Estimating inbreeding coefficients from NGS data: Impact on genotype calling and allele frequency estimation

Cleave and Rescue gamete killers create conditions for gene drive in plants

Gene drive elements promote the spread of linked traits and can be used to change the composition or fate of wild populations. Cleave and Rescue (ClvR) drive elements sit at a fixed chromosomal position and include a DNA sequence-modifying enzyme such as Cas9/gRNAs that disrupts endogenous versions of an essential gene and a recoded version of the essential gene resistant to cleavage. ClvR spreads by creating conditions in which those lacking ClvR die because they lack functional versions of the essential gene. Here we demonstrate the essential features of the ClvR gene drive in the plant Arabidopsis thaliana through killing of gametes that fail to inherit a ClvR that targets the essential gene YKT61. Resistant alleles, which can slow or prevent drive, were not observed. Modelling shows plant ClvRs are robust to certain failure modes and can be used to rapidly drive population modification or suppression. Possible applications are discussed.

Signatures of adaptation at key insecticide resistance loci in Anopheles gambiae in Southern Ghana revealed by reduced-coverage WGS

Resistance to insecticides and adaptation to a diverse range of environments present challenges to Anopheles gambiae s.l. mosquito control efforts in sub-Saharan Africa. Whole-genome-sequencing is often employed for identifying the genomic basis underlying adaptation in Anopheles, but remains expensive for large-scale surveys. Reduced coverage whole-genome-sequencing can identify regions of the genome involved in adaptation at a lower cost, but is currently untested in Anopheles mosquitoes. Here, we use reduced coverage WGS to investigate population genetic structure and identify signatures of local adaptation in Anopheles mosquitoes across southern Ghana. In contrast to previous analyses, we find no structuring by ecoregion, with Anopheles coluzzii and Anopheles gambiae populations largely displaying the hallmarks of large, unstructured populations. However, we find signatures of selection at insecticide resistance loci that appear ubiquitous across ecoregions in An. coluzzii, and strongest in forest ecoregions in An. gambiae. Our study highlights resistance candidate genes in this region, and validates reduced coverage WGS, potentially to very low coverage levels, for population genomics and exploratory surveys for adaptation in Anopheles taxa.

Genomic analysis supports Cape Lion population connectivity prior to colonial eradication and extinction

Cape lions (Panthera leo melanochaitus) formerly ranged throughout the grassland plains of the "Cape Flats" in what is today known as the Western Cape Province, South Africa. Cape lions were likely eradicated because of overhunting and habitat loss after European colonization. European naturalists originally described Cape lions as "black-maned lions" and claimed that they were phenotypically distinct. However, other depictions and historical descriptions of lions from the Cape report mixed or light coloration and without black or extensively developed manes. These findings suggest that, rather than forming a distinct population, Cape lions may have had phenotypic and genotypic variation similar to other African lions. Here we investigate Cape lion genome characteristics, population dynamics, and genetic distinctiveness prior to their extinction. We generated genomic data from 2 historic Cape lions to compare to 118 existing high-coverage mitogenomes, and low-coverage nuclear genomes of 53 lions from 13 African countries. We show that, before their eradication, lions from the Cape Flats had diverse mitogenomes and nuclear genomes that clustered with lions from both southern and eastern Africa. Cape lions had high genome-wide heterozygosity and low inbreeding coefficients, indicating that populations in the Cape Flats went extinct so rapidly that genomic effects associated with long-term small population size and isolation were not detectable. Our findings do not support the characterization of Cape lions as phylogeographically distinct, as originally put forth by some European naturalists, and illustrates how alternative knowledge systems, for example, Indigenous perspectives, could potentially further inform interpretations of species histories.

Genomic signatures of climate adaptation in bank voles

Evidence for divergent selection and adaptive variation across the landscape can provide insight into a species' ability to adapt to different environments. However, despite recent advances in genomics, it remains difficult to detect the footprints of climate-mediated selection in natural populations. Here, we analysed ddRAD sequencing data (21,892 SNPs) in conjunction with geographic climate variation to search for signatures of adaptive differentiation in twelve populations of the bank vole (Clethrionomys glareolus) distributed across Europe. To identify the loci subject to selection associated with climate variation, we applied multiple genotype-environment association methods, two univariate and one multivariate, and controlled for the effect of population structure. In total, we identified 213 candidate loci for adaptation, 74 of which were located within genes. In particular, we identified signatures of selection in candidate genes with functions related to lipid metabolism and the immune system. Using the results of redundancy analysis, we demonstrated that population history and climate have joint effects on the genetic variation in the pan-European metapopulation. Furthermore, by examining only candidate loci, we found that annual mean temperature is an important factor shaping adaptive genetic variation in the bank vole. By combining landscape genomic approaches, our study sheds light on genome-wide adaptive differentiation and the spatial distribution of variants underlying adaptive variation influenced by local climate in bank voles.

Genetic and environmental drivers of migratory behavior in western burrowing owls and implications for conservation and management

Migration is driven by a combination of environmental and genetic factors, but many questions remain about those drivers. Potential interactions between genetic and environmental variants associated with different migratory phenotypes are rarely the focus of study. We pair low coverage whole genome resequencing with a de novo genome assembly to examine population structure, inbreeding, and the environmental factors associated with genetic differentiation between migratory and resident breeding phenotypes in a species of conservation concern, the western burrowing owl (Athene cunicularia hypugaea). Our analyses reveal a dichotomy in gene flow depending on whether the population is resident or migratory, with the former being genetically structured and the latter exhibiting no signs of structure. Among resident populations, we observed significantly higher genetic differentiation, significant isolation-by-distance, and significantly elevated inbreeding. Among migratory breeding groups, on the other hand, we observed lower genetic differentiation, no isolation-by-distance, and substantially lower inbreeding. Using genotype-environment association analysis, we find significant evidence for relationships between migratory phenotypes (i.e., migrant versus resident) and environmental variation associated with cold temperatures during the winter and barren, open habitats. In the regions of the genome most differentiated between migrants and residents, we find significant enrichment for genes associated with the metabolism of fats. This may be linked to the increased pressure on migrants to process and store fats more efficiently in preparation for and during migration. Our results provide a significant contribution toward understanding the evolution of migratory behavior and vital insight into ongoing conservation and management efforts for the western burrowing owl.

Microbiome composition is shaped by geography and population structure in the parasitic wasp Asobara japonica, but not in the presence of the endosymbiont Wolbachia

The microbial community composition is crucial for diverse life-history traits in many organisms. However, we still lack a sufficient understanding of how the host microbiome is acquired and maintained, a pressing issue in times of global environmental change. Here we investigated to what extent host genotype, environmental conditions, and the endosymbiont Wolbachia influence the bacterial communities in the parasitic wasp Asobara japonica. We sampled multiple wasp populations across 10 locations in their natural distribution range in Japan and sequenced the host genome (whole genome sequencing) and microbiome (16S rRNA gene). We compared the host population structure and bacterial community composition of wasps that reproduce sexually and are uninfected with Wolbachia with wasps that reproduce asexually and carry Wolbachia. The bacterial communities in asexual wasps were highly similar due to a strong effect of Wolbachia rather than host genomic structure. In contrast, in sexual wasps, bacterial communities appear primarily shaped by a combination of population structure and environmental conditions. Our research highlights that multiple factors shape the bacterial communities of an organism and that the presence of a single endosymbiont can strongly alter their compositions. This information is crucial to understanding how organisms and their associated microbiome will react in the face of environmental change.

