112 research outputs found

    NgsRelate:a software tool for estimating pairwise relatedness from next-generation sequencing data

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    Motivation: Pairwise relatedness estimation is important in many contexts such as disease mapping and population genetics. However, all existing estimation methods are based on called genotypes, which is not ideal for next-generation sequencing (NGS) data of low depth from which genotypes cannot be called with high certainty. Results: We present a software tool, NgsRelate, for estimating pairwise relatedness from NGS data. It provides maximum likelihood estimates that are based on genotype likelihoods instead of genotypes and thereby takes the inherent uncertainty of the genotypes into account. Using both simulated and real data, we show that NgsRelate provides markedly better estimates for low-depth NGS data than two state-of-the-art genotype-based methods. Availability: NgsRelate is implemented in C++ and is available under the GNU license at www.popgen.dk/software. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online

    Identifying a living great-grandson of the Lakota Sioux leader Tatanka Iyotake (Sitting Bull).

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    A great-grandson of the legendary Lakota Sioux leader Sitting Bull (Tatanka Iyotake), Ernie LaPointe, wished to have their familial relationship confirmed via genetic analysis, in part, to help settle concerns over Sitting Bull’s final resting place. To address Ernie LaPointe’s claim of family relationship, we obtained minor amounts of genomic data from a small piece of hair from Sitting Bull’s scalp lock, which was repatriated in 2007. We then compared these data to genome-wide data from LaPointe and other Lakota Sioux using a new probabilistic approach and concluded that Ernie LaPointe is Sitting Bull’s great-grandson. To our knowledge, this is the first published example of a familial relationship between contemporary and a historical individual that has been confirmed using such limited amounts of ancient DNA across such distant relatives. Hence, this study opens the possibility for broadening genealogical research, even when only minor amounts of ancient genetic material are accessible

    Identification of novel genetic determinants of erythrocyte membrane fatty acid composition among Greenlanders

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    Fatty acids (FAs) are involved in cellular processes important for normal body function, and perturbation of FA balance has been linked to metabolic disturbances, including type 2 diabetes. An individual's level of FAs is affected by diet, lifestyle, and genetic variation. We aimed to improve the understanding of the mechanisms and pathways involved in regulation of FA tissue levels, by identifying genetic loci associated with inter-individual differences in erythrocyte membrane FA levels. We assessed the levels of 22 FAs in the phospholipid fraction of erythrocyte membranes from 2,626 Greenlanders in relation to single nucleotide polymorphisms genotyped on the MetaboChip or imputed. We identified six independent association signals. Novel loci were identified on chromosomes 5 and 11 showing strongest association with oleic acid (rs76430747 in ACSL6, beta (SE): -0.386% (0.034), p = 1.8x10-28) and docosahexaenoic acid (rs6035106 in DTD1, 0.137% (0.025), p = 6.4x10-8), respectively. For a missense variant (rs80356779) in CPT1A, we identified a number of novel FA associations, the strongest with 11-eicosenoic acid (0.473% (0.035), p = 2.6x10-38), and for variants in FADS2 (rs174570), LPCAT3 (rs2110073), and CERS4 (rs11881630) we replicated known FA associations. Moreover, we observed metabolic implications of the ACSL6 (rs76430747) and CPT1A (rs80356779) variants, which both were associated with altered HbA1c (0.051% (0.013), p = 5.6x10-6 and -0.034% (0.016), p = 3.1x10-4, respectively). The latter variant was also associated with reduced insulin resistance (HOMA-IR, -0.193 (0.050), p = 3.8x10-6), as well as measures of smaller body size, including weight (-2.676 kg (0.523), p = 2.4x10-7), lean mass (-1.200 kg (0.271), p = 1.7x10-6), height (-0.966 cm (0.230), p = 2.0x10-5), and BMI (-0.638 kg/m2 (0.181), p = 2.8x10-4). In conclusion, we have identified novel genetic determinants of FA composition in phospholipids in erythrocyte membranes, and have shown examples of links between genetic variants associated with altered FA membrane levels and changes in metabolic traits

