A genome scan for genes underlying adult body size differences between Central African hunter-gatherers and farmers.

The evolutionary and biological bases of the Central African "pygmy" phenotype, a characteristic of rainforest hunter-gatherers defined by reduced body size compared with neighboring farmers, remain largely unknown. Here, we perform a joint investigation in Central African hunter-gatherers and farmers of adult standing height, sitting height, leg length, and body mass index (BMI), considering 358 hunter-gatherers and 169 farmers with genotypes for 153,798 SNPs. In addition to reduced standing heights, hunter-gatherers have shorter sitting heights and leg lengths and higher sitting/standing height ratios than farmers and lower BMI for males. Standing height, sitting height, and leg length are strongly correlated with inferred levels of farmer genetic ancestry, whereas BMI is only weakly correlated, perhaps reflecting greater contributions of non-genetic factors to body weight than to height. Single- and multi-marker association tests identify one region and eight genes associated with hunter-gatherer/farmer status, and 24 genes associated with the height-related traits. Many of these genes have putative functions consistent with roles in determining their associated traits and the pygmy phenotype, and they include three associated with standing height in non-Africans (PRKG1, DSCAM, MAGI2). We find evidence that European height-associated SNPs or variants in linkage disequilibrium with them contribute to standing- and sitting-height determination in Central Africans, but not to the differential status of hunter-gatherers and farmers. These findings provide new insights into the biological basis of the pygmy phenotype, and they highlight the potential of cross-population studies for exploring the genetic basis of phenotypes that vary naturally across populations.

Relationship between Deleterious Variation, Genomic Autozygosity, and Disease Risk: Insights from The 1000 Genomes Project.

Genomic regions of autozygosity (ROAs) represent segments of individual genomes that are homozygous for haplotypes inherited identical-by-descent (IBD) from a common ancestor. ROAs are nonuniformly distributed across the genome, and increased ROA levels are a reported risk factor for numerous complex diseases. Previously, we hypothesized that long ROAs are enriched for deleterious homozygotes as a result of young haplotypes with recent deleterious mutations-relatively untouched by purifying selection-being paired IBD as a consequence of recent parental relatedness, a pattern supported by ROA and whole-exome sequence data on 27 individuals. Here, we significantly bolster support for our hypothesis and expand upon our original analyses using ROA and whole-genome sequence data on 2,436 individuals from The 1000 Genomes Project. Considering CADD deleteriousness scores, we reaffirm our previous observation that long ROAs are enriched for damaging homozygotes worldwide. We show that strongly damaging homozygotes experience greater enrichment than weaker damaging homozygotes, while overall enrichment varies appreciably among populations. Mendelian disease genes and those encoding FDA-approved drug targets have significantly increased rates of gain in damaging homozygotes with increasing ROA coverage relative to all other genes. In genes implicated in eight complex phenotypes for which ROA levels have been identified as a risk factor, rates of gain in damaging homozygotes vary across phenotypes and populations but frequently differ significantly from non-disease genes. These findings highlight the potential confounding effects of population background in the assessment of associations between ROA levels and complex disease risk, which might underlie reported inconsistencies in ROA-phenotype associations.

Weighted likelihood inference of genomic autozygosity patterns in dense genotype data.

