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qpAdm is a statistical tool for studying the ancestry of populations with histories that involve admixture between two or more source populations. Using qpAdm, it is possible to identify plausible models of admixture that fit the population history of a group of interest and to calculate the relative proportion of ancestry that can be ascribed to each source population in the model. Although qpAdm is widely used in studies of population history of human (and nonhuman) groups, relatively little has been done to assess its performance. We performed a simulation study to assess the behavior of qpAdm under various scenarios in order to identify areas of potential weakness and establish recommended best practices for use. We find that qpAdm is a robust tool that yields accurate results in many cases, including when data coverage is low, there are high rates of missing data or ancient DNA damage, or when diploid calls cannot be made. However, we caution against co-analyzing ancient and present-day data, the inclusion of an extremely large number of reference populations in a single model, and analyzing population histories involving extended periods of gene flow. We provide a user guide suggesting best practices for the use of qpAdm., (© The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America.)

Testing for Hardy-Weinberg equilibrium (HWE) is an important component in almost all analyses of population genetic data. Genetic markers that violate HWE are often treated as special cases; for example, they may be flagged as possible genotyping errors, or they may be investigated more closely for evolutionary signatures of interest. The presence of population structure is one reason why genetic markers may fail a test of HWE. This is problematic because almost all natural populations studied in the modern setting show some degree of structure. Therefore, it is important to be able to detect deviations from HWE for reasons other than structure. To this end, we extend statistical tests of HWE to allow for population structure, which we call a test of "structural HWE." Additionally, our new test allows one to automatically choose tuning parameters and identify accurate models of structure. We demonstrate our approach on several important studies, provide theoretical justification for the test, and present empirical evidence for its utility. We anticipate the proposed test will be useful in a broad range of analyses of genome-wide population genetic data., (Copyright © 2019 Hao and Storey.)

We present an algorithm for inferring ancestry segments and characterizing admixture events, which involve an arbitrary number of genetically differentiated groups coming together. This allows inference of the demographic history of the species, properties of admixing groups, identification of signatures of natural selection, and may aid disease gene mapping. The algorithm employs nested hidden Markov models to obtain local ancestry estimation along the genome for each admixed individual. In a range of simulations, the accuracy of these estimates equals or exceeds leading existing methods. Moreover, and unlike these approaches, we do not require any prior knowledge of the relationship between subgroups of donor reference haplotypes and the unseen mixing ancestral populations. Our approach infers these in terms of conditional "copying probabilities." In application to the Human Genome Diversity Project, we corroborate many previously inferred admixture events ( e.g. , an ancient admixture event in the Kalash). We further identify novel events such as complex four-way admixture in San-Khomani individuals, and show that Eastern European populations possess [Formula: see text] ancestry from a group resembling modern-day central Asians. We also identify evidence of recent natural selection favoring sub-Saharan ancestry at the human leukocyte antigen (HLA) region, across North African individuals. We make available an R and C++ software library, which we term MOSAIC (which stands for MOSAIC Organizes Segments of Ancestry In Chromosomes)., (Copyright © 2019 Salter-Townshend and Myers.)

Inferring relatedness from genomic data is an essential component of genetic association studies, population genetics, forensics, and genealogy. While numerous methods exist for inferring relatedness, thorough evaluation of these approaches in real data has been lacking. Here, we report an assessment of 12 state-of-the-art pairwise relatedness inference methods using a data set with 2485 individuals contained in several large pedigrees that span up to six generations. We find that all methods have high accuracy (92-99%) when detecting first- and second-degree relationships, but their accuracy dwindles to <43% for seventh-degree relationships. However, most identical by descent (IBD) segment-based methods inferred seventh-degree relatives correct to within one relatedness degree for >76% of relative pairs. Overall, the most accurate methods are Estimation of Recent Shared Ancestry (ERSA) and approaches that compute total IBD sharing using the output from GERMLINE and Refined IBD to infer relatedness. Combining information from the most accurate methods provides little accuracy improvement, indicating that novel approaches, such as new methods that leverage relatedness signals from multiple samples, are needed to achieve a sizeable jump in performance., (Copyright © 2017 Ramstetter et al.)

Admixture mapping has been enormously resourceful in identifying genetic variations linked to phenotypes, adaptation, and diseases. In this study through analysis of copy number variable regions (CNVRs), we report extensive restructuring in the genomes of the recently admixed African-Indian population (OG-W-IP) that inhabits a highly saline environment in Western India. The study included subjects from OG-W-IP (OG), five different Indian and three HapMap populations that were genotyped using Affymetrix version 6.0 arrays. Copy number variations (CNVs) detected using Birdsuite were used to define CNVRs. Population structure with respect to CNVRs was delineated using random forest approach. OG genomes have a surprising excess of CNVs in comparison to other studied populations. Individual ancestry proportions computed using STRUCTURE also reveals a unique genetic component in OGs. Population structure analysis with CNV genotypes indicates OG to be distant from both the African and Indian ancestral populations. Interestingly, it shows genetic proximity with respect to CNVs to only one Indian population IE-W-LP4, which also happens to reside in the same geographical region. We also observe a significant enrichment of molecular processes related to ion binding and receptor activity in genes encompassing OG-specific CNVRs. Our results suggest that retention of CNVRs from ancestral natives and de novo acquisition of CNVRs could accelerate the process of adaptation especially in an extreme environment. Additionally, this population would be enormously useful for dissecting genes and delineating the involvement of CNVs in salt adaptation., (© The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Genome-wide association studies (GWASs) have identified thousands of variants for disease risk. These studies have predominantly been conducted in individuals of European ancestries, which raises questions about their transferability to individuals of other ancestries. Of particular interest are admixed populations, usually defined as populations with recent ancestry from two or more continental sources. Admixed genomes contain segments of distinct ancestries that vary in composition across individuals in the population, allowing for the same allele to induce risk for disease on different ancestral backgrounds. This mosaicism raises unique challenges for GWASs in admixed populations, such as the need to correctly adjust for population stratification. In this work we quantify the impact of differences in estimated allelic effect sizes for risk variants between ancestry backgrounds on association statistics. Specifically, while the possibility of estimated allelic effect-size heterogeneity by ancestry (HetLanc) can be modeled when performing a GWAS in admixed populations, the extent of HetLanc needed to overcome the penalty from an additional degree of freedom in the association statistic has not been thoroughly quantified. Using extensive simulations of admixed genotypes and phenotypes, we find that controlling for and conditioning effect sizes on local ancestry can reduce statistical power by up to 72%. This finding is especially pronounced in the presence of allele frequency differentiation. We replicate simulation results using 4,327 African-European admixed genomes from the UK Biobank for 12 traits to find that for most significant SNPs, HetLanc is not large enough for GWASs to benefit from modeling heterogeneity in this way.

