简短的沟通:包括基因组信息增加了在小型户外有机猪群中育种价值估计的准确性

IF 4.2 2区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE
R.M. Zaalberg, A.J. Buitenhuis, J. Jensen, T.T. Chu, T.M. Villumsen
{"title":"简短的沟通:包括基因组信息增加了在小型户外有机猪群中育种价值估计的准确性","authors":"R.M. Zaalberg,&nbsp;A.J. Buitenhuis,&nbsp;J. Jensen,&nbsp;T.T. Chu,&nbsp;T.M. Villumsen","doi":"10.1016/j.animal.2025.101434","DOIUrl":null,"url":null,"abstract":"<div><div>To optimise organic pig breeding, we studied the effect of including genomic information for predicting breeding values (<strong>EBVs</strong>) in a small organic pig population. The recorded traits were the number of functional teats (n = 16 494), BW at birth (n = 36 995) and on day 10 (n = 29 744), and litter size on day 0, 4, or 11 (n ≈ 5 900 litters). Genomic information from 18 929 SNPs was available for 1 394 pigs, including Landrace sows and boars, and Yorkshire x Landrace crossbred sows. Throughout the study, a purebred- and crossbred correlation of 1 was assumed. Univariate mixed models that either included pedigree information or both pedigree and genomic information were used to estimate parameters and EBV. The prediction accuracy of the EBV was based on a forward prediction of data from the final 11 months of data. For the number of functional teats, the direct additive genetic component was considered, whereas for the other traits, the maternal genetic component was considered. The accuracy of predicting EBV for individuals without their own phenotype increased for all traits when genomic information was included, especially when the heritability was low. In conclusion, including genomic information can improve EBV prediction accuracy, which can optimise the genetic improvement in small breeding programmes.</div></div>","PeriodicalId":50789,"journal":{"name":"Animal","volume":"19 3","pages":"Article 101434"},"PeriodicalIF":4.2000,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Short communication: Including genomic information increases accuracy of breeding value estimation in a small outdoor organic pig population\",\"authors\":\"R.M. Zaalberg,&nbsp;A.J. Buitenhuis,&nbsp;J. Jensen,&nbsp;T.T. Chu,&nbsp;T.M. Villumsen\",\"doi\":\"10.1016/j.animal.2025.101434\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>To optimise organic pig breeding, we studied the effect of including genomic information for predicting breeding values (<strong>EBVs</strong>) in a small organic pig population. The recorded traits were the number of functional teats (n = 16 494), BW at birth (n = 36 995) and on day 10 (n = 29 744), and litter size on day 0, 4, or 11 (n ≈ 5 900 litters). Genomic information from 18 929 SNPs was available for 1 394 pigs, including Landrace sows and boars, and Yorkshire x Landrace crossbred sows. Throughout the study, a purebred- and crossbred correlation of 1 was assumed. Univariate mixed models that either included pedigree information or both pedigree and genomic information were used to estimate parameters and EBV. The prediction accuracy of the EBV was based on a forward prediction of data from the final 11 months of data. For the number of functional teats, the direct additive genetic component was considered, whereas for the other traits, the maternal genetic component was considered. The accuracy of predicting EBV for individuals without their own phenotype increased for all traits when genomic information was included, especially when the heritability was low. In conclusion, including genomic information can improve EBV prediction accuracy, which can optimise the genetic improvement in small breeding programmes.</div></div>\",\"PeriodicalId\":50789,\"journal\":{\"name\":\"Animal\",\"volume\":\"19 3\",\"pages\":\"Article 101434\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2025-01-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Animal\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1751731125000175\",\"RegionNum\":2,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRICULTURE, DAIRY & ANIMAL SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Animal","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1751731125000175","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, DAIRY & ANIMAL SCIENCE","Score":null,"Total":0}
引用次数: 0

摘要

为了优化有机猪育种,我们研究了包含基因组信息在小型有机猪群体中预测育种值(ebv)的效果。记录的性状为功能乳头数(n = 16 494)、出生体重(n = 36 995)和第10天体重(n = 29 744)以及第0、4、11天产仔数(n≈5 900窝)。1 394头猪(包括长白猪、长白猪和约克郡与长白猪杂交母猪)共获得18 929个snp的基因组信息。在整个研究中,假设纯种和杂交的相关系数为1。单变量混合模型要么包含家系信息,要么同时包含家系和基因组信息,用于估计参数和EBV。EBV的预测精度是基于对最后11个月数据的前向预测。对于功能乳头数,考虑直接加性遗传成分,而对于其他性状,考虑母体遗传成分。当包含基因组信息时,特别是在遗传力较低的情况下,对无自身表型的个体预测EBV的准确性在所有性状中都有所提高。综上所述,包含基因组信息可以提高EBV预测的准确性,从而可以优化小型育种计划的遗传改良。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Short communication: Including genomic information increases accuracy of breeding value estimation in a small outdoor organic pig population
To optimise organic pig breeding, we studied the effect of including genomic information for predicting breeding values (EBVs) in a small organic pig population. The recorded traits were the number of functional teats (n = 16 494), BW at birth (n = 36 995) and on day 10 (n = 29 744), and litter size on day 0, 4, or 11 (n ≈ 5 900 litters). Genomic information from 18 929 SNPs was available for 1 394 pigs, including Landrace sows and boars, and Yorkshire x Landrace crossbred sows. Throughout the study, a purebred- and crossbred correlation of 1 was assumed. Univariate mixed models that either included pedigree information or both pedigree and genomic information were used to estimate parameters and EBV. The prediction accuracy of the EBV was based on a forward prediction of data from the final 11 months of data. For the number of functional teats, the direct additive genetic component was considered, whereas for the other traits, the maternal genetic component was considered. The accuracy of predicting EBV for individuals without their own phenotype increased for all traits when genomic information was included, especially when the heritability was low. In conclusion, including genomic information can improve EBV prediction accuracy, which can optimise the genetic improvement in small breeding programmes.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Animal
Animal 农林科学-奶制品与动物科学
CiteScore
7.50
自引率
2.80%
发文量
246
审稿时长
3 months
期刊介绍: Editorial board animal attracts the best research in animal biology and animal systems from across the spectrum of the agricultural, biomedical, and environmental sciences. It is the central element in an exciting collaboration between the British Society of Animal Science (BSAS), Institut National de la Recherche Agronomique (INRA) and the European Federation of Animal Science (EAAP) and represents a merging of three scientific journals: Animal Science; Animal Research; Reproduction, Nutrition, Development. animal publishes original cutting-edge research, ''hot'' topics and horizon-scanning reviews on animal-related aspects of the life sciences at the molecular, cellular, organ, whole animal and production system levels. The main subject areas include: breeding and genetics; nutrition; physiology and functional biology of systems; behaviour, health and welfare; farming systems, environmental impact and climate change; product quality, human health and well-being. Animal models and papers dealing with the integration of research between these topics and their impact on the environment and people are particularly welcome.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信