The Role of (Co)variation in Shaping the Response to Selection in New World Leaf-Nosed Bats.

AbstractUnderstanding and predicting the evolutionary responses of complex morphological traits to selection remains a major challenge in evolutionary biology. Because traits are genetically correlated, selection on a particular trait produces both direct effects on the distribution of that trait and indirect effects on other traits in the population. The correlations between traits can strongly impact evolutionary responses to selection and may thus impose constraints on adaptation. Here, we used museum specimens and comparative quantitative genetic approaches to investigate whether the covariation among cranial traits facilitated or constrained the response to selection during the major dietary transitions in one of the world's most ecologically diverse mammalian families-the phyllostomid bats. We reconstructed the set of net selection gradients that would have acted on each cranial trait during the major transitions to feeding specializations and decomposed the selection responses into their direct and indirect components. We found that for all transitions, most traits capturing craniofacial length evolved toward adaptive directions owing to direct selection. Additionally, we showed instances of dietary transitions in which the complex interaction between the patterns of covariation among traits and the strength and direction of selection either constrained or facilitated evolution. Our work highlights the importance of considering the within-species covariation estimates to quantify evolvability and to disentangle the relative contribution of variational constraints versus selective causes for observed patterns.

Mutation predicts 40 million years of fly wing evolution.

Mutation enables evolution, but the idea that adaptation is also shaped by mutational variation is controversial. Simple evolutionary hypotheses predict such a relationship if the supply of mutations constrains evolution, but it is not clear that constraints exist, and, even if they do, they may be overcome by long-term natural selection. Quantification of the relationship between mutation and phenotypic divergence among species will help to resolve these issues. Here we use precise data on over 50,000 Drosophilid fly wings to demonstrate unexpectedly strong positive relationships between variation produced by mutation, standing genetic variation, and the rate of evolution over the last 40 million years. Our results are inconsistent with simple constraint hypotheses because the rate of evolution is very low relative to what both mutational and standing variation could allow. In principle, the constraint hypothesis could be rescued if the vast majority of mutations are so deleterious that they cannot contribute to evolution, but this also requires the implausible assumption that deleterious mutations have the same pattern of effects as potentially advantageous ones. Our evidence for a strong relationship between mutation and divergence in a slowly evolving structure challenges the existing models of mutation in evolution.

Predicting the Evolution of Sexual Dimorphism in Gene Expression.

Sexual dimorphism in gene expression is likely to be the underlying source of dimorphism in a variety of traits. Many analyses implicitly make the assumption that dimorphism only evolves when selection favors different phenotypes in the two sexes, although theory makes clear that it can also evolve as an indirect response to other kinds of selection. Furthermore, previous analyses consider the evolution of a single transcript or trait at a time, ignoring the genetic covariance with other transcripts and traits. We first show which aspects of the genetic-variance-covariance matrix, G, affect dimorphism when these assumptions about selection are relaxed. We then reanalyze gene expression data from Drosophila melanogaster with these predictions in mind. Dimorphism of gene expression for individual transcripts shows the signature of both direct selection for dimorphism and indirect responses to selection. To account for the effect of measurement error on evolutionary predictions, we estimated a G matrix for eight linear combinations of expression traits. Sex-specific genetic variances in female- and male-biased transcription, as well as one relatively unbiased combination, were quite unequal, ensuring that most forms of selection on these traits will have large effects on dimorphism. Predictions of response to selection based on the whole G matrix showed that sexually concordant and antagonistic selection are equally capable of changing sexual dimorphism. In addition, the indirect responses of dimorphism due to cross-trait covariances were quite substantial. The assumption that sexual dimorphism in transcription is an adaptation could be incorrect in many specific cases.

Predicting Multivariate Responses of Sexual Dimorphism to Direct and Indirect Selection.