Admixture estimation plays a crucial role in ancestry inference and genome-wide association studies (GWASs). Computer programs such as ADMIXTURE and STRUCTURE are commonly employed to estimate the admixture proportions of sample individuals. However, these programs can be overwhelmed by the computational burdens imposed by the 105 to 106 samples and millions of markers commonly found in modern biobanks. An attractive strategy is to run these programs on a set of ancestry-informative SNP markers (AIMs) that exhibit substantially different frequencies across populations. Unfortunately, existing methods for identifying AIMs require knowing ancestry labels for a subset of the sample. This supervised learning approach creates a chicken and the egg scenario. In this paper, we present an unsupervised, scalable framework that seamlessly carries out AIM selection and likelihood-based estimation of admixture proportions. Our simulated and real data examples show that this approach is scalable to modern biobank datasets. OpenADMIXTURE, our Julia implementation of the method, is open source and available for free.

Conservation translocations have become an increasingly popular method to restore or secure vulnerable populations. However, translocations greatly vary in success. The use of population viability analysis (PVA) may increase the likelihood of meeting translocation goals. However, the quality of PVAs to inform translocations is dependent on the availability of ecological data and clear translocation objectives to guide them. Here, we used PVAs to inform the planned conservation translocation of the Western Grasswren (Amytornis textilis textilis) from mainland Shark Bay onto Dirk Hartog Island, Western Australia. A range of translocation scenarios were modelled and scored against success criteria as determined by translocation objectives. Simulations of 20-yr outcomes found that a minimum founder population of 112 individuals meet all success criteria. PVA supported sourcing individuals from 2 subpopulations to maximize genetic diversity. No impact to source populations was detected for the proposed harvest quantities despite conservative estimates of initial source population sizes. Here we demonstrate that creating clear, measurable objectives alongside a PVA lessens ambiguity about which translocation scenarios could be viable. In doing so, we have identified the minimum translocation sizes needed to maintain genetic diversity and population growth, thus increasing the likelihood of translocation success without impacting the source population. [ABSTRACT FROM AUTHOR]

Inferring the structure of human populations from genetic variation data is a key task in population and medical genomic studies. Although a number of methods for population structure inference have been proposed, current methods are impractical to run on biobank-scale genomic datasets containing millions of individuals and genetic variants. We introduce SCOPE, a method for population structure inference that is orders of magnitude faster than existing methods while achieving comparable accuracy. SCOPE infers population structure in about a day on a dataset containing one million individuals and variants as well as on the UK Biobank dataset containing 488,363 individuals and 569,346 variants. Furthermore, SCOPE can leverage allele frequencies from previous studies to improve the interpretability of population structure estimates.

One of the most powerful and commonly used approaches for detecting local adaptation in the genome is the identification of extreme allele frequency differences between populations. In this article, we present a new maximum likelihood method for finding regions under positive selection. It is based on a Gaussian approximation to allele frequency changes and it incorporates admixture between populations. The method can analyze multiple populations simultaneously and retains power to detect selection signatures specific to ancestry components that are not representative of any extant populations. Using simulated data, we compare our method to related approaches, and show that it is orders of magnitude faster than the state-of-the-art, while retaining similar or higher power for most simulation scenarios. We also apply it to human genomic data and identify loci with extreme genetic differentiation between major geographic groups. Many of the genes identified are previously known selected loci relating to hair pigmentation and morphology, skin, and eye pigmentation. We also identify new candidate regions, including various selected loci in the Native American component of admixed Mexican-Americans. These involve diverse biological functions, such as immunity, fat distribution, food intake, vision, and hair development.

BackgroundCurrent South American populations trace their origins mainly to three continental ancestries, i.e. European, Amerindian and African. Individual variation in relative proportions of each of these ancestries may be confounded with socio-economic factors due to population stratification. Therefore, ancestry is a potential confounder variable that should be considered in epidemiologic studies and in public health plans. However, there are few studies that have assessed the ancestry of the current admixed Chilean population. This is partly due to the high cost of genome-scale technologies commonly used to estimate ancestry. In this study we have designed a small panel of SNPs to accurately assess ancestry in the largest sampling to date of the Chilean mestizo population (n = 3349) from eight cities. Our panel is also able to distinguish between the two main Amerindian components of Chileans: Aymara from the north and Mapuche from the south.ResultsA panel of 150 ancestry-informative markers (AIMs) of SNP type was selected to maximize ancestry informativeness and genome coverage. Of these, 147 were successfully genotyped by KASPar assays in 2843 samples, with an average missing rate of 0.012, and a 0.95 concordance with microarray data. The ancestries estimated with the panel of AIMs had relative high correlations (0.88 for European, 0.91 for Amerindian, 0.70 for Aymara, and 0.68 for Mapuche components) with those obtained with AXIOM LAT1 array. The country's average ancestry was 0.53 ± 0.14 European, 0.04 ± 0.04 African, and 0.42 ± 0.14 Amerindian, disaggregated into 0.18 ± 0.15 Aymara and 0.25 ± 0.13 Mapuche. However, Mapuche ancestry was highest in the south (40.03%) and Aymara in the north (35.61%) as expected from the historical location of these ethnic groups. We make our results available through an online app and demonstrate how it can be used to adjust for ancestry when testing association between incidence of a disease and nongenetic risk factors.ConclusionsWe have conducted the most extensive sampling, across many different cities, of current Chilean population. Ancestry varied significantly by latitude and human development. The panel of AIMs is available to the community for estimating ancestry at low cost in Chileans and other populations with similar ancestry.

