Institute of Crop Science/CIMMYT-China, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
CIMMYT-China Tropical Maize Research Center, Foshan University, Foshan 528231, China.
Plant Commun. 2019 Oct 16;1(1):100005. doi: 10.1016/j.xplc.2019.100005. eCollection 2020 Jan 13.
Although long-term genetic gain has been achieved through increasing use of modern breeding methods and technologies, the rate of genetic gain needs to be accelerated to meet humanity's demand for agricultural products. In this regard, genomic selection (GS) has been considered most promising for genetic improvement of the complex traits controlled by many genes each with minor effects. Livestock scientists pioneered GS application largely due to livestock's significantly higher individual values and the greater reduction in generation interval that can be achieved in GS. Large-scale application of GS in plants can be achieved by refining field management to improve heritability estimation and prediction accuracy and developing optimum GS models with the consideration of genotype-by-environment interaction and non-additive effects, along with significant cost reduction. Moreover, it would be more effective to integrate GS with other breeding tools and platforms for accelerating the breeding process and thereby further enhancing genetic gain. In addition, establishing an open-source breeding network and developing transdisciplinary approaches would be essential in enhancing breeding efficiency for small- and medium-sized enterprises and agricultural research systems in developing countries. New strategies centered on GS for enhancing genetic gain need to be developed.
尽管通过不断增加现代育种方法和技术的使用已经实现了长期的遗传增益，但为了满足人类对农产品的需求，遗传增益的速度仍需要加快。在这方面，基因组选择 (GS) 被认为是最有前途的方法，可用于遗传改良由许多基因控制的复杂性状，这些基因的每个基因的影响都很小。由于家畜的个体价值显著更高，并且在 GS 中可以实现更大的世代间隔缩短，因此家畜科学家率先应用 GS。通过改进田间管理以提高遗传力估计和预测准确性，并开发考虑基因型-环境互作和非加性效应的最佳 GS 模型，同时显著降低成本，可以在植物中大规模应用 GS。此外，将 GS 与其他育种工具和平台集成以加速育种过程，从而进一步提高遗传增益，将会更有效。此外，建立开源育种网络和开发跨学科方法对于提高发展中国家中小企业和农业研究系统的育种效率至关重要。需要制定以 GS 为中心的新策略来提高遗传增益。
