The era of the ARG: an empiricist's guide to ancestral recombination graphs

TL;DR

This paper reviews ancestral recombination graphs (ARGs), highlighting recent methodological advances that enable their practical use in evolutionary biology to better understand complex genealogical relationships.

Contribution

It provides an accessible overview of ARGs, surveys recent breakthroughs, and discusses their potential to expand research possibilities in evolutionary genomics.

Findings

Recent progress in ARG reconstruction makes their application feasible.

ARGs encode detailed ancestral relationships, offering insights beyond traditional trees.

The review encourages broader adoption of ARG-based methods in empirical studies.

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 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.