Admixture is increasingly being recognized as an important factor in evolutionary genetics. The distribution of genomic admixture tracts, and the resulting effects on admixture linkage disequilibrium, can be used to date the timing of admixture between species or populations. However, the theory used for such prediction assumes selective neutrality despite the fact that many famous examples of admixture involve natural selection acting for or against admixture. In this paper, we investigate the effects of positive selection on the distribution of tract lengths. We develop a theoretical framework that relies on approximating the trajectory of the selected allele using a logistic function. By numerically calculating the expected allele trajectory, we also show that the approach can be extended to cases where the logistic approximation is poor due to the effects of genetic drift. Using simulations, we show that the model is highly accurate under most scenarios. We use the model to show that positive selection on average will tend to increase the admixture tract length. However, perhaps counter-intuitively, conditional on the allele frequency at the time of sampling, positive selection will actually produce shorter expected tract lengths. We discuss the consequences of our results in interpreting the timing of the introgression of EPAS1 from Denisovans into the ancestors of Tibetans.

We evaluated ancestry effects on mutation rates, DNA methylation, and mRNA and miRNA expression among 10,678 patients across 33 cancer types from The Cancer Genome Atlas. We demonstrated that cancer subtypes and ancestry-related technical artifacts are important confounders that have been insufficiently accounted for. Once accounted for, ancestry-associated differences spanned all molecular features and hundreds of genes. Biologically significant differences were usually tissue specific but not specific to cancer. However, admixture and pathway analyses suggested some of these differences are causally related to cancer. Specific findings included increased FBXW7 mutations in patients of African origin, decreased VHL and PBRM1 mutations in renal cancer patients of African origin, and decreased immune activity in bladder cancer patients of East Asian origin.

People in the Americas represent a diverse continuum of populations with varying degrees of admixture among African, European, and Amerindigenous ancestries. In the United States, populations with non-European ancestry remain understudied, and thus little is known about the genetic architecture of phenotypic variation in these populations. Using genotype data from the Hispanic Community Health Study/Study of Latinos, we find that Amerindigenous ancestry increased by an average of ~20% spanning 1940s-1990s in Mexican Americans. These patterns result from complex interactions between several population and cultural factors which shaped patterns of genetic variation and influenced the genetic architecture of complex traits in Mexican Americans. We show for height how polygenic risk scores based on summary statistics from a European-based genome-wide association study perform poorly in Mexican Americans. Our findings reveal temporal changes in population structure within Hispanics/Latinos that may influence biomedical traits, demonstrating a need to improve our understanding of admixed populations.

Natural populations often exist in spatially diverse environments and may experience variation in the strength and targets of natural selection across their ranges. Drosophila provides an excellent opportunity to study the effects of spatially varying selection in natural populations, as both Drosophila melanogaster and Drosophila simulans live across a wide range of environments in North America. Here, we characterize patterns of variation in transposable elements (TEs) from six populations of D. melanogaster and nine populations of D. simulans sampled from multiple latitudes across North America. We find a nearly twofold excess of TEs in D. melanogaster relative to D. simulans, with this difference largely driven by TEs segregating at the lowest and highest allele frequencies. We find no effect of latitude on either total TE abundance or average TE allele frequencies in either species. Moreover, we show that, as a class of mutations, the most common patterns of TE variation do not coincide with the sampled latitudinal gradient, nor are they consistent with local adaptation acting on environmental differences found in the most extreme latitudes. We also do not find a cline in ancestry for North American D. melanogaster-for either TEs or single nucleotide polymorphisms-suggesting a limited role for demography in shaping patterns of TE variation. Though we find little evidence for widespread clinality among TEs in Drosophila, this does not necessarily imply a limited role for TEs in adaptation. We discuss the need for improved models of adaptation to large-scale environmental heterogeneity, and how these might be applied to TEs.

For establishing databases that capture the existing diversity in populations, the sample collection strategy is a determining factor and caution must be taken when choosing the suitable approach. Many researchers choose to restrict the sampling to individuals with inheritance for three generations in a specific geographic location. However, the appropriate database in a forensic context is the one representing the current population. We analyzed mtDNA composition across generations in populations from Colombia, Ecuador, and Paraguay. An overall genetic homogeneity was detected, with statistically significant differences on macrohaplogroup frequencies for few department/regions. [ABSTRACT FROM AUTHOR]

Admixture, the mixing of genetically distinct populations, is increasingly recognized as a fundamental biological process. One major goal of admixture analyses is to estimate the timing of admixture events. Whereas most methods today can only detect the most recent admixture event, here, we present coalescent theory and associated software that can be used to estimate the timing of multiple admixture events in an admixed population. We extensively validate this approach and evaluate the conditions under which it can successfully distinguish one- from two-pulse admixture models. We apply our approach to real and simulated data of Drosophila melanogaster We find evidence of a single very recent pulse of cosmopolitan ancestry contributing to African populations, as well as evidence for more ancient admixture among genetically differentiated populations in sub-Saharan Africa. These results suggest our method can quantify complex admixture histories involving genetic material introduced by multiple discrete admixture pulses. The new method facilitates the exploration of admixture and its contribution to adaptation, ecological divergence, and speciation.

Statistical models in medical and population genetics typically assume that individuals assort randomly in a population. While this simplifies model complexity, it contradicts an increasing body of evidence of nonrandom mating in human populations. Specifically, it has been shown that assortative mating is significantly affected by genomic ancestry. In this work, we examine the effects of ancestry-assortative mating on the linkage disequilibrium between local ancestry tracks of individuals in an admixed population. To accomplish this, we develop an extension to the Wright-Fisher model that allows for ancestry-based assortative mating. We show that ancestry-assortment perturbs the distribution of local ancestry linkage disequilibrium (LAD) and the variance of ancestry in a population as a function of the number of generations since admixture. This assortment effect can induce errors in demographic inference of admixed populations when methods assume random mating. We derive closed form formulae for LAD under an assortative-mating model with and without migration. We observe that LAD depends on the correlation of global ancestry of couples in each generation, the migration rate of each of the ancestral populations, the initial proportions of ancestral populations, and the number of generations since admixture. We also present the first direct evidence of ancestry-assortment in African Americans and examine LAD in simulated and real admixed population data of African Americans. We find that demographic inference under the assumption of random mating significantly underestimates the number of generations since admixture, and that accounting for assortative mating using the patterns of LAD results in estimates that more closely agrees with the historical narrative.

