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Multiple ancestral haplotypes harboring regulatory mutations cumulatively contribute to a QTL affecting chicken growth traits

文献类型： 外文期刊

作者： Wang, Yuzhe 1 ; Cao, Xuemin 1 ; Luo, Chenglong 3 ; Sheng, Zheya 1 ; Zhang, Chunyuan 1 ; Bian, Cheng 1 ; Feng, Chungang 1 ;

作者机构： 1.China Agr Univ, Coll Biol Sci, State Key Lab Agrobiotechnol, Beijing 100193, Peoples R China

2.China Agr Univ, Coll Anim Sci & Technol, Beijing 100193, Peoples R China

3.Guangdong Acad Agr Sci, Inst Anim Sci, State Key Lab Livestock & Poultry Breeding, Guangdong Key Lab Anim Breeding & Nutr, Guangzhou 510640, Peoples R China

4.Huazhong Agr Univ, Coll Anim Sci & Technol, Minist Educ, Key Lab Agr Anim Genet Breeding & Reprod, Wuhan 430070, Peoples R China

5.China Agr Univ, Beijing Adv Innovat Ctr Food Nutr & Human Hlth, Beijing 100193, Peoples R China

6.Uppsala Univ, Dept Med Biochem & Microbiol, SE-75123 Uppsala, Sweden

期刊名称：COMMUNICATIONS BIOLOGY （ 影响因子：6.268； 五年影响因子：6.268 ）

ISSN：

年卷期： 2020 年 3 卷 1 期

页码：

收录情况： SCI

摘要： In depth studies of quantitative trait loci (QTL) can provide insights to the genetic architectures of complex traits. A major effect QTL at the distal end of chicken chromosome 1 has been associated with growth traits in multiple populations. This locus was fine-mapped in a fifteen-generation chicken advanced intercross population including 1119 birds and explored in further detail using 222 sequenced genomes from 10 high/low body weight chicken stocks. We detected this QTL that, in total, contributed 14.4% of the genetic variance for growth. Further, nine mosaic precise intervals (Kb level) which contain ancestral regulatory variants were fine-mapped and we chose one of them to demonstrate the key regulatory role in the duodenum. This is the first study to break down the detail genetic architectures for the well-known QTL in chicken and provides a good example of the fine-mapping of various of quantitative traits in any species. Yuzhe Wang, Xuemin Cao et al. report the fine-mapping of a major growth trait QTL in chicken using genome-wide association and haplotype association analyses. They discover multiple mutations cumulatively contribute to the previously-reported QTL and identify one of a regulatory mutation that contributes to the variation in the measured traits.

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