    Uncovering the genetic history of the present-day greenlandic population

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    Because of past limitations in samples and genotyping technologies, important questions about the history of the present-day Greenlandic population remain unanswered. In an effort to answer these questions and in general investigate the genetic history of the Greenlandic population, we analyzed ∼200,000 SNPs from more than 10% of the adult Greenlandic population (n = 4,674). We found that recent gene flow from Europe has had a substantial impact on the population: more than 80% of the Greenlanders have some European ancestry (on average ∼25% of their genome). However, we also found that the amount of recent European gene flow varies across Greenland and is far smaller in the more historically isolated areas in the north and east and in the small villages in the south. Furthermore, we found that there is substantial population structure in the Inuit genetic component of the Greenlanders and that individuals from the east, west, and north can be distinguished from each other. Moreover, the genetic differences in the Inuit ancestry are consistent with a single colonization wave of the island from north to west to south to east. Although it has been speculated that there has been historical admixture between the Norse Vikings who lived in Greenland for a limited period ∼600–1,000 years ago and the Inuit, we found no evidence supporting this hypothesis. Similarly, we found no evidence supporting a previously hypothesized admixture event between the Inuit in East Greenland and the Dorset people, who lived in Greenland before the Inuit

    Paleogenomics. Genomic structure in Europeans dating back at least 36,200 years.

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    The origin of contemporary Europeans remains contentious. We obtained a genome sequence from Kostenki 14 in European Russia dating from 38,700 to 36,200 years ago, one of the oldest fossils of anatomically modern humans from Europe. We find that Kostenki 14 shares a close ancestry with the 24,000-year-old Mal'ta boy from central Siberia, European Mesolithic hunter-gatherers, some contemporary western Siberians, and many Europeans, but not eastern Asians. Additionally, the Kostenki 14 genome shows evidence of shared ancestry with a population basal to all Eurasians that also relates to later European Neolithic farmers. We find that Kostenki 14 contains more Neandertal DNA that is contained in longer tracts than present Europeans. Our findings reveal the timing of divergence of western Eurasians and East Asians to be more than 36,200 years ago and that European genomic structure today dates back to the Upper Paleolithic and derives from a metapopulation that at times stretched from Europe to central Asia.GeoGenetics members were supported by the Lundbeck Foundation and the Danish National Research Foundation (DNRF94). ASM was supported by the Swiss National Science Foundation (PBSKP3_143529). Research on the archaeological background by PRN was supported by a MC Career Integration Grant (322261).This is the accepted manuscript. The final version is available from Science at http://www.sciencemag.org/content/346/6213/1113.short

    A novel splice-affecting HNF1A variant with large population impact on diabetes in Greenland

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    Background: The genetic disease architecture of Inuit includes a large number of common high-impact variants. Identification of such variants contributes to our understanding of the genetic aetiology of diseases and improves global equity in genomic personalised medicine. We aimed to identify and characterise novel variants in genes associated with Maturity Onset Diabetes of the Young (MODY) in the Greenlandic population. Methods: Using combined data from Greenlandic population cohorts of 4497 individuals, including 448 whole genome sequenced individuals, we screened 14 known MODY genes for previously identified and novel variants. We functionally characterised an identified novel variant and assessed its association with diabetes prevalence and cardiometabolic traits and population impact. Findings: We identified a novel variant in the known MODY gene HNF1A with an allele frequency of 1.9% in the Greenlandic Inuit and absent elsewhere. Functional assays indicate that it prevents normal splicing of the gene. The variant caused lower 30-min insulin (β = −232 pmol/L, βSD = −0.695, P = 4.43 × 10−4) and higher 30-min glucose (β = 1.20 mmol/L, βSD = 0.441, P = 0.0271) during an oral glucose tolerance test. Furthermore, the variant was associated with type 2 diabetes (OR 4.35, P = 7.24 × 10−6) and HbA1c (β = 0.113 HbA1c%, βSD = 0.205, P = 7.84 × 10−3). The variant explained 2.5% of diabetes variance in Greenland. Interpretation: The reported variant has the largest population impact of any previously reported variant within a MODY gene. Together with the recessive TBC1D4 variant, we show that close to 1 in 5 cases of diabetes (18%) in Greenland are associated with high-impact genetic variants compared to 1–3% in large populations.publishedVersio
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