Accuracy of Demographic Inferences from the Site Frequency Spectrum: The Case of the Yoruba Population

Resilience of genetic diversity in forest trees over the Quaternary

The effect of past environmental changes on the demography and genetic diversity of natural populations remains a contentious issue and has rarely been investigated across multiple, phylogenetically distant species. Here, we perform comparative population genomic analyses and demographic inferences for seven widely distributed and ecologically contrasting European forest tree species based on concerted sampling of 164 populations across their natural ranges. For all seven species, the effective population size, Ne, increased or remained stable over many glacial cycles and up to 15 million years in the most extreme cases. Surprisingly, the drastic environmental changes associated with the Pleistocene glacial cycles have had little impact on the level of genetic diversity of dominant forest tree species, despite major shifts in their geographic ranges. Based on their trajectories of Ne over time, the seven tree species can be divided into three major groups, highlighting the importance of life history and range size in determining synchronous variation in genetic diversity over time. Altogether, our results indicate that forest trees have been able to retain their evolutionary potential over very long periods of time despite strong environmental changes.

Unveiling the Genome-Wide Consequences of Range Expansion and Mating System Transitions in Primula vulgaris

Genetic diversity is heterogeneously distributed among populations of the same species, due to the joint effects of multiple demographic processes, including range contractions and expansions, and mating systems shifts. Here, we ask how both processes shape genomic diversity in space and time in the classical Primula vulgaris model. This perennial herb originated in the Caucasus region and was hypothesized to have expanded westward following glacial retreat in the Quaternary. Moreover, this species is a long-standing model for mating system transitions, exemplified by shifts from heterostyly to homostyly. Leveraging a high-quality reference genome of the closely related Primula veris and whole-genome resequencing data from both heterostylous and homostylous individuals from populations encompassing a wide distribution of P. vulgaris, we reconstructed the demographic history of P. vulgaris. Results are compatible with the previously proposed hypothesis of range expansion from the Caucasus region approximately 79,000 years ago and suggest later shifts to homostyly following rather than preceding postglacial colonization of England. Furthermore, in accordance with population genetic theoretical predictions, both processes are associated with reduced genetic diversity, increased linkage disequilibrium, and reduced efficacy of purifying selection. A novel result concerns the contrasting effects of range expansion versus shift to homostyly on transposable elements, for the former, process is associated with changes in transposable element genomic content, while the latter is not. Jointly, our results elucidate how the interactions among range expansion, transitions to selfing, and Quaternary climatic oscillations shape plant evolution.

Characterization and distribution of de novo mutations in the zebra finch

Germline de novo mutations (DNMs) provide the raw material for evolution. The DNM rate varies considerably between species, sexes and chromosomes. Here, we identify DNMs in the zebra finch (Taeniopygia guttata) across 16 parent-offspring trios using two genome assemblies of different quality. Using an independent genotyping assay, we validate 82% of the 150 candidate DNMs. DNM rates are consistent between both assemblies, with estimates of 6.14 × 10-9 and 6.36 × 10-9 per site per generation. We observe a strong paternal bias in DNM rates (male-to-female ratio ɑ ≈ 4), but this bias is in transition mutations only, leading to a transition-to-transversion ratio of 3.18 and 3.57. Finally, we find that DNMs tend to be randomly distributed across chromosomes, not associated with recombination hotspots or genic regions. However, the sex chromosome chrZ shows a roughly fourfold increased DNM rate compared to autosomes, which is more than the expected increase due to chrZ spending two-thirds of its time in males. Overall, our results further enhance our understanding of DNMs in passerine songbirds.

Rolling down that mountain: microgeographical adaptive divergence during a fast population expansion along a steep environmental gradient in European beech

Forest tree populations harbour high genetic diversity thanks to large effective population sizes and strong gene flow, allowing them to diversify through adaptation to local environmental pressures within dispersal distance. Many tree populations also experienced historical demographic fluctuations, including spatial population contraction or expansions at various temporal scales, which may constrain their ability to adapt to environmental variations. Our aim is to investigate how recent contraction and expansion events interfere with local adaptation, by studying patterns of adaptive divergence between closely related stands undergoing environmentally contrasted conditions, and having or not recently expanded. To investigate genome-wide signatures of local adaptation while accounting for demography, we analysed divergence in a European beech population by testing pairwise differentiation among four tree stands at ~35k Single Nucleotide Polymorphisms from ~9k genomic regions. We applied three divergence outlier search methods resting on different assumptions and targeting either single SNPs or contiguous genomic regions, while accounting for the effect of population size variations on genetic divergence. We found 27 signals of selective signatures in 19 target regions. Putatively adaptive divergence involved all stand pairs. We retrieved signals both when comparing old-growth stands and recently colonised areas and when comparing stands within the old-growth area. Therefore, adaptive divergence processes have taken place both over short time spans, under strong environmental contrasts, and over short ecological gradients, in populations that have been stable in the long term. This suggests that standing genetic variation supports local, microgeographic divergence processes, which can maintain genetic diversity at the landscape level.

Modelling the demographic history of human North African genomes points to a recent soft split divergence between populations

BACKGROUND

North African human populations present a complex demographic scenario due to the presence of an autochthonous genetic component and population substructure, plus extensive gene flow from the Middle East, Europe, and sub-Saharan Africa.

RESULTS

We conducted a comprehensive analysis of 364 genomes to construct detailed demographic models for the North African region, encompassing its two primary ethnic groups, the Arab and Amazigh populations. This was achieved through an Approximate Bayesian Computation with Deep Learning (ABC-DL) framework and a novel algorithm called Genetic Programming for Population Genetics (GP4PG). This innovative approach enabled us to effectively model intricate demographic scenarios, utilizing a subset of 16 whole genomes at > 30X coverage. The demographic model suggested by GP4PG exhibited a closer alignment with the observed data compared to the ABC-DL model. Both point to a back-to-Africa origin of North African individuals and a close relationship with Eurasian populations. Results support different origins for Amazigh and Arab populations, with Amazigh populations originating back in Epipaleolithic times, while GP4PG supports Arabization as the main source of Middle Eastern ancestry. The GP4PG model includes population substructure in surrounding populations (sub-Saharan Africa and Middle East) with continuous decaying gene flow after population split. Contrary to ABC-DL, the best GP4PG model does not require pulses of admixture from surrounding populations into North Africa pointing to soft splits as drivers of divergence in North Africa.

CONCLUSIONS

We have built a demographic model on North Africa that points to a back-to-Africa expansion and a differential origin between Arab and Amazigh populations.

Genomic insights on conservation priorities for North Sea houting and European lake whitefish (Coregonus spp.)