Bayesian tests for random mating in polyploids

Hardy-Weinberg proportions (HWP) are often explored to evaluate the assumption of random mating. However, in autopolyploids, organisms with more than two sets of homologous chromosomes, HWP and random mating are different hypotheses that require different statistical testing approaches. Currently, the only available methods to test for random mating in autopolyploids (i) heavily rely on asymptotic approximations and (ii) assume genotypes are known, ignoring genotype uncertainty. Furthermore, these approaches are all frequentist, and so do not carry the benefits of Bayesian analysis, including ease of interpretability, incorporation of prior information, and consistency under the null. Here, we present Bayesian approaches to test for random mating, bringing the benefits of Bayesian analysis to this problem. Our Bayesian methods also (i) do not rely on asymptotic approximations, being appropriate for small sample sizes, and (ii) optionally account for genotype uncertainty via genotype likelihoods. We validate our methods in simulations and demonstrate on two real datasets how testing for random mating is more useful for detecting genotyping errors than testing for HWP (in a natural population) and testing for Mendelian segregation (in an experimental S1 population). Our methods are implemented in Version 2.0.2 of the hwep R package on the Comprehensive R Archive Network https://cran.r-project.org/package=hwep.

Estimating admixture pedigrees of recent hybrids without a contiguous reference genome

The genome of recently admixed individuals or hybrids has characteristic genetic patterns that can be used to learn about their recent admixture history. One of these are patterns of interancestry heterozygosity, which can be inferred from SNP data from either called genotypes or genotype likelihoods, without the need for information on genomic location. This makes them applicable to a wide range of data that are often used in evolutionary and conservation genomic studies, such as low-depth sequencing mapped to scaffolds and reduced representation sequencing. Here we implement maximum likelihood estimation of interancestry heterozygosity patterns using two complementary models. We furthermore develop apoh (Admixture Pedigrees of Hybrids), a software that uses estimates of paired ancestry proportions to detect recently admixed individuals or hybrids, and to suggest possible admixture pedigrees. It furthermore calculates several hybrid indices that make it easier to identify and rank possible admixture pedigrees that could give rise to the estimated patterns. We implemented apoh both as a command line tool and as a Graphical User Interface that allows the user to automatically and interactively explore, rank and visualize compatible recent admixture pedigrees, and calculate the different summary indices. We validate the performance of the method using admixed family trios from the 1000 Genomes Project. In addition, we show its applicability on identifying recent hybrids from RAD-seq data of Grant's gazelle (Nanger granti and Nanger petersii) and whole genome low-depth data of waterbuck (Kobus ellipsiprymnus) which shows complex admixture of up to four populations.

Purging due to self-fertilization does not prevent accumulation of expansion load

As species expand their geographic ranges, colonizing populations face novel ecological conditions, such as new environments and limited mates, and suffer from evolutionary consequences of demographic change through bottlenecks and mutation load accumulation. Self-fertilization is often observed at species range edges and, in addition to countering the lack of mates, is hypothesized as an evolutionary advantage against load accumulation through increased homozygosity and purging. We study how selfing impacts the accumulation of genetic load during range expansion via purging and/or speed of colonization. Using simulations, we disentangle inbreeding effects due to demography versus due to selfing and find that selfers expand faster, but still accumulate load, regardless of mating system. The severity of variants contributing to this load, however, differs across mating system: higher selfing rates purge large-effect recessive variants leaving a burden of smaller-effect alleles. We compare these predictions to the mixed-mating plant Arabis alpina, using whole-genome sequences from refugial outcrossing populations versus expanded selfing populations. Empirical results indicate accumulation of expansion load along with evidence of purging in selfing populations, concordant with our simulations, suggesting that while purging is a benefit of selfing evolving during range expansions, it is not sufficient to prevent load accumulation due to range expansion.

Genetic evidence of population subdivision among Masai giraffes separated by the Gregory Rift Valley in Tanzania

The Masai giraffe has experienced a population decline from 70,000 to 35,000 in the past three decades and was declared an endangered subspecies by the IUCN in 2019. The remaining number of Masai giraffe are geographically separated by the steep cliffs of the Gregory Rift escarpments (GRE) in Tanzania and Kenya dividing them into two populations, one west and one east of the GRE. The cliffs of the GRE are formidable barriers to east-west dispersal and gene flow and the few remaining natural corridors through the GRE are occupied by human settlements. To assess the impact of the GRE on Masai giraffe gene flow, we examined whole genome sequences of nuclear and mitochondrial DNA (mtDNA) variation in populations located east (Tarangire ecosystem) and west (Serengeti ecosystem) of the GRE in northern Tanzania. Evidence from mtDNA variation, which measures female-mediated gene flow, suggests that females have not migrated across the GRE between populations in the Serengeti and Tarangire ecosystems in the past ~289,000 years. The analysis of nuclear DNA variation compared to mtDNA DNA variation suggests that male-mediated gene flow across the GRE has occurred more recently but stopped a few thousand years ago. Our findings show that Masai giraffes are split into two populations and fulfill the criteria for designation as distinct evolutionary significant units (ESUs), which we denote as western Masai giraffe and eastern Masai giraffe. While establishing giraffe dispersal corridors across the GRE is impractical, conservation efforts should be focused on maintaining connectivity among populations within each of these two populations. The importance of these efforts is heightened by our finding that the inbreeding coefficients are high in some of these Masai giraffe populations, which could result in inbreeding depression in the small and fragmented populations.

Genomic insights into inter- and intraspecific mating system shifts in Primulina

The mating system shift from outcrossing to selfing is one of the most frequent evolutionary trends in flowering plants. However, the genomic consequences of this shift remain poorly understood. Specifically, the relative importance of the demographic and genetic processes causing changes in genetic variation and selection efficacy associated with the evolution of selfing is unclear. Here we sequenced the genomes of two Primulina species with contrasting mating systems: P. eburnea (outcrossing) versus P. tabacum (outcrossing, mixed-mating and selfing populations). Whole-genome resequencing data were used to investigate the genomic consequences of mating system shifts within and between species. We found that highly selfing populations of P. tabacum display loss of genetic diversity, increased deleterious mutations, higher genomic burden and fewer adaptive substitutions. However, compared with outcrossing populations, mixed-mating populations did not display loss of genetic diversity and accumulation of genetic load. We find no evidence of population bottlenecks associated with the shift to selfing, which suggests that the genetic effects of selfing on N_e and possibly linked selection, rather than demographic history, are the primary drivers of diversity reduction in highly selfing populations. Our results highlight the importance of distinguishing the relative contribution of mating system and demography on the genomic consequences associated with mating system evolution in plants.

