Gorka Alkorta-Aranburu

Reconstructing Native American population history.

The peopling of the Americas has been the subject of extensive genetic, archaeological and linguistic research; however, central questions remain unresolved. One contentious issue is whether the settlement occurred by means of a single migration or multiple streams of migration from Siberia. The pattern of dispersals within the Americas is also poorly understood. To address these questions at a higher resolution than was previously possible, we assembled data from 52 Native American and 17 Siberian groups genotyped at 364,470 single nucleotide polymorphisms. Here we show that Native Americans descend from at least three streams of Asian gene flow. Most descend entirely from a single ancestral population that we call ‘First American’. However, speakers of Eskimo–Aleut languages from the Arctic inherit almost half their ancestry from a second stream of Asian gene flow, and the Na-Dene-speaking Chipewyan from Canada inherit roughly one-tenth of their ancestry from a third stream. We show that the initial peopling followed a southward expansion facilitated by the coast, with sequential population splits and little gene flow after divergence, especially in South America. A major exception is in Chibchan speakers on both sides of the Panama isthmus, who have ancestry from both North and South America.

Adaptations to Climate-Mediated Selective Pressures in Humans

Humans inhabit a remarkably diverse range of environments, and adaptation through natural selection has likely played a central role in the capacity to survive and thrive in extreme climates. Unlike numerous studies that used only population genetic data to search for evidence of selection, here we scan the human genome for selection signals by identifying the SNPs with the strongest correlations between allele frequencies and climate across 61 worldwide populations. We find a striking enrichment of genic and nonsynonymous SNPs relative to non-genic SNPs among those that are strongly correlated with these climate variables. Among the most extreme signals, several overlap with those from GWAS, including SNPs associated with pigmentation and autoimmune diseases. Further, we find an enrichment of strong signals in gene sets related to UV radiation, infection and immunity, and cancer. Our results imply that adaptations to climate shaped the spatial distribution of variation in humans.

Human adaptations to diet, subsistence, and ecoregion are due to subtle shifts in allele frequency

Human populations use a variety of subsistence strategies to exploit an exceptionally broad range of ecoregions and dietary components. These aspects of human environments have changed dramatically during human evolution, giving rise to new selective pressures. To understand the genetic basis of human adaptations, we combine population genetics data with ecological information to detect variants that increased in frequency in response to new selective pressures. Our approach detects SNPs that show concordant differences in allele frequencies across populations with respect to specific aspects of the environment. Genic and especially nonsynonymous SNPs are overrepresented among those most strongly correlated with environmental variables. This provides genome-wide evidence for selection due to changes in ecoregion, diet, and subsistence. We find particularly strong signals associated with polar ecoregions, with foraging, and with a diet rich in roots and tubers. Interestingly, several of the strongest signals overlap with those implicated in energy metabolism phenotypes from genome-wide association studies, including SNPs influencing glucose levels and susceptibility to type 2 diabetes. Furthermore, several pathways, including those of starch and sucrose metabolism, are enriched for strong signals of adaptations to a diet rich in roots and tubers, whereas signals associated with polar ecoregions are overrepresented in genes associated with energy metabolism pathways.

Adaptations to new environments in humans: the role of subtle allele frequency shifts

Humans show tremendous phenotypic diversity across geographically distributed populations, and much of this diversity undoubtedly results from genetic adaptations to different environmental pressures. The availability of genome-wide genetic variation data from densely sampled populations offers unprecedented opportunities for identifying the loci responsible for these adaptations and for elucidating the genetic architecture of human adaptive traits. Several approaches have been used to detect signals of selection in human populations, and these approaches differ in the assumptions they make about the underlying mode of selection. We contrast the results of approaches based on haplotype structure and differentiation of allele frequencies to those from a method for identifying single nucleotide polymorphisms strongly correlated with environmental variables. Although the first group of approaches tends to detect new beneficial alleles that were driven to high frequencies by selection, the environmental correlation approach has power to identify alleles that experienced small shifts in frequency owing to selection. We suggest that the first group of approaches tends to identify only variants with relatively strong phenotypic effects, whereas the environmental correlation methods can detect variants that make smaller contributions to an adaptive trait.

Admixture facilitates genetic adaptations to high altitude in Tibet

Admixture is recognized as a widespread feature of human populations, renewing interest in the possibility that genetic exchange can facilitate adaptations to new environments. Studies of Tibetans revealed candidates for high-altitude adaptations in the EGLN1 and EPAS1 genes, associated with lower haemoglobin concentration. However, the history of these variants or that of Tibetans remains poorly understood. Here we analyse genotype data for the Nepalese Sherpa, and find that Tibetans are a mixture of ancestral populations related to the Sherpa and Han Chinese. EGLN1 and EPAS1 genes show a striking enrichment of high-altitude ancestry in the Tibetan genome, indicating that migrants from low altitude acquired adaptive alleles from the highlanders. Accordingly, the Sherpa and Tibetans share adaptive haemoglobin traits. This admixture-mediated adaptation shares important features with adaptive introgression. Therefore, we identify a novel mechanism, beyond selection on new mutations or on standing variation, through which populations can adapt to local environments.