Population genomics analysis holds great potential for informing conservation of endangered populations. We focused on a controversial case of European whitefish (Coregonus spp.) populations. The endangered North Sea houting is the only coregonid fish that tolerates oceanic salinities and was previously considered a species (C. oxyrhinchus) distinct from European lake whitefish (C. lavaretus). However, no firm evidence for genetic-based salinity adaptation has been available. Also, studies based on microsatellite and mitogenome data suggested surprisingly recent divergence (c. 2500 years bp) between houting and lake whitefish. These data types furthermore have provided no evidence for possible inbreeding. Finally, a controversial taxonomic revision recently classified all whitefish in the region as C. maraena, calling conservation priorities of houting into question. We used whole-genome and ddRAD sequencing to analyse six lake whitefish populations and the only extant indigenous houting population. Demographic inference indicated post-glacial expansion and divergence between lake whitefish and houting occurring not long after the Last Glaciation, implying deeper population histories than previous analyses. Runs of homozygosity analysis suggested not only high inbreeding (FROH up to 30.6%) in some freshwater populations but also FROH up to 10.6% in the houting prompting conservation concerns. Finally, outlier scans provided evidence for adaptation to high salinities in the houting. Applying a framework for defining conservation units based on current and historical reproductive isolation and adaptive divergence led us to recommend that the houting be treated as a separate conservation unit regardless of species status. In total, the results underscore the potential of genomics to inform conservation practices, in this case clarifying conservation units and highlighting populations of concern.

Genomic Analyses Capture the Human-Induced Demographic Collapse and Recovery in a Wide-Ranging Cervid

The glacial cycles of the Quaternary heavily impacted species through successions of population contractions and expansions. Similarly, populations have been intensely shaped by human pressures such as unregulated hunting and land use changes. White-tailed and mule deer survived in different refugia through the Last Glacial Maximum, and their populations were severely reduced after the European colonization. Here, we analyzed 73 resequenced deer genomes from across their North American range to understand the consequences of climatic and anthropogenic pressures on deer demographic and adaptive history. We found strong signals of climate-induced vicariance and demographic decline; notably, multiple sequentially Markovian coalescent recovers a severe decline in mainland white-tailed deer effective population size (Ne) at the end of the Last Glacial Maximum. We found robust evidence for colonial overharvest in the form of a recent and dramatic drop in Ne in all analyzed populations. Historical census size and restocking data show a clear parallel to historical Ne estimates, and temporal Ne/Nc ratio shows patterns of conservation concern for mule deer. Signatures of selection highlight genes related to temperature, including a cold receptor previously highlighted in woolly mammoth. We also detected immune genes that we surmise reflect the changing land use patterns in North America. Our study provides a detailed picture of anthropogenic and climatic-induced decline in deer diversity and clues to understanding the conservation concerns of mule deer and the successful demographic recovery of white-tailed deer.

Past volcanic activity predisposes an endemic threatened seabird to negative anthropogenic impacts

Humans are regularly cited as the main driver of current biodiversity extinction, but the impact of historic volcanic activity is often overlooked. Pre-human evidence of wildlife abundance and diversity are essential for disentangling anthropogenic impacts from natural events. Réunion Island, with its intense and well-documented volcanic activity, endemic biodiversity, long history of isolation and recent human colonization, provides an opportunity to disentangle these processes. We track past demographic changes of a critically endangered seabird, the Mascarene petrel Pseudobulweria aterrima, using genome-wide SNPs. Coalescent modeling suggested that a large ancestral population underwent a substantial population decline in two distinct phases, ca. 125,000 and 37,000 years ago, coinciding with periods of major eruptions of Piton des Neiges. Subsequently, the ancestral population was fragmented into the two known colonies, ca. 1500 years ago, following eruptions of Piton de la Fournaise. In the last century, both colonies declined significantly due to anthropogenic activities, and although the species was initially considered extinct, it was rediscovered in the 1970s. Our findings suggest that the current conservation status of wildlife on volcanic islands should be firstly assessed as a legacy of historic volcanic activity, and thereafter by the increasing anthropogenic impacts, which may ultimately drive species towards extinction.

Demogenomic inference from spatially and temporally heterogeneous samples

Modern and ancient genomes are not necessarily drawn from homogeneous populations, as they may have been collected from different places and at different times. This heterogeneous sampling can be an issue for demographic inferences and results in biased demographic parameters and incorrect model choice if not properly considered. When explicitly accounted for, it can result in very complex models and high data dimensionality that are difficult to analyse. In this paper, we formally study the impact of such spatial and temporal sampling heterogeneity on demographic inference, and we introduce a way to circumvent this problem. To deal with structured samples without increasing the dimensionality of the site frequency spectrum (SFS), we introduce a new structured approach to the existing program fastsimcoal2. We assess the efficiency and relevance of this methodological update with simulated and modern human genomic data. We particularly focus on spatial and temporal heterogeneities to evidence the interest of this new SFS-based approach, which can be especially useful when handling scattered and ancient DNA samples, as in conservation genetics or archaeogenetics.

Inference of the demographic histories and selective effects of human gut commensal microbiota over the course of human history

Despite the importance of gut commensal microbiota to human health, there is little knowledge about their evolutionary histories, including their population demographic histories and their distributions of fitness effects (DFE) of new mutations. Here, we infer the demographic histories and DFEs of 27 of the most highly prevalent and abundant commensal gut microbial species in North Americans over timescales exceeding human generations using a collection of lineages inferred from a panel of healthy hosts. We find overall reductions in genetic variation among commensal gut microbes sampled from a Western population relative to an African rural population. Additionally, some species in North American microbiomes display contractions in population size and others expansions, potentially occurring at several key historical moments in human history. DFEs across species vary from highly to mildly deleterious, with accessory genes experiencing more drift compared to core genes. Within genera, DFEs tend to be more congruent, reflective of underlying phylogenetic relationships. Taken together, these findings suggest that human commensal gut microbes have distinct evolutionary histories, possibly reflecting the unique roles of individual members of the microbiome.

A likelihood-based framework for demographic inference from genealogical trees

The demographic history of a population drives the pattern of genetic variation and is encoded in the gene-genealogical trees of the sampled alleles. However, existing methods to infer demographic history from genetic data tend to use relatively low-dimensional summaries of the genealogy, such as allele frequency spectra. As a step toward capturing more of the information encoded in the genome-wide sequence of genealogical trees, here we propose a novel framework called the genealogical likelihood (gLike), which derives the full likelihood of a genealogical tree under any hypothesized demographic history. Employing a graph-based structure, gLike summarizes across independent trees the relationships among all lineages in a tree with all possible trajectories of population memberships through time and efficiently computes the exact marginal probability under a parameterized demographic model. Through extensive simulations and empirical applications on populations that have experienced multiple admixtures, we showed that gLike can accurately estimate dozens of demographic parameters when the true genealogy is known, including ancestral population sizes, admixture timing, and admixture proportions. Moreover, when using genealogical trees inferred from genetic data, we showed that gLike outperformed conventional demographic inference methods that leverage only the allele-frequency spectrum and yielded parameter estimates that align with established historical knowledge of the past demographic histories for populations like Latino Americans and Native Hawaiians. Furthermore, our framework can trace ancestral histories by analyzing a sample from the admixed population without proxies for its source populations, removing the need to sample ancestral populations that may no longer exist. Taken together, our proposed gLike framework harnesses underutilized genealogical information to offer exceptional sensitivity and accuracy in inferring complex demographies for humans and other species, particularly as estimation of genome-wide genealogies improves.

Recurrent mutation in the ancestry of a rare variant

Recurrent mutation produces multiple copies of the same allele which may be co-segregating in a population. Yet, most analyses of allele-frequency or site-frequency spectra assume that all observed copies of an allele trace back to a single mutation. We develop a sampling theory for the number of latent mutations in the ancestry of a rare variant, specifically a variant observed in relatively small count in a large sample. Our results follow from the statistical independence of low-count mutations, which we show to hold for the standard neutral coalescent or diffusion model of population genetics as well as for more general coalescent trees. For populations of constant size, these counts are distributed like the number of alleles in the Ewens sampling formula. We develop a Poisson sampling model for populations of varying size and illustrate it using new results for site-frequency spectra in an exponentially growing population. We apply our model to a large data set of human SNPs and use it to explain dramatic differences in site-frequency spectra across the range of mutation rates in the human genome.

Species-specific traits mediate avian demographic responses under past climate change

Anticipating species' responses to environmental change is a pressing mission in biodiversity conservation. Despite decades of research investigating how climate change may affect population sizes, historical context is lacking, and the traits that mediate demographic sensitivity to changing climate remain elusive. We use whole-genome sequence data to reconstruct the demographic histories of 263 bird species over the past million years and identify networks of interacting morphological and life history traits associated with changes in effective population size (N_e) in response to climate warming and cooling. Our results identify direct and indirect effects of key traits representing dispersal, reproduction and survival on long-term demographic responses to climate change, thereby highlighting traits most likely to influence population responses to ongoing climate warming.

Interpreting the pervasive observation of U-shaped Site Frequency Spectra

The standard neutral model of molecular evolution has traditionally been used as the null model for population genomics. We gathered a collection of 45 genome-wide site frequency spectra from a diverse set of species, most of which display an excess of low and high frequency variants compared to the expectation of the standard neutral model, resulting in U-shaped spectra. We show that multiple merger coalescent models often provide a better fit to these observations than the standard Kingman coalescent. Hence, in many circumstances these under-utilized models may serve as the more appropriate reference for genomic analyses. We further discuss the underlying evolutionary processes that may result in the widespread U-shape of frequency spectra.

Population genomic structure in Goodman's mouse lemur reveals long-standing separation of Madagascar's Central Highlands and eastern rainforests

Madagascar's Central Highlands are largely composed of grasslands, interspersed with patches of forest. The historical perspective was that Madagascar's grasslands had anthropogenic origins, but emerging evidence suggests that grasslands were a component of the pre-human Central Highlands vegetation. Consequently, there is now vigorous debate regarding the extent to which these grasslands have expanded due to anthropogenic pressures. Here, we shed light on the temporal dynamics of Madagascar's vegetative composition by conducting a population genomic investigation of Goodman's mouse lemur (Microcebus lehilahytsara; Cheirogaleidae). These small-bodied primates occur both in Madagascar's eastern rainforests and in the Central Highlands, making them a valuable indicator species. Population divergences among forest-dwelling mammals will reflect changes to their habitat, including fragmentation, whereas patterns of post-divergence gene flow can reveal formerly wooded migration corridors. To explore these patterns, we used RADseq data to infer population genetic structure, demographic models of post-divergence gene flow, and population size change through time. The results offer evidence that open habitats are an ancient component of the Central Highlands, and that wide-spread forest fragmentation occurred naturally during a period of decreased precipitation near the Last Glacial Maximum. Models of gene flow suggest that migration across the Central Highlands has been possible from the Pleistocene through the recent Holocene via riparian corridors. Though our findings support the hypothesis that Central Highland grasslands predate human arrival, we also find evidence for human-mediated population declines. This highlights the extent to which species imminently threatened by human-mediated deforestation may already be vulnerable from paleoclimatic conditions.

The bounded coalescent model: Conditioning a genealogy on a minimum root date

The coalescent model represents how individuals sampled from a population may have originated from a last common ancestor. The bounded coalescent model is obtained by conditioning the coalescent model such that the last common ancestor must have existed after a certain date. This conditioned model arises in a variety of applications, such as speciation, horizontal gene transfer or transmission analysis, and yet the bounded coalescent model has not been previously analysed in detail. Here we describe a new algorithm to simulate from this model directly, without resorting to rejection sampling. We show that this direct simulation algorithm is more computationally efficient than the rejection sampling approach. We also show how to calculate the probability of the last common ancestor occurring after a given date, which is required to compute the probability density of realisations under the bounded coalescent model. Our results are applicable in both the isochronous (when all samples have the same date) and heterochronous (where samples can have different dates) settings. We explore the effect of setting a bound on the date of the last common ancestor, and show that it affects a number of properties of the resulting phylogenies. All our methods are implemented in a new R package called BoundedCoalescent which is freely available online.

Evaluating the accuracy of variant calling methods using the frequency of parent-offspring genotype mismatch

The use of next‐generation sequencing (NGS) data sets has increased dramatically over the last decade, but there have been few systematic analyses quantifying the accuracy of the commonly used variant caller programs. Here we used a familial design consisting of diploid tissue from a single lodgepole pine (Pinus contorta) parent and the maternally derived haploid tissue from 106 full‐sibling offspring, where mismatches could only arise due to mutation or bioinformatic error. Given the rarity of mutation, we used the rate of mismatches between parent and offspring genotype calls to infer the single nucleotide polymorphism (SNP) genotyping error rates of FreeBayes, HaplotypeCaller, SAMtools, UnifiedGenotyper, and VarScan. With baseline filtering HaplotypeCaller and UnifiedGenotyper yielded more SNPs and higher error rates by one to two orders of magnitude, whereas FreeBayes, SAMtools and VarScan yielded lower numbers of SNPs and more modest error rates. To facilitate comparison between variant callers we standardized each SNP set to the same number of SNPs using additional filtering, where UnifiedGenotyper consistently produced the smallest proportion of genotype errors, followed by HaplotypeCaller, VarScan, SAMtools, and FreeBayes. Additionally, we found that error rates were minimized for SNPs called by more than one variant caller. Finally, we evaluated the performance of various commonly used filtering metrics on SNP calling. Our analysis provides a quantitative assessment of the accuracy of five widely used variant calling programs and offers valuable insights into both the choice of variant caller program and the choice of filtering metrics, especially for researchers using non‐model study systems.

