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水产养殖物种的基因组选择

Genomic Selection in Aquaculture Species.

作者信息

Allal François, Nguyen Nguyen Hong

机构信息

MARBEC, Université de Montpellier, CNRS, Ifremer, IRD, Palavas-les-Flots, France.

School of Science, Technology and Engineering, University of the Sunshine Coast, Sippy Downs, QLD, Australia.

出版信息

Methods Mol Biol. 2022;2467:469-491. doi: 10.1007/978-1-0716-2205-6_17.

Abstract

To date, genomic prediction has been conducted in about 20 aquaculture species, with a preference for intra-family genomic selection (GS). For every trait under GS, the increase in accuracy obtained by genomic estimated breeding values instead of classical pedigree-based estimation of breeding values is very important in aquaculture species ranging from 15% to 89% for growth traits, and from 0% to 567% for disease resistance. Although the implementation of GS in aquaculture is of little additional investment in breeding programs already implementing sib testing on pedigree, the deployment of GS remains sparse, but could be boosted by adaptation of cost-effective imputation from low-density panels. Moreover, GS could help to anticipate the effect of climate change by improving sustainability-related traits such as production yield (e.g., carcass or fillet yields), feed efficiency or disease resistance, and by improving resistance to environmental variation (tolerance to temperature or salinity variation). This chapter synthesized the literature in applications of GS in finfish, crustaceans and molluscs aquaculture in the present and future breeding programs.

摘要

迄今为止,基因组预测已在约20种水产养殖物种中开展,且更倾向于家系内基因组选择(GS)。对于GS所涉及的每一个性状,在水产养殖物种中,通过基因组估计育种值而非传统的基于系谱的育种值估计所获得的准确性提升非常显著,生长性状的提升幅度在15%至89%之间,抗病性的提升幅度在0%至567%之间。尽管在已经对系谱进行同胞测试的育种计划中实施GS只需少量额外投资,但GS的应用仍然较少,不过通过采用经济高效的低密度面板推算方法,其应用可能会得到推动。此外,GS有助于通过改善与可持续性相关的性状(如产量,例如胴体或鱼片产量)、饲料效率或抗病性,并提高对环境变化的抗性(对温度或盐度变化的耐受性)来预测气候变化的影响。本章综述了GS在当前和未来育种计划中应用于硬骨鱼类、甲壳类动物和软体动物养殖的文献。

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