Identifying Signatures of Natural Selection in Tibetan and Andean Populations Using Dense Genome Scan Data

High-altitude hypoxia (reduced inspired oxygen tension due to decreased barometric pressure) exerts severe physiological stress on the human body. Two high-altitude regions where humans have lived for millennia are the Andean Altiplano and the Tibetan Plateau. Populations living in these regions exhibit unique circulatory, respiratory, and hematological adaptations to life at high altitude. Although these responses have been well characterized physiologically, their underlying genetic basis remains unknown. We performed a genome scan to identify genes showing evidence of adaptation to hypoxia. We looked across each chromosome to identify genomic regions with previously unknown function with respect to altitude phenotypes. In addition, groups of genes functioning in oxygen metabolism and sensing were examined to test the hypothesis that particular pathways have been involved in genetic adaptation to altitude. Applying four population genetic statistics commonly used for detecting signatures of natural selection, we identified selection-nominated candidate genes and gene regions in these two populations (Andeans and Tibetans) separately. The Tibetan and Andean patterns of genetic adaptation are largely distinct from one another, with both populations showing evidence of positive natural selection in different genes or gene regions. Interestingly, one gene previously known to be important in cellular oxygen sensing, EGLN1 (also known as PHD2), shows evidence of positive selection in both Tibetans and Andeans. However, the pattern of variation for this gene differs between the two populations. Our results indicate that several key HIF-regulatory and targeted genes are responsible for adaptation to high altitude in Andeans and Tibetans, and several different chromosomal regions are implicated in the putative response to selection. These data suggest a genetic role in high-altitude adaption and provide a basis for future genotype/phenotype association studies necessary to confirm the role of selection-nominated candidate genes and gene regions in adaptation to altitude

A Markov blanket-based method for detecting causal SNPs in GWAS

<p>Abstract</p> <p>Background</p> <p>Detecting epistatic interactions associated with complex and common diseases can help to improve prevention, diagnosis and treatment of these diseases. With the development of genome-wide association studies (GWAS), designing powerful and robust computational method for identifying epistatic interactions associated with common diseases becomes a great challenge to bioinformatics society, because the study of epistatic interactions often deals with the large size of the genotyped data and the huge amount of combinations of all the possible genetic factors. Most existing computational detection methods are based on the classification capacity of SNP sets, which may fail to identify SNP sets that are strongly associated with the diseases and introduce a lot of false positives. In addition, most methods are not suitable for genome-wide scale studies due to their computational complexity.</p> <p>Results</p> <p>We propose a new Markov Blanket-based method, DASSO-MB (Detection of ASSOciations using Markov Blanket) to detect epistatic interactions in case-control GWAS. Markov blanket of a target variable T can completely shield T from all other variables. Thus, we can guarantee that the SNP set detected by DASSO-MB has a strong association with diseases and contains fewest false positives. Furthermore, DASSO-MB uses a heuristic search strategy by calculating the association between variables to avoid the time-consuming training process as in other machine-learning methods. We apply our algorithm to simulated datasets and a real case-control dataset. We compare DASSO-MB to other commonly-used methods and show that our method significantly outperforms other methods and is capable of finding SNPs strongly associated with diseases.</p> <p>Conclusions</p> <p>Our study shows that DASSO-MB can identify a minimal set of causal SNPs associated with diseases, which contains less false positives compared to other existing methods. Given the huge size of genomic dataset produced by GWAS, this is critical in saving the potential costs of biological experiments and being an efficient guideline for pathogenesis research.</p

Straightforward Inference of Ancestry and Admixture Proportions through Ancestry-Informative Insertion Deletion Multiplexing

Ancestry-informative markers (AIMs) show high allele frequency divergence between different ancestral or geographically distant populations. These genetic markers are especially useful in inferring the likely ancestral origin of an individual or estimating the apportionment of ancestry components in admixed individuals or populations. The study of AIMs is of great interest in clinical genetics research, particularly to detect and correct for population substructure effects in case-control association studies, but also in population and forensic genetics studies

Effect of metal Ions (Ni2+, Cu2+ and Zn2+) and water coordination on the structure of L-phenylalanine, L-tyrosine, L-tryptophan and their zwitterionic forms

Methods of quantum chemistry have been applied to double-charged complexes involving the transition metals Ni2+, Cu2+ and Zn2+ with the aromatic amino acids (AAA) phenylalanine, tyrosine and tryptophan. The effect of hydration on the relative stability and geometry of the individual species studied has been evaluated within the supermolecule approach. The interaction enthalpies, entropies and Gibbs energies of nine complexes Phe•M, Tyr•M, Trp•M, (M = Ni2+, Cu2+ and Zn2+) were determined at the Becke3LYP density functional level of theory. Of the transition metals studied the bivalent copper cation forms the strongest complexes with AAAs. For Ni2+and Cu2+ the most stable species are the NO coordinated cations in the AAA metal complexes, Zn2+cation prefers a binding to the aromatic part of the AAA (complex II). Some complexes energetically unfavored in the gas-phase are stabilized upon microsolvation

Metal–organic complexation in the marine environment

We discuss the voltammetric methods that are used to assess metal–organic complexation in seawater. These consist of titration methods using anodic stripping voltammetry (ASV) and cathodic stripping voltammetry competitive ligand experiments (CSV-CLE). These approaches and a kinetic approach using CSV-CLE give similar information on the amount of excess ligand to metal in a sample and the conditional metal ligand stability constant for the excess ligand bound to the metal. CSV-CLE data using different ligands to measure Fe(III) organic complexes are similar. All these methods give conditional stability constants for which the side reaction coefficient for the metal can be corrected but not that for the ligand. Another approach, pseudovoltammetry, provides information on the actual metal–ligand complex(es) in a sample by doing ASV experiments where the deposition potential is varied more negatively in order to destroy the metal–ligand complex. This latter approach gives concentration information on each actual ligand bound to the metal as well as the thermodynamic stability constant of each complex in solution when compared to known metal–ligand complexes. In this case the side reaction coefficients for the metal and ligand are corrected. Thus, this method may not give identical information to the titration methods because the excess ligand in the sample may not be identical to some of the actual ligands binding the metal in the sample

Spectroscopic Properties of pigment Li2-xZn1-xPrxTi3O8

Inorganic compounds doped with rare earths (Ce3+, Pr3+, Nd3+, Sm3+, Eu 3+, Gd 3+, Tb 3+, Tm3+) have been used in various applications including light-emitting devices such as fluorescent lamps, cathode ray tubes, lasers and inorganic pigments. In this study, Pr3+ is doped in spinel Li2ZnTi3O8 system and synthesized by the polymeric precursor method, which is based on the process developed by the Pechini, and characterized by X-ray diffraction, UV-visible and CIE-L colorimetric measures * a * b *., in order to study the effect of doping and thermal treatment on its colorimetric properties. With three different samples of Pr3+ doping (0.01; 0.05 and 0.1 mol%) were prepared and calcined at 500°C, 600°C, 700°C, 800°C and 900°C for 4 h. The analysis of X-ray diffraction confirmed the formation of pure phases with spinel structure and average crystallite size of less than 46 nm. It was found that the colorimetric properties ranging from green to red, in accordance with the increase in the concentration of Pr3+ and thermal processing temperature

ICAR: endoscopic skull‐base surgery

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Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe