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◆ Genetics, selection, evolution : GSE2026-08-27

Genomic selection improves survival time under high ammonia nitrogen stress in Litopenaeus vannamei.

Shuo Fu, Yuan Zhang, Guangbo Wu, Chaoan Guo, Jianyong Liu

一句话结论 · In one sentence

The integration of BLUP with GS provides an economically feasible breeding strategy for shrimp. This approach balances accuracy and cost, making genomic information practical for commercial shrimp breeding.

原始摘要(英文原文)· Original abstract
BACKGROUND: Litopenaeus vannamei is an economically important species in global aquaculture. Enhancing its environmental resistance through selective breeding is important for improving the efficiency of intensive farming. Genomic selection (GS) can speed up genetic improvement, but it has not been widely used in commercial shrimp breeding because genotyping entire candidate populations is too expensive. In this study, we compared the predictive ability of six GS models with that of the traditional pedigree-based best linear unbiased prediction (PBLUP) model to evaluate the effect of GS on the high ammonia nitrogen resistance in L. vannamei. We then proposed and validated a cost-effective breeding strategy that combines BLUP method with GS in the progeny. RESULTS: The heritability of high ammonia nitrogen tolerance was 0.26 from the pedigree model, and 0.56-0.58 from genomic models. GS improved prediction accuracy by 32.45-39.25% compared with pedigree-based PBLUP. Progeny validation based on ssGBLUP showed that the high-resistance group had 11.38-11.82% longer survival time than the sensitive group, with a significant positive correlation between Genomic Estimated Breeding Values (GEBVs) and observed survival time. CONCLUSIONS: The integration of BLUP with GS provides an economically feasible breeding strategy for shrimp. This approach balances accuracy and cost, making genomic information practical for commercial shrimp breeding.
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Genomic selection improves survival time under high ammonia nitrogen stress in Litopenaeus vannamei. — 科研速览 Science Skim