1,369 research outputs found

    Selection on Coding and Regulatory Variation Maintains Individuality in Major Urinary Protein Scent Marks in Wild Mice

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    Recognition of individuals by scent is widespread across animal taxa. Though animals can often discriminate chemical blends based on many compounds, recent work shows that specific protein pheromones are necessary and sufficient for individual recognition via scent marks in mice. The genetic nature of individuality in scent marks (e.g. coding versus regulatory variation) and the evolutionary processes that maintain diversity are poorly understood. The individual signatures in scent marks of house mice are the protein products of a group of highly similar paralogs in the major urinary protein (Mup) gene family. Using the offspring of wild-caught mice, we examine individuality in the major urinary protein (MUP) scent marks at the DNA, RNA and protein levels. We show that individuality arises through a combination of variation at amino acid coding sites and differential transcription of central Mup genes across individuals, and we identify eSNPs in promoters. There is no evidence of post-transcriptional processes influencing phenotypic diversity as transcripts accurately predict the relative abundance of proteins in urine samples. The match between transcripts and urine samples taken six months earlier also emphasizes that the proportional relationships across central MUP isoforms in urine is stable. Balancing selection maintains coding variants at moderate frequencies, though pheromone diversity appears limited by interactions with vomeronasal receptors. We find that differential transcription of the central Mup paralogs within and between individuals significantly increases the individuality of pheromone blends. Balancing selection on gene regulation allows for increased individuality via combinatorial diversity in a limited number of pheromones

    A multilocus assay reveals high nucleotide diversity and limited differentiation among Scandinavian willow grouse (Lagopus lagopus)

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    <p>Abstract</p> <p>Background</p> <p>There is so far very little data on autosomal nucleotide diversity in birds, except for data from the domesticated chicken and some passerines species. Estimates of nucleotide diversity reported so far in birds have been high (~10<sup>-3</sup>) and a likely explanation for this is the generally higher effective population sizes compared to mammals. In this study, the level of nucleotide diversity has been examined in the willow grouse, a non-domesticated bird species from the order Galliformes, which also holds the chicken. The willow grouse (<it>Lagopus lagopus</it>) has an almost circumpolar distribution but is absent from Greenland and the north Atlantic islands. It primarily inhabits tundra, forest edge habitats and sub-alpine vegetation. Willow grouse are hunted throughout its range, and regionally it is a game bird of great cultural and economical importance.</p> <p>Results</p> <p>We sequenced 18 autosomal protein coding loci from approximately 15–18 individuals per population. We found a total of 127 SNP's, which corresponds to 1 SNP every 51 bp. 26 SNP's were amino acid replacement substitutions. Total nucleotide diversity (<it>π</it><sub><it>t</it></sub>) was between 1.30 × 10<sup>-4 </sup>and 7.66 × 10<sup>-3 </sup>(average <it>π</it><sub><it>t </it></sub>= 2.72 × 10<sup>-3 </sup>± 2.06 × 10<sup>-3</sup>) and silent nucleotide diversity varied between 4.20 × 10<sup>-4</sup>and 2.76 × 10<sup>-2 </sup>(average <it>π</it><sub><it>S </it></sub>= 9.22 × 10<sup>-3 </sup>± 7.43 × 10<sup>-4</sup>). The synonymous diversity is approximately 20 times higher than in humans and two times higher than in chicken. Non-synonymous diversity was on average 18 times lower than the synonymous diversity and varied between 0 and 4.90 × 10<sup>-3 </sup>(average <it>π</it><sub><it>a </it></sub>= 5.08 × 10<sup>-4 </sup>± 7.43 × 10<sup>3</sup>), which suggest that purifying selection is strong in these genes. <it>F</it><sub>ST </sub>values based on synonymous SNP's varied between -5.60 × 10<sup>-4 </sup>and 0.20 among loci and revealed low levels of differentiation among the four localities, with an overall value of <it>F</it><sub>ST </sub>= 0.03 (95% CI: 0.006 – 0.057) over 60 unlinked loci. Non-synonymous SNP's gave similar results. Low levels of linkage disequilibrium were observed within genes, with an average r<sup>2 </sup>= 0.084 ± 0.110, which is expected for a large outbred population with no population differentiation. The mean per site per generation recombination parameter (ρ) was comparably high (0.028 ± 0.018), indicating high recombination rates in these genes.</p> <p>Conclusion</p> <p>We found unusually high levels of nucleotide diversity in the Scandinavian willow grouse as well as very little population structure among localities with up to 1647 km distance. There are also low levels of linkage disequilibrium within the genes and the population recombination rate is high, which is indicative of an old panmictic population, where recombination has had time to break up any haplotype blocks. The non-synonymous nucleotide diversity is low compared with the silent, which is in agreement with effective purifying selection, possibly due to the large effective population size.</p