Naturally occurring admixture has now been documented in every major primate lineage, suggesting its key role in primate evolutionary history. Active primate hybrid zones can provide valuable insight into this process. Here, we investigate the history of admixture in one of the best-studied natural primate hybrid zones, between yellow baboons (Papio cynocephalus) and anubis baboons (Papio anubis) in the Amboseli ecosystem of Kenya. We generated a new genome assembly for yellow baboon and low-coverage genomewide resequencing data from yellow baboons, anubis baboons and known hybrids (n = 44). Using a novel composite likelihood method for estimating local ancestry from low-coverage data, we found high levels of genetic diversity and genetic differentiation between the parent taxa, and excellent agreement between genome-scale ancestry estimates and a priori pedigree, life history and morphology-based estimates (r(2)  = 0.899). However, even putatively unadmixed Amboseli yellow individuals carried a substantial proportion of anubis ancestry, presumably due to historical admixture. Further, the distribution of shared vs. fixed differences between a putatively unadmixed Amboseli yellow baboon and an unadmixed anubis baboon, both sequenced at high coverage, is inconsistent with simple isolation-migration or equilibrium migration models. Our findings suggest a complex process of intermittent contact that has occurred multiple times in baboon evolutionary history, despite no obvious fitness costs to hybrids or major geographic or behavioural barriers. In combination with the extensive phenotypic data available for baboon hybrids, our results provide valuable context for understanding the history of admixture in primates, including in our own lineage.

Hungarian Grey is an indigenous cattle breed that is one of the national symbols of Hungary. However, genetic description of the Hungarian Grey cattle has not yet been conducted based on whole-genome screening. Using the GeneSeek high-density Bovine SNP (single nucleotide polymorphism) 150 K BeadChip, we sampled the genome of 36 Hungarian Grey, 12 Maremmana, 13 Hungarian Fleckvieh and 5 Holstein-Friesian cattle for population studies and used data of 139 other cattle from an additional dataset created on European cattle breeds (Upadhyay et al.2017. Heredity 118, 169–176). The performance of a multidimensional scaling plot showed that Hungarian Grey clustered independently from other European cattle. The number and total length of runs of homozygosity (ROH) is similar or slightly below the value of other European cattle; FROH coefficients (proportion of the autosomal genome covered by ROH) are similar to Maremmana and Maronesa. The frequency of ROH does not show increased values as it can be noticed in Heck and Maltese. These results indicate that the Hungarian Grey cattle have been successfully maintained avoiding negative genetic effects, and reflect the uniqueness among European cattle. The identification of breed-specific loci has been aimed at differentiating Hungarian Grey (n = 136 in this case) from other cattle breeds (n = 169). Ten loci (−log10P > 5) were identified as markers capable for differentiation of Hungarian Grey. These markers are located on chromosomes 6, 14, 15, 16, 20 and 24.

One of the most celebrated examples of sympatric speciation in nature are monophyletic radiations of cichlid fishes endemic to Cameroon crater lakes. However, phylogenetic inference of monophyly may not detect complex colonization histories involving some allopatric isolation, such as double invasions obscured by genome-wide gene flow. Population genomic approaches are better suited to test hypotheses of sympatric speciation in these cases. Here, we use comprehensive sampling from all four sympatric crater lake cichlid radiations in Cameroon and outgroups across Africa combined with next-generation sequencing to genotype tens of thousands of SNPs. We find considerable evidence of gene flow between all four radiations and neighboring riverine populations after initial colonization. In a few cases, some sympatric species are more closely related to outgroups than others, consistent with secondary gene flow facilitating their speciation. Our results do not rule out sympatric speciation in Cameroon cichlids, but rather reveal a complex history of speciation with gene flow, including allopatric and sympatric phases, resulting in both reproductively isolated species and incipient species complexes. The best remaining non-cichlid examples of sympatric speciation all involve assortative mating within microhabitats. We speculate that this feature may be necessary to complete the process of sympatric speciation in nature.

Objectives: Gullah African Americans are descendants of formerly enslaved Africans living in the Sea Islands along the coast of the southeastern U.S., from North Carolina to Florida. Their relatively high numbers and geographic isolation were conducive to the development and preservation of a unique culture that retains deep African features. Although historical evidence supports a West‐Central African ancestry for the Gullah, linguistic and cultural evidence of a connection to Sierra Leone has led to the suggestion of this country/region as their ancestral home. This study sought to elucidate the genetic structure and ancestry of the Gullah. Materials and Methods: We leveraged whole‐genome genotype data from Gullah, African Americans from Jackson, Mississippi, African populations from Sierra Leone, and population reference panels from Africa and Europe to infer population structure, ancestry proportions, and global estimates of admixture. Results: Relative to non‐Gullah African Americans from the Southeast US, the Gullah exhibited higher mean African ancestry, lower European admixture, a similarly small Native American contribution, and increased male‐biased European admixture. A slightly tighter bottleneck in the Gullah 13 generations ago suggests a largely shared demographic history with non‐Gullah African Americans. Despite a slightly higher relatedness to populations from Sierra Leone, our data demonstrate that the Gullah are genetically related to many West African populations. Discussion: This study confirms that subtle differences in African American population structure exist at finer regional levels. Such observations can help to inform medical genetics research in African Americans, and guide the interpretation of genetic data used by African Americans seeking to explore ancestral identities. [ABSTRACT FROM AUTHOR]

The Mangalitza pig breed has suffered strong population reductions due to competition with more productive cosmopolitan breeds. In the current work, we aimed to investigate the effects of this sustained demographic recession on the genomic diversity of Mangalitza pigs. By using the Porcine Single Nucleotid Polymorphism BeadChip, we have characterized the genome-wide diversity of 350 individuals including 45 Red Mangalitza (number of samples; n=20 from Hungary and n=25 from Romania), 37 Blond Mangalitza, 26 Swallow-belly Mangalitza, 48 Blond Mangalitza × Duroc crossbreds, 5 Bazna swine, 143 pigs from the Hampshire, Duroc, Landrace, Large White and Pietrain breeds and 46 wild boars from Romania (n=18) and Hungary (n=28). Performance of a multidimensional scaling plot showed that Landrace, Large White and Pietrain pigs clustered independently from Mangalitza pigs and Romanian and Hungarian wild boars. The number and total length of ROH (runs of homozygosity), as well as FROH coefficients (proportion of the autosomal genome covered ROH) did not show major differences between Mangalitza pigs and other wild and domestic pig populations. However, Romanian and Hungarian Red Mangalitza pigs displayed an increased frequency of very long ROH (>30 Mb) when compared with other porcine breeds. These results indicate that Red Mangalitza pigs underwent recent and strong inbreeding probably as a consequence of severe reductions in census size.

Hybridization is an evolutionary process that can generate diverse outcomes, such as reinforcing species boundaries, generating new species, or facilitating the introgression of locally-adapted alleles into new genomic backgrounds. Liolaemus is a highly diverse clade of South American lizards with ~260 species and as many as ten new species are described each year. Previous Liolaemus studies have detected gene flow and introgression among species using phylogenetic network methods and/or through comparisons of nuclear and mitochondrial DNA patterns, yet no study has systematically studied hybrid zones between Liolaemus species. Here, we compared three hybrid zones between four species in the Liolaemus fitzingerii group of lizards in Central Argentina where two species, L. melanops and L. xanthoviridis, each hybridize with two other species (L. shehuen and L. fitzingerii). We sampled three transects that were each ~120 km in length and sequenced both mitochondrial and genome-wide SNP data for 267 individuals. In our analyses of nuclear DNA, we also compared bi-allelic SNPs to phased alleles (50 bp RAD loci). Population structure analyses confirmed that boundaries separating species are sharp, and all clines are

Adaptive introgression—the flow of adaptive genetic variation between species or populations—has attracted significant interest in recent years and it has been implicated in a number of cases of adaptation, from pesticide resistance and immunity, to local adaptation. Despite this, methods for identification of adaptive introgression from population genomic data are lacking. Here, we present Ancestry_HMM-S, a hidden Markov model-based method for identifying genes undergoing adaptive introgression and quantifying the strength of selection acting on them. Through extensive validation, we show that this method performs well on moderately sized data sets for realistic population and selection parameters. We apply Ancestry_HMM-S to a data set of an admixed Drosophila melanogaster population from South Africa and we identify 17 loci which show signatures of adaptive introgression, four of which have previously been shown to confer resistance to insecticides. Ancestry_HMM-S provides a powerful method for inferring adaptive introgression in data sets that are typically collected when studying admixed populations. This method will enable powerful insights into the genetic consequences of admixture across diverse populations. Ancestry_HMM-S can be downloaded from https://github.com/jesvedberg/Ancestry_HMM-S/. [ABSTRACT FROM AUTHOR]

Populations of widely distributed species encounter and must adapt to local environmental conditions. However, comprehensive characterization of the genetic basis of adaptation is demanding, requiring genome-wide genotype data, multiple sampled populations, and an understanding of population structure and potential selection pressures. Here, we used single-nucleotide polymorphism genotyping and data on numerous environmental variables to describe the genetic basis of local adaptation in 21 populations of teosinte, the wild ancestor of maize. We found complex hierarchical genetic structure created by altitude, dispersal events, and admixture among subspecies, which complicated identification of locally beneficial alleles. Patterns of linkage disequilibrium revealed four large putative inversion polymorphisms showing clinal patterns of frequency. Population differentiation and environmental correlations suggest that both inversions and intergenic polymorphisms are involved in local adaptation.

In this study, we consider admixed populations through their expected heterozygosity, a measure of genetic diversity. A population is termed admixed if its members possess recent ancestry from two or more separate sources. As a result of the fusion of source populations with different genetic variants, admixed populations can exhibit high levels of genetic diversity, reflecting contributions of their multiple ancestral groups. For a model of an admixed population derived from K source populations, we obtain a relationship between its heterozygosity and its proportions of admixture from the various source populations. We show that the heterozygosity of the admixed population is at least as great as that of the least heterozygous source population, and that it potentially exceeds the heterozygosities of all of the source populations. The admixture proportions that maximize the heterozygosity possible for an admixed population formed from a specified set of source populations are also obtained under specific conditions. We examine the special case of K = 2 source populations in detail, characterizing the maximal admixture in terms of the heterozygosities of the two source populations and the value of F ST between them. In this case, the heterozygosity of the admixed population exceeds the maximal heterozygosity of the source groups if the divergence between them, measured by F ST , is large enough, namely above a certain bound that is a function of the heterozygosities of the source groups. We present applications to simulated data as well as to data from human admixture scenarios, providing results useful for interpreting the properties of genetic variability in admixed populations. [ABSTRACT FROM AUTHOR]

Analyses of genetic polymorphism data have the potential to be highly informative about the demographic history of Native American populations, but due to a combination of historical and political factors, there are essentially no autosomal sequence polymorphism data from any Native American group. However, there are many resequencing studies involving Latinos, whose genomes contain segments inherited from their Native American ancestors. In this study, we introduce a new method for estimating local ancestry across the genomes of admixed individuals and show how this method, along with dense genotyping and targeted resequencing, can be used to assay genetic variation in ancestral Native American groups. We analyze roughly 6 Mb of resequencing data from 22 Mexican Americans to provide the first large-scale view of sequence level variation in Native Americans. We observe low levels of diversity and high levels of linkage disequilibrium in the Native American-derived sequences, consistent with a recent severe population bottleneck associated with the initial peopling of the Americas. Using two different computational approaches, one novel, we estimate that this bottleneck occurred roughly 12.5 Kya; when uncertainty in the estimation process is taken into account, our results are consistent with archeological estimates for the colonization of the Americas.

