Ancestry informative markers are genetic markers that show distinct genetic divergences among different populations. These markers can be utilized to discern population substructures and estimate the ancestral origins of unknown individuals. Previously, we developed a multiplex system of 30 ancestry informative single nucleotide polymorphism (AISNP) loci to facilitate ancestral inferences in different continental populations. In the current study, we first compared the ancestry resolutions of the 30 AISNPs and the other previously reported AISNP panels for African, European, East Asian, South Asian and American populations. Next, the genetic components of the Xinjiang Hui group were further explored in comparison to these continental populations based on the 30 AISNPs. Genetic divergence analyses of the 30 AISNPs in these five continental populations revealed that most of the AISNPs showed high genetic differentiations between these populations. Ancestry analysis comparisons of the 30 AISNPs and other published AISNPs revealed that these 30 AISNPs had comparable efficiency to other AISNP panels. Genetic relationship analyses among the studied Hui group and other continental populations demonstrated that the Hui group had close genetic affinities with East Asian populations and might share the genetic ancestries with East Asian populations. Overall, the 30 AISNPs can be used to predict the bio-geographical origins of different continental populations. Moreover, the obtained genetic data of 30 AISNPs in the Hui group can further enrich the extant reference data, which can be used as reference data for ancestry analyses of the Hui group.

Genetic ancestry is known to impact outcomes of genotype-phenotype studies that are designed to identify risk for common diseases in human populations. Failure to control for population stratification due to genetic ancestry can significantly confound results of disease association studies. Moreover, ancestry is a critical factor in assessing lifetime risk of disease, and can play an important role in optimizing treatment. As modern medicine moves towards using personal genetic information for clinical applications, it is important to determine genetic ancestry in an accurate, cost-effective and efficient manner. Self-identified race is a common method used to track and control for population stratification; however, social constructs of race are not necessarily informative for genetic applications. The use of ancestry informative markers (AIMs) is a more accurate method for determining genetic ancestry for the purposes of population stratification.

Smoking is a leading risk factor for many of the top ten causes of death worldwide. Of the 1.3 billion smokers globally, 80% live in low- and middle-income countries, where the number of deaths due to tobacco use is expected to double in the next decade according to the World Health Organization. Genetic studies have helped to identify biological pathways for smoking behaviours, but have mostly focussed on individuals of European ancestry or living in either North America or Europe. We performed a genome-wide association study of two smoking behaviour traits in 10,558 men of African ancestry living in five African countries and the UK. Eight independent variants were associated with either smoking initiation or cessation at P-value < 5 × 10-6, four being monomorphic or rare in European populations. Gene prioritisation strategy highlighted five genes, including SEMA6D, previously described as associated with several smoking behaviour traits. These results confirm the importance of analysing underrepresented populations in genetic epidemiology, and the urgent need for larger genomic studies to boost discovery power to better understand smoking behaviours, as well as many other traits.

The variables such as race, skin colour and ethnicity have become intensely discussed in medicine research, as a response to the rising debate over the importance of the ethnic-racial dimension in the scope of health-disease processes. The aim of this study was to identify the European (EUR), African (AFR) and Amerindian (AMR) ancestries on Brazilian health outcomes through a systematic literature review. This study was carried out by searching in three electronic databases, for studies published between 2005 and 2017. A total of 13 papers were eligible. The search identified the following health outcomes: visceral leishmaniosis, malaria, Alzheimer's disease, neuromyelitis optica, multiple sclerosis, prostate cancer, non-syndromic cleft lip/palate, chronic heart failure, sickle cell disease, primary congenital glaucoma, preterm labour, preterm premature rupture of membranes, systemic lupus erythematosus and type 1 diabetes mellitus. Research paper assessments were guided by the STROBE instrument, and agreements between results were determined by comparing the points attributed by two authors. Increased EUR ancestry was identified from preterm labour (PTL), type 1 diabetes (T1D) and non-syndromic cleft lip with or without cleft palate (NSCL), as well as in patients presenting aggressive prostate cancer prognoses. On the other hand, the highest AFR ancestral component was verified from systemic lupus erythematosus (SLE) and primary congenital glaucoma (PCG) cases, presenting worse prognoses. AMR ancestry may be a protective factor in the development of Alzheimer's disease (AD). The worst hemodynamic parameters in cases of heart failure (HF) were identified among individuals with greater AMR and AFR ancestry indices.

