Biology subjects

Houle, D.

Publications and source records attributed to Houle, D..

10 recordsLinked to original sources

bioRxiv2026

Behavior evolves as a correlated response to selection on cuticle color in Drosophila melanogaster and D. simulans

To predict adaptive evolution, we need to understand the degree to which selection on one trait can constrain or redirect evolutionary responses in other traits. We used artificial selection on cuticle color in Drosophila melanogaster and D. simulans to investigate whether color and behavior evolve in tandem. We selected for light and dark thoracic colors for 16 generations in two populations per species and measured correlated responses in aggression, basal activity, total activity, sleep, and geotaxis. Dark selected individuals consistently showed higher aggression and basal activity than light selected or control flies across both species and sexes, pointing to a modest but repeatable correlated response. In contrast, patterns for geotaxis, sleep, and total activity evolved unpredictably, often varying across species and populations, and showed no clear association with color. Within-population phenotypic correlations between color and aggression were significant but weak (rho = -0.035, rho{superscript 2} = 0.001), suggesting that color is a poor predictor of individual aggressive behavior. Populations evolving higher aggression also tended to evolve higher basal activity (rho = 0.52, p = 0.004), suggesting activity may have evolved as a correlated response rather than through a direct color-activity link. The persistence of correlated responses in aggression and basal activity in response to selection on color is consistent with a conserved genetic basis, such as pleiotropy or linkage disequilibrium, although our data do not distinguish between these mechanisms. Identifying the loci underlying variation in both color and behavior, and testing their effects experimentally, will clarify how multivariate genetic covariance shapes the direction and pace of adaptive evolution.

evolutionary biology↗

bioRxiv2025

Appendometer: A system for simultaneous, high-throughput morphometry of Drosophila legs and wings

O_LIThe inheritance of many different organismal features is correlated, as is their evolution, sug-gesting that we need to understand the pattern and causes of those correlations to understand evolution. Unfortunately, we generally lack the ability to rapidly and accurately measure large numbers of traits, making it difficult to describe the patterns of trait relationships or for-mulate hypothesis about the causes of their entanglement. We have previously developed a system to make high-dimensional measurements of Drosophilid fly wings in live specimens. Here, we report the extension of this approach to rapidly assess the dimensions of the distal leg segments, femur, tibia, and tarsi. Using the system, we describe the covariance of the wing and leg morphology and evaluate the relative rates of evolution of legs and wings. C_LIO_LIWe use two simple suction devices to immobilize and position legs and wings of an anaes-thetized fly for imaging, then take a single image incorporating both appendages. We em-ployed a machine learning method to measure leg segment lengths, which should be broadly applicable across diverse taxa. Experienced users can image the legs and wings of a fly every two minutes, with outlier detection and correction taking approximately 40 seconds. To demonstrate the usefulness of these methods, we measured the legs and wings of over 4,000 specimens from 43 different Drosophilid taxa. We estimated the rate of wing and leg evolu-tion using a phylogenetic mixed model. C_LIO_LIRepeatabilities of leg segments lengths averaged over 80%. The rate of evolution of wing and leg sizes are similar, but the rate of wing proportion evolution is 1.6 times as high as that of leg proportions due to strong allometric changes in wing shape. Within-species variation in leg proportions is highly correlated with the rate of leg proportion evolution, as is true for wings. Relative lengths of leg segments showed a strong pattern of negative correlations be-tween the lengths of the tarsal segments and of the femurs and tibias, while all other segment correlations were positive. This pattern was repeated in the rate estimates, suggesting that se-lection favors tradeoffs between tarsi and the remainder of the leg. C_LIO_LIOur simple system for imaging and measuring legs and wings simultaneously has high throughput and repeatability. It is readily applicable to a wide variety of winged insects and other traits, including wings, that could be imaged. Applied to Drosophila, our morphometric system enlarges the ability to study inheritance, pleiotropy, and evolution in this important model taxon. C_LI

evolutionary biology↗

bioRxiv2022

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 (GWAS) 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 GWAS (Pitchers et al. 2019) in three genes: dachsous (ds), extra-macrochaete (emc) and neuralized (neur), 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 ds shape change vector, we observe genetic differentiation of variants in ds 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 emc 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 ds, 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.