Recommendations for improving statistical inference in population genomics

The field of population genomics has grown rapidly in response to the recent advent of affordable, large-scale sequencing technologies. As opposed to the situation during the majority of the 20th century, in which the development of theoretical and statistical population genetic insights outpaced the generation of data to which they could be applied, genomic data are now being produced at a far greater rate than they can be meaningfully analyzed and interpreted. With this wealth of data has come a tendency to focus on fitting specific (and often rather idiosyncratic) models to data, at the expense of a careful exploration of the range of possible underlying evolutionary processes. For example, the approach of directly investigating models of adaptive evolution in each newly sequenced population or species often neglects the fact that a thorough characterization of ubiquitous nonadaptive processes is a prerequisite for accurate inference. We here describe the perils of these tendencies, present our consensus views on current best practices in population genomic data analysis, and highlight areas of statistical inference and theory that are in need of further attention. Thereby, we argue for the importance of defining a biologically relevant baseline model tuned to the details of each new analysis, of skepticism and scrutiny in interpreting model fitting results, and of carefully defining addressable hypotheses and underlying uncertainties.

Revisiting the out of Africa event with a deep-learning approach

Anatomically modern humans evolved around 300 thousand years ago in Africa. They started to appear in the fossil record outside of Africa as early as 100 thousand years ago, although other hominins existed throughout Eurasia much earlier. Recently, several studies argued in favor of a single out of Africa event for modern humans on the basis of whole-genome sequence analyses. However, the single out of Africa model is in contrast with some of the findings from fossil records, which support two out of Africa events, and uniparental data, which propose a back to Africa movement. Here, we used a deep-learning approach coupled with approximate Bayesian computation and sequential Monte Carlo to revisit these hypotheses from the whole-genome sequence perspective. Our results support the back to Africa model over other alternatives. We estimated that there are two sequential separations between Africa and out of African populations happening around 60-90 thousand years ago and separated by 13-15 thousand years. One of the populations resulting from the more recent split has replaced the older West African population to a large extent, while the other one has founded the out of Africa populations.

Impact of model assumptions on demographic inferences: the case study of two sympatric mouse lemurs in northwestern Madagascar

BACKGROUND

Quaternary climate fluctuations have been acknowledged as major drivers of the geographical distribution of the extraordinary biodiversity observed in tropical biomes, including Madagascar. The main existing framework for Pleistocene Malagasy diversification assumes that forest cover was strongly shaped by warmer Interglacials (leading to forest expansion) and by cooler and arid glacials (leading to forest contraction), but predictions derived from this scenario for forest-dwelling animals have rarely been tested with genomic datasets.

RESULTS

We generated genomic data and applied three complementary demographic approaches (Stairway Plot, PSMC and IICR-simulations) to infer population size and connectivity changes for two forest-dependent primate species (Microcebus murinus and M. ravelobensis) in northwestern Madagascar. The analyses suggested major demographic changes in both species that could be interpreted in two ways, depending on underlying model assumptions (i.e., panmixia or population structure). Under panmixia, the two species exhibited larger population sizes across the Last Glacial Maximum (LGM) and towards the African Humid Period (AHP). This peak was followed by a population decline in M. ravelobensis until the present, while M. murinus may have experienced a second population expansion that was followed by a sharp decline starting 3000 years ago. In contrast, simulations under population structure suggested decreasing population connectivity between the Last Interglacial and the LGM for both species, but increased connectivity during the AHP exclusively for M. murinus.

CONCLUSION

Our study shows that closely related species may differ in their responses to climatic events. Assuming that Pleistocene climatic conditions in the lowlands were similar to those in the Malagasy highlands, some demographic dynamics would be better explained by changes in population connectivity than in population size. However, changes in connectivity alone cannot be easily reconciled with a founder effect that was shown for M. murinus during its colonization of the northwestern Madagascar in the late Pleistocene. To decide between the two alternative models, more knowledge about historic forest dynamics in lowland habitats is necessary. Altogether, our study stresses that demographic inferences strongly depend on the underlying model assumptions. Final conclusions should therefore be based on a comparative evaluation of multiple approaches.

Genetic diversity and the origins of parthenogenesis in the teiid lizard Aspidoscelis laredoensis

Unisexual vertebrates typically form through hybridization events between sexual species in which reproductive mode transitions occur in the hybrid offspring. This evolutionary history is thought to have important consequences for the ecology of unisexual lineages and their interactions with congeners in natural communities. However, these consequences have proven challenging to study owing to uncertainty about patterns of population genetic diversity in unisexual lineages. Of particular interest is resolving the contribution of historical hybridization events versus post formational mutation to patterns of genetic diversity in nature. Here we use restriction site associated DNA genotyping to evaluate genetic diversity and demographic history in Aspidoscelis laredoensis, a diploid unisexual lizard species from the vicinity of the Rio Grande River in southern Texas and northern Mexico. The sexual progenitor species from which one or more lineages are derived also occur in the Rio Grande Valley region, although patterns of distribution across individual sites are quite variable. Results from population genetic and phylogenetic analyses resolved the major axes of genetic variation in this species and highlight how these match predictions based on historical patterns of hybridization. We also found discordance between results of demographic modelling using different statistical approaches with the genomic data. We discuss these insights within the context of the ecological and evolutionary mechanisms that generate and maintain lineage diversity in unisexual species. As one of the most dynamic, intriguing, and geographically well investigated groups of whiptail lizards, these species hold substantial promise for future studies on the constraints of diversification in unisexual vertebrates.

50,000 years of ice and seals: Impacts of the Last Glacial Maximum on Antarctic fur seals

Ice is one of the most important drivers of population dynamics in polar organisms, influencing the locations, sizes, and connectivity of populations. Antarctic fur seals, Arctocephalus gazella, are particularly interesting in this regard, as they are concomitantly reliant on both ice-associated prey and ice-free coastal breeding areas. We reconstructed the history of this species through the Last Glacial Maximum (LGM) using genomic sequence data from seals across their range. Population size trends and divergence events were investigated using continuous-time size estimation analysis and divergence time estimation models. The combined results indicated that a panmictic population present prior to the LGM split into two small refugial populations during peak ice extent. Following ice decline, the western refugial population founded colonies at the South Shetlands, South Georgia, and Bouvetøya, while the eastern refugial population founded the colony on Iles Kerguelen. Postglacial population divergence times closely match geological estimates of when these coastal breeding areas became ice free. Given the predictions regarding continued future warming in polar oceans, these responses of Antarctic fur seals to past climate variation suggest it may be worthwhile giving conservation consideration to potential future breeding locations, such as areas further south along the Antarctic Peninsula, in addition to present colony areas.

Past environmental changes affected lemur population dynamics prior to human impact in Madagascar

Quaternary climatic changes have been invoked as important drivers of species diversification worldwide. However, the impact of such changes on vegetation and animal population dynamics in tropical regions remains debated. To overcome this uncertainty, we integrated high-resolution paleoenvironmental reconstructions from a sedimentary record covering the past 25,000 years with demographic inferences of a forest-dwelling primate species (Microcebus arnholdi), in northern Madagascar. Result comparisons suggest that climate changes through the African Humid Period (15.2 - 5.5 kyr) strongly affected the demographic dynamics of M. arnholdi. We further inferred a population decline in the last millennium which was likely shaped by the combination of climatic and anthropogenic impacts. Our findings demonstrate that population fluctuations in Malagasy wildlife were substantial prior to a significant human impact. This provides a critical knowledge of climatically driven, environmental and ecological changes in the past, which is essential to better understand the dynamics and resilience of current biodiversity.

