122 research outputs found

    Genome-wide association studies using single-nucleotide polymorphisms versus haplotypes: an empirical comparison with data from the North American Rheumatoid Arthritis Consortium

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    The high genomic density of the single-nucleotide polymorphism (SNP) sets that are typically surveyed in genome-wide association studies (GWAS) now allows the application of haplotype-based methods. Although the choice of haplotype-based vs. individual-SNP approaches is expected to affect the results of association studies, few empirical comparisons of method performance have been reported on the genome-wide scale in the same set of individuals. To measure the relative ability of the two strategies to detect associations, we used a large dataset from the North American Rheumatoid Arthritis Consortium to: 1) partition the genome into haplotype blocks, 2) associate haplotypes with disease, and 3) compare the results with individual-SNP association mapping. Although some associations were shared across methods, each approach uniquely identified several strong candidate regions. Our results suggest that the application of both haplotype-based and individual-SNP testing to GWAS should be adopted as a routine procedure

    A first genetic portrait of synaptonemal complex variation.

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    The synaptonemal complex (SC) is a proteinaceous scaffold required for synapsis and recombination between homologous chromosomes during meiosis. Although the SC has been linked to differences in genome-wide crossover rates, the genetic basis of standing variation in SC structure remains unknown. To investigate the possibility that recombination evolves through changes to the SC, we characterized the genetic architecture of SC divergence on two evolutionary timescales. Applying a novel digital image analysis technique to spermatocyte spreads, we measured total SC length in 9,532 spermatocytes from recombinant offspring of wild-derived mouse strains with differences in this fundamental meiotic trait. Using this large dataset, we identified the first known genomic regions involved in the evolution of SC length. Distinct loci affect total SC length divergence between and within subspecies, with the X chromosome contributing to both. Joint genetic analysis of MLH1 foci-immunofluorescent markers of crossovers-from the same spermatocytes revealed that two of the identified loci also confer differences in the genome-wide recombination rate. Causal mediation analysis suggested that one pleiotropic locus acts early in meiosis to designate crossovers prior to SC assembly, whereas a second locus primarily shapes crossover number through its effect on SC length. One genomic interval shapes the relationship between SC length and recombination rate, likely modulating the strength of crossover interference. Our findings pinpoint SC formation as a key step in the evolution of recombination and demonstrate the power of genetic mapping on standing variation in the context of the recombination pathway

    Contrasting multi-site genotypic distributions among discordant quantitative phenotypes: the APOA1/C3/A4/A5 gene cluster and cardiovascular disease risk factors

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    Most tests of association between DNA sequence variation and quantitative phenotypes in samples of randomly chosen individuals rely on specification of genotypic strata followed by comparison of phenotypes across these strata. This strategy often succeeds when phenotypic differences are caused by one or two single nucleotide polymorphisms (SNPs) among the surveyed markers. However, when multiple-SNP haplotypes account for observed phenotypic variation, identification of the best partitioning requires examination of an inordinate number of SNP combinations. An alternative approach is to rank individuals by their phenotypic measures and ask whether attributes of the genotypic variation show a non-random distribution along this phenotypic ranking. One simple version of this strategy selects the top and bottom tails of the distribution, and then tests whether genotypes from these two samples are drawn from a single population. This framework does not require the recovery of phased haplotypes and allows contrasts between large numbers of sites at once. We use a method based on this approach to identify associations between plasma triglyceride level, a risk factor for cardiovascular disease, and multi-site genotypes located in the APOA1/C3/A4/A5 cluster of apolipoprotein genes in unrelated individuals (1,071 African-American females, 780 African-American males, 1,036 European-American females, and 930 European-American males) sampled from four US cities as part of the Coronary Artery Risk Development in Young Adults (CARDIA) study. Method performance is investigated using simulations that model genealogical variation and different genetic architectures. Results indicate that this multi-site test can identify genotype-phenotype associations with reasonable power, including those generated by some simple epistatic models. Genet. Epidemiol . 2006. © 2006 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/55790/1/20163_ftp.pd

    Genetic Dissection of a Key Reproductive Barrier Between Nascent Species of House Mice