BACKGROUND: Genomic regions of autozygosity (ROA) arise when an individual is homozygous for haplotypes inherited identical-by-descent from ancestors shared by both parents. Over the past decade, they have gained importance for understanding evolutionary history and the genetic basis of complex diseases and traits. However, methods to infer ROA in dense genotype data have not evolved in step with advances in genome technology that now enable us to rapidly create large high-resolution genotype datasets, limiting our ability to investigate their constituent ROA patterns. METHODS: We report a weighted likelihood approach for inferring ROA in dense genotype data that accounts for autocorrelation among genotyped positions and the possibilities of unobserved mutation and recombination events, and variability in the confidence of individual genotype calls in whole genome sequence (WGS) data. RESULTS: Forward-time genetic simulations under two demographic scenarios that reflect situations where inbreeding and its effect on fitness are of interest suggest this approach is better powered than existing state-of-the-art methods to infer ROA at marker densities consistent with WGS and popular microarray genotyping platforms used in human and non-human studies. Moreover, we present evidence that suggests this approach is able to distinguish ROA arising via consanguinity from ROA arising via endogamy. Using subsets of The 1000 Genomes Project Phase 3 data we show that, relative to WGS, intermediate and long ROA are captured robustly with popular microarray platforms, while detection of short ROA is more variable and improves with marker density. Worldwide ROA patterns inferred from WGS data are found to accord well with those previously reported on the basis of microarray genotype data. Finally, we highlight the potential of this approach to detect genomic regions enriched for autozygosity signals in one group relative to another based upon comparisons of per-individual autozygosity likelihoods instead of inferred ROA frequencies. CONCLUSIONS: This weighted likelihood ROA inference approach can assist population- and disease-geneticists working with a wide variety of data types and species to explore ROA patterns and to identify genomic regions with differential ROA signals among groups, thereby advancing our understanding of evolutionary history and the role of recessive variation in phenotypic variation and disease.

Parallel Trajectories of Genetic and Linguistic Admixture in a Genetically Admixed Creole Population.

Joint analyses of genes and languages, both of which are transmitted in populations by descent with modification-genes vertically by Mendel's laws, language via combinations of vertical, oblique, and horizontal processes [1-4]-provide an informative approach for human evolutionary studies [5-10]. Although gene-language analyses have employed extensive data on individual genetic variation [11-23], their linguistic data have not considered corresponding long-recognized [24] variability in individual speech patterns, or idiolects. Genetically admixed populations that speak creole languages show high genetic and idiolectal variation-genetic variation owing to heterogeneity in ancestry within admixed groups [25, 26] and idiolectal variation owing to recent language formation from differentiated sources [27-31]. To examine cotransmission of genetic and linguistic variation within populations, we collected genetic markers and speech recordings in the admixed creole-speaking population of Cape Verde, whose Kriolu language traces to West African languages and Portuguese [29, 32-35] and whose genetic ancestry has individual variation in European and continental African contributions [36-39]. In parallel with the combined Portuguese and West African origin of Kriolu, we find that genetic admixture in Cape Verde varies on an axis separating Iberian and Senegambian populations. We observe, analogously to vertical genetic transmission, transmission of idiolect from parents to offspring, as idiolect is predicted by parental birthplace, even after controlling for shared parent-child birthplaces. Further, African genetic admixture correlates with an index tabulating idiolectal features with likely African origins. These results suggest that Cape Verdean genetic and linguistic admixture have followed parallel evolutionary trajectories, with cotransmission of genetic and linguistic variation.

Linkage disequilibrium matches forensic genetic records to disjoint genomic marker sets.

Combining genotypes across datasets is central in facilitating advances in genetics. Data aggregation efforts often face the challenge of record matching-the identification of dataset entries that represent the same individual. We show that records can be matched across genotype datasets that have no shared markers based on linkage disequilibrium between loci appearing in different datasets. Using two datasets for the same 872 people-one with 642,563 genome-wide SNPs and the other with 13 short tandem repeats (STRs) used in forensic applications-we find that 90-98% of forensic STR records can be connected to corresponding SNP records and vice versa. Accuracy increases to 99-100% when ∼30 STRs are used. Our method expands the potential of data aggregation, but it also suggests privacy risks intrinsic in maintenance of databases containing even small numbers of markers-including databases of forensic significance.

GARLIC: Genomic Autozygosity Regions Likelihood-based Inference and Classification.