genetics↗

bioRxiv2021

Interactions between xylem traits linked to hydraulics during xylem development optimize growth performance in conifer seedlings

O_LIClimate change has threatened forests globally, challenging tree species ability to track the rapidly changing environment (e.g., drought and temperature rise). Conifer species face strong environmental filters due to climatic seasonality. Investigating how conifers change their hydraulic architecture during xylem development across the growing season may shed light on possible mechanisms underlying hydraulic adaptation in conifers. C_LIO_LILaser microscopy was used to assess the three-dimensional hydraulic architecture of balsam fir (Abies balsamea (Linnaeus) Miller), jack pine (Pinus banksiana Lambert), white spruce (Picea glauca (Moench) Voss), and black spruce (Picea mariana (Miller) Britton, Sterns & Poggenburgh) seedlings. We measured hydraulic-related xylem traits in different regions (from early to latewood), during four years of plant growth. C_LIO_LIThe xylem development of jack pine seedlings contrasts with the other species by maintaining torus overlap (a hydraulic safety-associated xylem trait), relatively constant across the season (from early to latewood), and over the years studied. The expansion of tracheids and torus was positively associated with plant growth. C_LIO_LIPit aperture-torus covariance is central to the seasonal dynamics of jack pine xylem development, which jointly with a rapid tracheid and pit expansion is consistent with strong growth performance. Linking xylem structural changes during xylem development with hydraulics is a major issue for future research to assess conifers vulnerability to climate change. C_LI

ecology↗

bioRxiv2020

Fly wing evolutionary rate is a near-isometric function of mutational variation

If there is abundant mutational and standing genetic variation, most expect that the rate of evolution would be driven primarily by natural selection, and potentially be independent of current variability or variation. Contrary to this expectation, we (H17: Houle et al. 2017 Nature 548:447) found surprisingly strong scaling relationships with slopes near one between mutational variance, standing genetic variance and macro-evolutionary rate in Drosophilid wing traits. Jiang and Zhang (J&Z20: 2020 Evolution https://doi.org/10.1111/evo.14076) have challenged these results and our interpretation of them. J&Z20 showed that the method used in H17 to estimate the scaling relationship between variation at different biological levels is uninformative. Using an alternative method, they estimated that the scaling relationship has a slope substantially less than one, and propose a variant of our neutral subset hypothesis to explain this. Here we use simulations to confirm J&Z20s finding that the H17 method for estimating scaling of variances is uninformative. The simulations also show their alternative method for estimating scaling is likely to be seriously biased towards lower scaling relationships. We propose and verify an alternative approach to calculating scaling relationships based on independently estimated variance matrices, which we call the Q method. Simulations and reanalyses of the Drosophilid data set using the Q method suggests that our original estimates of the scaling relationship were close to the true value. We propose an analytical version of the neutral subset model, and show that it can indeed explain any scaling slope by varying assumptions about the pattern of pleiotropy. We continue to regard neutral subset models as implausible for wing shape in Drosophilids due to the likelihood that wing shape is subject to direct selection. Hybrid models in which pleiotropy reduces the available genetic and mutational variation, and a combination of selection and drift controls the change in species means seem more biologically promising.

evolutionary biology↗

bioRxiv2020

Colormesh: A novel method for quantifying variation in complex color patterns

Color variation is one of the most obvious examples of variation in nature. Objective quantification and interpretation of variation in color and complex patterns is challenging. Assessment of variation in color patterns is limited by the reduction of color into categorical measures and lack of spatial information. We present Colormesh as a novel method for analyzing complex color patterns that offers unique capabilities. Compared to other methods, Colormesh maintains the continuous measure of color at individual sampling points throughout the pattern. This is particularly useful for analyses of variation in color patterns, whether interest is in specific locations or the pattern as a whole. In our approach, the use of Delaunay triangulation to determine sampling location eliminates the need for color patterns to have clearly defined pattern elements, and users are not required to identify discrete color categories. This method is complementary to several other methods available for color pattern quantification, and can be usefully deployed to address a wide range of questions about color pattern variation.

evolutionary biology↗

bioRxiv2020

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 is likely to be incorrect in many specific cases.

evolutionary biology↗

bioRxiv2020

Heterologous production of 1-tuberculosinyladenosine in Mycobacterium kansasii models pathoevolution towards the transcellular lifestyle of Mycobacterium tuberculosis.

