http://precedings.nature.com/tags/genetic%20variation Recently posted documents tagged with 'genetic variation' Nature Publishing Group en Nature Precedings http://precedings.nature.com/images/header_logo.gif http://precedings.nature.com http://precedings.nature.com/documents/1988/version/1 The natural genetics of an organism is determined by the distribution of sequences of its genome. Here we present one- to four-fold, with some deeper, coverage of the genome sequences of over seventy isolates of the domesticated baker’s yeast, Saccharomyces cerevisiae, and its closest relative, the wild S. paradoxus, which has never been associated with human activity. These were collected from numerous geographic locations and sources (including wild, clinical, baking, wine, laboratory and food spoilage). These sequences provide an unprecedented view of the population structure, natural (and artificial) selection and genome evolution in these species. Variation in gene content, SNPs, indels, copy numbers and transposable elements provide insights into the evolution of different lineages. Phenotypic variation broadly correlates with global genome-wide phylogenetic relationships however there is no correlation with source. S. paradoxus populations are well delineated along geographic boundaries while the variation among worldwide S. cerevisiae isolates show less differentiation and is comparable to a single S. paradoxus population. Rather than one or two domestication events leading to the extant baker’s yeasts, the population structure of S. cerevisiae shows a few well defined geographically isolated lineages and many different mosaics of these lineages, supporting the notion that human influence provided the opportunity for outbreeding and production of new combinations of pre-existing variation. http://precedings.nature.com/documents/1988/version/1 Fri, 20 Jun 2008 15:24:32 UTC Population genomics of domestic and wild yeasts hdl:10101/npre.2008.1988.1 2008-06-20 Edward Louis Nature Precedings 2008-06-20T15:24:32Z Manuscript Ecology Genetics & Genomics Bioinformatics Evolutionary Biology http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/1799/version/1 Genetic variation is known to influence the amount of mRNA produced by a gene. Given that the molecular machines control mRNA levels of multiple genes, we expect genetic variation in the components of these machines would influence multiple genes in a similar fashion. In this study we show that this assumption is correct by using correlation of mRNA levels measured independently in the brain, kidney or liver of multiple, genetically typed, mice strains to detect shared genetic influences. These correlating groups of genes (CGG) have collective properties that account for 40-90% of the variability of their constituent genes and in some cases, but not all, contain genes encoding functionally related proteins. Critically, we show that the genetic influences are essentially tissue specific and consequently the same genetic variations in the one animal may up-regulate a CGG in one tissue but down-regulate the same CGG in a second tissue. We further show similarly paradoxical behaviour of CGGs within the same tissues of different individuals. The implication of this study is that this class of genetic variation can result in complex inter- and intra-individual and tissue differences and that this will create substantial challenges to the investigation of phenotypic outcomes, particularly in humans where multiple tissues are not readily available. http://precedings.nature.com/documents/1799/version/1 Tue, 15 Apr 2008 12:55:56 UTC Intra- and inter-individual genetic differences in gene expression hdl:10101/npre.2008.1799.1 2008-04-15 Mark J. Cowley Nature Precedings 2008-04-15T12:55:56Z Manuscript Genetics & Genomics Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2007.1243.1 Understanding of the mechanism of DNA mutation process is critical for studying the functional consequences of genetic variation in clinical medicine (eg. drug response) as well as other complex traits (eg. gene expression and cause of common diseases). During the last several decades, many probabilistic models of DNA nucleotide substitution have been proposed for studying this process. A common feature of these mutation models is that they assume the nucleotides evolve independently at each site. In other words, they are sequence context-independent models. However, based on various biochemical studies, it is now recognized that the DNA mutation process resulting in substitutions in both coding and non-coding regions may depend on sequence context. We proposed here a more realistic sequence context-dependent mutation model, which could contribute to the better understanding of the DNA mutation spectrum in genomes.We also showed its application to protein evolution by separating the mutation bias and selection bias in amino acid substitutions. http://dx.doi.org/10.1038/npre.2007.1243.1 Tue, 23 Oct 2007 17:07:55 UTC Estimation of DNA Sequence Context-dependent Mutation Rates Using Primate Genomic Sequences: Application to Estimation of Selection Bias in Protein (Human TP53) Evolution doi:10.1038/npre.2007.1243.1 2009-03-04 Wei Zhang Nature Precedings 2007-10-23T17:07:55Z Presentation Ecology Bioinformatics Evolutionary Biology http://creativecommons.org/licenses/by/2.5/