Adam Eyre-Walker

The capacity to adapt is essential for a population to avoid extinction in a changing world and is recognized as a global conservation priority. Adaptation requires additive (heritable) genetic variation for traits that influence survival and fecundity, but measuring this variation is difficult, particularly in species of conservation concern. Instead, molecular genetic diversity is often used to infer adaptive potential. However, previous research has cast doubt on the suitability of traditional molecular markers (allozymes and microsatellites) for this purpose given their weak relationship with heritability—a common measure of additive genetic variance. Advances in sequencing technology have since shifted focus toward nucleotide diversity and variation in functional regions, but their practicality for predicting adaptive potential remains debated. Furthermore, heritability itself is a poor proxy for adaptive potential because it depends on environmental variance. We collated 2,113 published estimates of evolvability—a measure of additive genetic variance that avoids environmental confounding—across 193 eukaryotic species, and evaluated how well evolvability is predicted by molecular diversity. We find that microsatellite and nucleotide diversity are not significantly correlated to each other, and neither predict evolvability. Nucleotide diversity explains 1.1% of interspecific differences in evolvability and doubling nucleotide diversity only corresponds to a 11.7% increase in evolvability. With theoretical work, we show that such weak associations are expected. Together, our results suggest that simple molecular measures of genetic variation are insufficient for predicting adaptive potential and reliance on these metrics risks misinforming conservation management.

In honey bees ( Apis mellifera ), the ancient and multifunctional protein Vitellogenin (Vg) is tightly linked to colony health. Vg contributes to several key traits, including nutrient transport, immunity support, and regulation of social behavior. However, the role of selective forces in shaping natural variation in this gene is poorly understood. To address this, we use a population genetic approach based on long‐read sequences to characterize full‐length vg haplotype variation. Using sequences from 543 honey bees sampled in Europe and the USA, including different subspecies and multiple geographical locations and we test whether patterns of variation and divergence are compatible with selection. Our findings show that vg segregates into two main haplotype versions (haplogroups), defined by 65 common polymorphisms, which together account for 69% of the sampled haplotypes. One haplogroup is abundant in A. m. mellifera conservatory samples. At the protein level, the haplogroups differ at only seven positions, all of which are in the protein's lipid‐binding cavity. This concentration at a single functional region motivates the hypothesis that haplogroup differences may affect lipid binding or transport. The remaining 58 polymorphisms are synonymous or in noncoding regions, which could influence gene expression and splicing. We further find that comparisons of variation across our samples are compatible with a history of positive selection at vg , in line with prior work. Taken together, our results document substantial vg haplotype structure across sampled honey bees and identify protein‐coding differences concentrated in the lipid‐binding cavity. This provides a foundation for future work linking vg genetic variation to Vg function and colony‐related phenotypes.

Bacterial genomes often contain many genes that are only present in a subset of strains, the so-called accessory genes. Whether these genes are adaptive, neutral or deleterious remains contentious. Here we introduce a simple test to differentiate between these possibilities. If an accessory gene is adaptive then the sequence of the gene should be conserved, and the ratio of non-synonymous to synonymous diversity, π _n ⁄ π _s , should be less than one. In contrast, if the gene is neutral or deleterious, selection should not conserve the gene sequence, and π _n ⁄ π _s should equal one. We apply this test to accessory genes in Escherichia coli and Staphylococcus aureus , two highly divergent bacterial species with a large and a small pangenome respectively. We find π _n ⁄ π _s 75% of them are, in two highly divergent bacterial species. This radically alters our view of this type of genetic variation and bacterial evolution.

The effective population size ( N _e ) is a fundamental parameter in population genetics. Despite its central importance, there are relatively few estimates of N _e available and there have been limited attempts to compare values across eukaryotes. Here, we estimate long‐term effective population sizes for 120 species, broadly distributed across the eukaryotic tree of life, using nucleotide diversity and direct mutation rate estimates. We find that N _e varies by nearly 4 orders of magnitude and that it shows strong phylogenetic structure across broad taxonomic scales but not within individual lineages. Phylogenetically controlled regressions reveal that Nₑ correlates with key life history traits, including generation time and propagule size, and that nucleotide diversity serves as a useful proxy for Nₑ . Finally, we show that small Nₑ is generally associated with a reduction in the efficacy of natural selection, as indicated by an elevated ratio of non‐synonymous to synonymous diversity (π _N /π _S ), but not with an increase in genome size after accounting for phylogenetic non‐independence. These results provide a broad comparative perspective on the factors driving variation in Nₑ and its evolutionary consequences across eukaryotes.