Variability in Codon Usage in Coronaviruses Is Mainly Driven by Mutational Bias and Selective Constraints on CpG Dinucleotide

The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the third human-emerged virus of the 21st century from the Coronaviridae family, causing the ongoing coronavirus disease 2019 (COVID-19) pandemic. Due to the high zoonotic potential of coronaviruses, it is critical to unravel their evolutionary history of host species breadth, host-switch potential, adaptation and emergence, to identify viruses posing a pandemic risk in humans. We present here a comprehensive analysis of the composition and codon usage bias of the 82 Orthocoronavirinae members, infecting 47 different avian and mammalian hosts. Our results clearly establish that synonymous codon usage varies widely among viruses, is only weakly dependent on their primary host, and is dominated by mutational bias towards AU-enrichment and by CpG avoidance. Indeed, variation in GC3 explains around 34%, while variation in CpG frequency explains around 14% of total variation in codon usage bias. Further insight on the mutational equilibrium within Orthocoronavirinae revealed that most coronavirus genomes are close to their neutral equilibrium, the exception being the three recently infecting human coronaviruses, which lie further away from the mutational equilibrium than their endemic human coronavirus counterparts. Finally, our results suggest that, while replicating in humans, SARS-CoV-2 is slowly becoming AU-richer, likely until attaining a new mutational equilibrium.

Coalescence times, life history traits and conservation concerns: An example from four coastal shark species from the Indo-Pacific

Dispersal abilities play a crucial role in shaping the extent of population genetic structure, with more mobile species being panmictic over large geographical ranges and less mobile ones organized in metapopulations exchanging migrants to different degrees. In turn, population structure directly influences the coalescence pattern of the sampled lineages, but the consequences on the estimated variation of the effective population size (N_e ) over time obtained by means of unstructured demographic models remain poorly understood. However, this knowledge is crucial for biologically interpreting the observed N_e trajectory and further devising conservation strategies in endangered species. Here we investigated the demographic history of four shark species (Carharhinus melanopterus, Carharhinus limbatus, Carharhinus amblyrhynchos, Galeocerdo cuvier) with different degrees of endangered status and life history traits related to dispersal distributed in the Indo-Pacific and sampled off New Caledonia. We compared several evolutionary scenarios representing both structured (metapopulation) and unstructured models and then inferred the N_e variation through time. By performing extensive coalescent simulations, we provided a general framework relating the underlying population structure and the observed N_e dynamics. On this basis, we concluded that the recent decline observed in three out of the four considered species when assuming unstructured demographic models can be explained by the presence of population structure. Furthermore, we also demonstrated the limits of the inferences based on the sole site frequency spectrum and warn that statistics based on linkage disequilibrium will be needed to exclude recent demographic events affecting meta-populations.

Genomic signatures of spatially divergent selection at clownfish range margins

Understanding how evolutionary forces interact to drive patterns of selection and distribute genetic variation across a species' range is of great interest in ecology and evolution, especially in an era of global change. While theory predicts how and when populations at range margins are likely to undergo local adaptation, empirical evidence testing these models remains sparse. Here, we address this knowledge gap by investigating the relationship between selection, gene flow and genetic drift in the yellowtail clownfish, Amphiprion clarkii, from the core to the northern periphery of the species range. Analyses reveal low genetic diversity at the range edge, gene flow from the core to the edge and genomic signatures of local adaptation at 56 single nucleotide polymorphisms in 25 candidate genes, most of which are significantly correlated with minimum annual sea surface temperature. Several of these candidate genes play a role in functions that are upregulated during cold stress, including protein turnover, metabolism and translation. Our results illustrate how spatially divergent selection spanning the range core to the periphery can occur despite the potential for strong genetic drift at the range edge and moderate gene flow from the core populations.

The germline mutational process in rhesus macaque and its implications for phylogenetic dating

BACKGROUND

Understanding the rate and pattern of germline mutations is of fundamental importance for understanding evolutionary processes.

RESULTS

Here we analyzed 19 parent-offspring trios of rhesus macaques (Macaca mulatta) at high sequencing coverage of ∼76× per individual and estimated a mean rate of 0.77 × 10-8de novo mutations per site per generation (95% CI: 0.69 × 10-8 to 0.85 × 10-8). By phasing 50% of the mutations to parental origins, we found that the mutation rate is positively correlated with the paternal age. The paternal lineage contributed a mean of 81% of the de novo mutations, with a trend of an increasing male contribution for older fathers. Approximately 3.5% of de novo mutations were shared between siblings, with no parental bias, suggesting that they arose from early development (postzygotic) stages. Finally, the divergence times between closely related primates calculated on the basis of the yearly mutation rate of rhesus macaque generally reconcile with divergence estimated with molecular clock methods, except for the Cercopithecoidea/Hominoidea molecular divergence dated at 58 Mya using our new estimate of the yearly mutation rate.

CONCLUSIONS

When compared to the traditional molecular clock methods, new estimated rates from pedigree samples can provide insights into the evolution of well-studied groups such as primates.

Inferring number of populations and changes in connectivity under the n-island model

Inferring the demographic history of species is one of the greatest challenges in populations genetics. This history is often represented as a history of size changes, ignoring population structure. Alternatively, when structure is assumed, it is defined a priori as a population tree and not inferred. Here we propose a framework based on the IICR (Inverse Instantaneous Coalescence Rate). The IICR can be estimated for a single diploid individual using the PSMC method of Li and Durbin (2011). For an isolated panmictic population, the IICR matches the population size history, and this is how the PSMC outputs are generally interpreted. However, it is increasingly acknowledged that the IICR is a function of the demographic model and sampling scheme with limited connection to population size changes. Our method fits observed IICR curves of diploid individuals with IICR curves obtained under piecewise stationary symmetrical island models. In our models we assume a fixed number of time periods during which gene flow is constant, but gene flow is allowed to change between time periods. We infer the number of islands, their sizes, the periods at which connectivity changes and the corresponding rates of connectivity. Validation with simulated data showed that the method can accurately recover most of the scenario parameters. Our application to a set of five human PSMCs yielded demographic histories that are in agreement with previous studies using similar methods and with recent research suggesting ancient human structure. They are in contrast with the view of human evolution consisting of one ancestral population branching into three large continental and panmictic populations with varying degrees of connectivity and no population structure within each continent.

The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects

Current procedures for inferring population history generally assume complete neutrality—that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the distribution of fitness effect as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy.