Admixed populations can make an important contribution to the discovery of disease susceptibility genes if the parental populations exhibit substantial variation in susceptibility. Admixture mapping has been used successfully, but is not designed to cope with populations that have more than two or three ancestral populations. The inference of admixture proportions and local ancestry and the imputation of missing genotypes in admixed populations are crucial in both understanding variation in disease and identifying novel disease loci. These inferences make use of reference populations, and accuracy depends on the choice of ancestral populations. Using an insufficient or inaccurate ancestral panel can result in erroneously inferred ancestry and affect the detection power of GWAS and meta-analysis when using imputation. Current algorithms are inadequate for multi-way admixed populations. To address these challenges we developed PROXYANC, an approach to select the best proxy ancestral populations. From the simulation of a multi-way admixed population we demonstrate the capability and accuracy of PROXYANC and illustrate the importance of the choice of ancestry in both estimating admixture proportions and imputing missing genotypes. We applied this approach to a complex, uniquely admixed South African population. Using genome-wide SNP data from over 764 individuals, we accurately estimate the genetic contributions from the best ancestral populations: isiXhosa [Formula: see text], ‡Khomani SAN [Formula: see text], European [Formula: see text], Indian [Formula: see text], and Chinese [Formula: see text]. We also demonstrate that the ancestral allele frequency differences correlate with increased linkage disequilibrium in the South African population, which originates from admixture events rather than population bottlenecks.

Genome-wide association studies (GWAS) in samples of European ancestry have identified thousands of genetic variants associated with complex traits in humans. However, it remains largely unclear whether these associations can be used in non-European populations. Here, we seek to quantify the proportion of genetic variation for a complex trait shared between continental populations. We estimated the between-population correlation of genetic effects at all SNPs ([Formula: see text]) or genome-wide significant SNPs ([Formula: see text]) for height and body mass index (BMI) in samples of European (EUR; [Formula: see text]) and African (AFR; [Formula: see text]) ancestry. The [Formula: see text] between EUR and AFR was 0.75 ([Formula: see text]) for height and 0.68 ([Formula: see text]) for BMI, and the corresponding [Formula: see text] was 0.82 ([Formula: see text]) for height and 0.87 ([Formula: see text]) for BMI, suggesting that a large proportion of GWAS findings discovered in Europeans are likely applicable to non-Europeans for height and BMI. There was no evidence that [Formula: see text] differs in SNP groups with different levels of between-population difference in allele frequency or linkage disequilibrium, which, however, can be due to the lack of power.

The ancestry of the Colombian population comprises a large number of well differentiated Native communities belonging to diverse linguistic groups. In the late fifteenth century, a process of admixture was initiated with the arrival of the Europeans, and several years later, Africans also became part of the Colombian population. Therefore, the genepool of the current Colombian population results from the admixture of Native Americans, Europeans and Africans. This admixture occurred differently in each region of the country, producing a clearly stratified population. Considering the importance of population substructure in both clinical and forensic genetics, we sought to investigate and compare patterns of genetic ancestry in Colombia by studying samples from Native and non-Native populations living in its 5 continental regions: the Andes, Caribe, Amazonia, Orinoquía, and Pacific regions. For this purpose, 46 AIM-Indels were genotyped in 761 non-related individuals from current populations. Previously published genotype data from 214 Colombian Natives from five communities were used for population comparisons. Significant differences were observed between Native and non-Native populations, among non-Native populations from different regions and among Native populations from different ethnic groups. The Pacific was the region with the highest African ancestry, Amazonia harboured the highest Native ancestry and the Andean and Orinoquían regions showed the highest proportion of European ancestry. The Andean region was further sub-divided into 6 sub-regions: North East, Central West, Central East, West, South West and South East. Among these regions, the South West region showed a significantly lower European admixture than the other regions. Hardy-Weinberg equilibrium and variance values of ancestry among individuals within populations showed a potential stratification of the Pacific population.

