Detection of QTL for traits related to adaptation to sub-optimal climatic conditions in chickens

Genetics Selection Evolution

Research Article

Woei-Fuh Wang¹  Chih-Feng Chen²  Shih-Wen Wu³  Michèle Tixier-Boichard⁴  Ching-Yi Lien⁵  Chen Siang Ng⁶ 

[1] Biodiversity Research Center, Academia Sinica, 128 Academia Rd., Section 2, Nankang, 11529, Taipei, Taiwan;Department of Animal Science, National Chung Hsing University, 145 Xingda Rd., South District, 40227, Taichung, Taiwan;Center for the Integrative and Evolutionary Galliformes Genomics, National Chung Hsing University, No. 250, Guoguang Rd., South District, 40227, Taichung, Taiwan;Fonghuanggu Bird and Ecology Park, National Museum of Natural Science, 1-9 Renyi Rd., Lugu Township, 55841, Nantou County, Taiwan;GABI, INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France;GABI, INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France;Department of Animal Science, National Chung Hsing University, 145 Xingda Rd., South District, 40227, Taichung, Taiwan;Livestock Research Institute, Council of Agriculture, Executive Yuan, 112 Muchang, Xinhua District, 71246, Tainan, Taiwan;Institute of Molecular and Cellular Biology, National Tsing Hua University, No. 101, Section 2, Kuang-Fu Rd., 30013, Hsinchu, Taiwan;

关键词: Quantitative Trait Locus;    Quantitative Trait Locus Mapping;    Quantitative Trait Locus Region;    Quantitative Trait Locus Effect;    Quantitative Trait Locus Detection;   

DOI  :  10.1186/s12711-017-0314-5

 received in 2016-07-20, accepted in 2017-03-31,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundGrowth traits can be used as indicators of adaptation to sub-optimal conditions. The current study aimed at identifying quantitative trait loci (QTL) that control performance under variable temperature conditions in chickens.MethodsAn F2 population was produced by crossing the Taiwan Country chicken L2 line (selected for body weight, comb area, and egg production) with an experimental line of Rhode Island Red layer R- (selected for low residual feed consumption). A total of 844 animals were genotyped with the 60 K Illumina single nucleotide polymorphism (SNP) chip. Whole-genome interval linkage mapping and a genome-wide association study (GWAS) were performed for body weight at 0, 4, 8, 12, and 16 weeks of age, shank length at 8 weeks of age, size of comb area at 16 weeks of age, and antibody response to sheep red blood cells at 11 weeks of age (7 and 14 days after primary immunization). Relevant genes were identified based on functional annotation of candidate genes and potentially relevant SNPs were detected by comparing whole-genome sequences of several birds between the parental lines.ResultsWhole-genome QTL analysis revealed 47 QTL and 714 effects associated with 178 SNPs were identified by GWAS with 5% Bonferroni genome-wide significance. Little overlap was observed between the QTL and GWAS results, with only two chromosomal regions detected by both approaches, i.e. one on GGA24 (GGA for Gallus gallus chromosome) for BW04 and one on GGAZ for six growth-related traits. Based on whole-genome sequence, differences between the parental lines based on several birds were screened in the genome-wide QTL regions and in a region detected by both methods, resulting in the identification of 106 putative candidate genes with a total of 15,443 SNPs, of which 41 were missense and 1698 were not described in the dbSNP archive.ConclusionsThe QTL detected in this study for growth and morphological traits likely influence adaptation of chickens to sub-tropical climate. Using whole-genome sequence data, we identified candidate SNPs for further confirmation of QTL in the F2 design. A strong QTL effect found on GGAZ underlines the importance of sex-linked inheritance for growth traits in chickens.

【 授权许可】

CC BY   
© The Author(s) 2017