Variation of the adaptive substitution rate between species and within genomes

Evolutionary Ecology (2020) 34:315–338 https://doi.org/10.1007/s10682-019-10026-z ORIGINAL PAPER Variation of the adaptive substitution rate between species and within genomes Ana Filipa Moutinho1 · Thomas Bataillon2 · Julien Y. Dutheil1,3 Received: 15 May 2019 / Accepted: 4 December 2019 / Published online: 14 December 2019 © The Author(s) 2019 Abstract The importance of adaptive mutations in molecular evolution is extensively debated. Recent developments in population genomics allow inferring rates of adaptive mutations by fitting a distribution of fitness effects to the observed patterns of polymorphism and divergence at sites under selection and sites assumed to evolve neutrally. Here, we summarize the current state-of-the-art of these methods and review the factors that affect the molecular rate of adaptation. Several studies have reported extensive cross-species variation in the proportion of adaptive amino-acid substitutions (α) and predicted that species with larger effective population sizes undergo less genetic drift and higher rates of adaptation. Disentangling the rates of positive and negative selection, however, revealed that mutations with deleterious effects are the main driver of this population size effect and that adaptive substitution rates vary comparatively little across species. Conversely, rates of adaptive substitution have been documented to vary substantially within genomes. On a genome-wide scale, gene density, recombination and mutation rate were observed to play a role in shaping molecular rates of adaptation, as predicted under models of linked selection. At the gene level, it has been reported that the gene functional category and the macromolecular structure substantially impact the rate of adaptive mutations. Here, we deliver a comprehensive review of methods used to infer the molecular adaptive rate, the potential drivers of adaptive evolution and how positive selection shapes molecular evolution within genes, across genes within species and between species. Keywords Adaptive evolution · Between-species · Within-genomes · Intra-molecular · Molecular evolution * Ana Filipa Moutinho 1 Research Group Molecular Systems Evolution, Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, August‑Thienemann‑Str. 2, 24306 Plön, Germany 2 Bioinformatics Research Center, Aarhus University, C.F. Møllers Allé 8, 8000 Aarhus C, Denmark 3 UMR 5554, Institut des Sciences de l’Evolution, CNRS, IRD, EPHE, Université de Montpellier, Place E. Bataillon, 34095 Montpellier, France 13 Vol.:(0123456789) 316 Evolutionary Ecology (2020) 34:315–338 Introduction After Darwin proposed that natural selection acts as a main driver of evolution, a major goal of evolutionary biologists has been to understand how beneficial mutations shape species adaptation to their environment. Over the years, the number of approaches used to detect positive selection has increased substantially, making use of the increasing amount of genome data available. In particular, methods have been developed to pinpoint genes, or positions within these genes, that exhibit a pattern of genetic variation statistically incompatible with a pure nearly-neutral scenario (Ohta 1992), where mutations are considered to be neutral, nearly neutral or deleterious (i.e. Nielsen et al. 2005; Ometto et al. 2005; Kosiol et al. 2008). The ecological relevance of such candidate genes can be further tested using functional annotations, when available, or experimentally, for instance, by using reverse genetics and ancestral allele reconstruction (i.e. Hilson et al. 2004; Nielsen et al. 2005; Voight et al. 2006; Roux et al. 2014). This allowed to detect instances of adaptive evolution in many functional categories, such as immune genes in ants (Roux et al. 2014) and in hominids (Nielsen et al. 2005), virulence associated genes in pathogens (Stukenbrock et al. 2011; Dong et al. 2014), and coat-color related genes in hares (Jones et al. 2018) and mice (Hoekstra et al. 2006). While such methods allow a detailed understanding of case-studies, they do not enable one to assess the genome-wide distribution of the fitness effects of mutations. By contrast, mutation accumulation (MA) experiments are specifically designed to estimate a genome-wide rate of mutation and distribution of effects of mutations on fitness (i.e. Shaw et al. 2002; Bataillon 2003; Rutter et al. 2012). With this approach, one can infer (1) the number of mutations that led to the divergence between MA lines, and (2) the fitness effects of these mutations on the (fitness-related) trait of interest (i.e. viability or lifetime reproductive success; see Glossary). Previous studies have inferred the presence of beneficial mutations in MA line experiments both in the field and in greenhouse studies of A. thaliana (Shaw et al. 2002; Rutter et al. 2012). Nonetheless, MA approaches can only give insight on recent adaptive events, and, therefore, provide little information regarding the proportion of adaptive genetic differences between species. Furthermore, MA experiments yield too few beneficial mutations to be able to test for the occurrence of genomic regions where adaptive mutations are more likely to occur. Conversely, population genomic approaches only offer indirect insights on mutation rates and fitness effects but can leverage patterns of sequence variation between and within species to infer rates of adaptive evolution, thus providing knowledge on the drivers of adaptation at deeper scales of evolution. The role of positive (a.k.a. Darwinian) selection in molecular evolution is still widely debated (Hey 1999; Gillespie 2000; Kern and Hahn 2018; Jensen et al. 2019). The neutral theory of molecular evolution (Kimura 1968) states that the bulk of segregating polymorphisms is either neutral or deleterious and that the genetic differences between species are explained mainly by neutral substitutions (see Glossary), while beneficial mutations are considered to be too rare to contribute much to the observed polymorphism and divergence. With an increasing amount of data becoming available, however, the question of whether adaptive mutations play a role in molecular evolution can be investigated with a greater precision. “How much of the genetic variation can be explained by adaptive evolution? What is the frequency of adaptive mutations along the genome? Are there regions where adaptive mutations are more likely to occur?” are 13 Evolutionary Ecology (2020) 34:315–338 317 some of the questions that can now be addressed with population genomics data and statistical methods for the inference of selection. Here, we present the current state-of-the-art methods used to model the distribution of fitness effects (DFE) and infer the frequency of adaptive mutations. We then review evidence for variation in the rate of adaptive evolution within genes, within genomes and between species. Synthesis of methods In the f (...truncated)