The Genetic Architecture of Adaptations to High Altitude in Ethiopia

Although hypoxia is a major stress on physiological processes, several human populations have survived for millennia at high altitudes, suggesting that they have adapted to hypoxic conditions. This hypothesis was recently corroborated by studies of Tibetan highlanders, which showed that polymorphisms in candidate genes show signatures of natural selection as well as well-replicated association signals for variation in hemoglobin levels. We extended genomic analysis to two Ethiopian ethnic groups: Amhara and Oromo. For each ethnic group, we sampled low and high altitude residents, thus allowing genetic and phenotypic comparisons across altitudes and across ethnic groups. Genome-wide SNP genotype data were collected in these samples by using Illumina arrays. We find that variants associated with hemoglobin variation among Tibetans or other variants at the same loci do not influence the trait in Ethiopians. However, in the Amhara, SNP rs10803083 is associated with hemoglobin levels at genome-wide levels of significance. No significant genotype association was observed for oxygen saturation levels in either ethnic group. Approaches based on allele frequency divergence did not detect outliers in candidate hypoxia genes, but the most differentiated variants between high- and lowlanders have a clear role in pathogen defense. Interestingly, a significant excess of allele frequency divergence was consistently detected for genes involved in cell cycle control and DNA damage and repair, thus pointing to new pathways for high altitude adaptations. Finally, a comparison of CpG methylation levels between high- and lowlanders found several significant signals at individual genes in the Oromo.

Phenotypic heterogeneity in monogenic diabetes: The clinical and diagnostic utility of a gene panel-based next-generation sequencing approach

Single gene mutations that primarily affect pancreatic β-cell function account for approximately 1-2% of all cases of diabetes. Overlapping clinical features with common forms of diabetes makes diagnosis of monogenic diabetes challenging. A genetic diagnosis often leads to significant alterations in treatment, allows better prediction of disease prognosis and progression, and has implications for family members. Currently, genetic testing for monogenic diabetes relies on selection of appropriate individual genes for analysis based on the availability of often-limited phenotypic information, decreasing the likelihood of making a genetic diagnosis. We thus developed a targeted next-generation sequencing (NGS) assay for the detection of mutations in 36 genes known to cause monogenic forms of diabetes, including transient or permanent neonatal diabetes mellitus (TNDM or PNDM), maturity-onset diabetes of the young (MODY) and rare syndromic forms of diabetes. A total of 95 patient samples were analyzed: 19 with known causal mutations and 76 with a clinically suggestive phenotype but lacking a genetic diagnosis. All previously identified mutations were detected, validating our assay. Pathogenic sequence changes were identified in 19 out of 76 (25%) patients: 7 of 32 (22%) NDM cases, and 12 of 44 (27%) MODY cases. In 2 NDM patients the causal mutation was not expected as consanguinity was not reported and there were no clinical features aside from diabetes. A 3 year old patient with NDM diagnosed at 3 months of age, who previously tested negative for INS, KCNJ11 and ABCC8 mutations, was found to carry a novel homozygous mutation in EIF2AK3 (associated with Wolcott-Rallison syndrome), a gene not previously suspected because consanguinity, delayed growth, abnormal bone development and hepatic complications had not been reported. Similarly, another infant without a history of consanguinity was found to have a homozygous GCK mutation causing PNDM at birth. This study demonstrates the effectiveness of multi-gene panel analysis in uncovering molecular diagnoses in patients with monogenic forms of diabetes.

Strong Artificial Selection in Domestic Mammals Did Not Result in an Increased Recombination Rate

Recombination rates vary in intensity and location at the species, individual, sex and chromosome levels. Despite the fundamental biological importance of this process, the selective forces that operate to shape recombination rate and patterns are unclear. Domestication offers a unique opportunity to study the interplay between recombination and selection. In domesticates, intense selection for particular traits is imposed on small populations over many generations, resulting in organisms that differ, sometimes dramatically, in morphology and physiology from their wild ancestor. Although earlier studies suggested increased recombination rate in domesticates, a formal comparison of recombination rates between domestic mammals and their wild congeners was missing. In order to determine broad-scale recombination rate, we used immunolabeling detection of MLH1 foci as crossover markers in spermatocytes in three pairs of closely related wild and domestic species (dog and wolf, goat and ibex, and sheep and mouflon). In the three pairs, and contrary to previous suggestions, our data show that contemporary recombination rate is higher in the wild species. Subsequently, we inferred recombination breakpoints in sequence data for 16 genomic regions in dogs and wolves, each containing a locus associated with a dog phenotype potentially under selection during domestication. No difference in the number and distribution of recombination breakpoints was found between dogs and wolves. We conclude that our data indicate that strong directional selection did not result in changes in recombination in domestic mammals, and that both upper and lower bounds for crossover rates may be tightly regulated.

Plasma hepcidin of Ethiopian highlanders with steady-state hypoxia

To the editor: Hepcidin impedes iron absorption and is suppressed when erythropoietic iron requirements are increased. Recent studies show that during acute exposure to high-altitude hypoxia, plasma hepcidin concentrations drop when iron demands for erythropoiesis and hemoglobin synthesis are

PRIMAL: Fast and Accurate Pedigree-based Imputation from Sequence Data in a Founder Population

Founder populations and large pedigrees offer many well-known advantages for genetic mapping studies, including cost-efficient study designs. Here, we describe PRIMAL (PedigRee IMputation ALgorithm), a fast and accurate pedigree-based phasing and imputation algorithm for founder populations. PRIMAL incorporates both existing and original ideas, such as a novel indexing strategy of Identity-By-Descent (IBD) segments based on clique graphs. We were able to impute the genomes of 1,317 South Dakota Hutterites, who had genome-wide genotypes for ~300,000 common single nucleotide variants (SNVs), from 98 whole genome sequences. Using a combination of pedigree-based and LD-based imputation, we were able to assign 87% of genotypes with >99% accuracy over the full range of allele frequencies. Using the IBD cliques we were also able to infer the parental origin of 83% of alleles, and genotypes of deceased recent ancestors for whom no genotype information was available. This imputed data set will enable us to better study the relative contribution of rare and common variants on human phenotypes, as well as parental origin effect of disease risk alleles in >1,000 individuals at minimal cost.