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Accelerating crop genetic gains with genomic selection

机译:通过基因组选择加速作物遗传增益

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Key messageGenomic prediction based on additive genetic effects can accelerate genetic gain. There are opportunities for further improvement by including non-additive effects that access untapped sources of genetic diversity.AbstractSeveral studies have reported a worrying gap between the projected global future demand for plant-based products and the current annual rates of production increase, indicating that enhancing the rate of genetic gain might be critical for future food security. Therefore, new breeding technologies and strategies are required to significantly boost genetic improvement of future crop cultivars. Genomic selection (GS) has delivered considerable genetic gain in animal breeding and is becoming an essential component of many modern plant breeding programmes as well. In this paper, we review the lessons learned from implementing GS in livestock and the impact of GS on crop breeding, and discuss important features for the success of GS under different breeding scenarios. We highlight major challenges associated with GS including rapid genotyping, phenotyping, genotype-by-environment interaction and non-additivity and give examples for opportunities to overcome these issues. Finally, the potential of combining GS with other modern technologies in order to maximise the rate of crop genetic improvement is discussed, including the potential of increasing prediction accuracy by integration of crop growth models in GS frameworks.
机译:基于添加剂遗传效应的关键消息预测可以加速​​遗传增益。通过包括访问未开发的遗传多样性来源的非添加效应,有机会进一步改善。抽象鉴定的研究已经报告了预计的全球未来对工厂产品的需求和目前的产量增长率之间的令人担忧的差距,表明增强遗传增益率可能对未来的粮食安全至关重要。因此,需要新的育种技术和策略来显着提高未来作物品种的遗传改善。基因组选择(GS)在动物育种中提供了相当大的遗传增益,也成为许多现代植物育种计划的重要组成部分。在本文中,我们审查了从牲畜中实施GS和GS对作物育种的影响的经验教训,并在不同育种情景下讨论GS成功的重要特征。我们突出了与GS相关的主要挑战,包括快速基因分型,表型,基因型 - 环境相互作用和非增殖性,并为克服这些问题提供机会的示例。最后,讨论了将GS与其他现代技术组合以最大化作物遗传改进率的潜力,包括通过在GS框架中集成作物生长模型来增加预测准确性的可能性。

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