Mating system evolution and genetic structure of diploid sexual populations of Cyrtomium falcatum in Japan

Evolution of mating systems has become one of the most important research areas in evolutionary biology. Cyrtomium falcatum is a homosporous fern species native to eastern Asia. Two subspecies belonging to a sexual diploid race of C. falcatum are recognized: subsp. littorale and subsp. australe. Subspecies littorale shows intermediate selfing rates, while subsp. australe is an obligate outcrosser. We aimed to evaluate the process of mating system evolution and divergence for the two subspecies using restriction site associated DNA sequencing (RAD-seq). The results showed that subsp. littorale had lower genetic diversity and stronger genetic drift than subsp. australe. Fluctuations in the effective population size over time were evaluated by extended Bayesian skyline plot and Stairway plot analyses, both of which revealed a severe population bottleneck about 20,000 years ago in subsp. littorale. This bottleneck and the subsequent range expansion after the LGM appear to have played an important role in the divergence of the two subspecies and the evolution of selfing in subsp. littorale. These results shed new light on the relationship between mating system evolution and past demographic change in fern species.

The impact of purifying and background selection on the inference of population history: problems and prospects

Current procedures for inferring population history generally assume complete neutrality - that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects (DFE) and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the DFE as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy.

So many Nigerians: why is Nigeria overrepresented as the ancestral genetic homeland of Legacy African North Americans?

The genetics of African North Americans are complex amalgamations of various West and Central African peoples with modest gene flow from specific European and Amerindian peoples. A comprehensive understanding of African North American biohistory is a prerequisite for accurate interpretations of the ancestral genetics of this population. Too often, genetic interpretations falter with ahistorical reconstructions. The recently reported overrepresentation of Nigerian lineages in African North Americans reflects pronounced limitations in the African genomic database, the artificiality of the colonial maps of Africa, the contributions of multiple African empires and kingdoms into the transatlantic trade in enslaved Africans, and the overrepresentation of Yoruba peoples in the existing limited representation of West Africans in public genomic databases. This Matters Arising paper is in response to Micheletti et al. (2020), published in The American Journal of Human Genetics. See also the response by Micheletti et al. (2020), published in this issue.

Stairway Plot 2: demographic history inference with folded SNP frequency spectra

Inferring the demographic histories of populations has wide applications in population, ecological, and conservation genomics. We present Stairway Plot 2, a cross-platform program package for this task using SNP frequency spectra. It is based on a nonparametric method with the capability of handling folded SNP frequency spectra (that is, when the ancestral alleles of the SNPs are unknown) of thousands of samples produced with genotyping-by-sequencing technologies; therefore, it is particularly suitable for nonmodel organisms.

Distinguishing among complex evolutionary models using unphased whole-genome data through random forest approximate Bayesian computation

Inferring past demographic histories is crucial in population genetics, and the amount of complete genomes now available should in principle facilitate this inference. In practice, however, the available inferential methods suffer from severe limitations. Although hundreds complete genomes can be simultaneously analysed, complex demographic processes can easily exceed computational constraints, and the procedures to evaluate the reliability of the estimates contribute to increase the computational effort. Here we present an approximate Bayesian computation framework based on the random forest algorithm (ABC-RF), to infer complex past population processes using complete genomes. To this aim, we propose to summarize the data by the full genomic distribution of the four mutually exclusive categories of segregating sites (FDSS), a statistic fast to compute from unphased genome data and that does not require the ancestral state of alleles to be known. We constructed an efficient ABC pipeline and tested how accurately it allows one to recognize the true model among models of increasing complexity, using simulated data and taking into account different sampling strategies in terms of number of individuals analysed, number and size of the genetic loci considered. We also compared the FDSS with the unfolded and folded site frequency spectrum (SFS), and for these statistics we highlighted the experimental conditions maximizing the inferential power of the ABC-RF procedure. We finally analysed real data sets, testing models on the dispersal of anatomically modern humans out of Africa and exploring the evolutionary relationships of the three species of Orangutan inhabiting Borneo and Sumatra.

Gene flow as a simple cause for an excess of high-frequency-derived alleles

Most human populations exhibit an excess of high-frequency variants, leading to a U-shaped site-frequency spectrum (uSFS). This pattern has been generally interpreted as a signature of ongoing episodes of positive selection, or as evidence for a mis-assignment of ancestral/derived allelic states, but uSFS has also been observed in populations receiving gene flow from a ghost population, in structured populations, or after range expansions. In order to better explain the prevalence of high-frequency variants in humans and other populations, we describe here which patterns of gene flow and population demography can lead to uSFS by using extensive coalescent simulations. We find that uSFS can often be observed in a population if gene flow brings a few ancestral alleles from a well-differentiated population. Gene flow can either consist in single pulses of admixture or continuous immigration, but different demographic conditions are necessary to observe uSFS in these two scenarios. Indeed, an extremely low and recent gene flow is required in the case of single admixture events, while with continuous immigration, uSFS occurs only if gene flow started recently at a high rate or if it lasted for a long time at a low rate. Overall, we find that a neutral uSFS occurs under more restrictive conditions in populations having received single pulses of gene flow than in populations exposed to continuous gene flow. We also show that the uSFS observed in human populations from the 1000 Genomes Project can easily be explained by gene flow from surrounding populations without requiring past episodes of positive selection. These results imply that uSFS should be common in non-isolated populations, such as most wild or domesticated plants and animals.

Conservation Genomics of a Threatened Rhododendron: Contrasting Patterns of Population Structure Revealed From Neutral and Selected SNPs

Though it is well-acknowledged that next generation sequencing (NGS) technologies can provide further insights into plant conservation management than traditional molecular markers, studies employing NGS to address conservation genomics and subsequent conservation strategies for threatened plants are still rare. Rhododendron is the largest genus of woody plants in China, and many species are threatened, however, to date there has been no conservation genetic research using NGS in this genus. In the present study, we investigated the conservation genetics of R. cyanocarpum, a threatened species endemic to the Cangshan Mountains in Yunnan, China, using a double digest restriction-site-associated DNA-sequencing (ddRAD-seq) approach. Due to the availability of sufficient SNPs, we were able to distinguish between neutral and putatively selected SNPs and were able to further investigate the genetic diversity, population structure, and differentiation in R. cyanocarpum, as well as make an estimation of its demographic history. A total of 6,584 SNPs were obtained, of which 5,729 were neutral (detected using Tajima’s D). In terms of the 5,729 neutral SNPs, R. cyanocarpum had a higher genetic diversity (π = 0.0702 ± 0.0017, H_e = 0.0675 ± 0.0016) than other plant species assessed using Rad-seq methods, while population differentiation (F_st from 0.0314 to 0.0452) was weak. Interestingly, contrasting patterns of population structure were revealed from all neutral and selected SNPs, with distinct genetic clusters forming for all SNPs and neutral SNPs, but no distinct subgroups for selected ones. Moreover, we were able to detect changes in effective population size (N_e) of R. cyanocarpum from 150,000 years ago, including a bottleneck event ca. 60,000 years ago, followed by recovery of N_e over a short period, and a subsequent gradual decline in N_e to date. Implications for conserving R. cyanocarpum based on these main results are then discussed.