A popular approach to learning about admixture from population genetic data is by computing the allele‐sharing summary statistics known as f‐statistics. Compared to some methods in population genetics, f‐statistics are relatively simple, but interpreting them can still be complicated at times. In addition, f‐statistics can be used to build admixture graphs (multi‐population trees allowing for admixture events), which provide more explicit and thorough modelling capabilities but are correspondingly more complex to work with. Here, I discuss some of these issues to provide users of these tools with a basic guide for protocols and procedures. My focus is on the kinds of conclusions that can or cannot be drawn from the results of f4‐statistics and admixture graphs, illustrated with real‐world examples involving human populations. [ABSTRACT FROM AUTHOR]

The red junglefowl Gallus gallus is the ancestor of the domestic chicken and arguably the most important bird species on Earth. Continual gene flow between domestic and wild populations has compromised its gene pool, especially since the last century when human encroachment and habitat loss would have led to increased contact opportunities. We present the first combined genomic and morphological admixture assessment of a native population of red junglefowl, sampled from recolonized parts of its former range in Singapore, partly using whole genomes resequenced from dozens of individuals. Crucially, this population was genomically anchored to museum samples from adjacent Peninsular Malaysia collected ~110–150 years ago to infer the magnitude of modern domestic introgression across individuals. We detected a strong feral–wild genomic continuum with varying levels of domestic introgression in different subpopulations across Singapore. Using a trait scoring scheme, we determined morphological thresholds that can be used by conservation managers to successfully identify individuals with low levels of domestic introgression, and selected traits that were particularly useful for predicting domesticity in genomic profiles. Our study underscores the utility of combined genomic and morphological approaches in population management and suggests a way forward to safeguard the allelic integrity of wild red junglefowl in perpetuity. [ABSTRACT FROM AUTHOR]

Hungarian Grey is an indigenous cattle breed that is one of the national symbols of Hungary. However, genetic description of the Hungarian Grey cattle has not yet been conducted based on whole-genome screening. Using the GeneSeek high-density Bovine SNP (single nucleotide polymorphism) 150 K BeadChip, we sampled the genome of 36 Hungarian Grey, 12 Maremmana, 13 Hungarian Fleckvieh and 5 Holstein-Friesian cattle for population studies and used data of 139 other cattle from an additional dataset created on European cattle breeds (Upadhyay et al.2017. Heredity 118, 169–176). The performance of a multidimensional scaling plot showed that Hungarian Grey clustered independently from other European cattle. The number and total length of runs of homozygosity (ROH) is similar or slightly below the value of other European cattle; FROH coefficients (proportion of the autosomal genome covered by ROH) are similar to Maremmana and Maronesa. The frequency of ROH does not show increased values as it can be noticed in Heck and Maltese. These results indicate that the Hungarian Grey cattle have been successfully maintained avoiding negative genetic effects, and reflect the uniqueness among European cattle. The identification of breed-specific loci has been aimed at differentiating Hungarian Grey (n = 136 in this case) from other cattle breeds (n = 169). Ten loci (−log10P > 5) were identified as markers capable for differentiation of Hungarian Grey. These markers are located on chromosomes 6, 14, 15, 16, 20 and 24. [ABSTRACT FROM AUTHOR]

Varicella zoster virus (VZV) is the causative agent of chickenpox and shingles. The geographic distribution of VZV clades was taken as evidence that VZV migrated out of Africa with human populations. We show that extant VZV strains most likely originated in Europe and not in Africa. Europe was also identified as the ancestral location for most internal nodes of the VZV phylogeny, including the ancestor of clade 5 strains. We also show that strains from clades 1, 2, 3, and 5 derived a major proportion of their ancestry from each of 4 ancestral populations. Conversely, viruses from other clades displayed variable levels of admixture. Some low-level admixture was also observed for clade 5 genomes, but only for non-African viruses. This pattern indicates that the clade 5 VZV strains do not represent recent introductions from Africa due to migratory fluxes. These data have also relevance for the definition and classification of VZV clades. [ABSTRACT FROM AUTHOR]

Background: Global and local ancestry inference in admixed human populations can be performed using computational tools implementing distinct algorithms. The development and resulting accuracy of these tools has been tested largely on populations with relatively straightforward admixture histories but little is known about how well they perform in more complex admixture scenarios. Results: Using simulations, we show that RFMix outperforms ADMIXTURE in determining global ancestry proportions even in a complex 5-way admixed population, in addition to assigning local ancestry with an accuracy of 89%. The ability of RFMix to determine global and local ancestry to a high degree of accuracy, particularly in admixed populations provides the opportunity for more accurate association analyses. Conclusion: This study highlights the utility of the extension of computational tools to become more compatible to genetically structured populations, as well as the need to expand the sampling of diverse world-wide populations. This is particularly noteworthy as modern-day societies are becoming increasingly genetically complex and some genetic tools and commonly used ancestral populations are less appropriate. Based on these caveats and the results presented here, we suggest that RFMix be used for both global and local ancestry estimation in world-wide complex admixture scenarios particularly when including these estimates in association studies. [ABSTRACT FROM AUTHOR]

Ancestry-informative markers (AIMs) can be used to infer the ancestry of an individual to minimize the inaccuracy of self-reported ethnicity in biomedical research. In this study, we describe three methods for selecting AIM SNPs for the Malay population (Malay AIM panel) using different approaches based on pairwise FST, informativeness for assignment (In), and PCA-correlated SNPs (PCAIMs). These Malay AIM panels were extracted from genotype data stored in SNP arrays hosted by the Malaysian node of the Human Variome Project (MyHVP) and the Singapore Genome Variation Project (SGVP). In particular, genotype data from a total of 165 Malay individuals were analyzed, comprising data on 117 individual genotypes from the Affymetrix SNP-6 SNP array platform and data on 48 individual genotypes from the OMNI 2.5 Illumina SNP array platform. The HapMap phase 3 database (1397 individuals from 11 populations) was used as a reference for comparison with the Malay genotype data. The accuracy of each resulting Malay AIM panel was evaluated using a machine learning "ancestry-predictive model" constructed by using WEKA, a comprehensive machine learning platform written in Java. A total of 1250 SNPs were finally selected, which successfully identified Malay individuals from other world populations with an accuracy of 90%, but the accuracy decreased to 80% using 157 SNPs according to the pairwise FST method, while a panel of 200 SNPs selected using In and PCAIMs could be used to identify Malay individuals with an accuracy of approximately 80%. [ABSTRACT FROM AUTHOR]