A population’s ability to adapt is determined by its levels of additive genetic variance (V _A ), and while it is agreed that most organisms have genetic variation for most traits, the extent to which it varies between species is poorly characterised. Here we investigate this question by compiling 3209 and 1852 estimates of heritability and evolvability (the additive genetic variance divided by the square of the mean) estimates respectively, for a variety of traits, from 220 and 172 multicellular eukaryotic species. Using phylogenetic generalised linear mixed models, we find substantial and highly significant interspecific variation in evolvability. Much of the variation is explained by phylogenetic relatedness, with plants in our data having substantially higher evolvability than animals. While heritability also varies between species, the differences are more subtle, and plants are not exceptional. We investigate whether the variation in evolvability and heritability between species is due to variation in the mutation rate, effective population size, genome size, ploidy and recombination rate, but find little evidence of any factor being important. However, the confidence intervals are large suggesting that we have little power to detect any associations between these factors and our estimates of V _A .

A capacity to adapt is essential for a population to avoid extinction in a changing world and is recognised as a global conservation priority. Adaptation requires additive (heritable) genetic variation for traits that influence survival and fecundity, but measuring this variation is difficult, particularly in species of conservation concern. Instead, molecular genetic diversity is often used to infer adaptive potential. However, previous research has cast doubt on the suitability of traditional molecular markers (allozymes and microsatellites) for this purpose given their weak relationship with heritability - a common measure of additive genetic variance. Recent advances in sequencing technology have since shifted focus towards nucleotide diversity and variation in functional regions, but their practicality for predicting adaptive potential remains debated and untested. Furthermore, heritability itself is a poor proxy for adaptive potential because it depends on environmental variance. We collated 2,113 published estimates of evolvability - a measure of additive genetic variance that avoids environmental confounding - across 193 eukaryotic species, and evaluated how well evolvability is predicted by molecular diversity. We find that microsatellite and nucleotide diversity are not significantly correlated to each other, and neither predict evolvability (nucleotide diversity explains 0.7% of interspecific differences in evolvability and doubling nucleotide diversity only corresponds to a 9.2% increase in evolvability). With new theoretical work, we show that such weak associations are expected. Together, our results suggest that simple molecular measures of genetic variation are insufficient for predicting adaptive potential and continued reliance on these metrics risks misinforming conservation management.

Rates of molecular evolution are known to vary across species, often deviating from the classical expectation of a strict molecular clock. In many cases, the rate of molecular evolution has been found to correlate to generation time, an effect that could be explained if species with shorter generation times have higher mutation rates per year. We investigate this hypothesis using direct estimates of the mutation rate for 133 eukaryotic species from diverse taxonomic groups. Using a phylogenetic comparative approach, we find a strong negative correlation between mutation rate per year and generation time, consistent across all phylogenetic groups. Our results provide a simple explanation for why generation time plays a pivotal role in driving rates of molecular evolution across eukaryotes.

Bacteria lose and gain repair genes as they evolve. Here, we investigate the consequences of gain and loss of 11 DNA repair genes across a broad range of bacteria. Using synonymous polymorphisms from bacteria and a set of 50 phylogenetically independent contrasts, we find no evidence that the presence or absence of these 11 genes affects either the overall level of diversity or the pattern of mutation. Using phylogenetic generalized linear squares yields a similar conclusion. It seems likely that the lack of an effect is due to variation in the genetic background and the environment which obscures any effects that the presence or absence of individual genes might have.

Welcome to 2024 at Genome Biology and Evolution (GBE). After a few turbulent years due to the Covid pandemic, this last year has felt relatively normal. Last summer, the Society of Molecular Biology and Evolution (SMBE), the society that owns this journal, ran its annual meeting in person, and the number of submissions to GBE has returned to pre-pandemic levels. We have also been able to launch new initiatives and analyze data on GBE outcomes.

We are launching a series to celebrate the 40th anniversary of the first issue of Molecular Biology and Evolution. In 2024, we will publish virtual issues containing selected papers published in the Society for Molecular Biology and Evolution journals, Molecular Biology and Evolution and Genome Biology and Evolution. Each virtual issue will be accompanied by a perspective that highlights the historic and contemporary contributions of our journals to a specific topic in molecular evolution. This perspective, the first in the series, presents an account of the broad array of methods that have been published in the Society for Molecular Biology and Evolution journals, including methods to infer phylogenies, to test hypotheses in a phylogenetic framework, and to infer population genetic processes. We also mention many of the software implementations that make methods tractable for empiricists. In short, the Society for Molecular Biology and Evolution community has much to celebrate after four decades of publishing high-quality science including numerous important inferential methods.