Mycobacterium kansasii is an environmental non-tuberculous mycobacterium that causes opportunistic tuberculosis-like disease. It is one of the most closely related species to the M. tuberculosis complex. Using M. kansasii as a proxy for the M. kansasii-M. tuberculosis-common ancestor, we asked whether introducing the M. tuberculosis-specific gene pair Rv3377c-Rv3378c into M. kansasii affects the course of experimental infection. Expression of these genes resulted in the production of an adenosine-linked lipid species, known as 1-tuberculosinyladenosine (1-TbAd), but did not alter growth in vitro under standard conditions. Production of 1-TbAd enhanced growth of M. kansasii under acidic conditions through a bacterial cell-intrinsic mechanism independent of controlling pH in the bulk extracellular and intracellular spaces. Production of 1-TbAd led to greater burden of M. kansasii in the lung of C57Bl/6 mice during the first 24 hours after infection and ex vivo infections of alveolar macrophages recapitulated this phenotype within the same time frame. However, in long-term infections, production of 1-TbAd resulted in impaired bacterial survival in both C57Bl/6 mice and Ccr2-/- mice. We have demonstrated that M. kansasii is a valid surrogate of M. tuberculosis to study virulence factors acquired by the latter organism, yet shown the challenge inherent to studying the complex evolution of mycobacterial pathogenicity with isolated gene complementation. IMPORTANCEThis work sheds light on the role of the lipid 1-tuberculosinyladenosine in the evolution of an environmental ancestor to M. tuberculosis. On a larger scale, it reinforces the importance of horizontal gene transfer in bacterial evolution and examines novel models and methods to provide a better understanding of the subtle effects of individual M. tuberculosis-specific virulence factors in infection settings that are relevant to the pathogen.

microbiology↗

bioRxiv2017

Quantitative morphological variation in the developing Drosophila wing

Quantitative variation in morphology is pervasive in all species and is the basis for the evolution of differences among species. The developmental causes of such variation are a relatively neglected research topic. 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. We measured shape and size variation in the wing of Drosophila melanogaster at three developmental stages: late third instar, post-pupariation and in the adult fly. Flies of a wild-type and two mutants (shf and ds) with effects on the adult wing shape and size were studied. 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. In addition we provide linear rules allowing to link late disc morphology with early wings. 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.

genetics↗

bioRxiv2017

The power of a multivariate approach to genome-wide association studies: an example with Drosophila melanogaster wing shape

Due to the complexity of genotype-phenotype relationships, simultaneous analyses of genomic associations with multiple traits will be more powerful and more informative than a series of univariate analyses. In most cases, however, studies of genotype-phenotype relationships have analyzed only one trait at a time, even as the rapid advances in molecular tools have expanded our view of the genotype to include whole genomes. 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 labs. We found 2,396 significant SNPs using a 5% FDR cutoff in the multivariate analyses, but just 4 significant SNPs in univariate analyses of scores on the first 20 principal component axes. A key advantage of multivariate analysis is that the direction of the estimated phenotypic effect is much more informative than a univariate one. Exploiting this feature, we show that the directions of effects were on average replicable in an unrelated panel of inbred lines. Effects of knockdowns of genes implicated in the initial screen were on average more similar than expected under a null model. Association studies that take a phenomic approach in considering many traits simultaneously are an important complement to the power of genomics. Multivariate analyses of such data are more powerful, more informative, and allow the unbiased study of pleiotropy.

genetics↗