There are nearly 400 modern domestic dog breeds with a unique histories and genetic profiles. To track the genetic signatures of breed development, we have assembled the most diverse dataset of dog breeds, reflecting their extensive phenotypic variation and heritage. Combining genetic distance, migration, and genome-wide haplotype sharing analyses, we uncover geographic patterns of development and independent origins of common traits. Our analyses reveal the hybrid history of breeds and elucidate the effects of immigration, revealing for the first time a suggestion of New World dog within some modern breeds. Finally, we used cladistics and haplotype sharing to show that some common traits have arisen more than once in the history of the dog. These analyses characterize the complexities of breed development, resolving longstanding questions regarding individual breed origination, the effect of migration on geographically distinct breeds, and, by inference, transfer of trait and disease alleles among dog breeds.

The Mangalitza pig breed has suffered strong population reductions due to competition with more productive cosmopolitan breeds. In the current work, we aimed to investigate the effects of this sustained demographic recession on the genomic diversity of Mangalitza pigs. By using the Porcine Single Nucleotid Polymorphism BeadChip, we have characterized the genome-wide diversity of 350 individuals including 45 Red Mangalitza (number of samples; n =20 from Hungary and n =25 from Romania), 37 Blond Mangalitza, 26 Swallow-belly Mangalitza, 48 Blond Mangalitza × Duroc crossbreds, 5 Bazna swine, 143 pigs from the Hampshire, Duroc, Landrace, Large White and Pietrain breeds and 46 wild boars from Romania (n =18) and Hungary (n =28). Performance of a multidimensional scaling plot showed that Landrace, Large White and Pietrain pigs clustered independently from Mangalitza pigs and Romanian and Hungarian wild boars. The number and total length of ROH (runs of homozygosity), as well as F ROH coefficients (proportion of the autosomal genome covered ROH) did not show major differences between Mangalitza pigs and other wild and domestic pig populations. However, Romanian and Hungarian Red Mangalitza pigs displayed an increased frequency of very long ROH (>30 Mb) when compared with other porcine breeds. These results indicate that Red Mangalitza pigs underwent recent and strong inbreeding probably as a consequence of severe reductions in census size. [ABSTRACT FROM AUTHOR]

Summary: North Africa has a great diversity of indigenous sheep breeds whose origin is linked to its environmental characteristics and to certain historical events that took place in the region. To date, few genome‐wide studies have been conducted to investigate the population structure of North African indigenous sheep. The objective of the present study was to provide a detailed assessment of the genetic structure and admixture patterns of six Maghreb sheep populations using the Illumina 50K Ovine BeadChip and comparisons with 22 global populations of sheep and mouflon. Regardless of the method of analysis used, patterns of multiple hybridization events were observed within all North African populations, leading to a heterogeneous genetic architecture that varies according to the breed. The Barbarine population showed the lowest genetic heterogeneity and major southwest Asian ancestry, providing additional support to the Asian origin of the North African fat‐tailed sheep. All other breeds presented substantial Merino introgression ranging from 15% for D'man to 31% for Black Thibar. We highlighted several signals of ancestral introgression between North African and southern European sheep. In addition, we identified two opposite gradients of ancestry, southwest Asian and central European, occurring between North Africa and central Europe. Our results provide further evidence of the weak global population structure of sheep resulting from high levels of gene flow among breeds occurring worldwide. At the regional level, signs of recent admixture among North African populations, resulting in a change of the original genomic architecture of minority breeds, were also detected. [ABSTRACT FROM AUTHOR]

Over the past decade, studies of admixed populations have increasingly gained interest in both medical and population genetics. These studies have so far shed light on the patterns of genetic variation throughout modern human evolution and have improved our understanding of the demographics and adaptive processes of human populations. To date, there exist about 20 methods or tools to deconvolve local ancestry. These methods have merits and drawbacks in estimating local ancestry in multiway admixed populations. In this article, we survey existing ancestry deconvolution methods, with special emphasis on multiway admixture, and compare these methods based on simulation results reported by different studies, computational approaches used, including mathematical and statistical models, and biological challenges related to each method. This should orient users on the choice of an appropriate method or tool for given population admixture characteristics and update researchers on current advances, challenges and opportunities behind existing ancestry deconvolution methods. [ABSTRACT FROM AUTHOR]