Speciation of pelagic zooplankton: Invisible boundaries can drive isolation of oceanic ctenophores

The study of evolution and speciation in non-model systems provides us with an opportunity to expand our understanding of biodiversity in nature. Connectivity studies generally focus on species with obvious boundaries to gene flow, but in open-ocean environments, such boundaries are difficult to identify. Due to the lack of obvious boundaries, speciation and population subdivision in the pelagic environment remain largely unexplained. Comb jellies (Phylum Ctenophora) are mostly planktonic gelatinous invertebrates, many of which are considered to have freely interbreeding distributions worldwide. It is thought that the lobate ctenophore Bolinopsis infundibulum is distributed throughout cooler northern latitudes and B. vitrea warmer. Here, we examined the global population structure for species of Bolinopsis with genetic and morphological data. We found distinct evolutionary patterns within the genus, where B. infundibulum had a broad distribution from northern Pacific to Atlantic waters despite many physical barriers, while other species were geographically segregated despite few barriers. Divergent patterns of speciation within the genus suggest that oceanic currents, sea-level, and geological changes over time can act as either barriers or aids to dispersal in the pelagic environment. Further, we used population genomic data to examine evolution in the open ocean of a distinct lineage of Bolinopsis ctenophores from the North Eastern Pacific. Genetic information and morphological observations validated this as a separate species, Bolinopsis microptera, which was previously described but has recently been called B. infundibulum. We found that populations of B. microptera from California were in cytonuclear discordance, which indicates a secondary contact zone for previously isolated populations. Discordance at this scale is rare, especially in a continuous setting.

Moment estimators of relatedness from low-depth whole-genome sequencing data

Background

Estimating relatedness is an important step for many genetic study designs. A variety of methods for estimating coefficients of pairwise relatedness from genotype data have been proposed. Both the kinship coefficient \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varphi$$\end{document}φ and the fraternity coefficient \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document}ψ for all pairs of individuals are of interest. However, when dealing with low-depth sequencing or imputation data, individual level genotypes cannot be confidently called. To ignore such uncertainty is known to result in biased estimates. Accordingly, methods have recently been developed to estimate kinship from uncertain genotypes.

Results

We present new method-of-moment estimators of both the coefficients \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varphi$$\end{document}φ and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document}ψ calculated directly from genotype likelihoods. We have simulated low-depth genetic data for a sample of individuals with extensive relatedness by using the complex pedigree of the known genetic isolates of Cilento in South Italy. Through this simulation, we explore the behaviour of our estimators, demonstrate their properties, and show advantages over alternative methods. A demonstration of our method is given for a sample of 150 French individuals with down-sampled sequencing data.

Conclusions

We find that our method can provide accurate relatedness estimates whilst holding advantages over existing methods in terms of robustness, independence from external software, and required computation time. The method presented in this paper is referred to as LowKi (Low-depth Kinship) and has been made available in an R package (https://github.com/genostats/LowKi).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04795-8.

Population structure in Neotropical plants: integrating pollination biology, topography and climatic niches

Animal pollinators mediate gene flow among plant populations, but in contrast to well‐studied topographic and (Pleistocene) environmental isolating barriers, their impact on population genetic differentiation remains largely unexplored. Comparing how these multifarious factors drive microevolutionary histories is, however, crucial for better resolving macroevolutionary patterns of plant diversification. Here we combined genomic analyses with landscape genetics and niche modelling across six related Neotropical plant species (424 individuals across 33 localities) differing in pollination strategy to test the hypothesis that highly mobile (vertebrate) pollinators more effectively link isolated localities than less mobile (bee) pollinators. We found consistently higher genetic differentiation (F_ST) among localities of bee‐ than vertebrate‐pollinated species with increasing geographical distance, topographic barriers and historical climatic instability. High admixture among montane populations further suggested relative climatic stability of Neotropical montane forests during the Pleistocene. Overall, our results indicate that pollinators may differentially impact the potential for allopatric speciation, thereby critically influencing diversification histories at macroevolutionary scales.

Genomic and common garden approaches yield complementary results for quantifying environmental drivers of local adaptation in rubber rabbitbrush, a foundational Great Basin shrub

The spatial structure of genomic and phenotypic variation across populations reflects historical and demographic processes as well as evolution via natural selection. Characterizing such variation can provide an important perspective for understanding the evolutionary consequences of changing climate and for guiding ecological restoration. While evidence for local adaptation has been traditionally evaluated using phenotypic data, modern methods for generating and analyzing landscape genomic data can directly quantify local adaptation by associating allelic variation with environmental variation. Here, we analyze both genomic and phenotypic variation of rubber rabbitbrush (Ericameria nauseosa), a foundational shrub species of western North America. To quantify landscape genomic structure and provide perspective on patterns of local adaptation, we generated reduced representation sequencing data for 17 wild populations (222 individuals; 38,615 loci) spanning a range of environmental conditions. Population genetic analyses illustrated pronounced landscape genomic structure jointly shaped by geography and environment. Genetic-environment association (GEA) analyses using both redundancy analysis (RDA) and a machine-learning approach (Gradient Forest) indicated environmental variables (precipitation seasonality, slope, aspect, elevation, and annual precipitation) influenced spatial genomic structure and were correlated with allele frequency shifts indicative of local adaptation at a consistent set of genomic regions. We compared our GEA-based inference of local adaptation with phenotypic data collected by growing seeds from each population in a greenhouse common garden. Population differentiation in seed weight, emergence, and seedling traits was associated with environmental variables (e.g., precipitation seasonality) that were also implicated in GEA analyses, suggesting complementary conclusions about the drivers of local adaptation across different methods and data sources. Our results provide a baseline understanding of spatial genomic structure for E. nauseosa across the western Great Basin and illustrate the utility of GEA analyses for detecting the environmental causes and genetic signatures of local adaptation in a widely distributed plant species of restoration significance.

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.

A beginner's guide to low-coverage whole genome sequencing for population genomics

Low-coverage whole genome sequencing (lcWGS) has emerged as a powerful and cost-effective approach for population genomic studies in both model and non-model species. However, with read depths too low to confidently call individual genotypes, lcWGS requires specialized analysis tools that explicitly account for genotype uncertainty. A growing number of such tools have become available, but it can be difficult to get an overview of what types of analyses can be performed reliably with lcWGS data, and how the distribution of sequencing effort between the number of samples analyzed and per-sample sequencing depths affects inference accuracy. In this introductory guide to lcWGS, we first illustrate how the per-sample cost for lcWGS is now comparable to RAD-seq and Pool-seq in many systems. We then provide an overview of software packages that explicitly account for genotype uncertainty in different types of population genomic inference. Next, we use both simulated and empirical data to assess the accuracy of allele frequency and genetic diversity estimation, detection of population structure, and selection scans under different sequencing strategies. Our results show that spreading a given amount of sequencing effort across more samples with lower depth per sample consistently improves the accuracy of most types of inference, with a few notable exceptions. Finally, we assess the potential for using imputation to bolster inference from lcWGS data in non-model species, and discuss current limitations and future perspectives for lcWGS-based population genomics research. With this overview, we hope to make lcWGS more approachable and stimulate its broader adoption.

