Biology subjects

Ayroles, J.

Publications and source records attributed to Ayroles, J..

11 recordsLinked to original sources

bioRxiv2026

Development and assessment of tailored illustrations to enhance community understandings of genetics topics

ObjectivesEffective communication about genetics concepts is essential for collaborative anthropological genetics research. However, communication can be challenging because many ideas are abstract and may be especially unfamiliar to communities with limited access to formal education. Indeed, there are no widely adopted models for communicating such information, nor a clear understanding of the social factors that may shape participant engagement. Here, we conducted a qualitative and quantitative, community-driven study to understand how illustrations can be useful to support concept sharing with two Indigenous groups--the Orang Asli of Peninsular Malaysia and the Turkana of Kenya. MethodsWe used a two phase approach to create and evaluate how illustrations can bolster communication about genetics concepts. First, we created images illustrating answers to frequently asked questions about genetics, iteratively updating the illustrations based on participant feedback. Second, we conducted 92 interviews to evaluate the finalized illustrations effectiveness. Finally, we analyzed the interview data using thematic analyses, multivariable modeling, and multiple correspondence analyses to identify patterns in participant understanding and feedback, including age, sex, market integration, and schooling. ResultsParticipants reported high interest in genetics research (92%) and broadly positive perceptions of the illustrations. Familiar, locally-grounded imagery was preferred and associated with greater perceived clarity, while more technical illustrations were more frequently reported as confusing. Quantitative analyses showed strong internal consistency across measures of engagement and understanding, with modest variation by degree of market-integration, schooling, and sex. DiscussionOur findings demonstrate that community-specific visualizations, co-developed through iterative feedback, can effectively support engagement with genetics research in participant communities.

scientific communication and education↗

bioRxiv2022

Chromatin activity identifies differential gene regulation across human ancestries

Current evidence suggests that cis-regulatory elements controlling gene expression may be the predominant target of natural selection in humans and other species. Detecting selection acting on these elements is critical to understanding evolution but remains challenging because we do not know which mutations will affect gene regulation. To address this, we devised an approach to search for lineage-specific selection on chromatin activity, transcription factor binding, and chromosomal looping--critical steps in transcriptional regulation. Applying this approach to lymphoblastoid cells from 831 individuals of either European or African descent, we find strong signals of differential chromatin activity linked to gene expression differences between ancestries in numerous contexts, but no evidence of functional differences in chromosomal looping. Moreover, we show that enhancers rather than promoters display the strongest signs of selection associated with sites of differential transcription factor binding. Overall, our study indicates that some cis-regulatory adaptation may be more easily detected at the level of chromatin than DNA sequence. This work provides a vast resource of genomic interaction data from diverse human populations and establishes a novel selection test that will benefit future study of regulatory evolution in humans and other species.

genomics↗

bioRxiv2022

Wolbachia interacts with the microbiome to shape fitness-associated traits during seasonal adaptation in Drosophila melanogaster

The microbiome contributes to many different host traits, but its role in host adaptation remains enigmatic. The fitness benefits of the microbiome often depend on ecological conditions, but fluctuations in both the microbiome and environment modulate these fitness benefits. Moreover, vertically transmitted bacteria might constrain the ability of both the microbiome and host to respond to changing environments. Drosophila melanogaster provides an excellent system to investigate the evolutionary effects of interactions between the microbiome and the environment. To address this question, we created field mesocosms of D. melanogaster undergoing seasonal adaptation with and without the vertically transmitted bacteria, Wolbachia pipientis. Sampling temporal patterns in the microbiome revealed that Wolbachia constrained microbial diversity. Furthermore, interactions between Wolbachia and the microbiome contributed to fitness-associated traits. Wolbachia often exerted negative fitness effects on hosts, and the microbiome modulated these effects. Our work supports recent theoretical advances suggesting that hosts in temporally fluctuating environments benefit from flexible microbial associations with low transmission fidelity--specifically when changes in the microbiome can better enable host phenotypes to match environment change. We conclude by exploring the consequences of complex interactions between Wolbachia and the microbiome for our understanding of eco-evolutionary processes and the utility of Wolbachia in combating vector-borne disease.