    High performance computing for haplotyping: Models and platforms

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    \u3cp\u3eThe reconstruction of the haplotype pair for each chromosome is a hot topic in Bioinformatics and Genome Analysis. In Haplotype Assembly (HA), all heterozygous Single Nucleotide Polymorphisms (SNPs) have to be assigned to exactly one of the two chromosomes. In this work, we outline the state-of-the-art on HA approaches and present an in-depth analysis of the computational performance of GenHap, a recent method based on Genetic Algorithms. GenHap was designed to tackle the computational complexity of the HA problem by means of a divide-et-impera strategy that effectively leverages multi-core architectures. In order to evaluate GenHap’s performance, we generated different instances of synthetic (yet realistic) data exploiting empirical error models of four different sequencing platforms (namely, Illumina NovaSeq, Roche/454, PacBio RS II and Oxford Nanopore Technologies MinION). Our results show that the processing time generally decreases along with the read length, involving a lower number of sub-problems to be distributed on multiple cores.\u3c/p\u3

    Delay to celiac disease diagnosis and its implications for health-related quality of life

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    <p>Abstract</p> <p>Background</p> <p>To determine how the delay in diagnosing celiac disease (CD) has developed during recent decades and how this affects the burden of disease in terms of health-related quality of life (HRQoL), and also to consider differences with respect to sex and age.</p> <p>Methods</p> <p>In collaboration with the Swedish Society for Coeliacs, a questionnaire was sent to 1,560 randomly selected members, divided in equal-sized age- and sex strata, and 1,031 (66%) responded. HRQoL was measured with the EQ-5D descriptive system and was then translated to quality-adjusted life year (QALY) scores. A general population survey was used as comparison.</p> <p>Results</p> <p>The mean delay to diagnosis from the first symptoms was 9.7 years, and from the first doctor visit it was 5.8 years. The delay has been reduced over time for some age groups, but is still quite long. The mean QALY score during the year prior to initiated treatment was 0.66; it improved after diagnosis and treatment to 0.86, and was then better than that of a general population (0.79).</p> <p>Conclusions</p> <p>The delay from first symptoms to CD diagnosis is unacceptably long for many persons. Untreated CD results in poor HRQoL, which improves to the level of the general population if diagnosed and treated. By shortening the diagnostic delay it is possible to reduce this unnecessary burden of disease. Increased awareness of CD as a common health problem is needed, and active case finding should be intensified. Mass screening for CD might be an option in the future.</p

    Human Population Differentiation Is Strongly Correlated with Local Recombination Rate

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    Allele frequency differences across populations can provide valuable information both for studying population structure and for identifying loci that have been targets of natural selection. Here, we examine the relationship between recombination rate and population differentiation in humans by analyzing two uniformly-ascertained, whole-genome data sets. We find that population differentiation as assessed by inter-continental FST shows negative correlation with recombination rate, with FST reduced by 10% in the tenth of the genome with the highest recombination rate compared with the tenth of the genome with the lowest recombination rate (P≪10−12). This pattern cannot be explained by the mutagenic properties of recombination and instead must reflect the impact of selection in the last 100,000 years since human continental populations split. The correlation between recombination rate and FST has a qualitatively different relationship for FST between African and non-African populations and for FST between European and East Asian populations, suggesting varying levels or types of selection in different epochs of human history

    Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

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    Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

