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  • 1
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    A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk (2010)
    Nature Publishing Group (NPG)
    Details
    Publication Date: 2010-09-10
    Description: Combined analyses of gene networks and DNA sequence variation can provide new insights into the aetiology of common diseases that may not be apparent from genome-wide association studies alone. Recent advances in rat genomics are facilitating systems-genetics approaches. Here we report the use of integrated genome-wide approaches across seven rat tissues to identify gene networks and the loci underlying their regulation. We defined an interferon regulatory factor 7 (IRF7)-driven inflammatory network (IDIN) enriched for viral response genes, which represents a molecular biomarker for macrophages and which was regulated in multiple tissues by a locus on rat chromosome 15q25. We show that Epstein-Barr virus induced gene 2 (Ebi2, also known as Gpr183), which lies at this locus and controls B lymphocyte migration, is expressed in macrophages and regulates the IDIN. The human orthologous locus on chromosome 13q32 controlled the human equivalent of the IDIN, which was conserved in monocytes. IDIN genes were more likely to associate with susceptibility to type 1 diabetes (T1D)-a macrophage-associated autoimmune disease-than randomly selected immune response genes (P = 8.85 x 10(-6)). The human locus controlling the IDIN was associated with the risk of T1D at single nucleotide polymorphism rs9585056 (P = 7.0 x 10(-10); odds ratio, 1.15), which was one of five single nucleotide polymorphisms in this region associated with EBI2 (GPR183) expression. These data implicate IRF7 network genes and their regulatory locus in the pathogenesis of T1D.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3657719/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3657719/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Heinig, Matthias -- Petretto, Enrico -- Wallace, Chris -- Bottolo, Leonardo -- Rotival, Maxime -- Lu, Han -- Li, Yoyo -- Sarwar, Rizwan -- Langley, Sarah R -- Bauerfeind, Anja -- Hummel, Oliver -- Lee, Young-Ae -- Paskas, Svetlana -- Rintisch, Carola -- Saar, Kathrin -- Cooper, Jason -- Buchan, Rachel -- Gray, Elizabeth E -- Cyster, Jason G -- Cardiogenics Consortium -- Erdmann, Jeanette -- Hengstenberg, Christian -- Maouche, Seraya -- Ouwehand, Willem H -- Rice, Catherine M -- Samani, Nilesh J -- Schunkert, Heribert -- Goodall, Alison H -- Schulz, Herbert -- Roider, Helge G -- Vingron, Martin -- Blankenberg, Stefan -- Munzel, Thomas -- Zeller, Tanja -- Szymczak, Silke -- Ziegler, Andreas -- Tiret, Laurence -- Smyth, Deborah J -- Pravenec, Michal -- Aitman, Timothy J -- Cambien, Francois -- Clayton, David -- Todd, John A -- Hubner, Norbert -- Cook, Stuart A -- 061858/Wellcome Trust/United Kingdom -- 076113/Wellcome Trust/United Kingdom -- 089989/Wellcome Trust/United Kingdom -- MC_U120061454/Medical Research Council/United Kingdom -- MC_U120085815/Medical Research Council/United Kingdom -- MC_U120097112/Medical Research Council/United Kingdom -- P301/10/0290/British Heart Foundation/United Kingdom -- Medical Research Council/United Kingdom -- Wellcome Trust/United Kingdom -- England -- Nature. 2010 Sep 23;467(7314):460-4. doi: 10.1038/nature09386. Epub 2010 Sep 8.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Max-Delbruck-Center for Molecular Medicine (MDC), Berlin, Germany.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/20827270" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Base Sequence ; Chromosomes, Human, Pair 13/genetics ; Chromosomes, Mammalian/genetics ; Diabetes Mellitus, Type 1/*genetics/immunology ; Gene Regulatory Networks/genetics ; Genetic Loci/*genetics ; Genetic Predisposition to Disease/*genetics ; Genome-Wide Association Study ; Humans ; Immunity, Innate/*genetics ; Inflammation/genetics/immunology ; Interferon Regulatory Factor-7/immunology ; Macrophages/immunology/metabolism ; Organ Specificity ; Polymorphism, Single Nucleotide/genetics ; Quantitative Trait Loci/genetics ; Rats ; Receptors, G-Protein-Coupled/genetics/metabolism ; Viruses/*immunology
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Published by Nature Publishing Group (NPG)
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  • 2
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    A fine-scale map of recombination rates and hotspots across the human genome (2005)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2005-10-15