European and African descendants settled the continental US during the 17th-19th centuries, coming into contact with established Native American populations. The resulting admixture among these groups yielded a significant reservoir of Native American ancestry in the modern US population. We analyzed the patterns of Native American admixture seen for the three largest genetic ancestry groups in the US population: African descendants, Western European descendants, and Spanish descendants. The three groups show distinct Native American ancestry profiles, which are indicative of their historical patterns of migration and settlement across the country. Native American ancestry in the modern African descendant population does not coincide with local geography, instead forming a single group with origins in the southeastern US, consistent with the Great Migration of the early 20th century. Western European descendants show Native American ancestry that tracks their geographic origins across the US, indicative of ongoing contact during westward expansion, and Native American ancestry can resolve Spanish descendant individuals into distinct local groups formed by more recent migration from Mexico and Puerto Rico. We found an anomalous pattern of Native American ancestry from the US southwest, which most likely corresponds to the Nuevomexicano descendants of early Spanish settlers to the region. We addressed a number of controversies surrounding this population, including the extent of Sephardic Jewish ancestry. Nuevomexicanos are less admixed than nearby Mexican-American individuals, with more European and less Native American and African ancestry, and while they do show demonstrable Sephardic Jewish ancestry, the fraction is no greater than seen for other New World Spanish descendant populations.

Uveal melanoma (UM) is the most common cancer of the eye and leads to metastatic death in up to half of patients. Genomic prognostic biomarkers play an important role in clinical management in UM. However, research has been conducted almost exclusively in patients of European descent, such that the association between genetic admixture and prognostic biomarkers is unknown. In this study, we compiled 1381 control genomes from West African, European, East Asian, and Native American individuals, assembled a bioinformatic pipeline for assessing global and local ancestry, and performed an initial pilot study of 141 UM patients from our international referral center that manages many admixed individuals. Global and local estimates were associated with genomic prognostic determinants. Expression quantitative trait loci (eQTL) analysis was performed on variants found in segments. Globally, after correction for multiple testing, no prognostic variable was significantly enriched in a given ancestral group. However, there was a trend suggesting an increased proportion of European ancestry associated with expression of the PRAME oncogene (q = 0.06). Locally enriched European haplotypes were associated with the poor prognosis class 2 gene expression profile and with genes involved in immune regulation (q = 4.7 × 10-11). These findings reveal potential influences of genetic ancestry on prognostic variables, implicate immune genes in prognostic differences based on ancestry, and provide a basis for future studies of admixed patients with UM using rigorous genetic ancestry methodology.

Post-Human Genome Project progress has enabled a new wave of population genetic research, and intensified controversy over the use of race/ethnicity in this work. At the same time, the development of methods for inferring genetic ancestry offers more empirical means of assigning group labels. Here, we provide a systematic analysis of the use of race/ethnicity and ancestry in current genetic research. We base our analysis on key published recommendations for the use and reporting of race/ethnicity which advise that researchers: explain why the terms/categories were used and how they were measured, carefully define them, and apply them consistently. We studied 170 population genetic research articles from high impact journals, published 2008-2009. A comparative perspective was obtained by aligning study metrics with similar research from articles published 2001-2004. Our analysis indicates a marked improvement in compliance with some of the recommendations/guidelines for the use of race/ethnicity over time, while showing that important shortfalls still remain: no article using 'race', 'ethnicity' or 'ancestry' defined or discussed the meaning of these concepts in context; a third of articles still do not provide a rationale for their use, with those using 'ancestry' being the least likely to do so. Further, no article discussed potential socio-ethical implications of the reported research. As such, there remains a clear imperative for highlighting the importance of consistent and comprehensive reporting on human populations to the genetics/genomics community globally, to generate explicit guidelines for the uses of ancestry and genetic ancestry, and importantly, to ensure that guidelines are followed.