SUMMARY: Runs of homozygosity (ROH) are important genomic features that manifest when identical-by-descent haplotypes are inherited from parents. Their length distributions and genomic locations are informative about population history and they are useful for mapping recessive loci contributing to both Mendelian and complex disease risk. Here, we present software implementing a model-based method ( Pemberton et al., 2012 ) for inferring ROH in genome-wide SNP datasets that incorporates population-specific parameters and a genotyping error rate as well as provides a length-based classification module to identify biologically interesting classes of ROH. Using simulations, we evaluate the performance of this method. AVAILABILITY AND IMPLEMENTATION: GARLIC is written in C ++. Source code and pre-compiled binaries (Windows, OSX and Linux) are hosted on GitHub ( https://github.com/szpiech/garlic ) under the GNU General Public License version 3. CONTACT: zachary.szpiech@ucsf.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A comparison of worldwide phonemic and genetic variation in human populations.

Worldwide patterns of genetic variation are driven by human demographic history. Here, we test whether this demographic history has left similar signatures on phonemes-sound units that distinguish meaning between words in languages-to those it has left on genes. We analyze, jointly and in parallel, phoneme inventories from 2,082 worldwide languages and microsatellite polymorphisms from 246 worldwide populations. On a global scale, both genetic distance and phonemic distance between populations are significantly correlated with geographic distance. Geographically close language pairs share significantly more phonemes than distant language pairs, whether or not the languages are closely related. The regional geographic axes of greatest phonemic differentiation correspond to axes of genetic differentiation, suggesting that there is a relationship between human dispersal and linguistic variation. However, the geographic distribution of phoneme inventory sizes does not follow the predictions of a serial founder effect during human expansion out of Africa. Furthermore, although geographically isolated populations lose genetic diversity via genetic drift, phonemes are not subject to drift in the same way: within a given geographic radius, languages that are relatively isolated exhibit more variance in number of phonemes than languages with many neighbors. This finding suggests that relatively isolated languages are more susceptible to phonemic change than languages with many neighbors. Within a language family, phoneme evolution along genetic, geographic, or cognate-based linguistic trees predicts similar ancestral phoneme states to those predicted from ancient sources. More genetic sampling could further elucidate the relative roles of vertical and horizontal transmission in phoneme evolution.

Sequence differences at orthologous microsatellites inflate estimates of human-chimpanzee differentiation.

BACKGROUND: Microsatellites--contiguous arrays of 2-6 base-pair motifs--have formed the cornerstone of population-genetic studies for over two decades. Their genotype data typically takes the form of PCR fragment lengths obtained using locus-specific primer pairs to amplify the genomic region encompassing the microsatellite. Recently, we reported a dataset of 5,795 human and 84 chimpanzee individuals with genotypes at 246 human-derived autosomal microsatellites as a resource to facilitate interspecies comparisons. A major assumption underlying this dataset is that PCR amplicons at orthologous microsatellites are commensurable between species. RESULTS: We find this assumption to be frequently incorrect owing to discordance in microsatellite organization and variability, as well as nontrivial length imbalances caused by small species-specific indels in microsatellite flanking sequences. Converting PCR fragment lengths into the repeat numbers they represent at 138 microsatellites whose organization and variability was found to be highly similar in both species, we show that interspecies incommensurability among PCR amplicons can inflate FST and DPS estimates by up to 10.6%. Separate investigations of determinants of microsatellite variability in humans and chimpanzees uncover similar patterns with mean and maximum numbers of repeats, as well as numbers and ranges of distinct alleles, all important factors in predicting heterozygosity. In contrast, across microsatellites, numbers of repeats were significantly smaller in chimpanzees than in humans, while numbers and ranges of distinct alleles were instead larger. CONCLUSIONS: Our findings have fundamental implications for interspecies comparisons using microsatellites and offer new opportunities for more accurate comparisons of patterns of human and chimpanzee genetic variation in numerous areas of application.

Patterns of admixture and population structure in native populations of Northwest North America.