AbstractSexual dimorphism is often assumed to result from balancing the strength of antagonistic selection in favor of dimorphism against the degree of constraint imposed by the shared genome of the sexes, reflected in the B matrix of genetic intersexual covariances. To investigate the totality of forces shaping dimorphism, we reparameterized the Lande equation to predict changes in trait averages and trait differences between the sexes. As genetic constraints on the evolution of dimorphism in response to antagonistic selection become larger, dimorphism will tend to respond more rapidly to concordant selection (which favors the same direction of change in male and female traits) than to antagonistic selection. When we apply this theory to four empirical estimates of B in Drosophila melanogaster, the indirect responses of dimorphism to concordant selection are of comparable or larger magnitude than the direct responses of dimorphism to antagonistic selection in two suites of traits with typical levels of intersex correlation. Antagonistic selection is more important in two suites of traits where the intersex correlations are unusually low. This suggests that the evolution of sexual dimorphism may sometimes be dominated by concordant selection rather than antagonistic selection.

Complex constraints on allometry revealed by artificial selection on the wing of Drosophila melanogaster.

Precise exponential scaling with size is a fundamental aspect of phenotypic variation. These allometric power laws are often invariant across taxa and have long been hypothesized to reflect developmental constraints. Here we test this hypothesis by investigating the evolutionary potential of an allometric scaling relationship in drosophilid wing shape that is nearly invariant across 111 species separated by at least 50 million years of evolution. In only 26 generations of artificial selection in a population of Drosophila melanogaster, we were able to drive the allometric slope to the outer range of those found among the 111 sampled species. This response was rapidly lost when selection was suspended. Only a small proportion of this reversal could be explained by breakup of linkage disequilibrium, and direct selection on wing shape is also unlikely to explain the reversal, because the more divergent wing shapes produced by selection on the allometric intercept did not revert. We hypothesize that the reversal was instead caused by internal selection arising from pleiotropic links to unknown traits. Our results also suggest that the observed selection response in the allometric slope was due to a component expressed late in larval development and that variation in earlier development did not respond to selection. Together, these results are consistent with a role for pleiotropic constraints in explaining the remarkable evolutionary stability of allometric scaling.

Phenomics: the next challenge.

A key goal of biology is to understand phenotypic characteristics, such as health, disease and evolutionary fitness. Phenotypic variation is produced through a complex web of interactions between genotype and environment, and such a 'genotype-phenotype' map is inaccessible without the detailed phenotypic data that allow these interactions to be studied. Despite this need, our ability to characterize phenomes - the full set of phenotypes of an individual - lags behind our ability to characterize genomes. Phenomics should be recognized and pursued as an independent discipline to enable the development and adoption of high-throughput and high-dimensional phenotyping.

Making quantitative morphological variation from basic developmental processes: Where are we? The case of the Drosophila wing.

One of the aims of evolutionary developmental biology is to discover the developmental origins of morphological variation. The discipline has mainly focused on qualitative morphological differences (e.g., presence or absence of a structure) between species. Studies addressing subtle, quantitative variation are less common. The Drosophila wing is a model for the study of development and evolution, making it suitable to investigate the developmental mechanisms underlying the subtle quantitative morphological variation observed in nature. Previous reviews have focused on the processes involved in wing differentiation, patterning and growth. Here, we investigate what is known about how the wing achieves its final shape, and what variation in development is capable of generating the variation in wing shape observed in nature. Three major developmental stages need to be considered: larval development, pupariation, and pupal development. The major cellular processes involved in the determination of tissue size and shape are cell proliferation, cell death, oriented cell division and oriented cell intercalation. We review how variation in temporal and spatial distribution of growth and transcription factors affects these cellular mechanisms, which in turn affects wing shape. We then discuss which aspects of the wing morphological variation are predictable on the basis of these mechanisms. Developmental Dynamics 244:1058-1073, 2015. © 2015 Wiley Periodicals, Inc.

On The Importance Of Scale In Evolutionary Quantitative Genetics.