    Evidence That Mutation Is Universally Biased towards AT in Bacteria

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    Mutation is the engine that drives evolution and adaptation forward in that it generates the variation on which natural selection acts. Mutation is a random process that nevertheless occurs according to certain biases. Elucidating mutational biases and the way they vary across species and within genomes is crucial to understanding evolution and adaptation. Here we demonstrate that clonal pathogens that evolve under severely relaxed selection are uniquely suitable for studying mutational biases in bacteria. We estimate mutational patterns using sequence datasets from five such clonal pathogens belonging to four diverse bacterial clades that span most of the range of genomic nucleotide content. We demonstrate that across different types of sites and in all four clades mutation is consistently biased towards AT. This is true even in clades that have high genomic GC content. In all studied cases the mutational bias towards AT is primarily due to the high rate of C/G to T/A transitions. These results suggest that bacterial mutational biases are far less variable than previously thought. They further demonstrate that variation in nucleotide content cannot stem entirely from variation in mutational biases and that natural selection and/or a natural selection-like process such as biased gene conversion strongly affect nucleotide content

    Large scale variation in the rate of germ-line de novo mutation, base composition, divergence and diversity in humans

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    It has long been suspected that the rate of mutation varies across the human genome at a large scale based on the divergence between humans and other species. However, it is now possible to directly investigate this question using the large number of de novo mutations (DNMs) that have been discovered in humans through the sequencing of trios. We investi- gate a number of questions pertaining to the distribution of mutations using more than 130,000 DNMs from three large datasets. We demonstrate that the amount and pattern of variation differs between datasets at the 1MB and 100KB scales probably as a consequence of differences in sequencing technology and processing. In particular, datasets show differ- ent patterns of correlation to genomic variables such as replication time. Never-the-less there are many commonalities between datasets, which likely represent true patterns. We show that there is variation in the mutation rate at the 100KB, 1MB and 10MB scale that can- not be explained by variation at smaller scales, however the level of this variation is modest at large scales–at the 1MB scale we infer that ~90% of regions have a mutation rate within 50% of the mean. Different types of mutation show similar levels of variation and appear to vary in concert which suggests the pattern of mutation is relatively constant across the genome. We demonstrate that variation in the mutation rate does not generate large-scale variation in GC-content, and hence that mutation bias does not maintain the isochore struc- ture of the human genome. We find that genomic features explain less than 40% of the explainable variance in the rate of DNM. As expected the rate of divergence between spe- cies is correlated to the rate of DNM. However, the correlations are weaker than expected if all the variation in divergence was due to variation in the mutation rate. We provide evidence that this is due the effect of biased gene conversion on the probability that a mutation will become fixed. In contrast to divergence, we find that most of the variation in diversity can be explained by variation in the mutation rate. Finally, we show that the correlation between divergence and DNM density declines as increasingly divergent species are considered

    Natural Selection Affects Multiple Aspects of Genetic Variation at Putatively Neutral Sites across the Human Genome

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    A major question in evolutionary biology is how natural selection has shaped patterns of genetic variation across the human genome. Previous work has documented a reduction in genetic diversity in regions of the genome with low recombination rates. However, it is unclear whether other summaries of genetic variation, like allele frequencies, are also correlated with recombination rate and whether these correlations can be explained solely by negative selection against deleterious mutations or whether positive selection acting on favorable alleles is also required. Here we attempt to address these questions by analyzing three different genome-wide resequencing datasets from European individuals. We document several significant correlations between different genomic features. In particular, we find that average minor allele frequency and diversity are reduced in regions of low recombination and that human diversity, human-chimp divergence, and average minor allele frequency are reduced near genes. Population genetic simulations show that either positive natural selection acting on favorable mutations or negative natural selection acting against deleterious mutations can explain these correlations. However, models with strong positive selection on nonsynonymous mutations and little negative selection predict a stronger negative correlation between neutral diversity and nonsynonymous divergence than observed in the actual data, supporting the importance of negative, rather than positive, selection throughout the genome. Further, we show that the widespread presence of weakly deleterious alleles, rather than a small number of strongly positively selected mutations, is responsible for the correlation between neutral genetic diversity and recombination rate. This work suggests that natural selection has affected multiple aspects of linked neutral variation throughout the human genome and that positive selection is not required to explain these observations

    ATHENA detector proposal - a totally hermetic electron nucleus apparatus proposed for IP6 at the Electron-Ion Collider

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    ATHENA has been designed as a general purpose detector capable of delivering the full scientific scope of the Electron-Ion Collider. Careful technology choices provide fine tracking and momentum resolution, high performance electromagnetic and hadronic calorimetry, hadron identification over a wide kinematic range, and near-complete hermeticity.This article describes the detector design and its expected performance in the most relevant physics channels. It includes an evaluation of detector technology choices, the technical challenges to realizing the detector and the R&D required to meet those challenges
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