A brief history and popularity of methods and tools used to estimate micro-evolutionary forces.

Jonathan Kidner,Panagiotis Theodorou,Jan O Engler,Martin Taubert,Martin Husemann

doi:10.1002/ece3.8076

Abstract

Population genetics is a field of research that predates the current generations of sequencing technology. Those approaches, that were established before massively parallel sequencing methods, have been adapted to these new marker systems (in some cases involving the development of new methods) that allow genome‐wide estimates of the four major micro‐evolutionary forces—mutation, gene flow, genetic drift, and selection. Nevertheless, classic population genetic markers are still commonly used and a plethora of analysis methods and programs is available for these and high‐throughput sequencing (HTS) data. These methods employ various and diverse theoretical and statistical frameworks, to varying degrees of success, to estimate similar evolutionary parameters making it difficult to get a concise overview across the available approaches. Presently, reviews on this topic generally focus on a particular class of methods to estimate one or two evolutionary parameters. Here, we provide a brief history of methods and a comprehensive list of available programs for estimating micro‐evolutionary forces. We furthermore analyzed their usage within the research community based on popularity (citation bias) and discuss the implications of this bias for the software community. We found that a few programs received the majority of citations, with program success being independent of both the parameters estimated and the computing platform. The only deviation from a model of exponential growth in the number of citations was found for the presence of a graphical user interface (GUI). Interestingly, no relationship was found for the impact factor of the journals, when the tools were published, suggesting accessibility might be more important than visibility.

Highlights

The modern synthesis (Mayr & Provine, 1980) has revolutionized our perception of micro-evolution by providing a conceptual and theoretical framework to investigate its processes
Those approaches, that were established before massively parallel sequencing methods, have been adapted to these new marker systems that allow genome-wide estimates of the four major micro-evolutionary forces—mutation, gene flow, genetic drift, and selection
Mutations are the ultimate source of genetic variation, and the precise estimation of mutation rates (μ) is important to understand the mechanisms of evolution (Lynch, 2010)

Summary

Introduction

The modern synthesis (Mayr & Provine, 1980) has revolutionized our perception of micro-evolution by providing a conceptual and theoretical framework to investigate its processes In this synthesis, four main forces driving evolution were described as contributing to changes in allele frequencies: mutation (μ), gene flow (m), drift (estimated as its inverse effective population size (NE)), and selection (s). The types of population genetic markers have broadened substantially from its initial emergence; the earlier studies used allozymes to estimate population differentiation (for a review, see Allendorf, 2016) These were largely replaced by genetic markers, (Sunnucks, 2000), such as random primer binding (RAPD), restriction site polymorphisms (RFLP, AFLP), fragment length variation of satellite DNA (e.g., microsatellites), or sequence polymorphisms (single nucleotide polymorphisms, SNPs). Codominant markers have received increasing attention among researchers due to their greater information content

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