Inference of population splits and mixtures from genome-wide allele frequency data

Many aspects of the historical relationships between populations in a species are reflected in genetic data. Inferring these relationships from genetic data, however, remains a challenging task. In this paper, we present a statistical model for inferring the patterns of population splits and mixtures in multiple populations. In this model, the sampled populations in a species are related to their common ancestor through a graph of ancestral populations. Using genome-wide allele frequency data and a Gaussian approximation to genetic drift, we infer the structure of this graph. We applied this method to a set of 55 human populations and a set of 82 dog breeds and wild canids. In both species, we show that a simple bifurcating tree does not fully describe the data; in contrast, we infer many migration events. While some of the migration events that we find have been detected previously, many have not. For example, in the human data we infer that Cambodians trace approximately 16% of their ancestry to a population ancestral to other extant East Asian populations. In the dog data, we infer that both the boxer and basenji trace a considerable fraction of their ancestry (9% and 25%, respectively) to wolves subsequent to domestication, and that East Asian toy breeds (the Shih Tzu and the Pekingese) result from admixture between modern toy breeds and "ancient" Asian breeds. Software implementing the model described here, called TreeMix, is available at http://treemix.googlecode.comComment: 28 pages, 6 figures in main text. Attached supplement is 22 pages, 15 figures. This is an updated version of the preprint available at http://precedings.nature.com/documents/6956/version/

Impact of Common Variation in Bone-Related Genes on Type 2 Diabetes and Related Traits

Exploring genetic pleiotropy can provide clues to a mechanism underlying the observed epidemiological association between type 2 diabetes and heightened fracture risk. We examined genetic variants associated with bone mineral density (BMD) for association with type 2 diabetes and glycemic traits in large well-phenotyped and -genotyped consortia. We undertook follow-up analysis in ∼19,000 individuals and assessed gene expression. We queried single nucleotide polymorphisms (SNPs) associated with BMD at levels of genome-wide significance, variants in linkage disequilibrium (r2 > 0.5), and BMD candidate genes. SNP rs6867040, at the ITGA1 locus, was associated with a 0.0166 mmol/L (0.004) increase in fasting glucose per C allele in the combined analysis. Genetic variants in the ITGA1 locus were associated with its expression in the liver but not in adipose tissue. ITGA1 variants appeared among the top loci associated with type 2 diabetes, fasting insulin, β-cell function by homeostasis model assessment, and 2-h post–oral glucose tolerance test glucose and insulin levels. ITGA1 has demonstrated genetic pleiotropy in prior studies, and its suggested role in liver fibrosis, insulin secretion, and bone healing lends credence to its contribution to both osteoporosis and type 2 diabetes. These findings further underscore the link between skeletal and glucose metabolism and highlight a locus to direct future investigations

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits : A Multi-Ethnic Meta-Analysis of 45,891 Individuals

J. Kaprio, S. Ripatti ja M.-L. Lokki työryhmien jäseniä.Peer reviewe

Infectivity of Chlamydia trachomatis Serovar LGV but Not E Is Dependent on Host Cell Heparan Sulfate

The ability of heparan sulfate, heparin, and other glycosaminoglycans to inhibit the infectivity of Chlamydia trachomatis serovars E and LGV was examined using a simple competitive inhibition assay with three cell types from the human female reproductive tract, including primary human endosalpingeal cells. With the majority of the glycosaminoglycans tested, LGV was more significantly inhibited than serovar E. We have compared chlamydial infectivity between a wild-type Chinese hamster ovary cell line and two glycosaminoglycan-deficient cell lines. LGV was shown to be unable to infect heparan sulfate-deficient and GAG-deficient Chinese hamster ovary cell lines, whereas the E serovar infected these cells as efficiently as the control (nondeficient) cells. These two sets of experiments confirmed that serovar LGV is more dependent on a heparan sulfate-related mechanism of infectivity than is serovar E. This is further supported by the fact that attempts to purify a heparan sulfate-like molecule from either serovar cultured in glycosaminoglycan-deficient cell lines were nonproductive. Previous reports have suggested that chlamydia are able to produce a heparan sulfate-like molecule that is important for attachment and infectivity. We have attempted to detect possible binding of a specific heparan sulfate antibody to C. trachomatis by flow cytometry. Results showed no binding of the heparan sulfate antibody to C. trachomatis serovar LGV or E. Our results strongly indicate that chlamydiae do not produce a heparan sulfate-like molecule but rather use host cell heparan sulfate in order to infect cells

Impact of Common Variation in Bone-Related Genes on Type 2 Diabetes and Related Traits.

Exploring genetic pleiotropy can provide clues to a mechanism underlying the observed epidemiological association between type 2 diabetes and heightened fracture risk. We examined genetic variants associated with bone mineral density (BMD) for association with type 2 diabetes and glycemic traits in large well-phenotyped and -genotyped consortia. We undertook follow-up analysis in ∼19,000 individuals and assessed gene expression. We queried single nucleotide polymorphisms (SNPs) associated with BMD at levels of genome-wide significance, variants in linkage disequilibrium (r2 > 0.5), and BMD candidate genes. SNP rs6867040, at the ITGA1 locus, was associated with a 0.0166 mmol/L (0.004) increase in fasting glucose per C allele in the combined analysis. Genetic variants in the ITGA1 locus were associated with its expression in the liver but not in adipose tissue. ITGA1 variants appeared among the top loci associated with type 2 diabetes, fasting insulin, β-cell function by homeostasis model assessment, and 2-h post–oral glucose tolerance test glucose and insulin levels. ITGA1 has demonstrated genetic pleiotropy in prior studies, and its suggested role in liver fibrosis, insulin secretion, and bone healing lends credence to its contribution to both osteoporosis and type 2 diabetes. These findings further underscore the link between skeletal and glucose metabolism and highlight a locus to direct future investigations.Liana K. Billings, Yi-Hsiang Hsu, Rachel J. Ackerman, Josée Dupuis, Benjamin F. Voight, Laura J. Rasmussen-Torvik, Serge Hercberg, Mark Lathrop, Daniel Barnes, Claudia Langenberg, Jennie Hui, Mao Fu, Nabila Bouatia-Naji, Cecile Lecoeur, Ping An, Patrik K. Magnusson, Ida Surakka, Samuli Ripatti, Lene Christiansen, Christine Dalgård, Lasse Folkersen, Elin Grundberg, the MAGIC Investigators, the DIAGRAM, Consortium, the MuTHER Consortium, the ASCOT Investigators, the GEFOS Consortium, Per Eriksson, Jaakko Kaprio, Kirsten Ohm Kyvik, Nancy L. Pedersen, Ingrid B. Borecki, Michael A. Province, Beverley Balkau, Philippe Froguel, Alan R. Shuldiner, Lyle J. Palmer, Nick Wareham, Pierre Meneton, Toby Johnson, James S. Pankow, David Karasik, James B. Meigs, Douglas P. Kiel, and Jose C. Flore

Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways

Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an analysis framework to rank pathways that requires only summary statistics. We combined this score across disorders to find common pathways across three adult psychiatric disorders: schizophrenia, major depression and bipolar disorder. Histone methylation processes showed the strongest association, and we also found statistically significant evidence for associations with multiple immune and neuronal signaling pathways and with the postsynaptic density. Our study indicates that risk variants for psychiatric disorders aggregate in particular biological pathways and that these pathways are frequently shared between disorders. Our results confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders