The Paradox of Predictability Provides a Bridge Between Micro- and Macroevolution.

The relationship between the evolutionary dynamics observed in contemporary populations (microevolution) and evolution on timescales of millions of years (macroevolution) has been a topic of considerable debate. Historically, this debate centers on inconsistencies between microevolutionary processes and macroevolutionary patterns. Here, we characterize a striking exception: emerging evidence indicates that standing variation in contemporary populations and macroevolutionary rates of phenotypic divergence are often positively correlated. This apparent consistency between micro- and macroevolution is paradoxical because it contradicts our previous understanding of phenotypic evolution and is so far unexplained. Here, we explore the prospects for bridging evolutionary timescales through an examination of this "paradox of predictability." We begin by explaining why the divergence-variance correlation is a paradox, followed by data analysis to show that the correlation is a general phenomenon across a broad range of temporal scales, from a few generations to tens of millions of years. Then we review complementary approaches from quantitative-genetics, comparative morphology, evo-devo, and paleontology to argue that they can help to address the paradox from the shared vantage point of recent work on evolvability. In conclusion, we recommend a methodological orientation that combines different kinds of short-term and long-term data using multiple analytical frameworks in an interdisciplinary research program. Such a program will increase our general understanding about how evolution works within and across timescales.

Regularized regression can improve estimates of multivariate selection in the face of multicollinearity and limited data.

The breeder's equation, Δ z ¯ = G ß   , allows us to understand how genetics (the genetic covariance matrix, G) and the vector of linear selection gradients ß interact to generate evolutionary trajectories. Estimation of ß using multiple regression of trait values on relative fitness revolutionized the way we study selection in laboratory and wild populations. However, multicollinearity, or correlation of predictors, can lead to very high variances of and covariances between elements of ß, posing a challenge for the interpretation of the parameter estimates. This is particularly relevant in the era of big data, where the number of predictors may approach or exceed the number of observations. A common approach to multicollinear predictors is to discard some of them, thereby losing any information that might be gained from those traits. Using simulations, we show how, on the one hand, multicollinearity can result in inaccurate estimates of selection, and, on the other, how the removal of correlated phenotypes from the analyses can provide a misguided view of the targets of selection. We show that regularized regression, which places data-validated constraints on the magnitudes of individual elements of ß, can produce more accurate estimates of the total strength and direction of multivariate selection in the presence of multicollinearity and limited data, and often has little cost when multicollinearity is low. We also compare standard and regularized regression estimates of selection in a reanalysis of three published case studies, showing that regularized regression can improve fitness predictions in independent data. Our results suggest that regularized regression is a valuable tool that can be used as an important complement to traditional least-squares estimates of selection. In some cases, its use can lead to improved predictions of individual fitness, and improved estimates of the total strength and direction of multivariate selection.

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 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.

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.

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.

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.

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.

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.

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.

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.

A Multivariate Genome-Wide Association Study of Wing Shape in Drosophila melanogaster.

Due to the complexity of genotype-phenotype relationships, simultaneous analyses of genomic associations with multiple traits will be more powerful and informative than a series of univariate analyses. However, in most cases, studies of genotype-phenotype relationships have been analyzed only one trait at a time. Here, we report the results of a fully integrated multivariate genome-wide association analysis of the shape of the Drosophila melanogaster wing in the Drosophila Genetic Reference Panel. Genotypic effects on wing shape were highly correlated between two different laboratories. We found 2396 significant SNPs using a 5% false discovery rate cutoff in the multivariate analyses, but just four significant SNPs in univariate analyses of scores on the first 20 principal component axes. One quarter of these initially significant SNPs retain their effects in regularized models that take into account population structure and linkage disequilibrium. A key advantage of multivariate analysis is that the direction of the estimated phenotypic effect is much more informative than a univariate one. We exploit this fact to show that the effects of knockdowns of genes implicated in the initial screen were on average more similar than expected under a null model. A subset of SNP effects were replicable in an unrelated panel of inbred lines. Association studies that take a phenomic approach, considering many traits simultaneously, are an important complement to the power of genomics.

Quantitative Morphological Variation in the Developing Drosophila Wing.