The informed use of scales and units in evolutionary quantitative genetics is often neglected, and naïve standardizations can cause misinterpretations of empirical results. A potentially influential example of such neglect can be found in the recent book by Stevan J. Arnold (2023. Evolutionary Quantitative Genetics Oxford University Press). There, Arnold championed the use of heritability over mean-scaled genetic variance as a measure of evolutionary potential arguing that mean-scaled genetic variances are correlated with trait means while heritabilities are not. Here, we show that Arnold's empirical result is an artifact of ignoring the units in which traits are measured. More importantly, Arnold's argument mistakenly assumes that the goal of mean scaling is to remove the relationship between mean and variance. In our view, the purpose of mean scaling is to put traits with different units on a common scale that makes evolutionary changes, or their potential, readily interpretable and comparable in terms of proportions of the mean.

Direct estimation of per nucleotide and genomic deleterious mutation rates in Drosophila.

Spontaneous mutations are the source of genetic variation required for evolutionary change, and are therefore important for many aspects of evolutionary biology. For example, the divergence between taxa at neutrally evolving sites in the genome is proportional to the per nucleotide mutation rate, u (ref. 1), and this can be used to date speciation events by assuming a molecular clock. The overall rate of occurrence of deleterious mutations in the genome each generation (U) appears in theories of nucleotide divergence and polymorphism, the evolution of sex and recombination, and the evolutionary consequences of inbreeding. However, estimates of U based on changes in allozymes or DNA sequences and fitness traits are discordant. Here we directly estimate u in Drosophila melanogaster by scanning 20 million bases of DNA from three sets of mutation accumulation lines by using denaturing high-performance liquid chromatography. From 37 mutation events that we detected, we obtained a mean estimate for u of 8.4 x 10(-9) per generation. Moreover, we detected significant heterogeneity in u among the three mutation-accumulation-line genotypes. By multiplying u by an estimate of the fraction of mutations that are deleterious in natural populations of Drosophila, we estimate that U is 1.2 per diploid genome. This high rate suggests that selection against deleterious mutations may have a key role in explaining patterns of genetic variation in the genome, and help to maintain recombination and sexual reproduction.

Colloquium papers: Numbering the hairs on our heads: the shared challenge and promise of phenomics.

Evolution and medicine share a dependence on the genotype-phenotype map. Although genotypes exist and are inherited in a discrete space convenient for many sorts of analyses, the causation of key phenomena such as natural selection and disease takes place in a continuous phenotype space whose relationship to the genotype space is only dimly grasped. Direct study of genotypes with minimal reference to phenotypes is clearly insufficient to elucidate these phenomena. Phenomics, the comprehensive study of phenotypes, is therefore essential to understanding biology. For all of the advances in knowledge that a genomic approach to biology has brought, awareness is growing that many phenotypes are highly polygenic and susceptible to genetic interactions. Prime examples are common human diseases. Phenomic thinking is starting to take hold and yield results that reveal why it is so critical. The dimensionality of phenotypic data are often extremely high, suggesting that attempts to characterize phenotypes with a few key measurements are unlikely to be completely successful. However, once phenotypic data are obtained, causation can turn out to be unexpectedly simple. Phenotypic data can be informative about the past history of selection and unexpectedly predictive of long-term evolution. Comprehensive efforts to increase the throughput and range of phenotyping are an urgent priority.

Complexities of recapitulating polygenic effects in natural populations: replication of genetic effects on wing shape in artificially selected and wild-caught populations of Drosophila melanogaster.

Identifying the genetic architecture of complex traits is important to many geneticists, including those interested in human disease, plant and animal breeding, and evolutionary genetics. Advances in sequencing technology and statistical methods for genome-wide association studies have allowed for the identification of more variants with smaller effect sizes, however, many of these identified polymorphisms fail to be replicated in subsequent studies. In addition to sampling variation, this failure to replicate reflects the complexities introduced by factors including environmental variation, genetic background, and differences in allele frequencies among populations. Using Drosophila melanogaster wing shape, we ask if we can replicate allelic effects of polymorphisms first identified in a genome-wide association studies in three genes: dachsous, extra-macrochaete, and neuralized, using artificial selection in the lab, and bulk segregant mapping in natural populations. We demonstrate that multivariate wing shape changes associated with these genes are aligned with major axes of phenotypic and genetic variation in natural populations. Following seven generations of artificial selection along the dachsous shape change vector, we observe genetic differentiation of variants in dachsous and genomic regions containing other genes in the hippo signaling pathway. This suggests a shared direction of effects within a developmental network. We also performed artificial selection with the extra-macrochaete shape change vector, which is not a part of the hippo signaling network, but showed a largely shared direction of effects. The response to selection along the emc vector was similar to that of dachsous, suggesting that the available genetic diversity of a population, summarized by the genetic (co)variance matrix (G), influenced alleles captured by selection. Despite the success with artificial selection, bulk segregant analysis using natural populations did not detect these same variants, likely due to the contribution of environmental variation and low minor allele frequencies, coupled with small effect sizes of the contributing variants.

