Junjia Zeng , Ji Zhao , Jiaying Wang , Yuling Bai , Feng Long , Yacheng Deng , Pengxin Jiang , Junzhu Xiao , Ang Qu , Baichuan Tong , Mei Wang , Wei Liu , Fei Pu , Yaxian Li , Peng Xu
{"title":"Genetic linkage between swimming performance and disease resistance enables multitrait breeding strategies in large yellow croaker","authors":"Junjia Zeng , Ji Zhao , Jiaying Wang , Yuling Bai , Feng Long , Yacheng Deng , Pengxin Jiang , Junzhu Xiao , Ang Qu , Baichuan Tong , Mei Wang , Wei Liu , Fei Pu , Yaxian Li , Peng Xu","doi":"10.1016/j.agrcom.2023.100019","DOIUrl":null,"url":null,"abstract":"<div><p>Improving the robustness of fish stock has become a key issue in the advancement of aquaculture, as diseases and harsh aquatic conditions impact industry sustainability and yield. In this study, we identify several genetic loci that link swimming performance to disease resistance in large yellow croaker, and apply genomic selection (GS) for swimming performance to generate offspring with both enhanced swimming performance and disease resistance. First, we classified our reference population as superior swimmers (SS) or inferior swimmers (IS) by swimming tests and assessed inherent disease resistance. Consistent with previous research, SS displayed enhanced resistance to the parasite <em>Cryptocaryon irritans</em>. Through genotyping of parental reference and candidate populations, we generated a single nucleotide polymorphism (SNP) database, containing 45832 high-quality SNPs in total. We applied multitrait genome-wide association study analysis of swimming performance and disease resistance to this dataset and identified three linked SNPs, which were associated with 48 potential candidate genes, including <em>pp3r1b</em>, <em>mapk12b</em>, <em>mapk11</em>, and <em>tnfrsf11a</em>. Next, we generated a GS model using the BayesB method and calculated the candidate population's genetic estimated breeding value (GEBV). Individuals with GEBV's in the top 12 % were selected as broodstocks for breeding selective lines (SL), and the remaining individuals were used as the control group (CG). We found that SL exhibited both increased swimming performance and resistance to <em>C. irritans</em> compared to CG. Our study reveals the genetic basis related to swimming performance and disease resistance. This work has implications for designing multitrait breeding strategies and improving whole-fish fitness, both of which are critical in aquaculture.</p></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"1 2","pages":"Article 100019"},"PeriodicalIF":0.0000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949798123000194/pdfft?md5=856bf60d1227eea748bda6a99cd3af3a&pid=1-s2.0-S2949798123000194-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agriculture Communications","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949798123000194","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Improving the robustness of fish stock has become a key issue in the advancement of aquaculture, as diseases and harsh aquatic conditions impact industry sustainability and yield. In this study, we identify several genetic loci that link swimming performance to disease resistance in large yellow croaker, and apply genomic selection (GS) for swimming performance to generate offspring with both enhanced swimming performance and disease resistance. First, we classified our reference population as superior swimmers (SS) or inferior swimmers (IS) by swimming tests and assessed inherent disease resistance. Consistent with previous research, SS displayed enhanced resistance to the parasite Cryptocaryon irritans. Through genotyping of parental reference and candidate populations, we generated a single nucleotide polymorphism (SNP) database, containing 45832 high-quality SNPs in total. We applied multitrait genome-wide association study analysis of swimming performance and disease resistance to this dataset and identified three linked SNPs, which were associated with 48 potential candidate genes, including pp3r1b, mapk12b, mapk11, and tnfrsf11a. Next, we generated a GS model using the BayesB method and calculated the candidate population's genetic estimated breeding value (GEBV). Individuals with GEBV's in the top 12 % were selected as broodstocks for breeding selective lines (SL), and the remaining individuals were used as the control group (CG). We found that SL exhibited both increased swimming performance and resistance to C. irritans compared to CG. Our study reveals the genetic basis related to swimming performance and disease resistance. This work has implications for designing multitrait breeding strategies and improving whole-fish fitness, both of which are critical in aquaculture.