evolutionary biology↗

bioRxiv2022

Latitudinal cline does not predict variation in the microbiome of wild Drosophila melanogaster

Microbiomes affect many aspects of host biology, but the eco-evolutionary forces that shape their diversity in natural populations remain poorly understood. Geographic gradients, like latitudinal clines, generate predictable patterns in biodiversity at macroecological scales, but whether these macro-scale processes apply to host-microbiome interactions is an open question. To address this question, we sampled the microbiomes of 13 natural populations of Drosophila melanogaster along a latitudinal cline in eastern United States. The microbiomes were surprisingly consistent across the cline-latitude did not predict either alpha or beta diversity. Only a narrow taxonomic range of bacteria were present in all microbiomes, indicating that strict taxonomic filtering by the host and neutral ecological dynamics are the primary factors shaping the fly microbiome. Additional temporal sampling across two independent sites revealed significant differences in microbial communities over time, suggesting that local environmental differences that vary at fine spatiotemporal scales are more likely to shape the microbiome. Our findings reveal the complexity of eco-evolutionary interactions shaping microbial variation in D. melanogaster and highlight the need for additional sampling of the microbiomes in natural populations along environmental gradients.

ecology↗

bioRxiv2020

Selection on ancient variations drives the adaptive radiation of Metrosideros across the Hawaiian archipelago

Some of the most spectacular adaptive radiations begin with founder populations on remote islands. How genetically limited founder populations give rise to the striking phenotypic and ecological diversity characteristic of adaptive radiations is a paradox of evolutionary biology. We conducted an evolutionary genomic analysis of genus Metrosideros, a landscape-dominant, incipient adaptive radiation of woody plants that spans a striking range of phenotypes and environments across the Hawaiian Islands. Using nanopore-sequencing, we created a chromosome-level genome assembly for M. polymorpha var. incana and analyzed wholegenome sequences of 131 individuals from 11 taxa sampled across the islands. We found evidence of population structure that grouped taxa by island. Demographic modeling showed concordance between the divergence times of island-specific lineages and the geological formation of individual islands. Gene flow was also detected within and between island taxa, suggesting a complex reticulated evolutionary history. We investigated genomic regions with increased differentiation as these regions may harbor variants involved in local adaptation or reproductive isolation, thus forming the genomic basis of adaptive radiation. We discovered differentiation outliers have arisen from balancing selection on ancient divergent haplotypes that formed before the initial colonization of the archipelago. These regions experienced recurrent divergent selection as lineages colonized and diversified on new islands, and hybridization likely facilitated the transfer of these ancient variants between taxa. Balancing selection on multiple ancient haplotypes-or time-tested variants-may help to explain how lineages with limited gene pools can rapidly diversify to fill myriad ecological niches on remote islands. Significance statementSome of the most spectacular adaptive radiations of plants and animals occur on remote oceanic islands, yet such radiations are preceded by founding events that severely limit genetic variation. How genetically depauperate founder populations give rise to the spectacular phenotypic and ecological diversity characteristic of island adaptive radiations is not known. We generated novel genomic resources for Hawaiian Metrosideros--a hyper-variable incipient adaptive radiation of woody taxa--for insights into the paradox of remote island radiations. We found that Metrosideros colonized each island shortly after formation and diversified within islands through recurrent selection on ancient variations that predate the radiation. Recurring use of ancient variants may explain how genetically depauperate lineages can diversify to fill countless niches on remote islands.

evolutionary biology↗

bioRxiv2020

Wild flies hedge their thermal preference bets in response to seasonal fluctuations

