Genomic selection for hard-to-measure traits in aquaculture: Challenges in balancing genetic gain and diversity

文献类型： 外文期刊

第一作者： Kang, Ziyi

作者： Kang, Ziyi;Kong, Jie;Sui, Juan;Dai, Ping;Luo, Kun;Meng, Xianhong;Chen, Baolong;Cao, Jiawang;Tan, Jian;Fu, Qiang;Luan, Sheng;Kang, Ziyi;Kong, Jie;Sui, Juan;Dai, Ping;Luo, Kun;Meng, Xianhong;Chen, Baolong;Cao, Jiawang;Tan, Jian;Fu, Qiang;Luan, Sheng;Kang, Ziyi;Li, Qi;Wang, Zhaoxin

作者机构：

关键词： The family-based selective breeding program; Genomic selection; Long-term selection; Genetic diversity; Conversion efficiency

期刊名称：AQUACULTURE （ 影响因子：3.9； 五年影响因子：4.4 ）

ISSN： 0044-8486

年卷期： 2025 年 606 卷

页码：

收录情况： SCI

摘要： Genomic selection (GS) is being actively evaluated in aquaculture for its enhanced prediction accuracy over traditional pedigree-based selection (PS). However, the long-term efficiency of GS for the hard-to-measure trait in family-based aquaculture breeding programs remains unclear. This study simulated a typical family-based breeding program for Pacific white shrimp, focusing on a hard-to-measure trait with low heritability (0.10), to investigate genetic gain, genetic diversity, and conversion efficiency (CE) at the genome level. The impacts of panel density, reference group size, and genotype imputation on these metrics were assessed. GS increased genetic gain by 15.57 % to 113.29 % compared to PS when using panel densities of 12 to 1250 SNPs per chromosome. However, GS reduced genetic diversity by 6.36 % to 41.23 %, and decreased CE by 16.54 % to 57.60 % relative to PS, primarily due to poor within-family prediction accuracy, which biased the selection of candidates and the optimization of mating plans. When the within-family prediction accuracy reached 0.7, the CE of GS became comparable to that of PS. Genotype imputation improved CE in GS, particularly at panel densities of 3 to 23 SNPs per chromosome. Genotype imputation increased CE by 23.04 % to 158.72 % compared to non-imputed GS and by 9.70 % relative to PS. The reference group size and panel density exhibited inflection points in their impacts on the genetic gain and CE of GS. Beyond thresholds (panel density: 114 SNPs per chromosome; reference group size: 70 individuals per family), additional resource allocations resulted in significantly diminishing returns. Moreover, the inflection point for panel density was more pronounced than that for reference group size, as evidenced by the lack of significant CE improvements in GS when reference group sizes expanded from 30 to 200 individuals per family. Our findings highlight that managing within-family diversity in GS poses significant challenges, which negatively affect CE and the sustainability of breeding schemes. Nevertheless, low-density SNP panels combined with genotype imputation offer a cost-effective and practical strategy for achieving superior genetic gains while maintaining sustainability. Breeders should prioritize optimizing panel density when implementing GS under resource-limited conditions.

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