Lewanski Alexander L, Grundler Michael C, Bradburd Gideon S
Department of Integrative Biology, Michigan State University, East Lansing, MI, US.
W.K. Kellogg Biological Station, Michigan State University, Hickory Corners, MI, US.
ArXiv. 2023 Oct 18:arXiv:2310.12070v1.
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 (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 empirical 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.
在存在重组的情况下,一组抽样基因组之间的进化关系无法用单一的谱系树来描述。相反,这些基因组通过一个复杂的、相互交织的谱系集合联系在一起,这个集合在一种称为祖先重组图(ARG)的结构中被形式化。一个ARG广泛地编码了基因组的祖先信息,因此充满了用于解决进化生物学中各种问题的宝贵信息。尽管它有潜在的用途,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ARG在实证进化研究中的认知和应用。令人兴奋的是,最近在ARG重建和模拟方面的进展使基于ARG的方法对于许多问题和系统变得可行。在这篇综述中,我们对ARG进行了通俗易懂的介绍和探索,调查了最近的方法学突破,并描述了ARG在推进现有目标以及开辟进化基因组学中以前无法触及的探究途径方面的潜力。通过这次讨论,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的推断方法。