The initial contact of European populations with indigenous populations of the Americas produced diverse admixture processes across North, Central, and South America. Recent studies have examined the genetic structure of indigenous populations of Latin America and the Caribbean and their admixed descendants, reporting on the genomic impact of the history of admixture with colonizing populations of European and African ancestry. However, relatively little genomic research has been conducted on admixture in indigenous North American populations. In this study, we analyze genomic data at 475,109 single-nucleotide polymorphisms sampled in indigenous peoples of the Pacific Northwest in British Columbia and Southeast Alaska, populations with a well-documented history of contact with European and Asian traders, fishermen, and contract laborers. We find that the indigenous populations of the Pacific Northwest have higher gene diversity than Latin American indigenous populations. Among the Pacific Northwest populations, interior groups provide more evidence for East Asian admixture, whereas coastal groups have higher levels of European admixture. In contrast with many Latin American indigenous populations, the variance of admixture is high in each of the Pacific Northwest indigenous populations, as expected for recent and ongoing admixture processes. The results reveal some similarities but notable differences between admixture patterns in the Pacific Northwest and those in Latin America, contributing to a more detailed understanding of the genomic consequences of European colonization events throughout the Americas.

Population-genetic influences on genomic estimates of the inbreeding coefficient: a global perspective.

BACKGROUND/AIMS: Culturally driven marital practices provide a key instance of an interaction between social and genetic processes in shaping patterns of human genetic variation, producing, for example, increased identity by descent through consanguineous marriage. A commonly used measure to quantify identity by descent in an individual is the inbreeding coefficient, a quantity that reflects not only consanguinity, but also other aspects of kinship in the population to which the individual belongs. Here, in populations worldwide, we examine the relationship between genomic estimates of the inbreeding coefficient and population patterns in genetic variation. METHODS: Using genotypes at 645 microsatellites, we compare inbreeding coefficients from 5,043 individuals representing 237 populations worldwide to demographic consanguinity frequency estimates available for 26 populations as well as to other quantities that can illuminate population-genetic influences on inbreeding coefficients. RESULTS: We observe higher inbreeding coefficient estimates in populations and geographic regions with known high levels of consanguinity or genetic isolation and in populations with an increased effect of genetic drift and decreased genetic diversity with increasing distance from Africa. For the small number of populations with specific consanguinity estimates, we find a correlation between inbreeding coefficients and consanguinity frequency (r = 0.349, p = 0.040). CONCLUSIONS: The results emphasize the importance of both consanguinity and population-genetic factors in influencing variation in inbreeding coefficients, and they provide insight into factors useful for assessing the effect of consanguinity on genomic patterns in different populations.

A mutation in the canine gene encoding folliculin-interacting protein 2 (FNIP2) associated with a unique disruption in spinal cord myelination.

Novel mutations in myelin and myelin-associated genes have provided important information on oligodendrocytes and myelin and the effects of their disruption on the normal developmental process of myelination of the central nervous system (CNS). We report here a mutation in the folliculin-interacting protein 2 (FNIP2) gene in the Weimaraner dog that results in hypomyelination of the brain and a tract-specific myelin defect in the spinal cord. This myelination disruption results in a notable tremor syndrome from which affected dogs recover with time. In the peripheral tracts of the lateral and ventral columns of the spinal cord, there is a lack of mature oligodendrocytes. A genome-wide association study of DNA from three groups of dogs mapped the gene to canine chromosome 15. Sequencing of all the genes in the candidate region identified a frameshift mutation in the FNIP2 gene that segregated with the phenotype. While the functional role of FNIP2 is not known, our data would suggest that production of truncated protein results in a delay or failure of maturation of a subpopulation of oligodendrocytes.

Long runs of homozygosity are enriched for deleterious variation.

