中国畜牧兽医 ›› 2025, Vol. 52 ›› Issue (10): 4776-4784.doi: 10.16431/j.cnki.1671-7236.2025.10.023

• 遗传繁育 • 上一篇    

中国美利奴羊生长性状和毛用性状的基因组选择研究

闫娜娜1, 古丽孜议娜·阿斯哈尔2, 哈尼克孜·吐拉甫3, 斯木巴提古力·沙哈提奴尔4, 吾西夏尔·卡尼西4, 马军德4, 吴伟伟3, 刘玲玲1   

  1. 1. 新疆农业大学动物科学学院, 乌鲁木齐 830052;
    2. 伊犁职业技术学院, 伊犁 835100;
    3. 新疆维吾尔自治区畜牧科学院畜牧研究所, 乌鲁木齐 830000;
    4. 新疆巩乃斯种羊场有限公司, 伊犁 835808
  • 收稿日期:2025-01-06 发布日期:2025-09-30
  • 通讯作者: 刘玲玲 E-mail:673834944@qq.com
  • 作者简介:闫娜娜,E-mail:2624064140@qq.com。
  • 基金资助:
    科技2030生物育种重大专项优质抗病绒毛羊新品种设计与培育(2023ZD04051);自治区现代产业技术体系(XJARS-09-06);自治区肉毛兼用绒毛用羊品种选育提升计划(2024XJRMY-12)

Study on Genomic Selection of Growth and Wool Traits in Chinese Merino Sheep

YAN Nana1, GULIZGULINA Asghar2, HANIKZ Tulav3, SMUBATI Guli Shahatynur4, GURSIYAR Kanish4, MA Junde4, WU Weiwei3, LIU Lingling1   

  1. 1. College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China;
    2. Yili Vocational and Technical College, Yili 835100, China;
    3. Institute of Animal Husbandry, Xinjiang Academy of Animal Husbandry, Urumqi 830000, China;
    4. Xinjiang Kungnis Sheep Breeding Farm Co., Ltd., Yili 835808, China
  • Received:2025-01-06 Published:2025-09-30

摘要: 【目的】通过对中国美利奴羊核心群生长性状和毛用性状进行遗传参数和基因组育种值估计,为超细型细毛羊新品种(系)的培育提供依据。【方法】以新疆巩乃斯种羊场中国美利奴羊核心群为研究对象,采集该群体2013―2022年出生个体的系谱数据、表型数据(初生重、周岁重、日增重、毛长、剪毛量和剪毛后体重)和系统环境效应数据;以2023年该群体999个个体为参考群体进行低深度(1×)测序获得其基因型数据。通过SAS 9.2软件的最小二乘程序分析各系统环境效应,确定模型的固定效应。通过似然比检验模型1与模型2的差异来确定增加母体遗传效应是否对模型产生较大影响,并使用ASREML软件确定在本试验条件下的最优模型,运用ABLUP、GBLUP和ssGBLUP法对各性状进行遗传参数和基因组育种值估计,并验证准确性。【结果】中国美利奴羊核心群的初生重、周岁重、日增重、毛长、剪毛量和剪毛后体重的遗传力分别为0.1215~0.1647、0.1434~0.3631、0.1954~0.2545、0.1398~0.1781、0.1129~0.2076、0.2434~0.3017,为中、低遗传力性状。使用ssGBLUP法运用模型2估计的各性状的基因组估计育种值准确性最高,ssGBLUP法相较于ABLUP法总体准确性提高了1.48%~27.02%。【结论】本试验条件下,在对中国美利奴羊核心群的生长性状和毛用性状进行遗传参数估计和基因组估计育种值时,应同时考虑个体加性和母体遗传效应的模型并结合ssGBLUP法进行估计能够获得准确性最高的结果。

关键词: 中国美利奴羊; 生长性状; 毛用性状; 基因组选择

Abstract: 【Objective】 This study was conducted to perform a genetic evaluation and estimate the genomic breeding values of growth traits and wool traits in the core population of Chinese Merino sheep,so as to provide a foundation for breeding new ultra-fine wool sheep strains.【Method】 The core population of Chinese Merino sheep at the Xinjiang Gongnaisi Stud Farm was used as the research subject.Pedigree data,phenotypic data (including birth weight,yearling weight,daily weight gain,gross from length,shearing amount,and weight after shearing),and systematic environmental effect data were collected from individuals born between 2013 and 2022.In addition,a reference population consisting of 999 individuals from the 2023 cohort was subjected to low-depth (1×) sequencing to obtain their genotypic data.The least squares method in SAS 9.2 software was used to analyze systematic environmental effects and determine fixed effects in the model.The likelihood ratio test was conducted to compare model 1 and model 2 to assess whether including maternal genetic effects significantly impacted the model.The optimal model under these study conditions was determined and then applied using ASREML software.Genetic parameters and genomic breeding values for various traits were estimated using the ABLUP,GBLUP,and ssGBLUP methods,with validation of accuracy.【Result】 The estimated heritabilities of birth weight,yearling weight,daily weight gain,gross from length,shearing amount,and weight after shearing in the core population of Chinese Merino sheep were found to be 0.1215-0.1647,0.1434-0.3631,0.1954-0.2545,0.1398-0.1781,0.1129-0.2076,and 0.2434-0.3017,respectively,all were low to medium heritability traits.Among the different estimation methods,the highest accuracy for genomic estimated breeding values (GEBVs) was obtained using model 2 with ssGBLUP method.Compared with ABLUP method,the overall accuracy of ssGBLUP method improved by 1.48%-27.02%.【Conclusion】 Under the conditions of this study,the most accurate estimation of genetic parameters and genomic breeding values for growth and wool traits in the core population of Chinese Merino sheep was achieved using a model that incorporated both individual additive and maternal genetic effects in combination with ssGBLUP method.

Key words: Chinese Merino sheep; growth traits; wool traits; genomic selection

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