Centre of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502324, India; State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch WA 6150, Western Australia, Australia; The UWA Institute of Agriculture, The University of Western Australia, Perth, WA 6009, Australia.
ICAR-Indian Institute of Pulses Research (IIPR), Kanpur, India.
Trends Genet. 2021 Dec;37(12):1124-1136. doi: 10.1016/j.tig.2021.08.002. Epub 2021 Sep 14.
Crop production systems need to expand their outputs sustainably to feed a burgeoning human population. Advances in genome sequencing technologies combined with efficient trait mapping procedures accelerate the availability of beneficial alleles for breeding and research. Enhanced interoperability between different omics and phenotyping platforms, leveraged by evolving machine learning tools, will help provide mechanistic explanations for complex plant traits. Targeted and rapid assembly of beneficial alleles using optimized breeding strategies and precise genome editing techniques could deliver ideal crops for the future. Realizing desired productivity gains in the field is imperative for securing an adequate future food supply for 10 billion people.
作物生产系统需要可持续地扩大产量,以养活不断增长的人口。基因组测序技术的进步,加上高效的性状作图程序,加速了有益等位基因的出现,从而促进了作物的选育和研究。不同组学和表型平台之间的互操作性不断增强,借助于不断发展的机器学习工具,可以帮助我们对复杂的植物性状提供机制上的解释。利用优化的选育策略和精确的基因组编辑技术,有针对性地快速组装有益等位基因,将为未来培育出理想的作物。在田间实现理想的生产力增益对于确保未来为 100 亿人口提供充足的粮食供应至关重要。