Exome sequencing offers the potential to study the population-genomic variables that underlie patterns of deleterious variation. Runs of homozygosity (ROH) are long stretches of consecutive homozygous genotypes probably reflecting segments shared identically by descent as the result of processes such as consanguinity, population size reduction, and natural selection. The relationship between ROH and patterns of predicted deleterious variation can provide insight into the way in which these processes contribute to the maintenance of deleterious variants. Here, we use exome sequencing to examine ROH in relation to the distribution of deleterious variation in 27 individuals of varying levels of apparent inbreeding from 6 human populations. A significantly greater fraction of all genome-wide predicted damaging homozygotes fall in ROH than would be expected from the corresponding fraction of nondamaging homozygotes in ROH (p < 0.001). This pattern is strongest for long ROH (p < 0.05). ROH, and especially long ROH, harbor disproportionately more deleterious homozygotes than would be expected on the basis of the total ROH coverage of the genome and the genomic distribution of nondamaging homozygotes. The results accord with a hypothesis that recent inbreeding, which generates long ROH, enables rare deleterious variants to exist in homozygous form. Thus, just as inbreeding can elevate the occurrence of rare recessive diseases that represent homozygotes for strongly deleterious mutations, inbreeding magnifies the occurrence of mildly deleterious variants as well.

Population structure in a comprehensive genomic data set on human microsatellite variation.

Over the past two decades, microsatellite genotypes have provided the data for landmark studies of human population-genetic variation. However, the various microsatellite data sets have been prepared with different procedures and sets of markers, so that it has been difficult to synthesize available data for a comprehensive analysis. Here, we combine eight human population-genetic data sets at the 645 microsatellite loci they share in common, accounting for procedural differences in the production of the different data sets, to assemble a single data set containing 5795 individuals from 267 worldwide populations. We perform a systematic analysis of genetic relatedness, detecting 240 intra-population and 92 inter-population pairs of previously unidentified close relatives and proposing standardized subsets of unrelated individuals for use in future studies. We then augment the human data with a data set of 84 chimpanzees at the 246 loci they share in common with the human samples. Multidimensional scaling and neighbor-joining analyses of these data sets offer new insights into the structure of human populations and enable a comparison of genetic variation patterns in chimpanzees with those in humans. Our combined data sets are the largest of their kind reported to date and provide a resource for use in human population-genetic studies.

Genomic patterns of homozygosity in worldwide human populations.

Genome-wide patterns of homozygosity runs and their variation across individuals provide a valuable and often untapped resource for studying human genetic diversity and evolutionary history. Using genotype data at 577,489 autosomal SNPs, we employed a likelihood-based approach to identify runs of homozygosity (ROH) in 1,839 individuals representing 64 worldwide populations, classifying them by length into three classes-short, intermediate, and long-with a model-based clustering algorithm. For each class, the number and total length of ROH per individual show considerable variation across individuals and populations. The total lengths of short and intermediate ROH per individual increase with the distance of a population from East Africa, in agreement with similar patterns previously observed for locus-wise homozygosity and linkage disequilibrium. By contrast, total lengths of long ROH show large interindividual variations that probably reflect recent inbreeding patterns, with higher values occurring more often in populations with known high frequencies of consanguineous unions. Across the genome, distributions of ROH are not uniform, and they have distinctive continental patterns. ROH frequencies across the genome are correlated with local genomic variables such as recombination rate, as well as with signals of recent positive selection. In addition, long ROH are more frequent in genomic regions harboring genes associated with autosomal-dominant diseases than in regions not implicated in Mendelian diseases. These results provide insight into the way in which homozygosity patterns are produced, and they generate baseline homozygosity patterns that can be used to aid homozygosity mapping of genes associated with recessive diseases.

Impact of restricted marital practices on genetic variation in an endogamous Gujarati group.