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).

Genome-wide association studies (GWAS) 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 GWAS in admixed populations, such as the need to correctly adjust for population stratification to balance type I error with statistical power. 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 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 modeling HetLanc in its absence reduces 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 GWAS to benefit from modeling heterogeneity.

The current U.S. population represents an amalgam of individuals originating mainly from four continental regions (Africa, Europe, Asia and America). To study the genetic ancestry and compare with self-declared ancestry we have analyzed paternally, maternally and bi-parentally inherited DNA markers sensitive for indicating continental genetic ancestry in all four major U.S. American groups. We found that self-declared U.S. Hispanics and U.S. African Americans tend to show variable degrees of continental genetic admixture among the three genetic systems, with evidence for a marked sex-biased admixture history. Moreover, for these two groups we observed significant regional variation across the country in genetic admixture. In contrast, self-declared U.S. European and U.S. Asian Americans were genetically more homogeneous at the continental ancestry level. Two autosomal ancestry-sensitive markers located in skin pigmentation candidate genes showed significant differences in self-declared U.S. African Americans or U.S. European Americans, relative to their assumed parental populations from Africa or Europe. This provides genetic support for the importance of skin color in the complex process of ancestry identification.

Currently, the vast majority of genomic research cohorts are made up of participants with European ancestry. Genomic medicine will only reach its full potential when genomic studies become more broadly representative of global populations. We are working to support the establishment of genomic medicine in developing countries in Latin America via studies of ethnically and ancestrally diverse Colombian populations. The goal of this study was to analyze the effect of ethnicity and genetic ancestry on observed disease prevalence and predicted disease risk in Colombia. Population distributions of Colombia's three major ethnic groups - Mestizo, Afro-Colombian, and Indigenous - were compared to disease prevalence and socioeconomic indicators. Indigenous and Mestizo ethnicity show the highest correlations with disease prevalence, whereas the effect of Afro-Colombian ethnicity is substantially lower. Mestizo ethnicity is mostly negatively correlated with six high-impact health conditions and positively correlated with seven of eight common cancers; Indigenous ethnicity shows the opposite effect. Malaria prevalence in particular is strongly correlated with ethnicity. Disease prevalence co-varies across geographic regions, consistent with the regional distribution of ethnic groups. Ethnicity is also correlated with regional variation in human development, partially explaining the observed differences in disease prevalence. Patterns of genetic ancestry and admixture for a cohort of 624 individuals from Medellín were compared to disease risk inferred via polygenic risk scores (PRS). African genetic ancestry is most strongly correlated with predicted disease risk, whereas European and Native American ancestry show weaker effects. African ancestry is mostly positively correlated with disease risk, and European ancestry is mostly negatively correlated. The relationships between ethnicity and disease prevalence do not show an overall correspondence with the relationships between ancestry and disease risk. We discuss possible reasons for the divergent health effects of ethnicity and ancestry as well as the implication of our results for the development of precision medicine in Colombia.

