Title: The Genomic Landscapes of Desert Birds Form over Multiple Time Scales
Abstract Spatial models show that genetic differentiation between populations can be explained by factors ranging from geographic distance to environmental resistance across the landscape. However, genomes exhibit a landscape of differentiation, indicating that multiple processes may mediate divergence in different portions of the genome. We tested this idea by comparing alternative geographic predctors of differentiation in ten bird species that co-occur in Sonoran and Chihuahuan Deserts of North America. Using population-level genomic data, we described the genomic landscapes across species and modeled conditions that represented historical and contemporary mechanisms. The characteristics of genomic landscapes differed across species, influenced by varying levels of population structuring and admixture between deserts, and the best-fit models contrasted between the whole genome and partitions along the genome. Both historical and contemporary mechanisms were important in explaining genetic distance, but particularly past and current environments, suggesting that genomic evolution was modulated by climate and habitat There were also different best-ftit models across genomic partitions of the data, indicating that these regions capture different evolutionary histories. These results show that the genomic landscape of differentiation can be associated with alternative geographic factors operating on different portions of the genome, which reflect how heterogeneous patterns of genetic differentiation can evolve across species and genomes. more »« less
Thom, Gregory; Moreira, Lucas Rocha; Batista, Romina; Gehara, Marcelo; Aleixo, Alexandre; Smith, Brian Tilston
(, Genome Biology and Evolution)
Hancock, Angela
(Ed.)
Abstract Geographic barriers are frequently invoked to explain genetic structuring across the landscape. However, inferences on the spatial and temporal origins of population variation have been largely limited to evolutionary neutral models, ignoring the potential role of natural selection and intrinsic genomic processes known as genomic architecture in producing heterogeneity in differentiation across the genome. To test how variation in genomic characteristics (e.g. recombination rate) impacts our ability to reconstruct general patterns of differentiation between species that cooccur across geographic barriers, we sequenced the whole genomes of multiple bird populations that are distributed across rivers in southeastern Amazonia. We found that phylogenetic relationships within species and demographic parameters varied across the genome in predictable ways. Genetic diversity was positively associated with recombination rate and negatively associated with species tree support. Gene flow was less pervasive in genomic regions of low recombination, making these windows more likely to retain patterns of population structuring that matched the species tree. We further found that approximately a third of the genome showed evidence of selective sweeps and linked selection, skewing genome-wide estimates of effective population sizes and gene flow between populations toward lower values. In sum, we showed that the effects of intrinsic genomic characteristics and selection can be disentangled from neutral processes to elucidate spatial patterns of population differentiation.
INTRODUCTION The Anthropocene is marked by an accelerated loss of biodiversity, widespread population declines, and a global conservation crisis. Given limited resources for conservation intervention, an approach is needed to identify threatened species from among the thousands lacking adequate information for status assessments. Such prioritization for intervention could come from genome sequence data, as genomes contain information about demography, diversity, fitness, and adaptive potential. However, the relevance of genomic data for identifying at-risk species is uncertain, in part because genetic variation may reflect past events and life histories better than contemporary conservation status. RATIONALE The Zoonomia multispecies alignment presents an opportunity to systematically compare neutral and functional genomic diversity and their relationships to contemporary extinction risk across a large sample of diverse mammalian taxa. We surveyed 240 species spanning from the “Least Concern” to “Critically Endangered” categories, as published in the International Union for Conservation of Nature’s Red List of Threatened Species. Using a single genome for each species, we estimated historical effective population sizes ( N e ) and distributions of genome-wide heterozygosity. To estimate genetic load, we identified substitutions relative to reconstructed ancestral sequences, assuming that mutations at evolutionarily conserved sites and in protein-coding sequences, especially in genes essential for viability in mice, are predominantly deleterious. We examined relationships between the conservation status of species and metrics of heterozygosity, demography, and genetic load and used these data to train and test models to distinguish threatened from nonthreatened species. RESULTS Species with smaller historical N e are more likely to be categorized as at risk of extinction, suggesting that demography, even from periods more than 10,000 years in the past, may be informative of contemporary