Recent studies have examined the influence on patterns of human genetic variation of a variety of cultural practices. In India, centuries-old marriage customs have introduced extensive social structuring into the contemporary population, potentially with significant consequences for genetic variation. Social stratification in India is evident as social classes that are defined by endogamous groups known as castes. Within a caste, there exist endogamous groups known as gols (marriage circles), each of which comprises a small number of exogamous gotra (lineages). Thus, while consanguinity is strictly avoided and some randomness in mate selection occurs within the gol, gene flow is limited with groups outside the gol. Gujarati Patels practice this form of "exogamic endogamy." We have analyzed genetic variation in one such group of Gujarati Patels, the Chha Gaam Patels (CGP), who comprise individuals from six villages. Population structure analysis of 1,200 autosomal loci offers support for the existence of distinctive multilocus genotypes in the CGP with respect to both non-Gujaratis and other Gujaratis, and indicates that CGP individuals are genetically very similar. Analysis of Y-chromosomal and mitochondrial haplotypes provides support for both patrilocal and patrilineal practices within the gol, and a low-level of female gene flow into the gol. Our study illustrates how the practice of gol endogamy has introduced fine-scale genetic structure into the population of India, and contributes more generally to an understanding of the way in which marriage practices affect patterns of genetic variation.

Haplotype variation and genotype imputation in African populations.

Sub-Saharan Africa has been identified as the part of the world with the greatest human genetic diversity. This high level of diversity causes difficulties for genome-wide association (GWA) studies in African populations-for example, by reducing the accuracy of genotype imputation in African populations compared to non-African populations. Here, we investigate haplotype variation and imputation in Africa, using 253 unrelated individuals from 15 Sub-Saharan African populations. We identify the populations that provide the greatest potential for serving as reference panels for imputing genotypes in the remaining groups. Considering reference panels comprising samples of recent African descent in Phase 3 of the HapMap Project, we identify mixtures of reference groups that produce the maximal imputation accuracy in each of the sampled populations. We find that optimal HapMap mixtures and maximal imputation accuracies identified in detailed tests of imputation procedures can instead be predicted by using simple summary statistics that measure relationships between the pattern of genetic variation in a target population and the patterns in potential reference panels. Our results provide an empirical basis for facilitating the selection of reference panels in GWA studies of diverse human populations, especially those of African ancestry.

Inference of unexpected genetic relatedness among individuals in HapMap Phase III.

The International Haplotype Map Project (HapMap) has provided an essential database for studies of human population genetics and genome-wide association. Phases I and II of the HapMap project generated genotype data across ∼3 million SNP loci in 270 individuals representing four populations. Phase III provides dense genotype data on ∼1.5 million SNPs, generated by Illumina and Affymetrix platforms in a larger set of individuals. Release 3 of phase III of the HapMap contains 1397 individuals from 11 populations, including 250 of the original 270 phase I and phase II individuals and 1147 additional individuals. Although some known relationships among the phase III individuals have been described in the data release, the genotype data that are currently available provide an opportunity to empirically ascertain previously unknown relationships. We performed a systematic analysis of genetic relatedness and were able not only to confirm the reported relationships, but also to detect numerous additional, previously unidentified pairs of close relatives in the HapMap sample. The inferred relative pairs make it possible to propose standardized subsets of unrelated individuals for use in future studies in which relatedness needs to be clearly defined.

Comparing spatial maps of human population-genetic variation using Procrustes analysis.

Recent applications of principal components analysis (PCA) and multidimensional scaling (MDS) in human population genetics have found that "statistical maps" based on the genotypes in population-genetic samples often resemble geographic maps of the underlying sampling locations. To provide formal tests of these qualitative observations, we describe a Procrustes analysis approach for quantitatively assessing the similarity of population-genetic and geographic maps. We confirm in two scenarios, one using single-nucleotide polymorphism (SNP) data from Europe and one using SNP data worldwide, that a measurably high level of concordance exists between statistical maps of population-genetic variation and geographic maps of sampling locations. Two other examples illustrate the versatility of the Procrustes approach in population-genetic applications, verifying the concordance of SNP analyses using PCA and MDS, and showing that statistical maps of worldwide copy-number variants (CNVs) accord with statistical maps of SNP variation, especially when CNV analysis is limited to samples with the highest-quality data. As statistical maps with PCA and MDS have become increasingly common for use in summarizing population relationships, our examples highlight the potential of Procrustes-based quantitative comparisons for interpreting the results in these maps.