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群体规模下复杂基因组中准确、可扩展的结构变异基因分型

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

作者信息

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

机构信息

Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (South China), Ministry of Agriculture and Rural Affairs, College of Horticulture, South China Agricultural University, Guangdong 510642, China.

Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, State Key Laboratory of Tropical Crop Breeding, Laboratory of Crop Gene Resources and Germplasm Enhancement in South China, Ministry of Agriculture and Rural Affairs, Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation of Hainan Province, Hainan 571101, China.

出版信息

Mol Biol Evol. 2025 Jul 30;42(8). doi: 10.1093/molbev/msaf180.

Abstract

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.

摘要

完整基因组组装的比较为表征它们之间的所有遗传差异提供了一种直接方法。然而,现有工具通常局限于特定的比对器或针对特定生物体进行了优化,从而缩小了它们的适用性,特别是对于大型且重复的植物基因组。在此,我们介绍群体规模组装的结构变异基因分型(SVGAP),这是一种用于在群体水平上从高质量基因组组装中发现、基因分型和注释结构变异(SV)的流程。通过在个体、群体和系统发育背景下使用模拟SV数据集进行广泛的基准测试,我们证明SVGAP在SV发现方面相对于现有工具表现出色。此外,SVGAP是少数能够应对在大型组装基因组样本中对SV进行基因分型挑战的工具之一,并且它会生成完全基因分型的VCF文件。将SVGAP应用于26个玉米基因组,揭示了由着丝粒特异性LTR反转录转座子的大量插入驱动的着丝粒中隐藏的基因组多样性。SVGAP的输出非常适合构建泛基因组,并有助于解释以前未探索的基因组区域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c6e/12362251/a0cd21f8b4ea/msaf180f1.jpg

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