Fluctuating environmental pressures can challenge organisms by repeatedly shifting the optimum phenotype. Two contrasting evolutionary strategies to cope with these fluctuations are 1) evolution of the mean phenotype to follow the optimum (adaptive tracking) or 2) diversifying phenotypes so that at least some individuals have high fitness in the current fluctuation (bet-hedging). Bet-hedging could underlie stable differences in the behavior of individuals that are present even when genotype and environment are held constant. Instead of being simply noise, behavioral variation across individuals may reflect an evolutionary strategy of phenotype diversification. Using geographically diverse wild-derived fly strains and high-throughput assays of individual preference, we tested whether thermal preference variation in Drosophila melanogaster could reflect a bet-hedging strategy. We also looked for evidence that populations from different regions differentially adopt bet-hedging or adaptive-tracking strategies. Computational modeling predicted regional differences in the relative advantage of bet-hedging, and we found patterns consistent with that in regional variation in thermal preference heritability. In addition, we found that temporal patterns in mean preference support bet-hedging predictions and that there is a genetic basis for thermal preference variability. Our empirical results point to bet-hedging in thermal preference as a potentially important evolutionary strategy in wild populations.

evolutionary biology↗

bioRxiv2019

The structure of behavioral variation within a genotype

Individual animals vary in their behaviors. This is true even when they share the same genotype and were reared in the same environment. Clusters of covarying behaviors constitute behavioral syndromes, and an individuals position along such axes of covariation is a representation of their personality. Despite these conceptual frameworks, the structure of behavioral covariation within a genotype is essentially uncharacterized and its mechanistic origins unknown. Passing hundreds of inbred Drosophila individuals through an experimental pipeline that captured hundreds of behavioral measures, we found correlations only between sparse pairs of behaviors. Thus, the space of behavioral variation has many independent dimensions. Manipulating the physiology of the brain, and specific neural populations, altered specific correlations. We also observed that variation in gene expression can predict an individuals position on some behavior axes. This work represents the first steps in understanding the biological mechanisms determining the structure of behavioral variation within a genotype.

neuroscience↗

bioRxiv2019

Urbanization and market-integration have strong, non-linear effects on metabolic health in the Turkana tribe

Cardio-metabolic disease is a leading cause of death worldwide, with high prevalence in western, industrialized societies relative to developing nations and subsistence-level populations. This stark difference has been attributed to the dietary and lifestyle changes associated with industrialization, but current work has relied on health comparisons between separate, genetically distinct populations to draw conclusions. To more robustly determine how lifestyle impacts health, we collected interview and health biomarker data from a single population undergoing a rapid lifestyle transition. Specifically, we sampled Turkana individuals who practice subsistence-level, nomadic pastoralism (the traditional, ancestral way of life for this group), as well as individuals who no longer practice pastoralism and engage either minimally or strongly with the market economy. Comparisons across this lifestyle gradient revealed clear, non-linear effects of industrialization: only individuals with highly urban, market-integrated lifestyles experience increases in BMI, body fat, blood pressure, and other biomarkers of cardio-metabolic health. These health differences are partially mediated by increased consumption of refined carbohydrates, and more strongly by fine-scale measures of urbanicity. Finally, because many Turkana are transitioning between rural and urban areas within their lifetime, we were able to show that being born in an urban area is associated with worse adult metabolic health, independent of adult lifestyle. Together, these analyses provide comprehensive insight into the timing, magnitude, and causes of health declines in urban, industrialized groups - an area of critical study given the massive public health burden of cardio-metabolic disease and the rate at which developing nations are experiencing lifestyle transitions.\n\nSIGNIFICANCEThe \"mismatch\" between evolved human physiology and western, industrialized lifestyles is thought to explain to the current epidemic of cardiovascular disease (CVD). However, this hypothesis has been difficult to test in real time. To do so, we studied a traditional pastoralist group--the Turkana--that is currently transitioning from their ancestral way of life to an urban, industrialized lifestyle. We found that Turkana who move to cities exhibit poor cardio-metabolic health, partially because of a shift toward \"western diets\" high in carbohydrates. We also show that early life urbanicity independently predicts adult health, such that life-long city dwellers will experience the greatest CVD risk. Our work thus uncovers the timing, magnitude, and evolutionary causes of a major health gradient.

evolutionary biology↗

bioRxiv2019

Can the microbiome influence host evolutionary trajectories?

