A pangenome analysis pipeline provides insights into functional gene identification in rice

文献类型： 外文期刊

第一作者： Wang, Jian

作者： Wang, Jian;Yang, Wu;Zhang, Shaohong;Hu, Haifei;Dong, Jingfang;Chen, Luo;Ma, Yamei;Yang, Tifeng;Zhou, Lian;Chen, Jiansong;Liu, Bin;Zhao, Junliang;Wang, Jian;Yang, Wu;Zhang, Shaohong;Hu, Haifei;Dong, Jingfang;Chen, Luo;Ma, Yamei;Yang, Tifeng;Zhou, Lian;Chen, Jiansong;Liu, Bin;Zhao, Junliang;Wang, Jian;Yang, Wu;Zhang, Shaohong;Hu, Haifei;Dong, Jingfang;Chen, Luo;Ma, Yamei;Yang, Tifeng;Zhou, Lian;Chen, Jiansong;Liu, Bin;Zhao, Junliang;Hu, Haifei;Li, Chengdao;Yuan, Yuxuan;Yuan, Yuxuan;Edwards, David;Edwards, David

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关键词： Pangenome; Presence; absence variation; Genomic diversity; PAV-based GWAS

期刊名称：GENOME BIOLOGY （ 影响因子：12.3； 五年影响因子：17.4 ）

ISSN： 1474-760X

年卷期： 2023 年 24 卷 1 期

页码：

收录情况： SCI

摘要： BackgroundA pangenome aims to capture the complete genetic diversity within a species and reduce bias in genetic analysis inherent in using a single reference genome. However, the current linear format of most plant pangenomes limits the presentation of position information for novel sequences. Graph pangenomes have been developed to overcome this limitation. However, bioinformatics analysis tools for graph format genomes are lacking.ResultsTo overcome this problem, we develop a novel strategy for pangenome construction and a downstream pangenome analysis pipeline (PSVCP) that captures genetic variants' position information while maintaining a linearized layout. Using PSVCP, we construct a high-quality rice pangenome using 12 representative rice genomes and analyze an international rice panel with 413 diverse accessions using the pangenome as the reference. We show that PSVCP successfully identifies causal structural variations for rice grain weight and plant height. Our results provide insights into rice population structure and genomic diversity. We characterize a new locus (qPH8-1) associated with plant height on chromosome 8 undetected by the SNP-based genome-wide association study (GWAS).ConclusionsOur results demonstrate that the pangenome constructed by our pipeline combined with a presence and absence variation-based GWAS can provide additional power for genomic and genetic analysis. The pangenome constructed in this study and the associated genome sequence and genetic variants data provide valuable genomic resources for rice genomics research and improvement in future.

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