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    Reproductive isolation between species is often caused by deleterious interactions among loci in hybrids. Finding the genes involved in these incompatibilities provides insight into the mechanisms of speciation. With recently diverged subspecies, house mice provide a powerful system for understanding the genetics of reproductive isolation early in the speciation process. Although previous studies have yielded important clues about the genetics of hybrid male sterility in house mice, they have been restricted to F1 sterility or incompatibilities involving the X chromosome. To provide a more complete characterization of this key reproductive barrier, we conducted an F2 intercross between wild-derived inbred strains from two subspecies of house mice, Mus musculus musculus and Mus musculus domesticus. We identified a suite of autosomal and X-linked QTL that underlie measures of hybrid male sterility, including testis weight, sperm density, and sperm morphology. In many cases, the autosomal loci were unique to a specific sterility trait and exhibited an effect only when homozygous, underscoring the importance of examining reproductive barriers beyond the F1 generation. We also found novel two-locus incompatibilities between the M. m. musculus X chromosome and M. m. domesticus autosomal alleles. Our results reveal a complex genetic architecture for hybrid male sterility and suggest a prominent role for reproductive barriers in advanced generations in maintaining subspecies integrity in house mice

    Localizing Recent Adaptive Evolution in the Human Genome

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    Identifying genomic locations that have experienced selective sweeps is an important first step toward understanding the molecular basis of adaptive evolution. Using statistical methods that account for the confounding effects of population demography, recombination rate variation, and single-nucleotide polymorphism ascertainment, while also providing fine-scale estimates of the position of the selected site, we analyzed a genomic dataset of 1.2 million human single-nucleotide polymorphisms genotyped in African-American, European-American, and Chinese samples. We identify 101 regions of the human genome with very strong evidence (p < 10−5) of a recent selective sweep and where our estimate of the position of the selective sweep falls within 100 kb of a known gene. Within these regions, genes of biological interest include genes in pigmentation pathways, components of the dystrophin protein complex, clusters of olfactory receptors, genes involved in nervous system development and function, immune system genes, and heat shock genes. We also observe consistent evidence of selective sweeps in centromeric regions. In general, we find that recent adaptation is strikingly pervasive in the human genome, with as much as 10% of the genome affected by linkage to a selective sweep

    Predicting Unobserved Phenotypes for Complex Traits from Whole-Genome SNP Data

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    Genome-wide association studies (GWAS) for quantitative traits and disease in humans and other species have shown that there are many loci that contribute to the observed resemblance between relatives. GWAS to date have mostly focussed on discovery of genes or regulatory regions habouring causative polymorphisms, using single SNP analyses and setting stringent type-I error rates. Genome-wide marker data can also be used to predict genetic values and therefore predict phenotypes. Here, we propose a Bayesian method that utilises all marker data simultaneously to predict phenotypes. We apply the method to three traits: coat colour, %CD8 cells, and mean cell haemoglobin, measured in a heterogeneous stock mouse population. We find that a model that contains both additive and dominance effects, estimated from genome-wide marker data, is successful in predicting unobserved phenotypes and is significantly better than a prediction based upon the phenotypes of close relatives. Correlations between predicted and actual phenotypes were in the range of 0.4 to 0.9 when half of the number of families was used to estimate effects and the other half for prediction. Posterior probabilities of SNPs being associated with coat colour were high for regions that are known to contain loci for this trait. The prediction of phenotypes using large samples, high-density SNP data, and appropriate statistical methodology is feasible and can be applied in human medicine, forensics, or artificial selection programs

    Positive Selection for New Disease Mutations in the Human Germline: Evidence from the Heritable Cancer Syndrome Multiple Endocrine Neoplasia Type 2B

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    Multiple endocrine neoplasia type 2B (MEN2B) is a highly aggressive thyroid cancer syndrome. Since almost all sporadic cases are caused by the same nucleotide substitution in the RET proto-oncogene, the calculated disease incidence is 100–200 times greater than would be expected based on the genome average mutation frequency. In order to determine whether this increased incidence is due to an elevated mutation rate at this position (true mutation hot spot) or a selective advantage conferred on mutated spermatogonial stem cells, we studied the spatial distribution of the mutation in 14 human testes. In donors aged 36–68, mutations were clustered with small regions of each testis having mutation frequencies several orders of magnitude greater than the rest of the testis. In donors aged 19–23 mutations were almost non-existent, demonstrating that clusters in middle-aged donors grew during adulthood. Computational analysis showed that germline selection is the only plausible explanation. Testes of men aged 75–80 were heterogeneous with some like middle-aged and others like younger testes. Incorporating data on age-dependent death of spermatogonial stem cells explains the results from all age groups. Germline selection also explains MEN2B's male mutation bias and paternal age effect. Our discovery focuses attention on MEN2B as a model for understanding the genetic and biochemical basis of germline selection. Since RET function in mouse spermatogonial stem cells has been extensively studied, we are able to suggest that the MEN2B mutation provides a selective advantage by altering the PI3K/AKT and SFK signaling pathways. Mutations that are preferred in the germline but reduce the fitness of offspring increase the population's mutational load. Our approach is useful for studying other disease mutations with similar characteristics and could uncover additional germline selection pathways or identify true mutation hot spots