Analysis of Genomic Sequence Data Reveals the Origin and Evolutionary Separation of Hawaiian Hoary Bat Populations

We examine the genetic history and population status of Hawaiian hoary bats (Lasiurus semotus), the most isolated bats on Earth, and their relationship to northern hoary bats (Lasiurus cinereus), through whole-genome analysis of single-nucleotide polymorphisms mapped to a de novo-assembled reference genome. Profiles of genomic diversity and divergence indicate that Hawaiian hoary bats are distinct from northern hoary bats, and form a monophyletic group, indicating a single ancestral colonization event 1.34 Ma, followed by substantial divergence between islands beginning 0.51 Ma. Phylogenetic analysis indicates Maui is central to the radiation across the archipelago, with the southward expansion to Hawai'i and westward to O'ahu and Kaua'i. Because this endangered species is of conservation concern, a clearer understanding of the population genetic structure of this bat in the Hawaiian Islands is of timely importance.

Genetic Structure and Population Demography of White-Spotted Charr in the Upstream Watershed of a Large Dam

White-spotted charr (Salvelinus leucomaenis leucomaenis) is an anadromous fish that has been severely harmed by human land-use development, particularly through habitat fragmentation. However, the anthropogenic impacts on populations of this species have not been evaluated, except those on small dammed-off populations. Using multiplexed ISSR genotyping by sequencing, we investigated the genetic structure of white-spotted charr in four tributaries in the upper section of the Kanayama Dam in the Sorachi River, Hokkaido Island, Japan. There were no distinct genetic structures (FST = 0.014), probably because some active individuals migrate frequently among tributaries. By model-flexible demographic simulation, historical changes in the effective population size were inferred. The result indicates that the population size has decreased since the end of the last glacial period, with three major population decline events, including recent declines that were probably associated with recent human activities. Nevertheless, populations in the watershed upstream of the Kanayama Dam are still expected to be at low risk of immediate extinction, owing to the large watershed size and the limited number of small check dams. An effective conservation measure for sustaining the white-spotted charr population is to maintain high connectivity between tributaries, such as by providing fishways in check dams during construction.

Demographic history shaped geographical patterns of deleterious mutation load in a broadly distributed Pacific Salmon

A thorough reconstruction of historical processes is essential for a comprehensive understanding of the mechanisms shaping patterns of genetic diversity. Indeed, past and current conditions influencing effective population size have important evolutionary implications for the efficacy of selection, increased accumulation of deleterious mutations, and loss of adaptive potential. Here, we gather extensive genome-wide data that represent the extant diversity of the Coho salmon (Oncorhynchus kisutch) to address two objectives. We demonstrate that a single glacial refugium is the source of most of the present-day genetic diversity, with detectable inputs from a putative secondary micro-refugium. We found statistical support for a scenario whereby ancestral populations located south of the ice sheets expanded recently, swamping out most of the diversity from other putative micro-refugia. Demographic inferences revealed that genetic diversity was also affected by linked selection in large parts of the genome. Moreover, we demonstrate that the recent demographic history of this species generated regional differences in the load of deleterious mutations among populations, a finding that mirrors recent results from human populations and provides increased support for models of expansion load. We propose that insights from these historical inferences should be better integrated in conservation planning of wild organisms, which currently focuses largely on neutral genetic diversity and local adaptation, with the role of potentially maladaptive variation being generally ignored.

Reconstruction of a species’ past demographic history from genetic data can highlight historical factors that have shaped the distribution of genetic diversity along its genome and its geographic range. Here, we combine genotyping-by-sequencing with demographic modelling to address these issues in the Coho salmon, a Pacific salmon of conservation concern in some parts of its range, notably in the south. Our demographic reconstructions reveal a linear decrease in genetic diversity toward the north of the species range, supporting the hypothesis of a northern route of postglacial recolonization from a single major southern refugium. As predicted by theory, we also observed a higher proportion of deleterious mutations in the most distant populations from this refugium. Beyond this general pattern, among-site variation in the proportion of deleterious mutations is consistent with different local trends in effective population sizes. Our results highlight the potential importance of understanding historical factors that have shaped geographic patterns of the distribution of deleterious mutations in order to implement effective management programs for the conservation of wild populations. Such fundamental knowledge of human historical demography is now having major impacts on health sciences, and we argue it is time to integrate such approaches in conservation science as well.

Bayesian Inference of Species Trees using Diffusion Models

We describe a new and computationally efficient Bayesian methodology for inferring species trees and demographics from unlinked binary markers. Likelihood calculations are carried out using diffusion models of allele frequency dynamics combined with novel numerical algorithms. The diffusion approach allows for analysis of data sets containing hundreds or thousands of individuals. The method, which we call Snapper, has been implemented as part of the BEAST2 package. We conducted simulation experiments to assess numerical error, computational requirements, and accuracy recovering known model parameters. A reanalysis of soybean SNP data demonstrates that the models implemented in Snapp and Snapper can be difficult to distinguish in practice, a characteristic which we tested with further simulations. We demonstrate the scale of analysis possible using a SNP data set sampled from 399 fresh water turtles in 41 populations. [Bayesian inference; diffusion models; multi-species coalescent; SNP data; species trees; spectral methods.].

Coping with Pleistocene climatic fluctuations: Demographic responses in remote endemic reef fishes

Elucidating demographic history during the settlement of ecological communities is crucial for properly inferring the mechanisms that shape patterns of species diversity and their persistence through time. Here, we used genomic data and coalescent-based approaches to elucidate for the first time the demographic dynamics associated with the settlement by endemic reef fish fauna of one of the most remote peripheral islands of the Pacific Ocean, Rapa Nui (Easter Island). We compared the demographic history of nine endemic species in order to explore their demographic responses to Pleistocene climatic fluctuations. We found that species endemic to Rapa Nui share a common demographic history, as signatures of population expansions were retrieved for almost all of the species studied here, and synchronous demographic expansions initiated during the last glacial period were recovered for more than half of the studied species. These results suggest that eustatic fluctuations associated with Milankovitch cycles have played a central role in species demographic histories and in the final stage of the community assembly of many Rapa Nui reef fishes. Specifically, sea level lowstands resulted in the maximum reef habitat extension for Rapa Nui endemic species; we discuss the potential role of seamounts in allowing endemic species to cope with Pleistocene climatic fluctuations, and we highlight the importance of local historical processes over regional ones. Overall, our results shed light on the mechanisms by which endemism arises and is maintained in peripheral reef fish fauna.

