Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China.
State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China.
Nucleic Acids Res. 2023 Nov 10;51(20):10924-10933. doi: 10.1093/nar/gkad840.
Detailed knowledge of the genetic variations in diverse crop populations forms the basis for genetic crop improvement and gene functional studies. In the present study, we analyzed a large rice population with a total of 10 548 accessions to construct a rice super-population variation map (RSPVM), consisting of 54 378 986 single nucleotide polymorphisms, 11 119 947 insertion/deletion mutations and 184 736 presence/absence variations. Assessment of variation detection efficiency for different population sizes revealed a sharp increase of all types of variation as the population size increased and a gradual saturation of that after the population size reached 10 000. Variant frequency analysis indicated that ∼90% of the obtained variants were rare, and would therefore likely be difficult to detect in a relatively small population. Among the rare variants, only 2.7% were predicted to be deleterious. Population structure, genetic diversity and gene functional polymorphism of this large population were evaluated based on different subsets of RSPVM, demonstrating the great potential of RSPVM for use in downstream applications. Our study provides both a rich genetic basis for understanding natural rice variations and a powerful tool for exploiting great potential of rare variants in future rice research, including population genetics and functional genomics.
详细了解不同作物群体中的遗传变异是进行遗传作物改良和基因功能研究的基础。在本研究中,我们分析了一个包含 10548 个个体的大型水稻群体,构建了一个水稻超级群体变异图谱(RSPVM),包含 54378986 个单核苷酸多态性、11119947 个插入/缺失突变和 184736 个存在/缺失变异。不同群体大小下的变异检测效率评估表明,所有类型的变异都随着群体大小的增加而急剧增加,而在群体大小达到 10000 之后则逐渐饱和。变异频率分析表明,约 90%的获得变异是罕见的,因此在相对较小的群体中可能难以检测到。在这些罕见的变异中,只有 2.7%被预测为有害的。基于 RSPVM 的不同子集评估了该大型群体的种群结构、遗传多样性和基因功能多态性,表明 RSPVM 非常适用于下游应用。我们的研究为理解自然水稻变异提供了丰富的遗传基础,也为未来水稻研究中的稀有变异的潜在利用提供了强大的工具,包括群体遗传学和功能基因组学。