{"title":"Fish Genomics and Its Application in Disease‐Resistance Breeding","authors":"Yu Huang, Zeyu Li, Mengcheng Li, Xinhui Zhang, Qiong Shi, Zhen Xu","doi":"10.1111/raq.12973","DOIUrl":null,"url":null,"abstract":"Global aquaculture production has been rising for several decades, with up to 76% of the total production from fish. However, the problem of fish diseases is becoming more and more prominent in today's context of pursuing sustainable aquaculture. Since the first fish genome assembly reported in 2002, genomic approaches have been successfully implemented in fish breeding to enhance disease resistance and reduce economic losses caused by diverse fish diseases. Here, we present a review of the current progress in fish genomics and its application in disease‐resistance breeding. First, assembly data for all publicly available fish genomes were curated and statistical analysis of these data were performed. Subsequently, genomics‐assisted breeding approaches (including quantitative trait loci mapping, genome‐wide association study, marker‐assisted selection, genomic selection, gene transfer, and genome editing) that have been applied in practical disease–resistance breeding programs are outlined. In addition, candidate genetic markers that could possibly be utilized in breeding were summarized. Finally, remaining challenges and further directions were discussed. In summary, this review provides insight into fish genomics and genomics‐assisted breeding of disease‐resistant fish varieties.","PeriodicalId":227,"journal":{"name":"Reviews in Aquaculture","volume":"86 1","pages":""},"PeriodicalIF":8.8000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Reviews in Aquaculture","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1111/raq.12973","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FISHERIES","Score":null,"Total":0}
引用次数: 0
Abstract
Global aquaculture production has been rising for several decades, with up to 76% of the total production from fish. However, the problem of fish diseases is becoming more and more prominent in today's context of pursuing sustainable aquaculture. Since the first fish genome assembly reported in 2002, genomic approaches have been successfully implemented in fish breeding to enhance disease resistance and reduce economic losses caused by diverse fish diseases. Here, we present a review of the current progress in fish genomics and its application in disease‐resistance breeding. First, assembly data for all publicly available fish genomes were curated and statistical analysis of these data were performed. Subsequently, genomics‐assisted breeding approaches (including quantitative trait loci mapping, genome‐wide association study, marker‐assisted selection, genomic selection, gene transfer, and genome editing) that have been applied in practical disease–resistance breeding programs are outlined. In addition, candidate genetic markers that could possibly be utilized in breeding were summarized. Finally, remaining challenges and further directions were discussed. In summary, this review provides insight into fish genomics and genomics‐assisted breeding of disease‐resistant fish varieties.
期刊介绍:
Reviews in Aquaculture is a journal that aims to provide a platform for reviews on various aspects of aquaculture science, techniques, policies, and planning. The journal publishes fully peer-reviewed review articles on topics including global, regional, and national production and market trends in aquaculture, advancements in aquaculture practices and technology, interactions between aquaculture and the environment, indigenous and alien species in aquaculture, genetics and its relation to aquaculture, as well as aquaculture product quality and traceability. The journal is indexed and abstracted in several databases including AgBiotech News & Information (CABI), AgBiotechNet, Agricultural Engineering Abstracts, Environment Index (EBSCO Publishing), SCOPUS (Elsevier), and Web of Science (Clarivate Analytics) among others.