畜牧兽医学报 ›› 2025, Vol. 56 ›› Issue (7): 3164-3176.doi: 10.11843/j.issn.0366-6964.2025.07.012

• 遗传育种 • 上一篇    下一篇

基于50K液相芯片的中国绵羊群体遗传结构与羊毛性状选择信号分析

张嘉良1,3(), 黄畅1, 杨永林2, 杨华2, 白文林3, 马月辉1, 赵倩君1,*()   

  1. 1. 中国农业科学院北京畜牧兽医研究所,北京 100193
    2. 新疆农垦科学院,石河子 832000
    3. 沈阳农业大学,沈阳 110000
  • 收稿日期:2024-10-14 出版日期:2025-07-23 发布日期:2025-07-25
  • 通讯作者: 赵倩君 E-mail:18340756126@163.com;zhaoqianjun@caas.cn
  • 作者简介:张嘉良(1997-),男,辽宁东港人,硕士生,主要从事动物遗传育种研究,Tel:010-62815884,E-mail: 18340756126@163.com
  • 基金资助:
    国家重点研发计划“绵羊新品种新品系培育及良繁”(2021YFD1300901);国家绒毛用羊产业技术体系项目(CARS-39-01)

Genetic Structure and Wool Trait Selection Signatures Analysis of Chinese Sheep Populations Based on 50K Liquid SNP Chip

ZHANG Jialiang1,3(), HUANG Chang1, YANG Yonglin2, YANG Hua2, BAI Wenlin3, MA Yuehui1, ZHAO Qianjun1,*()   

  1. 1. Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
    2. Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi 832000, China
    3. Shenyang Agricultural University, Shenyang 110000, China
  • Received:2024-10-14 Online:2025-07-23 Published:2025-07-25
  • Contact: ZHAO Qianjun E-mail:18340756126@163.com;zhaoqianjun@caas.cn

摘要:

旨在揭示不同被毛类型绵羊群体的遗传结构特征,通过选择信号分析筛选与羊毛性状相关的候选基因。本研究选择8个绵羊群体(包括15只欧拉羊、13只塔什库尔干羊、15只阿勒泰羊、16只藏绵羊、12只青海毛肉兼用细毛羊、10只甘肃高山细毛羊、15只中国美利奴羊和11只敖汉细毛羊)共计107只个体作为研究对象。将绵羊群体按照不同羊毛类型分为两组,包括59只细毛型绵羊和48只粗毛型绵羊。使用自主研发的绵羊SNP 50K液相芯片对所选绵羊群体进行基因分型,经质控后进行主成分分析、邻接连接树和群体遗传结构分析。基于群体遗传分化指数(FST)和核苷酸多样性比值(θπ ratio)两种选择信号方法筛选与羊毛性状相关的候选基因,通过KEGG通路分析确定候选基因的功能。主成分分析、邻接连接树和群体遗传结构分析的结果表明,两组绵羊群体之间存在遗传分化。基于FST和θπ Ratio的结合分析,前1%区域作为受选择区域,检测到165个受选择区域,包含456个受选择基因。基因注释发现,受选择基因与毛囊及毛发发育(JAK2、SELENBP1)、黑色素合成(IRF4)、真皮乳头细胞的间接调控(RAC2)以及皮肤分子生物学中关键管家基因(SDHA)密切相关。本研究探究了8个我国绵羊群体的遗传结构, 细毛型和粗毛型绵羊群体间有明显的群体分化。基于两种选择信号检测方法筛选到与羊毛性状相关的候选基因(JAK2、IRF4、RAC2、IDUASDHASELENBP1)等。研究结果可为绵羊羊毛性状的分子遗传标记挖掘提供参考。

关键词: 绵羊, SNP芯片, 群体遗传结构, 选择信号

Abstract:

This study aimed to reveal the genetic structural characteristics of sheep populations with different wool types and screen candidate genes related to wool traits through selection signatures analysis. The sheep populations were divided into two groups based on different wool types, including 59 fine wool sheep and 48 coarse wool sheep.Genotyping of 8 sheep populations (15 Oula sheep, 13 Tashkurgan sheep, 15 Altay sheep, 16 Zangxi sheep, 12 Qinghai wool-mutton type sheep, 10 Gansu Alpine Merino, 15 Chinese Merino, 11 Aohan Merino) was performed using a self-developed ovine SNP 50K liquid chip, followed by principal component analysis, neighbor-joining tree, and population genetic structure analysis after quality control. Candidate genes associated with wool trait were screened based on two selection signal methods: population genetic differentiation index (FST) and nucleotide diversity ratio (θπ ratio). The functions of the candidate genes were determined through KEGG pathway enrichment analysis. The results of principal component analysis, neighbor-joining tree, and population genetic structure analysis indicated the presence of genetic differentiation between the two groups of sheep populations. Based on the combined analysis of FST and θπ ratio, the top 1% regions were identified as selected regions, 165 selected regions and 456 selected genes were identified. Several selected genes were identified that are closely associated with hair follicle development and hair growth (JAK2, SELENBP1), melanin synthesis (IRF4), the indirect regulation of dermal papilla cells (RAC2), and a key housekeeping gene in skin molecular biology (SDHA) through gene annotation. This study explored the genetic structure of 8 Chinese sheep populations with clear population differentiation between fine-wool and coarse-wool sheep groups. Selection signature analysis identified candidate genes associated with wool trait, such as JAK2, IRF4, RAC2, IDUA, SDHA and SELENBP1. This study will provide a reference for the molecular genetic marker discovery of wool trait in sheep.

Key words: sheep, SNP chip, population genetic structure, selection signatures

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