泛基因组图谱及其在生物多样性基因组学中的应用

IF 31.7 1区 生物学 Q1 GENETICS & HEREDITY
Simona Secomandi, Guido Roberto Gallo, Riccardo Rossi, Carlos Rodríguez Fernandes, Erich D. Jarvis, Andrea Bonisoli-Alquati, Luca Gianfranceschi, Giulio Formenti
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引用次数: 0

摘要

完整的遗传变异数据集是生物多样性基因组研究的关键。长读测序技术允许高度连续的常规组装,单倍型解决参考基因组。然而,即使是完整的,来自单个个体的参考基因组也可能会影响下游分析,不能充分代表群体或物种内的遗传多样性。通过将来自同一种群、物种或属的多个基因组的序列信息整合到单个参考中,由排列一致的高质量基因组集合组装而成的泛基因组图可以克服代表性偏差。在这里,我们回顾了可用的工具和数据结构来构建、可视化和操作泛基因组图,同时提供了实际的例子,并讨论了它们在生物多样性和保护基因组学中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Pangenome graphs and their applications in biodiversity genomics

Pangenome graphs and their applications in biodiversity genomics

Pangenome graphs and their applications in biodiversity genomics
Complete datasets of genetic variants are key to biodiversity genomic studies. Long-read sequencing technologies allow the routine assembly of highly contiguous, haplotype-resolved reference genomes. However, even when complete, reference genomes from a single individual may bias downstream analyses and fail to adequately represent genetic diversity within a population or species. Pangenome graphs assembled from aligned collections of high-quality genomes can overcome representation bias by integrating sequence information from multiple genomes from the same population, species or genus into a single reference. Here, we review the available tools and data structures to build, visualize and manipulate pangenome graphs while providing practical examples and discussing their applications in biodiversity and conservation genomics across the tree of life. Pangenomes integrate multiple genomes to mitigate reference bias. This Review presents tools to build, visualize and manipulate pangenome graphs and also highlights pangenome applications in biodiversity and conservation genomics.
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来源期刊
Nature genetics
Nature genetics 生物-遗传学
CiteScore
43.00
自引率
2.60%
发文量
241
审稿时长
3 months
期刊介绍: Nature Genetics publishes the very highest quality research in genetics. It encompasses genetic and functional genomic studies on human and plant traits and on other model organisms. Current emphasis is on the genetic basis for common and complex diseases and on the functional mechanism, architecture and evolution of gene networks, studied by experimental perturbation. Integrative genetic topics comprise, but are not limited to: -Genes in the pathology of human disease -Molecular analysis of simple and complex genetic traits -Cancer genetics -Agricultural genomics -Developmental genetics -Regulatory variation in gene expression -Strategies and technologies for extracting function from genomic data -Pharmacological genomics -Genome evolution
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