resilience. Species with smaller historical N e also carry proportionally higher burdens of weakly and moderately deleterious alleles, consistent with theoretical expectations of the long-term accumulation and fixation of genetic load under strong genetic drift. We found weak support for a causative link between fixed drift load and extinction risk; however, other types of genetic load not captured in our data, such as rare, highly deleterious alleles, may also play a role. Although ecological (e.g., physiological, life-history, and behavioral) variables were the best predictors of extinction risk, genomic variables nonrandomly distinguished threatened from nonthreatened species in regression and machine learning models. These results suggest that information encoded within even a single genome can provide a risk assessment in the absence of adequate ecological or population census data. CONCLUSION Our analysis highlights the potential for genomic data to rapidly and inexpensively gauge extinction risk by leveraging relationships between contemporary conservation status and genetic variation shaped by the long-term demographic history of species. As more resequencing data and additional reference genomes become available, estimates of genetic load, estimates of recent demographic history, and accuracy of predictive models will improve. We therefore echo calls for including genomic information in assessments of the conservation status of species. Genomic information can help predict extinction risk in diverse mammalian species. Across 240 mammals, species with smaller historical N e had lower genetic diversity, higher genetic load, and were more likely to be threatened with extinction. Genomic data were used to train models that predict whether a species is threatened, which can be valuable for assessing extinction risk in species lacking ecological or census data. [Animal silhouettes are from PhyloPic]
Abstract One key research goal of evolutionary biology is to understand the origin and maintenance of genetic variation. In the Cerrado, the South American savanna located primarily in the Central Brazilian Plateau, many hypotheses have been proposed to explain how landscape features (e.g., geographic distance, river barriers, topographic compartmentalization, and historical climatic fluctuations) have promoted genetic structure by mediating gene flow. Here, we asked whether these landscape features have influenced the genetic structure and differentiation in the lizard speciesNorops brasiliensis(Squamata: Dactyloidae). To achieve our goal, we used a genetic clustering analysis and estimate an effective migration surface to assess genetic structure in the focal species. Optimized isolation-by-resistance models and a simulation-based approach combined with machine learning (convolutional neural network; CNN) were then used to infer current and historical effects on population genetic structure through 12 unique landscape models. We recovered five geographically distributed populations that are separated by regions of lower-than-expected gene flow. The results of the CNN showed that geographic distance is the sole predictor of genetic variation inN. brasiliensis, and that slope, rivers, and historical climate had no discernible influence on gene flow. Our novel CNN approach was accurate (89.5%) in differentiating each landscape model. CNN and other machine learning approaches are still largely unexplored in landscape genetics studies, representing promising avenues for future research with increasingly accessible genomic datasets.
ABSTRACT Disentangling the drivers of genomic divergence during speciation is essential to our broader understanding of the generation of biological diversity. Genetic changes accumulate at variable rates across the genome as populations diverge, leading to heterogenous landscapes of genetic differentiation. The ‘islands of differentiation’ that characterise these landscapes harbour genetic signatures of the evolutionary processes that led to their formation, providing insight into the roles of these processes in adaptation and speciation. Here, we study swallows in the genusHirundoto investigate genomic landscapes of differentiation between species spanning a continuum of evolutionary divergence. Genomic differentiation spans a wide range of values (FST= 0.01–0.8) between species, with substantial heterogeneity in genome‐wide patterns. Genomic landscapes are strongly correlated among species (ρ= 0.46–0.99), both at shallow and deep evolutionary timescales, with broad evidence for the role of linked selection together with recombination rate in shaping genomic differentiation. Further dissection of genomic islands reveals patterns consistent with a model of ‘recurrent selection’, wherein differentiation increases due to selection in the same genomic regions in ancestral and descendant populations. Finally, we use measures of the site frequency spectrum to differentiate between alternative forms of selection, providing evidence that genetic hitchhiking due to positive selection has contributed substantially to genomic divergence. Our results demonstrate the pervasive role of recurrent linked selection in shaping genomic divergence despite a history of gene flow and underscore the importance of non‐neutral evolutionary processes in predictive frameworks for genomic divergence in speciation genomics studies.