A modelling framework for the analysis of artificial-selection time series.

Artificial-selection experiments constitute an important source of empirical information for breeders, geneticists and evolutionary biologists. Selected characters can generally be shifted far from their initial state, sometimes beyond what is usually considered as typical inter-specific divergence. A careful analysis of the data collected during such experiments may thus reveal the dynamical properties of the genetic architecture that underlies the trait under selection. Here, we propose a statistical framework describing the dynamics of selection-response time series. We highlight how both phenomenological models (which do not make assumptions on the nature of genetic phenomena) and mechanistic models (explaining the temporal trends in terms of e.g. mutations, epistasis or canalization) can be used to understand and interpret artificial-selection data. The practical use of the models and their implementation in a software package are demonstrated through the analysis of a selection experiment on the shape of the wing in Drosophila melanogaster.

Direct estimation of the mitochondrial DNA mutation rate in Drosophila melanogaster.

Mitochondrial DNA (mtDNA) variants are widely used in evolutionary genetics as markers for population history and to estimate divergence times among taxa. Inferences of species history are generally based on phylogenetic comparisons, which assume that molecular evolution is clock-like. Between-species comparisons have also been used to estimate the mutation rate, using sites that are thought to evolve neutrally. We directly estimated the mtDNA mutation rate by scanning the mitochondrial genome of Drosophila melanogaster lines that had undergone approximately 200 generations of spontaneous mutation accumulation (MA). We detected a total of 28 point mutations and eight insertion-deletion (indel) mutations, yielding an estimate for the single-nucleotide mutation rate of 6.2 x 10(-8) per site per fly generation. Most mutations were heteroplasmic within a line, and their frequency distribution suggests that the effective number of mitochondrial genomes transmitted per female per generation is about 30. We observed repeated occurrences of some indel mutations, suggesting that indel mutational hotspots are common. Among the point mutations, there is a large excess of G-->A mutations on the major strand (the sense strand for the majority of mitochondrial genes). These mutations tend to occur at nonsynonymous sites of protein-coding genes, and they are expected to be deleterious, so do not become fixed between species. The overall mtDNA mutation rate per base pair per fly generation in Drosophila is estimated to be about 10x higher than the nuclear mutation rate, but the mitochondrial major strand G-->A mutation rate is about 70x higher than the nuclear rate. Silent sites are substantially more strongly biased towards A and T than nonsynonymous sites, consistent with the extreme mutation bias towards A+T. Strand-asymmetric mutation bias, coupled with selection to maintain specific nonsynonymous bases, therefore provides an explanation for the extreme base composition of the mitochondrial genome of Drosophila.

A mutation accumulation assay reveals a broad capacity for rapid evolution of gene expression.

Mutation is the ultimate source of biological diversity because it generates the variation that fuels evolution. Gene expression is the first step by which an organism translates genetic information into developmental change. Here we estimate the rate at which mutation produces new variation in gene expression by measuring transcript abundances across the genome during the onset of metamorphosis in 12 initially identical Drosophila melanogaster lines that independently accumulated mutations for 200 generations. We find statistically significant mutational variation for 39% of the genome and a wide range of variability across corresponding genes. As genes are upregulated in development their variability decreases, and as they are downregulated it increases, indicating that developmental context affects the evolution of gene expression. A strong correlation between mutational variance and environmental variance shows that there is the potential for widespread canalization. By comparing the evolutionary rates that we report here with differences between species, we conclude that gene expression does not evolve according to strictly neutral models. Although spontaneous mutations have the potential to generate abundant variation in gene expression, natural variation is relatively constrained.