We detail the development of the ancestry informative single nucleotide polymorphisms (SNPs) panel forming part of the VISAGE Basic Tool (BT), which combines 41 appearance predictive SNPs and 112 ancestry predictive SNPs (three SNPs shared between sets) in one massively parallel sequencing (MPS) multiplex, whereas blood-based age analysis using methylation markers is run in a parallel MPS analysis pipeline. The selection of SNPs for the BT ancestry panel focused on established forensic markers that already have a proven track record of good sequencing performance in MPS, and the overall SNP multiplex scale closely matched that of existing forensic MPS assays. SNPs were chosen to differentiate individuals from the five main continental population groups of Africa, Europe, East Asia, America, and Oceania, extended to include differentiation of individuals from South Asia. From analysis of 1000 Genomes and HGDP-CEPH samples from these six population groups, the BT ancestry panel was shown to have no classification error using the Bayes likelihood calculators of the Snipper online analysis portal. The differentiation power of the component ancestry SNPs of BT was balanced as far as possible to avoid bias in the estimation of co-ancestry proportions in individuals with admixed backgrounds. The balancing process led to very similar cumulative population-specific divergence values for Africa, Europe, America, and Oceania, with East Asia being slightly below average, and South Asia an outlier from the other groups. Comparisons were made of the African, European, and Native American estimated co-ancestry proportions in the six admixed 1000 Genomes populations, using the BT ancestry panel SNPs and 572,000 Affymetrix Human Origins array SNPs. Very similar co-ancestry proportions were observed down to a minimum value of 10%, below which, low-level co-ancestry was not always reliably detected by BT SNPs. The Snipper analysis portal provides a comprehensive population dataset for the BT ancestry panel SNPs, comprising a 520-sample standardised reference dataset; 3445 additional samples from 1000 Genomes, HGDP-CEPH, Simons Foundation and Estonian Biocentre genome diversity projects; and 167 samples of six populations from in-house genotyping of individuals from Middle East, North and East African regions complementing those of the sampling regimes of the other diversity projects.

Cattle imported from the Iberian Peninsula spread throughout America in the early years of discovery and colonization to originate Creole breeds, which adapted to a wide diversity of environments and later received influences from other origins, including zebu cattle in more recent years. We analyzed uniparental genetic markers and autosomal microsatellites in DNA samples from 114 cattle breeds distributed worldwide, including 40 Creole breeds representing the whole American continent, and samples from the Iberian Peninsula, British islands, Continental Europe, Africa and American zebu. We show that Creole breeds differ considerably from each other, and most have their own identity or group with others from neighboring regions. Results with mtDNA indicate that T1c-lineages are rare in Iberia but common in Africa and are well represented in Creoles from Brazil and Colombia, lending support to a direct African influence on Creoles. This is reinforced by the sharing of a unique Y-haplotype between cattle from Mozambique and Creoles from Argentina. Autosomal microsatellites indicate that Creoles occupy an intermediate position between African and European breeds, and some Creoles show a clear Iberian signature. Our results confirm the mixed ancestry of American Creole cattle and the role that African cattle have played in their development.

At least 20% of Colombians identify as having African ancestry, yielding the second largest population of Afro-descendants in Latin America. To date, there have been relatively few studies focused on the genetic ancestry of Afro-Latino populations. We report a comparative analysis of the genetic ancestry of Chocó, a state located on Colombia's Pacific coast with a population that is >80% Afro-Colombian. We compared genome-wide patterns of genetic ancestry and admixture for Chocó to six other admixed American populations, with an emphasis on a Mestizo population from the nearby Colombian city of Medellín. One hundred sample donors from Chocó were genotyped across 610,545 genomic sites and compared with 94 publicly available whole genome sequences from Medellín. At the continental level, Chocó shows mostly African genetic ancestry (76%) with a nearly even split between European (13%) and Native American (11%) fractions, whereas Medellín has primarily European ancestry (75%), followed by Native American (18%) and African (7%). Sample donors from Chocó self-identify as having more African ancestry, and conversely less European and Native American ancestry, than can be genetically inferred, as opposed to what we previously found for Medellín, where individuals tend to overestimate levels of European ancestry. We developed a novel approach for subcontinental ancestry assignment, which allowed us to characterize subcontinental source populations for each of the three distinct continental ancestry fractions separately. Despite the clear differences between Chocó and Medellín at the level of continental ancestry, the two populations show overall patterns of subcontinental ancestry that are highly similar. Their African subcontinental ancestries are only slightly different, with Chocó showing more exclusive shared ancestry with the modern Yoruba (Nigerian) population, and Medellín having relatively more shared ancestry with West African populations in Sierra Leone and Gambia. Both populations show very similar Spanish ancestry within Europe and virtually identical patterns of Native American ancestry, with main contributions from the Embera and Waunana tribes. When the three subcontinental ancestry components are considered jointly, the populations of Chocó and Medellín are shown to be most closely related, to the exclusion of the other admixed American populations that we analyzed. We consider the implications of the existence of shared subcontinental ancestries for Colombian populations that appear, at first glance, to be clearly distinct with respect to competing notions of national identity that emphasize ethnic mixing (mestizaje) vs. group-specific identities (multiculturalism).