Quantitative genetic variation in morphology is pervasive in all species and is the basis for the evolution of differences among species. The measurement of morphological form in adults is now beginning to be combined with comparable measurements of form during development. Here we compare the shape of the developing wing to its adult form in a holometabolous insect, Drosophila melanogaster We used protein expression patterns to measure shape in the developing precursors of the final adult wing. Three developmental stages were studied: late larval third instar, post-pupariation and in the adult fly. We studied wild-type animals in addition to mutants of two genes (shf and ds) that have known effects on adult wing shape and size. Despite experimental noise related to the difficulty of comparing developing structures, we found consistent differences in wing shape and size at each developmental stage between genotypes. Quantitative comparisons of variation arising at different developmental stages with the variation in the final structure enable us to determine when variation arises, and to generate hypotheses about the causes of that variation. In addition we provide linear rules allowing us to link wing morphology in the larva, with wing morphology in the pupa. Our approach provides a framework to analyze quantitative morphological variation in the developing fly wing. This framework should help to characterize the natural variation of the larval and pupal wing shape, and to measure the contribution of the processes occurring during these developmental stages to the natural variation in adult wing morphology.

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.

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.

Patterned Anchorage to the Apical Extracellular Matrix Defines Tissue Shape in the Developing Appendages of Drosophila.

How tissues acquire their characteristic shape is a fundamental unresolved question in biology. While genes have been characterized that control local mechanical forces to elongate epithelial tissues, genes controlling global forces in epithelia have yet to be identified. Here, we describe a genetic pathway that shapes appendages in Drosophila by defining the pattern of global tensile forces in the tissue. In the appendages, shape arises from tension generated by cell constriction and localized anchorage of the epithelium to the cuticle via the apical extracellular-matrix protein Dumpy (Dp). Altering Dp expression in the developing wing results in predictable changes in wing shape that can be simulated by a computational model that incorporates only tissue contraction and localized anchorage. Three other wing shape genes, narrow, tapered, and lanceolate, encode components of a pathway that modulates Dp distribution in the wing to refine the global force pattern and thus wing shape.

Linkage Disequilibrium and Inversion-Typing of the Drosophila melanogaster Genome Reference Panel.

We calculated the linkage disequilibrium between all pairs of variants in the Drosophila Genome Reference Panel with minor allele count ≥5. We used r(2) ≥ 0.5 as the cutoff for a highly correlated SNP. We make available the list of all highly correlated SNPs for use in association studies. Seventy-six percent of variant SNPs are highly correlated with at least one other SNP, and the mean number of highly correlated SNPs per variant over the whole genome is 83.9. Disequilibrium between distant SNPs is also common when minor allele frequency (MAF) is low: 37% of SNPs with MAF < 0.1 are highly correlated with SNPs more than 100 kb distant. Although SNPs within regions with polymorphic inversions are highly correlated with somewhat larger numbers of SNPs, and these correlated SNPs are on average farther away, the probability that a SNP in such regions is highly correlated with at least one other SNP is very similar to SNPs outside inversions. Previous karyotyping of the DGRP lines has been inconsistent, and we used LD and genotype to investigate these discrepancies. When previous studies agreed on inversion karyotype, our analysis was almost perfectly concordant with those assignments. In discordant cases, and for inversion heterozygotes, our results suggest errors in two previous analyses or discordance between genotype and karyotype. Heterozygosities of chromosome arms are, in many cases, surprisingly highly correlated, suggesting strong epsistatic selection during the inbreeding and maintenance of the DGRP lines.

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.

Evolution of morphological allometry.

Morphological allometry refers to patterns of covariance between body parts resulting from variation in body size. Whether measured during growth (ontogenetic allometry), among individuals at similar developmental stage (static allometry), or among populations or species (evolutionary allometry), allometric relationships are often tight and relatively invariant. Consequently, it has been suggested that allometries have low evolvability and could constrain phenotypic evolution by forcing evolving species along fixed trajectories. Alternatively, allometric relationships may result from natural selection for functional optimization. Despite nearly a century of active research, distinguishing between these alternatives remains difficult, partly due to wide differences in the meaning assigned to the term allometry. In particular, a broad use of the term, encompassing any monotonic relationship between body parts, has become common. This usage breaks the connection to the proportional growth regulation that motivated Huxley's original narrow-sense use of allometry to refer to power-law relationships between traits. Focusing on the narrow-sense definition of allometry, we review here evidence for and against the allometry-as-a-constraint hypothesis. Although the low evolvability and the evolutionary invariance of the static allometric slope observed in some studies suggest a possible constraining effect of this parameter on phenotypic evolution, the lack of knowledge about selection on allometry prevents firm conclusions.