinese Academy of Fishery Sciences, No. 150 Qingta west Road, Fengtai District, Beijing 100141, People’s Republic of China
*
†E-mail: runqingyang@cafs.ac.cn
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Abstract

In order to map quantitative trait loci (QTLs) for allometries of body compositions and metabolic traits in chicken, we phenotypically characterize the allometric growths of multiple body components and metabolic traits relative to BWs using joint allometric scaling models and then establish random regression models (RRMs) to fit genetic effects of markers and minor polygenes derived from the pedigree on the allometric scalings. Prior to statistically inferring the QTLs for the allometric scalings by solving the RRMs, the LASSO technique is adopted to rapidly shrink most of marker genetic effects to zero. Computer simulation analysis confirms the reliability and adaptability of the so-called LASSO-RRM mapping method. In the F2 population constructed by multiple families, we formulate two joint allometric scaling models of body compositions and metabolic traits, in which six of nine body compositions are tested as significant, while six of eight metabolic traits are as significant. For body compositions, a total of 14 QTLs, of which 9 dominant, were detected to be associated with the allometric scalings of drumstick, fat, heart, shank, liver and spleen to BWs; while for metabolic traits, a total of 19 QTLs also including 9 dominant be responsible for the allometries of T4, IGFI, IGFII, GLC, INS, IGR to BWs. The detectable QTLs or highly linked markers can be used to regulate relative growths of the body components and metabolic traits to BWs in marker-assisted breeding of chickens.

Keywords

relative growthrandom regression modelorgan tissuequality traitlinkage analysis
Type
Research Article
Information
animal , Volume 14 , Issue 6 , June 2020 , pp. 1120 - 1127
Copyright
© The Animal Consortium 2020

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