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Analysis of genetic architecture and favorable allele usage of agronomic traits in a large collection of Chinese rice accessions

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Abstract

Genotyping and phenotyping large natural populations provide opportunities for population genomic analysis and genome-wide association studies (GWAS). Several rice populations have been re-sequenced in the past decade; however, many major Chinese rice cultivars were not included in these studies. Here, we report large-scale genomic and phenotypic datasets for a collection mainly comprised of 1,275 rice accessions of widely planted cultivars and parental hybrid rice lines from China. The population was divided into three indica/Xian and three japonica/Geng phylogenetic subgroups that correlate strongly with their geographic or breeding origins. We acquired a total of 146 phenotypic datasets for 29 agronomic traits under multi-environments for different subpopulations. With GWAS, we identified a total of 143 significant association loci, including three newly identified candidate genes or alleles that control heading date or amylose content. Our genotypic analysis of agronomically important genes in the population revealed that many favorable alleles are underused in elite accessions, suggesting they may be used to provide improvements in future breeding efforts. Our study provides useful resources for rice genetics research and breeding.

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Acknowledgements

This work was partially supported by the Chinese Academy of Sciences “Strategic Priority Research Program” fund (XDA08020302) and grants from State Key Laboratory of Plant Genomics.

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  1. Contributed equally to this work

Authors and Affiliations

  1. State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China

    Xiuxiu Li, Zhuo Chen, Hongwei Lu, Ming Qi, Ying Yu, Bingke Jiao, Xianfeng Zhao, Qiang Gao, Shanguo Yao, Zhukuang Cheng, Lihuang Zhu, Yongbiao Xue, Chengcai Chu & Chengzhi Liang

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Xiuxiu Li, Zhuo Chen, Hongwei Lu & Chengzhi Liang

  3. Biotechnology Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, 150086, China

    Guomin Zhang, Juntao Ma, Liyan Zhang, Yongli Wang & Lingwei Deng

  4. Rice Research Institute, State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China

    Peng Qin, Hao Wang & Shigui Li

  5. Lixiahe Agricultural Research Institute of Jiangsu Province, Yangzhou, 225009, China

    Yunyu Wu & Aihong Li

  6. Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing, 210095, China

    Yunyu Wu & Aihong Li

  7. State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan University, Kunming, 650091, China

    Diqiu Yu

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  1. Xiuxiu Li
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  2. Zhuo Chen
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Corresponding authors

Correspondence to Aihong Li, Shigui Li or Chengzhi Liang.

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Accession numbers

All raw reads generated for rice accessions used in this study have been deposited in the National Genomics Data Center with BioProject PRJCA000322 and GSA accession CRA000167.

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The author(s) declare that they have no conflict of interest.

Supporting Information

Figure S1 SNP density and distribution across the genome.

Figure S2 Linkage disequilibrium differentiation in different rice varietal groups.

Figure S3 GWAS of heading date for NE-GJ and CN-Mix GWAS panels.

Figure S4 GWAS of grain length for NE-GJ and CN-Mix GWAS panels.

Figure S5 GWAS of grain width for NE-GJ and CN-Mix GWAS panels.

Figure S6 The phenotype values were correlated well with genotypes of agronomically important functional genes.

Figure S7 Signals associated with multiple traits.

Figure S8 Local Manhattan plots for amylase content and grain length.

Figure S9 Association signals for heading date with OsMADS51 as a candidate gene.

Figure S10 The allele types of 63 genes containing functionally verified natural variants in all 1,275 rice accessions.

Table S1 The list of collected 1,275 rice accessions as well as their subpopulation classification and sequence information

Table S2 List of phenotypes used for GWAS

Table S3 The agro-ecologically diverse locations of multiple agronomic traits collected for NE-GJ and CN-Mix population panels

Table S4 The agronomic traits and multi-environmental phenotypes used in three NE-GJ-related GWAS panels

Table S5 The agronomic traits and multi-environmental phenotypes used in three CN-Mix-related GWAS panels

Table S6 The Pearson’s correlation between different locations in pair for all measured traits in multi-environments

Table S7 The associated loci and known genes located closely of all GWAS panels

Table S8 The allele types of 63 genes containing functionally verified natural variations in all 1,275 rice accessions

Table S9 The multiple comparisons (LSD) were evaluated for all known alleles of 27 agronomically important genes

The supporting information is available online at http://life.scichina.com and https://link.springer.com. The supporting materials are published as submitted, without typesetting or editing. The responsibility for scientific accuracy and content remains entirely with the authors.

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Li, X., Chen, Z., Zhang, G. et al. Analysis of genetic architecture and favorable allele usage of agronomic traits in a large collection of Chinese rice accessions. Sci. China Life Sci. 63, 1688–1702 (2020). https://doi.org/10.1007/s11427-019-1682-6

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