Museomics identifies genetic erosion in two butterfly species across the 20th century in Finland

Erosion of biodiversity generated by anthropogenic activities has been studied for decades and in many areas at the species level, using taxa monitoring. In contrast, genetic erosion within species has rarely been tracked, and is often studied by inferring past population dynamics from contemporaneous estimators. An alternative to such inferences is the direct examination of past genes, by analysing museum collection specimens. While providing direct access to genetic variation over time, historical DNA is usually not optimally preserved, and it is necessary to apply genotyping methods based on hybridization-capture to unravel past genetic variation. In this study, we apply such a method (i.e., HyRAD), to large time series of two butterfly species in Finland, and present a new bioinformatic pipeline, namely PopHyRAD, that standardizes and optimizes the analysis of HyRAD data at the within-species level. In the localities for which the data retrieved have sufficient power to accurately examine genetic dynamics through time, we show that genetic erosion has increased across the last 100 years, as revealed by signatures of allele extinctions and heterozygosity decreases, despite local variations. In one of the two butterflies (Erebia embla), isolation by distance also increased through time, revealing the effect of greater habitat fragmentation over time.

Contemporary Demographic Reconstruction Methods Are Robust to Genome Assembly Quality: A Case Study in Tasmanian Devils

Reconstructing species’ demographic histories is a central focus of molecular ecology and evolution. Recently, an expanding suite of methods leveraging either the sequentially Markovian coalescent (SMC) or the site-frequency spectrum has been developed to reconstruct population size histories from genomic sequence data. However, few studies have investigated the robustness of these methods to genome assemblies of varying quality. In this study, we first present an improved genome assembly for the Tasmanian devil using the Chicago library method. Compared with the original reference genome, our new assembly reduces the number of scaffolds (from 35,975 to 10,010) and increases the scaffold N90 (from 0.101 to 2.164 Mb). Second, we assess the performance of four contemporary genomic methods for inferring population size history (PSMC, MSMC, SMC++, Stairway Plot), using the two devil genome assemblies as well as simulated, artificially fragmented genomes that approximate the hypothesized demographic history of Tasmanian devils. We demonstrate that each method is robust to assembly quality, producing similar estimates of Ne when simulated genomes were fragmented into up to 5,000 scaffolds. Overall, methods reliant on the SMC are most reliable between ∼300 generations before present (gbp) and 100 kgbp, whereas methods exclusively reliant on the site-frequency spectrum are most reliable between the present and 30 gbp. Our results suggest that when used in concert, genomic methods for reconstructing species’ effective population size histories 1) can be applied to nonmodel organisms without highly contiguous reference genomes, and 2) are capable of detecting independently documented effects of historical geological events.

An ABC Method for Whole-Genome Sequence Data: Inferring Paleolithic and Neolithic Human Expansions

Species generally undergo a complex demographic history consisting, in particular, of multiple changes in population size. Genome-wide sequencing data are potentially highly informative for reconstructing this demographic history. A crucial point is to extract the relevant information from these very large data sets. Here, we design an approach for inferring past demographic events from a moderate number of fully sequenced genomes. Our new approach uses Approximate Bayesian Computation, a simulation-based statistical framework that allows 1) identifying the best demographic scenario among several competing scenarios and 2) estimating the best-fitting parameters under the chosen scenario. Approximate Bayesian Computation relies on the computation of summary statistics. Using a cross-validation approach, we show that statistics such as the lengths of haplotypes shared between individuals, or the decay of linkage disequilibrium with distance, can be combined with classical statistics (e.g., heterozygosity and Tajima's D) to accurately infer complex demographic scenarios including bottlenecks and expansion periods. We also demonstrate the importance of simultaneously estimating the genotyping error rate. Applying our method on genome-wide human-sequence databases, we finally show that a model consisting in a bottleneck followed by a Paleolithic and a Neolithic expansion is the most relevant for Eurasian populations.

Urbanization without isolation: the absence of genetic structure among cities and forests in the tiny acorn ant Temnothorax nylanderi

Urban alteration of neutral and adaptive evolutionary processes is still underexplored. Using a genome-wide SNP dataset, we investigated (i) urban-induced modifications of population demography, genetic diversity and population structure and (ii) signature of divergent selection between urban and forest populations in the ant species, Temnothorax nylanderi. Our results did not reveal an impact of urbanization on neutral processes since we observed: (i) analogous genetic diversity among paired urban/forest sites and two control populations; (ii) weak population genetic structure explained neither by habitat (urban versus forest) nor by geography; (iii) a remarkably similar demographic history across populations with an ancestral growth followed by a recent decline, regardless of their current habitat or geographical location. The micro-geographical home range of ants may explain their resilience to urbanization. Finally, we detected 19 candidate loci discriminating urban/forest populations and associated with core cellular components, molecular function or biological process. Two of these loci were associated with a gene ontology term that was previously found to belong to a module of co-expressed genes related to caste phenotype. These results call for transcriptomics analyses to identify genes associated with ant social traits and to infer their potential role in urban adaptation.

Inference of Historical Population-Size Changes with Allele-Frequency Data

With up to millions of nearly neutral polymorphisms now being routinely sampled in population-genomic surveys, it is possible to estimate the site-frequency spectrum of such sites with high precision. Each frequency class reflects a mixture of potentially unique demographic histories, which can be revealed using theory for the probability distributions of the starting and ending points of branch segments over all possible coalescence trees. Such distributions are completely independent of past population history, which only influences the segment lengths, providing the basis for estimating average population sizes separating tree-wide coalescence events. The history of population-size change experienced by a sample of polymorphisms can then be dissected in a model-flexible fashion, and extension of this theory allows estimation of the mean and full distribution of long-term effective population sizes and ages of alleles of specific frequencies. Here, we outline the basic theory underlying the conceptual approach, develop and test an efficient statistical procedure for parameter estimation, and apply this to multiple population-genomic datasets for the microcrustacean Daphnia pulex.

Transition from Background Selection to Associative Overdominance Promotes Diversity in Regions of Low Recombination

Linked selection is a major driver of genetic diversity. Selection against deleterious mutations removes linked neutral diversity (background selection [BGS]) [1], creating a positive correlation between recombination rates and genetic diversity. Purifying selection against recessive variants, however, can also lead to associative overdominance (AOD) [2, 3], due to an apparent heterozygote advantage at linked neutral loci that opposes the loss of neutral diversity by BGS. Zhao and Charlesworth [3] identified the conditions under which AOD should dominate over BGS in a single-locus model and suggested that the effect of AOD could become stronger if multiple linked deleterious variants co-segregate. We present a model describing how and under which conditions multi-locus dynamics can amplify the effects of AOD. We derive the conditions for a transition from BGS to AOD due to pseudo-overdominance [4], i.e., a form of balancing selection that maintains complementary deleterious haplotypes that mask the effect of recessive deleterious mutations. Simulations confirm these findings and show that multi-locus AOD can increase diversity in low-recombination regions much more strongly than previously appreciated. While BGS is known to drive genome-wide diversity in humans [5], the observation of a resurgence of genetic diversity in regions of very low recombination is indicative of AOD. We identify 22 such regions in the human genome consistent with multi-locus AOD. Our results demonstrate that AOD may play an important role in the evolution of low-recombination regions of many species.