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Whole genome SNPs among 8 chicken breeds enable identification of genetic signatures that underlie breed features

文献类型： 外文期刊

作者： Wang, Jie 1 ; Lei, Qiu-xia 1 ; Cao, Ding-guo 1 ; Zhou, Yan 1 ; Han, Hai-xia 1 ; Liu, Wei 1 ; Li, Da-peng 1 ; Li, Fu-wei 1 ; Liu, Jie 1 ;

作者机构： 1.Shandong Acad Agr Sci, Poultry Inst, Jinan 250100, Peoples R China

2.Poultry Breeding Engn Technol Ctr Shandong Prov, Jinan 250100, Peoples R China

关键词： chicken; genome; genetic diversity; support vector machine

期刊名称：JOURNAL OF INTEGRATIVE AGRICULTURE （ 影响因子：4.8； 五年影响因子：4.8 ）

ISSN： 2095-3119

年卷期： 2023 年 22 卷 7 期

页码：

收录情况： SCI

摘要： Many different chicken breeds are found around the world, their features vary among them, and they are valuable resources. Currently, there is a huge lack of knowledge of the genetic determinants responsible for phenotypic and biochemical properties of these breeds of chickens. Understanding the underlying genetic mechanisms that explain across-breed variation can help breeders develop improved chicken breeds. The whole-genomes of 140 chickens from 7 Shandong native breeds and 20 introduced recessive white chickens from China were re-sequenced. Comparative population genomics based on autosomal single nucleotide polymorphisms (SNPs) revealed geographically based clusters among the chickens. Through genome-wide scans for selective sweeps, we identified thyroid stimulating hormone receptor (TSHR, reproductive traits, circadian rhythm), erythrocyte membrane protein band 4.1 like 1 (EPB41L1, body size), and alkylglycerol monooxygenase (AGMO, aggressive behavior), as major candidate breed-specific determining genes in chickens. In addition, we used a machine learning classification model to predict chicken breeds based on the SNPs significantly associated with recourse characteristics, and the prediction accuracy was 92%, which can effectively achieve the breed identification of Laiwu Black chickens. We provide the first comprehensive genomic data of the Shandong indigenous chickens. Our analyses revealed phylogeographic patterns among the Shandong indigenous chickens and candidate genes that potentially contribute to breed-specific traits of the chickens. In addition, we developed a machine learning-based prediction model using SNP data to identify chicken breeds. The genetic basis of indigenous chicken breeds revealed in this study is useful to better understand the mechanisms underlying the resource characteristics of chicken.

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