33个遗传多样性水稻品种的泛基因组分析揭示隐藏的基因组变异
2021-06-01   阅读:613   来源:细胞

四川农业大学李仕贵等研究人员合作利用33个遗传多样性水稻品种的泛基因组分析揭示出隐藏的基因组变异。该项研究成果于2021年5月28日在线发表在《细胞》杂志上。

研究人员表示,结构变异(SV)和基因拷贝数变异(gCNV)有助于作物进化、驯化和改良。

研究人员组装了31个具有遗传多样性的水稻品种的高质量基因组。结合两个现有的程序集,研究人员开发了泛基因组规模的基因组资源,包括基于图像的基因组,可提供对水稻基因组变异的访问。具体来说,研究人员发现了171,072个SVs和25,549个gCNVs,并使用光稃稻(Oryza glaberrima )组装来推断 水稻种群中SVs的衍生状态。

研究人员对SV形成机制、基因表达的影响以及亚种群之间分布的分析表明,这些资源可用于了解SV和gCNV如何影响水稻的环境适应性和驯化。当仅使用SNP和单个参考装配体时,这个基于图像的基因组使得基于全基因组关联研究(GWAS)的表型相关遗传变异的鉴定无法检测到。这项工作提供了丰富的群体规模资源以及易于访问的工具,可促进水稻育种以及植物功能基因组学和进化生物学研究。 

附:英文原文

Title: Pan-genome analysis of 33 genetically diverse rice accessions reveals hidden genomic variations

Author: Peng Qin, Hongwei Lu, Huilong Du, Hao Wang, Weilan Chen, Zhuo Chen, Qiang He, Shujun Ou, Hongyu Zhang, Xuanzhao Li, Xiuxiu Li, Yan Li, Yi Liao, Qiang Gao, Bin Tu, Hua Yuan, Bingtian Ma, Yuping Wang, Yangwen Qian, Shijun Fan, Weitao Li, Jing Wang, Min He, Junjie Yin, Ting Li, Ning Jiang, Xuewei Chen, Chengzhi Liang, Shigui Li

Issue&Volume: 2021-05-28

Abstract: Structural variations (SVs) and gene copy number variations (gCNVs) have contributedto crop evolution, domestication, and improvement. Here, we assembled 31 high-qualitygenomes of genetically diverse rice accessions. Coupling with two existing assemblies,we developed pan-genome-scale genomic resources including a graph-based genome, providingaccess to rice genomic variations. Specifically, we discovered 171,072 SVs and 25,549gCNVs and used an Oryza glaberrima assembly to infer the derived states of SVs in the Oryza sativa population. Our analyses of SV formation mechanisms, impacts on gene expression,and distributions among subpopulations illustrate the utility of these resources forunderstanding how SVs and gCNVs shaped rice environmental adaptation and domestication.Our graph-based genome enabled genome-wide association study (GWAS)-based identificationof phenotype-associated genetic variations undetectable when using only SNPs and asingle reference assembly. Our work provides rich population-scale resources pairedwith easy-to-access tools to facilitate rice breeding as well as plant functionalgenomics and evolutionary biology research.

DOI: 10.1016/j.cell.2021.04.046

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