大黄鱼游动性能与抗病性之间的遗传联系使得大黄鱼的多性状育种策略成为可能

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
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引用次数: 0

摘要

由于疾病和恶劣的水生环境影响着产业的可持续性和产量,提高鱼类种群的稳健性已成为水产养殖发展的关键问题。在这项研究中,我们确定了大黄鱼游泳性能与抗病能力之间的几个基因位点,并应用基因组选择(GS)技术对游泳性能进行筛选,以产生既提高游泳性能又提高抗病能力的后代。首先,我们通过游泳测试将我们的参考人群分为优秀游泳者(SS)和劣等游泳者(IS),并评估了固有的抗病能力。与先前的研究一致,SS对寄生虫隐核虫的抗性增强。通过对亲本参考群体和候选群体进行基因分型,建立了包含45832个高质量SNP的单核苷酸多态性(SNP)数据库。我们对该数据集进行了游泳表现和抗病性的多性状全基因组关联研究分析,并确定了三个连锁snp,它们与48个潜在的候选基因相关,包括pp3r1b、mapk12b、mapk11和tnfrsf11a。其次,利用BayesB方法建立遗传估计育种模型,计算候选群体的遗传估计育种值(genetic estimated breeding value, GEBV)。选取GEBV值在前12%的个体作为选育株系(SL)的亲本,其余个体作为对照组(CG)。我们发现,与CG相比,SL表现出更高的游泳性能和对C. irritans的抵抗力。我们的研究揭示了与游泳成绩和抗病性有关的遗传基础。这项工作对设计多性状育种策略和提高全鱼适应性具有重要意义,这两者在水产养殖中都是至关重要的。
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Genetic linkage between swimming performance and disease resistance enables multitrait breeding strategies in large yellow croaker

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.

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