Abstract Understanding the genetics of adaptation and speciation is critical for a complete picture of how biodiversity is generated and maintained. Heterogeneous genomic differentiation between diverging taxa is commonly documented, with genomic regions of high differentiation interpreted as resulting from differential gene flow, linked selection and reduced recombination rates. Disentangling the roles of each of these non‐exclusive processes in shaping genome‐wide patterns of divergence is challenging but will enhance our knowledge of the repeatability of genomic landscapes across taxa. Here, we combine whole‐genome resequencing and genome feature data to investigate the processes shaping the genomic landscape of differentiation for a sister‐species pair of haplodiploid pine sawflies,Neodiprion leconteiandNeodiprion pinetum. We find genome‐wide correlations between genome features and summary statistics are consistent with pervasive linked selection, with patterns of diversity and divergence more consistently predicted by exon density and recombination rate than the neutral mutation rate (approximated by dS). We also find that both global and local patterns ofFST,dXYandπprovide strong support for recurrent selection as the primary selective process shaping variation across pine sawfly genomes, with some contribution from balancing selection and lineage‐specific linked selection. Because inheritance patterns for haplodiploid genomes are analogous to those of sex chromosomes, we hypothesize that haplodiploids may be especially prone to recurrent selection, even if gene flow occurred throughout divergence. Overall, our study helps fill an important taxonomic gap in the genomic landscape literature and contributes to our understanding of the processes that shape genome‐wide patterns of genetic variation.
Provost, Kaiya, Shue, Stephanie Yun, Forcellati, Meghan, Smith, Brian Tilston, and Yoder, ed., Anne. The Genomic Landscapes of Desert Birds Form over Multiple Time Scales. Molecular Biology and Evolution 39.10 Web. doi:10.1093/molbev/msac200.
Provost, Kaiya, Shue, Stephanie Yun, Forcellati, Meghan, Smith, Brian Tilston, & Yoder, ed., Anne. The Genomic Landscapes of Desert Birds Form over Multiple Time Scales. Molecular Biology and Evolution, 39 (10). https://doi.org/10.1093/molbev/msac200
Provost, Kaiya, Shue, Stephanie Yun, Forcellati, Meghan, Smith, Brian Tilston, and Yoder, ed., Anne.
"The Genomic Landscapes of Desert Birds Form over Multiple Time Scales". Molecular Biology and Evolution 39 (10). Country unknown/Code not available: Oxford University Press. https://doi.org/10.1093/molbev/msac200.https://par.nsf.gov/biblio/10375911.
@article{osti_10375911,
place = {Country unknown/Code not available},
title = {The Genomic Landscapes of Desert Birds Form over Multiple Time Scales},
url = {https://par.nsf.gov/biblio/10375911},
DOI = {10.1093/molbev/msac200},
abstractNote = {Abstract Spatial models show that genetic differentiation between populations can be explained by factors ranging from geographic distance to environmental resistance across the landscape. However, genomes exhibit a landscape of differentiation, indicating that multiple processes may mediate divergence in different portions of the genome. We tested this idea by comparing alternative geographic predctors of differentiation in ten bird species that co-occur in Sonoran and Chihuahuan Deserts of North America. Using population-level genomic data, we described the genomic landscapes across species and modeled conditions that represented historical and contemporary mechanisms. The characteristics of genomic landscapes differed across species, influenced by varying levels of population structuring and admixture between deserts, and the best-fit models contrasted between the whole genome and partitions along the genome. Both historical and contemporary mechanisms were important in explaining genetic distance, but particularly past and current environments, suggesting that genomic evolution was modulated by climate and habitat There were also different best-ftit models across genomic partitions of the data, indicating that these regions capture different evolutionary histories. These results show that the genomic landscape of differentiation can be associated with alternative geographic factors operating on different portions of the genome, which reflect how heterogeneous patterns of genetic differentiation can evolve across species and genomes.},
journal = {Molecular Biology and Evolution},
volume = {39},
number = {10},
publisher = {Oxford University Press},
author = {Provost, Kaiya and Shue, Stephanie Yun and Forcellati, Meghan and Smith, Brian Tilston and Yoder, ed., Anne},
}
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