Allometry constrains the evolution of sexual dimorphism in Drosophila across 33 million years of divergence.

Sexual dimorphism is widely viewed as adaptive, reflecting the evolution of males and females toward divergent fitness optima. Its evolution, however, may often be constrained by the shared genetic architecture of the sexes, and by allometry. Here, we investigated the evolution of sexual size dimorphism, shape dimorphism, and their allometric relationship, in the wings of 82 taxa in the family Drosophilidae that have been diverging for at least 33 million years. Shape dimorphism among species was remarkably similar, with males characterized by longer, thinner wings than females. There was, however, quantitative variation among species in both size and shape dimorphism, with evidence that they have adapted to different evolutionary optima in different clades on timescales of about 10 million years. Within species, shape dimorphism was predicted by size, and among species, there was a strong relationship between size dimorphism and shape dimorphism. Allometry constrained the evolution of shape dimorphism for the two most variable traits we studied, but dimorphism was evolutionary labile in other traits. The keys for disentangling alternative explanations for dimorphism evolution are studies of natural and sexual selection, together with a deeper understanding of how microevolutionary parameters of evolvability relate to macroevolutionary patterns of divergence.

Using Delaunay triangulation to sample whole-specimen color from digital images.

Color variation is one of the most obvious examples of variation in nature, but biologically meaningful quantification and interpretation of variation in color and complex patterns are challenging. Many current methods for assessing variation in color patterns classify color patterns using categorical measures and provide aggregate measures that ignore spatial pattern, or both, losing potentially important aspects of color pattern.Here, we present Colormesh, a novel method for analyzing complex color patterns that offers unique capabilities. Our approach is based on unsupervised color quantification combined with geometric morphometrics to identify regions of putative spatial homology across samples, from histology sections to whole organisms. Colormesh quantifies color at individual sampling points across the whole sample.We demonstrate the utility of Colormesh using digital images of Trinidadian guppies (Poecilia reticulata), for which the evolution of color has been frequently studied. Guppies have repeatedly evolved in response to ecological differences between up- and downstream locations in Trinidadian rivers, resulting in extensive parallel evolution of many phenotypes. Previous studies have, for example, compared the area and quantity of discrete color (e.g., area of orange, number of black spots) between these up- and downstream locations neglecting spatial placement of these areas. Using the Colormesh pipeline, we show that patterns of whole-animal color variation do not match expectations suggested by previous work.Colormesh can be deployed to address a much wider range of questions about color pattern variation than previous approaches. Colormesh is thus especially suited for analyses that seek to identify the biologically important aspects of color pattern when there are multiple competing hypotheses or even no a priori hypotheses at all.

A supermatrix-based molecular phylogeny of the family Drosophilidae.

The genus Drosophila is diverse and heterogeneous and contains a large number of easy-to-rear species, so it is an attractive subject for comparative studies. The ability to perform such studies is currently compromised by the lack of a comprehensive phylogeny for Drosophila and related genera. The genus Drosophila as currently defined is known to be paraphyletic with respect to several other genera, but considerable uncertainty remains about other aspects of the phylogeny. Here, we estimate a phylogeny for 176 drosophilid (12 genera) and four non-drosophilid species, using gene sequences for up to 13 different genes per species (average: 4333 bp, five genes per species). This is the most extensive set of molecular data on drosophilids yet analysed. Phylogenetic analyses were conducted with maximum-likelihood (ML) and Bayesian approaches. Our analysis confirms that the genus Drosophila is paraphyletic with 100% support in the Bayesian analysis and 90% bootstrap support in the ML analysis. The subgenus Sophophora, which includes Drosophila melanogaster, is the sister clade of all the other subgenera as well as of most species of six other genera. This sister clade contains two large, well-supported subclades. The first subclade contains the Hawaiian Drosophila, the genus Scaptomyza, and the virilis-repleta radiation. The second contains the immigrans-tripunctata radiation as well as the genera Hirtodrosophila (except Hirtodrosophila duncani), Mycodrosophila, Zaprionus and Liodrosophila. We argue that these results support a taxonomic revision of the genus Drosophila.