Benchmarking the performance of Pool-seq SNP callers using simulated and real sequencing data

Population genomics is a fast-developing discipline with promising applications in a growing number of life sciences fields. Advances in sequencing technologies and bioinformatics tools allow population genomics to exploit genome-wide information to identify the molecular variants underlying traits of interest and the evolutionary forces that modulate these variants through space and time. However, the cost of genomic analyses of multiple populations is still too high to address them through individual genome sequencing. Pooling individuals for sequencing can be a more effective strategy in Single Nucleotide Polymorphism (SNP) detection and allele frequency estimation because of a higher total coverage. However, compared to individual sequencing, SNP calling from pools has the additional difficulty of distinguishing rare variants from sequencing errors, which is often avoided by establishing a minimum threshold allele frequency for the analysis. Finding an optimal balance between minimizing information loss and reducing sequencing costs is essential to ensure the success of population genomics studies. Here, we have benchmarked the performance of SNP callers for Pool-seq data, based on different approaches, under different conditions, and using computer simulations and real data. We found that SNP callers performance varied for allele frequencies up to 0.35. We also found that SNP callers based on Bayesian (SNAPE-pooled) or maximum likelihood (MAPGD) approaches outperform the two heuristic callers tested (VarScan and PoolSNP), in terms of the balance between sensitivity and FDR both in simulated and sequencing data. Our results will help inform the selection of the most appropriate SNP caller not only for large-scale population studies but also in cases where the Pool-seq strategy is the only option, such as in metagenomic or polyploid studies.

Genomic characterization of selfing in the cyclic parthenogen Daphnia magna

Inbreeding refers to the fusion of related individuals' gametes, with self-fertilization (selfing) being an extreme form of inbreeding-involving gametes produced by the same individual. Selfing is expected to reduce heterozygosity by an average of 50% in one generation; however, little is known about the empirical variation on a genome level surrounding this figure and the factors that affect variation. We selfed genotypes of the cyclic parthenogen Daphnia magna and analysed whole genomes of mothers and selfed offspring, observing the predicted 50% heterozygosity reduction on average. We also saw substantial variation around this value and significant differences among mother-offspring pairs. Crossover analysis confirmed the known trend of recombination occurring more often towards the telomeres. This effect was shown, through simulations, to increase the variance of heterozygosity reduction compared to when a uniform distribution of crossovers was used. Similarly, we simulated inbred line production after several generations of selfing and we observed higher variance in achieved homozygosity when we consider a higher recombination rate towards the telomeres. Our empirical and simulation study highlights that the expected mean values of heterozygosity reduction show remarkable variation, which can help understand, for example, differences among inbred individuals.

High diversity, inbreeding and a dynamic Pleistocene demographic history revealed by African buffalo genomes

Genomes retain records of demographic changes and evolutionary forces that shape species and populations. Remnant populations of African buffalo (Syncerus caffer) in South Africa, with varied histories, provide an opportunity to investigate signatures left in their genomes by past events, both recent and ancient. Here, we produce 40 low coverage (7.14×) genome sequences of Cape buffalo (S. c. caffer) from four protected areas in South Africa. Genome-wide heterozygosity was the highest for any mammal for which these data are available, while differences in individual inbreeding coefficients reflected the severity of historical bottlenecks and current census sizes in each population. PSMC analysis revealed multiple changes in N_e between approximately one million and 20 thousand years ago, corresponding to paleoclimatic changes and Cape buffalo colonisation of southern Africa. The results of this study have implications for buffalo management and conservation, particularly in the context of the predicted increase in aridity and temperature in southern Africa over the next century as a result of climate change.

Model-based genotype and ancestry estimation for potential hybrids with mixed-ploidy

Non-random mating among individuals can lead to spatial clustering of genetically similar individuals and population stratification. This deviation from panmixia is commonly observed in natural populations. Consequently, individuals can have parentage in single populations or involving hybridization between differentiated populations. Accounting for this mixture and structure is important when mapping the genetics of traits and learning about the formative evolutionary processes that shape genetic variation among individuals and populations. Stratified genetic relatedness among individuals is commonly quantified using estimates of ancestry that are derived from a statistical model. Development of these models for polyploid and mixed-ploidy individuals and populations has lagged behind those for diploids. Here, we extend and test a hierarchical Bayesian model, called entropy, which can use low-depth sequence data to estimate genotype and ancestry parameters in autopolyploid and mixed-ploidy individuals (including sex chromosomes and autosomes within individuals). Our analysis of simulated data illustrated the trade-off between sequencing depth and genome coverage and found lower error associated with low-depth sequencing across a larger fraction of the genome than with high-depth sequencing across a smaller fraction of the genome. The model has high accuracy and sensitivity as verified with simulated data and through analysis of admixture among populations of diploid and tetraploid Arabidopsis arenosa.

Ancient genomes reveal early Andean farmers selected common beans while preserving diversity

All crops are the product of a domestication process that started less than 12,000 years ago from one or more wild populations^1,2. Farmers selected desirable phenotypic traits (such as improved energy accumulation, palatability of seeds and reduced natural shattering³) while leading domesticated populations through several more or less gradual demographic contractions^2,4. As a consequence, the erosion of wild genetic variation⁵ is typical of modern cultivars, making them highly susceptible to pathogens, pests and environmental change^6,7. The loss of genetic diversity hampers further crop improvement programmes to increase food production in a changing world, posing serious threats to food security^8,9. Using both ancient and modern seeds, we analysed the temporal dynamics of genetic variation and selection during the domestication process of the common bean (Phaseolus vulgaris) in the southern Andes. Here, we show that most domestic traits were selected for before 2,500 years ago, with no or only minor loss of whole-genome heterozygosity. In fact, most of the changes at coding genes and linked regions that differentiate wild and domestic genomes are already present in the ancient genomes analysed here, and all ancient domestic genomes dated between 600 and 2,500 years ago are highly variable (at least as variable as modern genomes from the wild). Single seeds from modern cultivars show reduced variation when compared with ancient seeds, indicating that intensive selection within cultivars in the past few centuries probably partitioned ancestral variation within different genetically homogenous cultivars. When cultivars from different Andean regions are pooled, the genomic variation of the pool is higher than that observed in the pool of ancient seeds from north and central western Argentina. Considering that most desirable phenotypic traits are probably controlled by multiple polymorphic genes¹⁰, a plausible explanation of this decoupling of selection and genetic erosion is that early farmers applied a relatively weak selection pressure² by using many phenotypically similar but genetically diverse individuals as parents. Our results imply that selection strategies during the past few centuries, as compared with earlier times, more intensively reduced genetic variation within cultivars and produced further improvements by focusing on a few plants carrying the traits of interest, at the cost of marked genetic erosion within Andean landraces.

