2,752 research outputs found

    Murine Warriors or Worriers: The Saga of Comt1, B2 SINE Elements, and the Future of Translational Genetics

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    Catechol-O-methyltransferase (COMT) is an extremely well characterized enzyme that degrades catecholamines. A common coding polymorphism (rs4680; Val158Met) in the human COMT gene has been associated with a diverse array of phenotypes including personality, cognition, pain sensitivity, and risk for psychiatric disorders (Tunbridg

    Dark Matter: Are Mice the Solution to Missing Heritability?

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    Genome-wide association studies (GWAS) in humans have identified hundreds of single nucleotide polymorphisms associated with complex traits, yet for most traits studied, the sum total of all these identified variants fail to explain a significant portion of the heritable variation. Reasons for this “missing heritability” are thought to include the existence of rare causative variants not captured by current genotyping arrays, structural variants that go undetected by existing technology, insufficient power to identify multi-gene interactions, small sample sizes, and the influence of environmental and epigenetic effects. As genotyping technologies have evolved it has become inexpensive and relatively straightforward to perform GWAS in mice. Mice offer a powerful tool for elucidating the genetic architecture of behavioral and physiological traits, and are complementary to human studies. Unlike F2 crosses of inbred strains, advanced intercross lines, heterogeneous stocks, outbred, and wild-caught mice have more rapid breakdown of linkage disequilibrium which allow for increasingly high resolution mapping. Because some of these populations are created using a small number of founder chromosomes they are not expected to harbor rare alleles. We discuss the differences between these mouse populations and examine their potential to overcome some of the pitfalls that have plagued human GWAS studies

    Role of Glyoxalase 1 (Glo1) and methylglyoxal (MG) in behavior: recent advances and mechanistic insights

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    Glyoxalase 1 (GLO1) is a ubiquitous cellular enzyme that participates in the detoxification of methylglyoxal (MG), a cytotoxic byproduct of glycolysis that induces protein modification (advanced glycation end-products, AGEs), oxidative stress, and apoptosis. The concentration of MG is elevated under high-glucose conditions, such as diabetes. As such, GLO1 and MG have been implicated in the pathogenesis of diabetic complications. Recently, findings have linked GLO1 to numerous behavioral phenotypes, including psychiatric diseases (anxiety, depression, schizophrenia, and autism) and pain. This review highlights GLO1's association with behavioral phenotypes, describes recent discoveries that have elucidated the underlying mechanisms, and identifies opportunities for future research

    QTLRel: an R Package for Genome-wide Association Studies in which Relatedness is a Concern

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    BACKGROUND Existing software for quantitative trait mapping is either not able to model polygenic variation or does not allow incorporation of more than one genetic variance component. Improperly modeling the genetic relatedness among subjects can result in excessive false positives. We have developed an R package, QTLRel, to enable more flexible modeling of genetic relatedness as well as covariates and non-genetic variance components. RESULTS We have successfully used the package to analyze many datasets, including F₃₄ body weight data that contains 688 individuals genotyped at 3105 SNP markers and identified 11 QTL. It took 295 seconds to estimate variance components and 70 seconds to perform the genome scan on an Linux machine equipped with a 2.40GHz Intel(R) Core(TM)2 Quad CPU. CONCLUSIONS QTLRel provides a toolkit for genome-wide association studies that is capable of calculating genetic incidence matrices from pedigrees, estimating variance components, performing genome scans, incorporating interactive covariates and genetic and non-genetic variance components, as well as other functionalities such as multiple-QTL mapping and genome-wide epistasis.This project was supported by NIH grants R01DA021336, R01MH079103 and R21DA024845
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