    Genetic Analysis of Genome-Scale Recombination Rate Evolution in House Mice

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    The rate of meiotic recombination varies markedly between species and among individuals. Classical genetic experiments demonstrated a heritable component to population variation in recombination rate, and specific sequence variants that contribute to recombination rate differences between individuals have recently been identified. Despite these advances, the genetic basis of species divergence in recombination rate remains unexplored. Using a cytological assay that allows direct in situ imaging of recombination events in spermatocytes, we report a large (∼30%) difference in global recombination rate between males of two closely related house mouse subspecies (Mus musculus musculus and M. m. castaneus). To characterize the genetic basis of this recombination rate divergence, we generated an F2 panel of inter-subspecific hybrid males (n = 276) from an intercross between wild-derived inbred strains CAST/EiJ (M. m. castaneus) and PWD/PhJ (M. m. musculus). We uncover considerable heritable variation for recombination rate among males from this mapping population. Much of the F2 variance for recombination rate and a substantial portion of the difference in recombination rate between the parental strains is explained by eight moderate- to large-effect quantitative trait loci, including two transgressive loci on the X chromosome. In contrast to the rapid evolution observed in males, female CAST/EiJ and PWD/PhJ animals show minimal divergence in recombination rate (∼5%). The existence of loci on the X chromosome suggests a genetic mechanism to explain this male-biased evolution. Our results provide an initial map of the genetic changes underlying subspecies differences in genome-scale recombination rate and underscore the power of the house mouse system for understanding the evolution of this trait

    Contributions of protein-coding and regulatory change to adaptive molecular evolution in murid rodents

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    The contribution of regulatory versus protein change to adaptive evolution has long been controversial. In principle, the rate and strength of adaptation within functional genetic elements can be quantified on the basis of an excess of nucleotide substitutions between species compared to the neutral expectation or from effects of recent substitutions on nucleotide diversity at linked sites. Here, we infer the nature of selective forces acting in proteins, their UTRs and conserved noncoding elements (CNEs) using genome-wide patterns of diversity in wild house mice and divergence to related species. By applying an extension of the McDonald-Kreitman test, we infer that adaptive substitutions are widespread in protein-coding genes, UTRs and CNEs, and we estimate that there are at least four times as many adaptive substitutions in CNEs and UTRs as in proteins. We observe pronounced reductions in mean diversity around nonsynonymous sites (whether or not they have experienced a recent substitution). This can be explained by selection on multiple, linked CNEs and exons. We also observe substantial dips in mean diversity (after controlling for divergence) around protein-coding exons and CNEs, which can also be explained by the combined effects of many linked exons and CNEs. A model of background selection (BGS) can adequately explain the reduction in mean diversity observed around CNEs. However, BGS fails to explain the wide reductions in mean diversity surrounding exons (encompassing ~100 Kb, on average), implying that there is a substantial role for adaptation within exons or closely linked sites. The wide dips in diversity around exons, which are hard to explain by BGS, suggest that the fitness effects of adaptive amino acid substitutions could be substantially larger than substitutions in CNEs. We conclude that although there appear to be many more adaptive noncoding changes, substitutions in proteins may dominate phenotypic evolution

    Mouse genomic variation and its effect on phenotypes and gene regulation

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    We report genome sequences of 17 inbred strains of laboratory mice and identify almost ten times more variants than previously known. We use these genomes to explore the phylogenetic history of the laboratory mouse and to examine the functional consequences of allele-specific variation on transcript abundance, revealing that at least 12% of transcripts show a significant tissue-specific expression bias. By identifying candidate functional variants at 718 quantitative trait loci we show that the molecular nature of functional variants and their position relative to genes vary according to the effect size of the locus. These sequences provide a starting point for a new era in the functional analysis of a key model organism
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