Pleistocene climate fluctuations drove demographic history of African golden wolves (Canis lupaster)

Pleistocene climate change impacted entire ecosystems throughout the world. In the northern hemisphere, the distribution of Arctic species expanded during glacial periods, while more temperate and mesic species contracted into climatic refugia, where isolation drove genetic divergence. Cycles of local cooling and warming in the Sahara region of northern Africa caused repeated contractions and expansions of savannah-like environments which connected mesic species isolated in refugia during interglacial times, possibly driving population expansions and contractions; divergence and geneflow in the associated fauna. Here, we use whole genome sequences of African golden wolves (Canis lupaster), a generalist mesopredator with a wide distribution in northern Africa to estimate their demographic history and past episodes of geneflow. We detect a correlation between divergence times and cycles of increased aridity-associated Pleistocene glacial cycles. A complex demographic history with responses to local climate change in different lineages was found, including a relict lineage north of the High Atlas Mountains of Morocco that has been isolated for more than 18,000 years, possibly a distinct ecotype.

Population genomics in two cave-obligate invertebrates confirms extremely limited dispersal between caves

Caves offer selective pressures that are distinct from the surface. Organisms that have evolved to exist under these pressures typically exhibit a suite of convergent characteristics, including a loss or reduction of eyes and pigmentation. As a result, cave-obligate taxa, termed troglobionts, are no longer viable on the surface. This circumstance has led to an understanding of highly constrained dispersal capabilities, and the prediction that, in the absence of subterranean connections, extreme genetic divergence between cave populations. An effective test of this model would involve (1) common troglobionts from (2) nearby caves in a cave-dense region, (3) good sample sizes per cave, (4) multiple taxa, and (5) genome-wide characterization. With these criteria in mind, we used RAD-seq to genotype an average of ten individuals of the troglobiotic spider Nesticus barri and the troglobiotic beetle Ptomaphagus hatchi, each from four closely located caves (ranging from 3 to 13 km apart) in the cave-rich southern Cumberland Plateau of Tennessee, USA. Consistent with the hypothesis of highly restricted dispersal, we find that populations from separate caves are indeed highly genetically isolated. Our results support the idea of caves as natural laboratories for the study of parallel evolutionary processes.

Whole-exome sequencing reveals a long-term decline in effective population size of red spruce (Picea rubens)

Understanding the factors influencing the current distribution of genetic diversity across a species range is one of the main questions of evolutionary biology, especially given the increasing threat to biodiversity posed by climate change. Historical demographic processes such as population expansion or bottlenecks and decline are known to exert a predominant influence on past and current levels of genetic diversity, and revealing this demo-genetic history can have immediate conservation implications. We used a whole-exome capture sequencing approach to analyze polymorphism across the gene space of red spruce (Picea rubens Sarg.), an endemic and emblematic tree species of eastern North America high-elevation forests that are facing the combined threat of global warming and increasing human activities. We sampled a total of 340 individuals, including populations from the current core of the range in northeastern USA and southeastern Canada and from the southern portions of its range along the Appalachian Mountains, where populations occur as highly fragmented mountaintop "sky islands." Exome capture baits were designed from the closely relative white spruce (P. glauca Voss) transcriptome, and sequencing successfully captured most regions on or near our target genes, resulting in the generation of a new and expansive genomic resource for studying standing genetic variation in red spruce applicable to its conservation. Our results, based on over 2 million exome-derived variants, indicate that red spruce is structured into three distinct ancestry groups that occupy different geographic regions of its highly fragmented range. Moreover, these groups show small Ne , with a temporal history of sustained population decline that has been ongoing for thousands (or even hundreds of thousands) of years. These results demonstrate the broad potential of genomic studies for revealing details of the demographic history that can inform management and conservation efforts of nonmodel species with active restoration programs, such as red spruce.

Inferring fetal fractions from read heterozygosity empowers the noninvasive prenatal screening

Purpose

Fetal fraction (FF) is the percent of cell-free DNA (cfDNA) in the mother’s peripheral blood that is of fetal origin, which plays a pivotal role in noninvasive prenatal screening (NIPS). We present a method that can reliably estimate FFs by examining autosome single-nucleotide polymorphisms (SNPs).

Methods

Even at a very low sequencing depth, there are plenty of SNPs covered by more than one read. At those SNPs, we define read heterozygosity and demonstrate that the percent of read heterozygosity is a function of FF, which allows FF to be inferred.

Results

We first demonstrated the effectiveness of our method in inferring FF. Then we used the inferred FF as an informative alternative prior to computing Bayes factors to test for aneuploidy, and observed better power than the Z-test. In analysis of clinical samples, we were able to identify female–male twins thanks to the accurate FF inference.

Conclusion

Knowing FF improves efficacy of NIPS. It brings a powerful Bayesian method, allows “no call” for samples with small FFs, renders screening for XXY syndrome simpler, and permits an adaptive design to sequence at a higher depth for samples with small FFs.

Testing for Hardy-Weinberg equilibrium in structured populations using genotype or low-depth next generation sequencing data

Testing for deviations from Hardy-Weinberg equilibrium (HWE) is a common practice for quality control in genetic studies. Variable sites violating HWE may be identified as technical errors in the sequencing or genotyping process, or they may be of particular evolutionary interest. Large-scale genetic studies based on next-generation sequencing (NGS) methods have become more prevalent as cost is decreasing but these methods are still associated with statistical uncertainty. The large-scale studies usually consist of samples from diverse ancestries that make the existence of some degree of population structure almost inevitable. Precautions are therefore needed when analysing these data set, as population structure causes deviations from HWE. Here we propose a method that takes population structure into account in the testing for HWE, such that other factors causing deviations from HWE can be detected. We show the effectiveness of PCAngsd in low-depth NGS data, as well as in genotype data, for both simulated and real data set, where the use of genotype likelihoods enables us to model the uncertainty.

Estimating the burden of α-thalassaemia in Thailand using a comprehensive prevalence database for Southeast Asia

Severe forms of α-thalassaemia, haemoglobin H disease and haemoglobin Bart’s hydrops fetalis, are an important public health concern in Southeast Asia. Yet information on the prevalence, genetic diversity and health burden of α-thalassaemia in the region remains limited. We compiled a geodatabase of α-thalassaemia prevalence and genetic diversity surveys and, using geostatistical modelling methods, generated the first continuous maps of α-thalassaemia mutations in Thailand and sub-national estimates of the number of newborns with severe forms in 2020. We also summarised the current evidence-base for α-thalassaemia prevalence and diversity for the region. We estimate that 3595 (95% credible interval 1,717–6,199) newborns will be born with severe α-thalassaemia in Thailand in 2020, which is considerably higher than previous estimates. Accurate, fine-scale epidemiological data are necessary to guide sustainable national and regional health policies for α-thalassaemia management. Our maps and newborn estimates are an important first step towards this aim.

Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Characterization of introgression from the teosinte Zea mays ssp. mexicana to Mexican highland maize

Background

The spread of maize cultivation to the highlands of central Mexico was accompanied by substantial introgression from the endemic wild teosinte Zea mays ssp. mexicana, prompting the hypothesis that the transfer of beneficial variation facilitated local adaptation.

Methods

We used whole-genome sequence data to map regions of Zea mays ssp. mexicana introgression in three Mexican highland maize individuals. We generated a genetic linkage map and performed Quantitative Trait Locus mapping in an F₂ population derived from a cross between lowland and highland maize individuals.

Results

Introgression regions ranged in size from several hundred base pairs to Megabase-scale events. Gene density within introgression regions was comparable to the genome as a whole, and over 1,000 annotated genes were located within introgression events. Quantitative Trait Locus mapping identified a small number of loci linked to traits characteristic of Mexican highland maize.

Discussion

Although there was no strong evidence to associate quantitative trait loci with regions of introgression, we nonetheless identified many Mexican highland alleles of introgressed origin that carry potentially functional sequence variants. The impact of introgression on stress tolerance and yield in the highland environment remains to be fully characterized.

Fast and accurate relatedness estimation from high-throughput sequencing data in the presence of inbreeding

BACKGROUND

The estimation of relatedness between pairs of possibly inbred individuals from high-throughput sequencing (HTS) data has previously not been possible for samples where we cannot obtain reliable genotype calls, as in the case of low-coverage data.

RESULTS

We introduce ngsRelateV2, a major revision of ngsRelateV1, a program that originally allowed for estimation of relatedness from HTS data among non-inbred individuals only. The new revised version takes into account the possibility of individuals being inbred by estimating the 9 condensed Jacquard coefficients along with various other relatedness statistics. The program is threaded and scales linearly with the number of cores allocated to the process.

CONCLUSION

The program is available as an open source C/C++ program under the GPL license and hosted at https://github.com/ANGSD/ngsRelate. To facilitate easy analysis, the program is able to work directly on the most commonly used container formats for raw sequence (BAM/CRAM) and summary data (VCF/BCF).

Out of Southern East Asia of the Brown Rat Revealed by Large-Scale Genome Sequencing

The geographic origin and migration of the brown rat (Rattus norvegicus) remain subjects of considerable debate. In this study, we sequenced whole genomes of 110 wild brown rats with a diverse world-wide representation. We reveal that brown rats migrated out of southern East Asia, rather than northern Asia as formerly suggested, into the Middle East and then to Europe and Africa, thousands of years ago. Comparison of genomes from different geographical populations reveals that many genes involved in the immune system experienced positive selection in the wild brown rat.

Cost-effective assembly of the African wild dog (Lycaon pictus) genome using linked reads

Background

A high-quality reference genome assembly is a valuable tool for the study of non-model organisms. Genomic techniques can provide important insights about past population sizes and local adaptation and can aid in the development of breeding management plans. This information is important for fields such as conservation genetics, where endangered species require critical and immediate attention. However, funding for genomic-based methods can be sparse for conservation projects, as costs for general species management can consume budgets.

Findings

Here, we report the generation of high-quality reference genomes for the African wild dog (Lycaon pictus) at a low cost (<$3000), thereby facilitating future studies of this endangered canid. We generated assemblies for three individuals using the linked-read 10x Genomics Chromium system. The most continuous assembly had a scaffold and contig N50 of 21 Mb and 83 Kb, respectively, and completely reconstructed 95% of a set of conserved mammalian genes. Additionally, we estimate the heterozygosity and demographic history of African wild dogs, revealing that although they have historically low effective population sizes, heterozygosity remains high.

Conclusions

We show that 10x Genomics Chromium data can be used to effectively generate high-quality genomes from Illumina short-read data of intermediate coverage (∼25x–50x). Interestingly, the wild dog shows higher heterozygosity than other species of conservation concern, possibly due to its behavioral ecology. The availability of reference genomes for non-model organisms will facilitate better genetic monitoring of threatened species such as the African wild dog and help conservationists to better understand the ecology and adaptability of those species in a changing environment.

Population genomics of grey wolves and wolf-like canids in North America

North America is currently home to a number of grey wolf (Canis lupus) and wolf-like canid populations, including the coyote (Canis latrans) and the taxonomically controversial red, Eastern timber and Great Lakes wolves. We explored their population structure and regional gene flow using a dataset of 40 full genome sequences that represent the extant diversity of North American wolves and wolf-like canid populations. This included 15 new genomes (13 North American grey wolves, 1 red wolf and 1 Eastern timber/Great Lakes wolf), ranging from 0.4 to 15x coverage. In addition to providing full genome support for the previously proposed coyote-wolf admixture origin for the taxonomically controversial red, Eastern timber and Great Lakes wolves, the discriminatory power offered by our dataset suggests all North American grey wolves, including the Mexican form, are monophyletic, and thus share a common ancestor to the exclusion of all other wolves. Furthermore, we identify three distinct populations in the high arctic, one being a previously unidentified "Polar wolf" population endemic to Ellesmere Island and Greenland. Genetic diversity analyses reveal particularly high inbreeding and low heterozygosity in these Polar wolves, consistent with long-term isolation from the other North American wolves.

Inferring Population Structure and Admixture Proportions in Low-Depth NGS Data

We here present two methods for inferring population structure and admixture proportions in low-depth next-generation sequencing (NGS) data. Inference of population structure is essential in both population genetics and association studies, and is often performed using principal component analysis (PCA) or clustering-based approaches. NGS methods provide large amounts of genetic data but are associated with statistical uncertainty, especially for low-depth sequencing data. Models can account for this uncertainty by working directly on genotype likelihoods of the unobserved genotypes. We propose a method for inferring population structure through PCA in an iterative heuristic approach of estimating individual allele frequencies, where we demonstrate improved accuracy in samples with low and variable sequencing depth for both simulated and real datasets. We also use the estimated individual allele frequencies in a fast non-negative matrix factorization method to estimate admixture proportions. Both methods have been implemented in the PCAngsd framework available at http://www.popgen.dk/software/.