European wildlife has been subjected to intensifying levels of anthropogenic impact throughout the Holocene, yet the main genetic partitioning of many species is thought to still reflect the late-Pleistocene glacial refugia. We analyzed 26,342 nuclear SNPs of 464 wild boar (Sus scrofa) across the European continent to infer demographic history and reassess the genetic consequences of natural and anthropogenic forces. We found that population fragmentation, inbreeding and recent hybridization with domestic pigs have caused the spatial genetic structure to be heterogeneous at the local scale. Underlying local anthropogenic signatures, we found a deep genetic structure in the form of an arch-shaped cline extending from the Dinaric Alps, via Southeastern Europe and the Baltic states, to Western Europe and, finally, to the genetically diverged Iberian peninsula. These findings indicate that, despite considerable anthropogenic influence, the deeper, natural continental structure is still intact. Regarding the glacial refugia, our findings show a weaker signal than generally assumed, but are nevertheless suggestive of two main recolonization routes, with important roles for Southern France and the Balkans. Our results highlight the importance of applying genomic resources and framing genetic results within a species' demographic history and geographic distribution for a better understanding of the complex mixture of underlying processes.

We examined the relationship between continental-level genetic ancestry and racial and ethnic identity in an admixed population in New Mexico with the goal of increasing our understanding of how racial and ethnic identity influence genetic substructure in admixed populations. Our sample consists of 98 New Mexicans who self-identified as Hispanic or Latino (NM-HL) and who further categorized themselves by race and ethnic subgroup membership. The genetic data consist of 270 newly-published autosomal microsatellites from the NM-HL sample and previously published data from 57 globally distributed populations, including 13 admixed samples from Central and South America. For these data, we 1) summarized the major axes of genetic variation using principal component analyses, 2) performed tests of Hardy Weinberg equilibrium, 3) compared empirical genetic ancestry distributions to those predicted under a model of admixture that lacked substructure, 4) tested the hypotheses that individuals in each sample had 100%, 0%, and the sample-mean percentage of African, European, and Native American ancestry. We found that most NM-HL identify themselves and their parents as belonging to one of two groups, conforming to a region-specific narrative that distinguishes recent immigrants from Mexico from individuals whose families have resided in New Mexico for generations and who emphasize their Spanish heritage. The "Spanish" group had significantly lower Native American ancestry and higher European ancestry than the "Mexican" group. Positive FIS values, PCA plots, and heterogeneous ancestry distributions suggest that most Central and South America admixed samples also contain substructure, and that this substructure may be related to variation in social identity. Genetic substructure appears to be common in admixed populations in the Americas and may confound attempts to identify disease-causing genes and to understand the social causes of variation in health outcomes and social inequality.

South Asians have a two- to fivefold higher risk of developing type 2 diabetes than those of white European descent. Greater central adiposity and storage of fat in deeper or ectopic depots are potential contributing mechanisms. We collated existing and new data on the amount of subcutaneous (SAT), visceral (VAT) and liver fat in adults of South Asian and white European descent to provide a robust assessment of potential ethnic differences in these factors.