The microbiome shapes many traits in hosts, but we still do not understand how it influences host evolution. To impact host evolution, the microbiome must be heritable and have phenotypic effects on the host. However, the complex inheritance and context-dependence of the microbiome challenges traditional models of organismal evolution. Here, we take a multifaceted approach to identify conditions in which the microbiome influences host evolutionary trajectories. We explore quantitative genetic models to highlight how microbial inheritance and phenotypic effects can modulate host evolutionary responses to selection. We synthesize the literature across diverse taxa to find common scenarios of microbiome driven host evolution. First, hosts may leverage locally adapted microbes, increasing survivorship in stressful environments. Second, microbial variation may increase host phenotypic variation, enabling exploration of novel fitness landscapes. We further illustrate these effects by performing a meta-analysis of artificial selection in Drosophila, finding that bacterial diversity also frequently responds to host selection. We conclude by outlining key avenues of research and experimental procedures to improve our understanding of the complex interplay between hosts and microbiomes. By synthesizing perspectives through multiple conceptual and analytical approaches, we show how microbiomes can influence the evolutionary trajectories of hosts.

evolutionary biology↗

bioRxiv2018

Genetic and environmental perturbations lead to regulatory decoherence

Correlation among traits is a fundamental feature of biological systems. From morphological characters, to transcriptional or metabolic networks, the correlations we routinely observe between traits reflect a shared regulation that remains poorly understood and difficult to study. To address this problem, we developed a new and flexible approach that allows us to identify factors associated with variation in correlation between individuals. Here, we use data from three large human cohorts to study the effects of genetic variation and environmental perturbation on correlations among mRNA transcripts and among NMR metabolites. We first show that environmental exposures (namely, infection and disease) lead to a systematic loss of correlation, which we define as decoherence. Using longitudinal data, we show that decoherent metabolites are better predictors of whether someone will develop metabolic syndrome than metabolites commonly used as biomarkers of this disease. Finally, we show that correlation itself is a trait under genetic control: specifically, we mapped and replicated hundreds of correlation QTLs, which often involve transcription factors or their known target genes. Together, this work furthers our understanding of how and why coordinated biological processes break down, and highlights the role of decoherence in disease emergence.

genomics↗

bioRxiv2017

Supervised machine learning reveals introgressed loci in the genomes of Drosophila simulans and D. sechellia

Hybridization and gene flow between species appears to be common. Even though it is clear that hybridization is widespread across all surveyed taxonomic groups, the magnitude and consequences of introgression are still largely unknown. Thus it is crucial to develop the statistical machinery required to uncover which genomic regions have recently acquired haplotypes via introgression from a sister population. We developed a novel machine learning framework, called FILET (Finding Introgressed Loci via Extra-Trees) capable of revealing genomic introgression with far greater power than competing methods. FILET works by combining information from a number of population genetic summary statistics, including several new statistics that we introduce, that capture patterns of variation across two populations. We show that FILET is able to identify loci that have experienced gene flow between related species with high accuracy, and in most situations can correctly infer which population was the donor and which was the recipient. Here we describe a data set of outbred diploid Drosophila sechellia genomes, and combine them with data from D. simulans to examine recent introgression between these species using FILET. Although we find that these populations may have split more recently than previously appreciated, FILET confirms that there has indeed been appreciable recent introgression (some of which might have been adaptive) between these species, and reveals that this gene flow is primarily in the direction of D. simulans to D. sechellia.\n\nAUTHOR SUMMARYUnderstanding the extent to which species or diverged populations hybridize in nature is crucially important if we are to understand the speciation process. Accordingly numerous research groups have developed methodology for finding the genetic evidence of such introgression. In this report we develop a supervised machine learning approach for uncovering loci which have introgressed across species boundaries. We show that our method, FILET, has greater accuracy and power than competing methods in discovering introgression, and in addition can detect the directionality associated with the gene flow between species. Using whole genome sequences from Drosophila simulans and Drosophila sechellia we show that FILET discovers quite extensive introgression between these species that has occurred mostly from D. simulans to D. sechellia. Our work highlights the complex process of speciation even within a well-studied system and points to the growing importance of supervised machine learning in population genetics.

evolutionary biology↗