Genetic and genomic monitoring with minimally invasive sampling methods

The decreasing cost and increasing scope and power of emerging genomic technologies are reshaping the field of molecular ecology. However, many modern genomic approaches (e.g., RAD-seq) require large amounts of high-quality template DNA. This poses a problem for an active branch of conservation biology: genetic monitoring using minimally invasive sampling (MIS) methods. Without handling or even observing an animal, MIS methods (e.g., collection of hair, skin, faeces) can provide genetic information on individuals or populations. Such samples typically yield low-quality and/or quantities of DNA, restricting the type of molecular methods that can be used. Despite this limitation, genetic monitoring using MIS is an effective tool for estimating population demographic parameters and monitoring genetic diversity in natural populations. Genetic monitoring is likely to become more important in the future as many natural populations are undergoing anthropogenically driven declines, which are unlikely to abate without intensive adaptive management efforts that often include MIS approaches. Here, we profile the expanding suite of genomic methods and platforms compatible with producing genotypes from MIS, considering factors such as development costs and error rates. We evaluate how powerful new approaches will enhance our ability to investigate questions typically answered using genetic monitoring, such as estimating abundance, genetic structure and relatedness. As the field is in a period of unusually rapid transition, we also highlight the importance of legacy data sets and recommend how to address the challenges of moving between traditional and next-generation genetic monitoring platforms. Finally, we consider how genetic monitoring could move beyond genotypes in the future. For example, assessing microbiomes or epigenetic markers could provide a greater understanding of the relationship between individuals and their environment.

Ancient genomes revisit the ancestry of domestic and Przewalski’s horses

The Eneolithic Botai culture of the Central Asian steppes provides the earliest archaeological evidence for horse husbandry, ~5500 years ago, but the exact nature of early horse domestication remains controversial. We generated 42 ancient-horse genomes, including 20 from Botai. Compared to 46 published ancient- and modern-horse genomes, our data indicate that Przewalski’s horses are the feral descendants of horses herded at Botai and not truly wild horses. All domestic horses dated from ~4000 years ago to present only show ~2.7% of Botai-related ancestry. This indicates that a massive genomic turnover underpins the expansion of the horse stock that gave rise to modern domesticates, which coincides with large-scale human population expansions during the Early Bronze Age.

Evolutionary Patterns and Processes: Lessons from Ancient DNA

Ever since its emergence in 1984, the field of ancient DNA has struggled to overcome the challenges related to the decay of DNA molecules in the fossil record. With the recent development of high-throughput DNA sequencing technologies and molecular techniques tailored to ultra-damaged templates, it has now come of age, merging together approaches in phylogenomics, population genomics, epigenomics, and metagenomics. Leveraging on complete temporal sample series, ancient DNA provides direct access to the most important dimension in evolution—time, allowing a wealth of fundamental evolutionary processes to be addressed at unprecedented resolution. This review taps into the most recent findings in ancient DNA research to present analyses of ancient genomic and metagenomic data.

Fantastic Beasts and How To Sequence Them: Ecological Genomics for Obscure Model Organisms

The application of genomic approaches to 'obscure model organisms' (OMOs), meaning species with no prior genomic resources, enables increasingly sophisticated studies of the genomic basis of evolution, acclimatization, and adaptation in real ecological contexts. I consider here ecological questions that can be addressed using OMOs, and indicate optimal sequencing and data-handling solutions for each case. With this I hope to promote the diversity of OMO-based projects that would capitalize on the peculiarities of the natural history of OMOs and could feasibly be completed within the scope of a single PhD thesis.

The interplay of demography and selection during maize domestication and expansion

BACKGROUND

The history of maize has been characterized by major demographic events, including population size changes associated with domestication and range expansion, and gene flow with wild relatives. The interplay between demographic history and selection has shaped diversity across maize populations and genomes.

RESULTS

We investigate these processes using high-depth resequencing data from 31 maize landraces spanning the pre-Columbian distribution of maize, and four wild teosinte individuals (Zea mays ssp. parviglumis). Genome-wide demographic analyses reveal that maize experienced pronounced declines in effective population size due to both a protracted domestication bottleneck and serial founder effects during post-domestication spread, while parviglumis in the Balsas River Valley experienced population growth. The domestication bottleneck and subsequent spread led to an increase in deleterious alleles in the domesticate compared to the wild progenitor. This cost is particularly pronounced in Andean maize, which has experienced a more dramatic founder event compared to other maize populations. Additionally, we detect introgression from the wild teosinte Zea mays ssp. mexicana into maize in the highlands of Mexico, Guatemala, and the southwestern USA, which reduces the prevalence of deleterious alleles likely due to the higher long-term effective population size of teosinte.

CONCLUSIONS

These findings underscore the strong interaction between historical demography and the efficiency of selection and illustrate how domesticated species are particularly useful for understanding these processes. The landscape of deleterious alleles and therefore evolutionary potential is clearly influenced by recent demography, a factor that could bear importantly on many species that have experienced recent demographic shifts.

The interplay of demography and selection during maize domestication and expansion

BACKGROUND

The history of maize has been characterized by major demographic events, including population size changes associated with domestication and range expansion, and gene flow with wild relatives. The interplay between demographic history and selection has shaped diversity across maize populations and genomes.

RESULTS

We investigate these processes using high-depth resequencing data from 31 maize landraces spanning the pre-Columbian distribution of maize, and four wild teosinte individuals (Zea mays ssp. parviglumis). Genome-wide demographic analyses reveal that maize experienced pronounced declines in effective population size due to both a protracted domestication bottleneck and serial founder effects during post-domestication spread, while parviglumis in the Balsas River Valley experienced population growth. The domestication bottleneck and subsequent spread led to an increase in deleterious alleles in the domesticate compared to the wild progenitor. This cost is particularly pronounced in Andean maize, which has experienced a more dramatic founder event compared to other maize populations. Additionally, we detect introgression from the wild teosinte Zea mays ssp. mexicana into maize in the highlands of Mexico, Guatemala, and the southwestern USA, which reduces the prevalence of deleterious alleles likely due to the higher long-term effective population size of teosinte.

CONCLUSIONS

These findings underscore the strong interaction between historical demography and the efficiency of selection and illustrate how domesticated species are particularly useful for understanding these processes. The landscape of deleterious alleles and therefore evolutionary potential is clearly influenced by recent demography, a factor that could bear importantly on many species that have experienced recent demographic shifts.

Whole-genome sequencing approaches for conservation biology: Advantages, limitations and practical recommendations

Whole-genome resequencing (WGR) is a powerful method for addressing fundamental evolutionary biology questions that have not been fully resolved using traditional methods. WGR includes four approaches: the sequencing of individuals to a high depth of coverage with either unresolved or resolved haplotypes, the sequencing of population genomes to a high depth by mixing equimolar amounts of unlabelled-individual DNA (Pool-seq) and the sequencing of multiple individuals from a population to a low depth (lcWGR). These techniques require the availability of a reference genome. This, along with the still high cost of shotgun sequencing and the large demand for computing resources and storage, has limited their implementation in nonmodel species with scarce genomic resources and in fields such as conservation biology. Our goal here is to describe the various WGR methods, their pros and cons and potential applications in conservation biology. WGR offers an unprecedented marker density and surveys a wide diversity of genetic variations not limited to single nucleotide polymorphisms (e.g., structural variants and mutations in regulatory elements), increasing their power for the detection of signatures of selection and local adaptation as well as for the identification of the genetic basis of phenotypic traits and diseases. Currently, though, no single WGR approach fulfils all requirements of conservation genetics, and each method has its own limitations and sources of potential bias. We discuss proposed ways to minimize such biases. We envision a not distant future where the analysis of whole genomes becomes a routine task in many nonmodel species and fields including conservation biology.

