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ARG 时代:祖先重组图及其在经验进化基因组学中的意义简介。

The era of the ARG: An introduction to ancestral recombination graphs and their significance in empirical evolutionary genomics.

机构信息

Department of Integrative Biology, Michigan State University, East Lansing, Michigan, United States of America.

W.K. Kellogg Biological Station, Michigan State University, Hickory Corners, Michigan, United States of America.

出版信息

PLoS Genet. 2024 Jan 18;20(1):e1011110. doi: 10.1371/journal.pgen.1011110. eCollection 2024 Jan.

Abstract

In the presence of recombination, the evolutionary relationships between a set of sampled genomes cannot be described by a single genealogical tree. Instead, the genomes are related by a complex, interwoven collection of genealogies formalized in a structure called an ancestral recombination graph (ARG). An ARG extensively encodes the ancestry of the genome(s) and thus is replete with valuable information for addressing diverse questions in evolutionary biology. Despite its potential utility, technological and methodological limitations, along with a lack of approachable literature, have severely restricted awareness and application of ARGs in evolution research. Excitingly, recent progress in ARG reconstruction and simulation have made ARG-based approaches feasible for many questions and systems. In this review, we provide an accessible introduction and exploration of ARGs, survey recent methodological breakthroughs, and describe the potential for ARGs to further existing goals and open avenues of inquiry that were previously inaccessible in evolutionary genomics. Through this discussion, we aim to more widely disseminate the promise of ARGs in evolutionary genomics and encourage the broader development and adoption of ARG-based inference.

摘要

在存在重组的情况下,一组采样基因组之间的进化关系不能仅用单个系统发育树来描述。相反,基因组通过复杂的、交织在一起的谱系集合相关联,这些谱系在称为祖先重组图 (ARG) 的结构中形式化。ARG 广泛编码基因组的祖先,因此为解决进化生物学中的各种问题提供了丰富的信息。尽管 ARG 具有潜在的应用价值,但技术和方法上的限制以及缺乏通俗易懂的文献,严重限制了进化研究中对 ARG 的认识和应用。令人兴奋的是,ARG 重建和模拟方面的最新进展使得基于 ARG 的方法在许多问题和系统中成为可能。在这篇综述中,我们提供了对 ARG 的通俗易懂的介绍和探索,调查了最近的方法突破,并描述了 ARG 在进一步实现现有目标和开辟以前在进化基因组学中无法进入的研究途径方面的潜力。通过这一讨论,我们旨在更广泛地传播 ARG 在进化基因组学中的前景,并鼓励更广泛地开发和采用基于 ARG 的推论。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4b4/10796009/d8b96b04c465/pgen.1011110.g001.jpg

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