Demographic and genetic constraints on evolution.

Populations unable to evolve to selectively favored states are constrained. Genetic constraints occur when additive genetic variance in selectively favored directions is absent (absolute constraints) or present but small (quantitative constraints). Quantitative--unlike absolute--constraints are presumed surmountable given time. This ignores that a population might become extinct before reaching the favored state, in which case demography effectively converts a quantitative into an absolute constraint. Here, we derive criteria for predicting when such conversions occur. We model the demography and evolution of populations subject to optimizing selection that experience either a single shift or a constant change in the optimum. In the single-shift case, we consider whether a population can evolve significantly without declining or else declines temporarily while avoiding low sizes consistent with high extinction risk. We analyze when populations in constantly changing environments evolve sufficiently to ensure long-term growth. From these, we derive formulas for critical levels of genetic variability that define demography-caused absolute constraints. The formulas depend on estimable properties of fitness, population size, or environmental change rates. Each extends to selection on multivariate traits. Our criteria define the nearly null space of a population's G matrix, the set of multivariate directions effectively inaccessible to it via adaptive evolution.

Cross-sex genetic covariances limit the evolvability of wing-shape within and among species of Drosophila.

The independent evolution of males and females is potentially constrained by both sexes inheriting the same alleles from their parents. This genetic constraint can limit the evolvability of complex traits; however, there are few studies of multivariate evolution that incorporate cross-sex genetic covariances in their predictions. Drosophila wing-shape has emerged as a model high-dimensional phenotype; wing-shape is highly evolvable in contemporary populations, and yet perplexingly stable across phylogenetic timescales. Here, we show that cross-sex covariances in Drosophila melanogaster, given by the B-matrix, may considerably bias wing-shape evolution. Using random skewers, we show that B would constrain the response to antagonistic selection by 90%, on average, but would double the response to concordant selection. Both cross-sex within-trait and cross-sex cross-trait covariances determined the predicted response to antagonistic selection, but only cross-sex within-trait covariances facilitated the predicted response to concordant selection. Similar patterns were observed in the direction of extant sexual dimorphism in D. melanogaster, and in directions of most and least dimorphic variation across the Drosophila phylogeny. Our results highlight the importance of considering between-sex genetic covariances when making predictions about evolution on both macro- and microevolutionary timescales, and may provide one more explanatory piece in the puzzle of stasis.

Why does allometry evolve so slowly?

Morphological allometry is striking due to its evolutionary conservatism, making it an example of a certain sort of evolutionary stasis. Organisms that vary in size, whether for developmental, environmental, or evolutionary reasons, adopt shapes that are predictable from that size alone. There are two major hypotheses to explain this. It may be that natural selection strongly favors each allometric pattern, or that organisms lack the development and genetic capacity to produce variant shapes for selection to act on. Using a high-throughput system for measuring the size and shape of Drosophila wings, we documented an allometric pattern that has been virtually unchanged for 40 million years. We performed an artificial selection experiment on the static allometric slope within one species. In just 26 generations, we were able to increase the slope from 1.1 to 1.4, and decrease it to 0.8. Once artificial selection was suspended, the slope rapidly evolved back to a value near the initial static slope. This result decisively rules out the hypothesis that allometry is preserved due to a lack of genetic variation, and provides evidence that natural selection acts to maintain allometric relationships. On the other hand, it seems implausible that selection on allometry in the wing alone could be sufficiently strong to maintain static allometries over millions of years. This suggests that a potential explanation for stasis is selection on a potentially large number of pleiotropic effects. This seems likely in the case of allometry, as the sizes of all parts of the body may be altered when the allometric slope of one body part is changed. Unfortunately, hypotheses about pleiotropy have been very difficult to test. We lay out an approach to begin the systematic study of pleiotropic effects using genetic manipulations and high-throughput phenotyping.