Asian wild rice is a hybrid swarm with extensive gene flow and feralization from domesticated rice

The domestication history of rice remains controversial, with multiple studies reaching different conclusions regarding its origin(s). These studies have generally assumed that populations of living wild rice, O. rufipogon, are descendants of the ancestral population that gave rise to domesticated rice, but relatively little attention has been paid to the origins and history of wild rice itself. Here, we investigate the genetic ancestry of wild rice by analyzing a diverse panel of rice genomes consisting of 203 domesticated and 435 wild rice accessions. We show that most modern wild rice is heavily admixed with domesticated rice through both pollen- and seed-mediated gene flow. In fact, much presumed wild rice may simply represent different stages of feralized domesticated rice. In line with this hypothesis, many presumed wild rice varieties show remnants of the effects of selective sweeps in previously identified domestication genes, as well as evidence of recent selection in flowering genes possibly associated with the feralization process. Furthermore, there is a distinct geographical pattern of gene flow from aus, indica, and japonica varieties into colocated wild rice. We also show that admixture from aus and indica is more recent than gene flow from japonica, possibly consistent with an earlier spread of japonica varieties. We argue that wild rice populations should be considered a hybrid swarm, connected to domesticated rice by continuous and extensive gene flow.

Genotype Calling from Population-Genomic Sequencing Data

Genotype calling plays important roles in population-genomic studies, which have been greatly accelerated by sequencing technologies. To take full advantage of the resultant information, we have developed maximum-likelihood (ML) methods for calling genotypes from high-throughput sequencing data. As the statistical uncertainties associated with sequencing data depend on depths of coverage, we have developed two types of genotype callers. One approach is appropriate for low-coverage sequencing data, and incorporates population-level information on genotype frequencies and error rates pre-estimated by an ML method. Performance evaluation using computer simulations and human data shows that the proposed framework yields less biased estimates of allele frequencies and more accurate genotype calls than current widely used methods. Another type of genotype caller applies to high-coverage sequencing data, requires no prior genotype-frequency estimates, and makes no assumption on the number of alleles at a polymorphic site. Using computer simulations, we determine the depth of coverage necessary to accurately characterize polymorphisms using this second method. We applied the proposed method to high-coverage (mean 18×) sequencing data of 83 clones from a population of Daphnia pulex. The results show that the proposed method enables conservative and reasonably powerful detection of polymorphisms with arbitrary numbers of alleles. We have extended the proposed method to the analysis of genomic data for polyploid organisms, showing that calling accurate polyploid genotypes requires much higher coverage than diploid genotypes.

Ancient genomic changes associated with domestication of the horse

The domestication of the horse was a seminal event in human cultural evolution. Libradoet al.obtained genome sequences from 14 horses from the Bronze and Iron Ages, about 2000 to 4000 years ago, soon after domestication. They identified variants determining coat color and genes selected during the domestication process. They could also see evidence of admixture with archaic horses and the demography of the domestication process, which included the accumulation of deleterious variants. The horse appears to have undergone a different type of domestication process than animals that were domesticated simply for food.

Science, this issue p.442

The landscape of extreme genomic variation in the highly adaptable Atlantic killifish

Understanding and predicting the fate of populations in changing environments require knowledge about the mechanisms that support phenotypic plasticity and the adaptive value and evolutionary fate of genetic variation within populations. Atlantic killifish (Fundulus heteroclitus) exhibit extensive phenotypic plasticity that supports large population sizes in highly fluctuating estuarine environments. Populations have also evolved diverse local adaptations. To yield insights into the genomic variation that supports their adaptability, we sequenced a reference genome and 48 additional whole genomes from a wild population. Evolution of genes associated with cell cycle regulation and apoptosis is accelerated along the killifish lineage, which is likely tied to adaptations for life in highly variable estuarine environments. Genome-wide standing genetic variation, including nucleotide diversity and copy number variation, is extremely high. The highest diversity genes are those associated with immune function and olfaction, whereas genes under greatest evolutionary constraint are those associated with neurological, developmental, and cytoskeletal functions. Reduced genetic variation is detected for tight junction proteins, which in killifish regulate paracellular permeability that supports their extreme physiological flexibility. Low-diversity genes engage in more regulatory interactions than high-diversity genes, consistent with the influence of pleiotropic constraint on molecular evolution. High genetic variation is crucial for continued persistence of species given the pace of contemporary environmental change. Killifish populations harbor among the highest levels of nucleotide diversity yet reported for a vertebrate species, and thus may serve as a useful model system for studying evolutionary potential in variable and changing environments.

Genomic resources for wild populations of the house mouse, Mus musculus and its close relative Mus spretus

Wild populations of the house mouse (Mus musculus) represent the raw genetic material for the classical inbred strains in biomedical research and are a major model system for evolutionary biology. We provide whole genome sequencing data of individuals representing natural populations of M. m. domesticus (24 individuals from 3 populations), M. m. helgolandicus (3 individuals), M. m. musculus (22 individuals from 3 populations) and M. spretus (8 individuals from one population). We use a single pipeline to map and call variants for these individuals and also include 10 additional individuals of M. m. castaneus for which genomic data are publically available. In addition, RNAseq data were obtained from 10 tissues of up to eight adult individuals from each of the three M. m. domesticus populations for which genomic data were collected. Data and analyses are presented via tracks viewable in the UCSC or IGV genome browsers. We also provide information on available outbred stocks and instructions on how to keep them in the laboratory.

angsd-wrapper: utilities for analysing next-generation sequencing data

High-throughput sequencing has changed many aspects of population genetics, molecular ecology and related fields, affecting both experimental design and data analysis. The software package angsd allows users to perform a number of population genetic analyses on high-throughput sequencing data. angsd uses probabilistic approaches which can directly make use of genotype likelihoods; thus, SNP calling is not required for comparative analyses. This takes advantage of all the sequencing data and produces more accurate results for samples with low sequencing depth. Here, we present angsd-wrapper, a set of wrapper scripts that provides a user-friendly interface for running angsd and visualizing results. angsd-wrapper supports multiple types of analyses including estimates of nucleotide sequence diversity neutrality tests, principal component analysis, estimation of admixture proportions for individual samples and calculation of statistics that quantify recent introgression. angsd-wrapper also provides interactive graphing of angsd results to enhance data exploration. We demonstrate the usefulness of angsd-wrapper by analysing resequencing data from populations of wild and domesticated Zea. angsd-wrapper is freely available from https://github.com/mojaveazure/angsd-wrapper.