Accurate, Scalable Structural Variant Genotyping in Complex Genomes at Population Scales

文献类型： 外文期刊

第一作者： Hu, Ming

作者： Hu, Ming;Wan, Penglong;Tang, Shuyuan;Chen, Jiahao;Wang, Liang;Liao, Yi;Chen, Chengjie;Zhou, Yongfeng;Chakraborty, Mahul;Chen, Jinfeng;Gaut, Brandon S.;Emerson, J. J.

作者机构：

关键词： structural variation; population genotyping; pangenome; comparing methods; plant genome

期刊名称：MOLECULAR BIOLOGY AND EVOLUTION （ 影响因子：5.3； 五年影响因子：11.9 ）

ISSN： 0737-4038

年卷期： 2025 年 42 卷 8 期

页码：

收录情况： SCI

摘要： Comparisons of complete genome assemblies offer a direct procedure for characterizing all genetic differences among them. However, existing tools are often limited to specific aligners or optimized for specific organisms, narrowing their applicability, particularly for large and repetitive plant genomes. Here, we introduce Structural Variants Genotyping of Assemblies on Population scales (SVGAP), a pipeline for structural variant (SV) discovery, genotyping, and annotation from high-quality genome assemblies at the population level. Through extensive benchmarks using simulated SV datasets at individual, population, and phylogenetic contexts, we demonstrate that SVGAP performs favorably relative to existing tools in SV discovery. Additionally, SVGAP is one of the few tools to address the challenge of genotyping SVs within large assembled genome samples, and it generates fully genotyped VCF files. Applying SVGAP to 26 maize genomes revealed hidden genomic diversity in centromeres, driven by abundant insertions of centromere-specific LTR-retrotransposons. The output of SVGAP is well-suited for pangenome construction and facilitates the interpretation of previously unexplored genomic regions.

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