• Indel resource is provided for Central/South Asian Hazara and Chinese Bouyei. • Investigator® DIPplex panel is informative in Mongolian-descent Hazara. • Four datasets reveal genetic affinity between Hazaras and Turkic speakers. • East-West Eurasian admixed genetic profile is found in Hazaras. • qpAdm reveals 57.8% Mongolian-related ancestry in Hazara. Afghanistan and Pakistan are rich with a complex landscape of culture, linguistics, ethnicity and genetic legacy at the crossroads between Indian-Subcontinent and Central Asia. Hazara people have historically been suggested to be Mongolian decedents but seldom been genetically studied. To dissect the genetic structure and explore the forensic characteristics of Hazara people, we first genotyped 30 Insertion/deletion (Indel) markers in 468 samples from 2 aboriginal Hazara populations from Afghanistan and Pakistan, and 100 East Asian comparative Bouyei samples using the Investigator® DIPplex kit. Subsequently, we carried out a comprehensive population genetic analysis from four different datasets: 8895 30-Indel genotype data from 51 populations, 15,895 30-Indel allele frequency data from 98 populations, 1048 genotypes of 993 STRs and Indels from 53 HGDP populations and 2068 whole-genomes (621,799 single nucleotide polymorphisms) from 165 worldwide Human origin reference populations, to further unravel the genetic complexity between Hazara and worldwide human populations using various statistical analysis. We find that 30 Indels are in accordance with HWE, and informative and polymorphic in both Central Asians Hazara and East Asian Bouyei populations. The forensic combined probability of exclusion is larger than 0.9943 and the cumulative power of discrimination is larger than 0.99999999999936. These forensic parameters show the high level of diversity, which makes the Indel amplification system suitable for forensic routine work and may be used as a supplementary assay for routine forensic investigation. The results from pairwise genetic distances, MDS, PCA, and phylogenetic relationship reconstruction demonstrate that present-day Hazaras are genetically closer to the Turkic-speaking populations (Uyghur, Kazakh, and Kyrgyz) residing in northwest China than with other Central/South Asian populations and Mongolian. Outgroup and admixture f 3, f 4 , f 4 -ratio, qpWave, and qpAdm results further demonstrate that Hazara shares more alleles with East Asians than with other Central Asians and carries 57.8% Mongolian-related ancestry. Overall, our findings suggest that Hazaras have experienced genetic admixture with the local or neighboring populations and formed the current East-West Eurasian admixed genetic profile after their separation from the Mongolians. [ABSTRACT FROM AUTHOR]

Inferring subject ancestry using genetic data is an important step in genetic association studies, required for dealing with population stratification. It has become more challenging to infer subject ancestry quickly and accurately since large amounts of genotype data, collected from millions of subjects by thousands of studies using different methods, are accessible to researchers from repositories such as the database of Genotypes and Phenotypes (dbGaP) at the National Center for Biotechnology Information (NCBI). Study-reported populations submitted to dbGaP are often not harmonized across studies or may be missing. Widely-used methods for ancestry prediction assume that most markers are genotyped in all subjects, but this assumption is unrealistic if one wants to combine studies that used different genotyping platforms. To provide ancestry inference and visualization across studies, we developed a new method, GRAF-pop, of ancestry prediction that is robust to missing genotypes and allows researchers to visualize predicted population structure in color and in three dimensions. When genotypes are dense, GRAF-pop is comparable in quality and running time to existing ancestry inference methods EIGENSTRAT, FastPCA, and FlashPCA2, all of which rely on principal components analysis (PCA). When genotypes are not dense, GRAFpop gives much better ancestry predictions than the PCA-based methods. GRAF-pop employs basic geometric and probabilistic methods; the visualized ancestry predictions have a natural geometric interpretation, which is lacking in PCA-based methods. Since February 2018, GRAF-pop has been successfully incorporated into the dbGaP quality control process to identify inconsistencies between study-reported and computationally predicted populations and to provide harmonized population values in all new dbGaP submissions amenable to population prediction, based on marker genotypes. [ABSTRACT FROM AUTHOR]

Quantifying the population stratification in genotype samples has become a standard procedure for data manipulation before conducting genome wide association studies, as well as for tracing patterns of migration in humans and animals, and for inference about extinct founder populations. The most widely used approach capable of providing biologically interpretable results is a likelihood formulation which allows for estimation of founder genome proportions and founder allele frequency conditional on the observed genotypes. However, if founder allele frequencies are known and samples are dominated by admixed genotypes this approach may lead to biased inference. In addition, processing time increases drastically with the number of genetic markers. This article describes a simplified approach for obtaining biologically meaningful measures of population stratification at the genotype level conditional on known founder allele frequencies. It was tested on cattle and human data sets with 4,022 and 150,000 genetic markers, respectively, and proved to be very accurate in situations where founder poplations were correctly specified, or under-, over-, and miss-specified. Moreover, processing time was only marginally affected by an increase in the number of markers.

The HLA system shows the most extensive polymorphism in the human genome. Allelic and haplotypic frequencies of HLA genes vary dramatically across human populations. Due to a complex history of migration, populations in Latin America show a broad variety of admixture proportions, usually varying not only between countries, but also within countries. Knowledge of HLA allele and haplotype frequencies is essential for medical fields such as transplantation, but also serves as a means to assess genetic diversity and ancestry in human populations. Here, we have determined high‐resolution HLA‐A, ‐B, ‐C, and ‐DRB1 allele and haplotype frequencies in a sample of 713 healthy subjects from three Mestizo populations, one population of African descent, and Amerindians of five different groups from Costa Rica and Nicaragua and compared their profiles to a large set of indigenous populations from Iberia, Sub‐Saharan Africa, and the Americas. Our results show a great degree of allelic and haplotypic diversity within and across these populations, with most extended haplotypes being private. Mestizo populations show alleles and haplotypes of putative European, Amerindian, and Sub‐Saharan African origin, albeit with differential proportions. Despite some degree of gene flow, Amerindians and Afro‐descendants show great similarity to other Amerindian and West African populations, respectively. This is the first comprehensive study reporting high‐resolution HLA diversity in Central America, and its results will shed light into the genetic history of this region while also supporting the development of medical programs for organ and stem cell transplantation. [ABSTRACT FROM AUTHOR]

Quantifying the population stratification in genotype samples has become a standard procedure for data manipulation before conducting genome wide association studies, as well as for tracing patterns of migration in humans and animals, and for inference about extinct founder populations. The most widely used approach capable of providing biologically interpretable results is a likelihood formulation which allows for estimation of founder genome proportions and founder allele frequency conditional on the observed genotypes. However, if founder allele frequencies are known and samples are dominated by admixed genotypes this approach may lead to biased inference. In addition, processing time increases drastically with the number of genetic markers. This article describes a simplified approach for obtaining biologically meaningful measures of population stratification at the genotype level conditional on known founder allele frequencies. It was tested on cattle and human data sets with 4,022 and 150,000 genetic markers, respectively, and proved to be very accurate in situations where founder poplations were correctly specified, or under-, over-, and miss-specified. Moreover, processing time was only marginally affected by an increase in the number of markers. [ABSTRACT FROM AUTHOR]