    Description: Genetic maps, which document the way in which recombination rates vary over a genome, are an essential tool for many genetic analyses. We present a high-resolution genetic map of the human genome, based on statistical analyses of genetic variation data, and identify more than 25,000 recombination hotspots, together with motifs and sequence contexts that play a role in hotspot activity. Differences between the behavior of recombination rates over large (megabase) and small (kilobase) scales lead us to suggest a two-stage model for recombination in which hotspots are stochastic features, within a framework in which large-scale rates are constrained.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Myers, Simon -- Bottolo, Leonardo -- Freeman, Colin -- McVean, Gil -- Donnelly, Peter -- U54 HG2750/HG/NHGRI NIH HHS/ -- Wellcome Trust/United Kingdom -- New York, N.Y. -- Science. 2005 Oct 14;310(5746):321-4.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UK.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/16224025" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Base Sequence ; *Chromosome Mapping ; Chromosomes, Human ; Evolution, Molecular ; Female ; *Genome, Human ; Humans ; Male ; Models, Genetic ; Polymorphism, Single Nucleotide ; Recombination, Genetic/*genetics
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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  • 3
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    Endonuclease G is a novel determinant of cardiac hypertrophy and mitochondrial function (2011)
    Nature Publishing Group (NPG)
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    Publication Date: 2011-10-08
    Description: Left ventricular mass (LVM) is a highly heritable trait and an independent risk factor for all-cause mortality. So far, genome-wide association studies have not identified the genetic factors that underlie LVM variation, and the regulatory mechanisms for blood-pressure-independent cardiac hypertrophy remain poorly understood. Unbiased systems genetics approaches in the rat now provide a powerful complementary tool to genome-wide association studies, and we applied integrative genomics to dissect a highly replicated, blood-pressure-independent LVM locus on rat chromosome 3p. Here we identified endonuclease G (Endog), which previously was implicated in apoptosis but not hypertrophy, as the gene at the locus, and we found a loss-of-function mutation in Endog that is associated with increased LVM and impaired cardiac function. Inhibition of Endog in cultured cardiomyocytes resulted in an increase in cell size and hypertrophic biomarkers in the absence of pro-hypertrophic stimulation. Genome-wide network analysis unexpectedly implicated ENDOG in fundamental mitochondrial processes that are unrelated to apoptosis. We showed direct regulation of ENDOG by ERR-alpha and PGC1alpha (which are master regulators of mitochondrial and cardiac function), interaction of ENDOG with the mitochondrial genome and ENDOG-mediated regulation of mitochondrial mass. At baseline, the Endog-deleted mouse heart had depleted mitochondria, mitochondrial dysfunction and elevated levels of reactive oxygen species, which were associated with enlarged and steatotic cardiomyocytes. Our study has further established the link between mitochondrial dysfunction, reactive oxygen species and heart disease and has uncovered a role for Endog in maladaptive cardiac hypertrophy.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3189541/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3189541/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉McDermott-Roe, Chris -- Ye, Junmei -- Ahmed, Rizwan -- Sun, Xi-Ming -- Serafin, Anna -- Ware, James -- Bottolo, Leonardo -- Muckett, Phil -- Canas, Xavier -- Zhang, Jisheng -- Rowe, Glenn C -- Buchan, Rachel -- Lu, Han -- Braithwaite, Adam -- Mancini, Massimiliano -- Hauton, David -- Marti, Ramon -- Garcia-Arumi, Elena -- Hubner, Norbert -- Jacob, Howard -- Serikawa, Tadao -- Zidek, Vaclav -- Papousek, Frantisek -- Kolar, Frantisek -- Cardona, Maria -- Ruiz-Meana, Marisol -- Garcia-Dorado, David -- Comella, Joan X -- Felkin, Leanne E -- Barton, Paul J R -- Arany, Zoltan -- Pravenec, Michal -- Petretto, Enrico -- Sanchis, Daniel -- Cook, Stuart A -- 087183/Wellcome Trust/United Kingdom -- MC_U120085815/Medical Research Council/United Kingdom -- MC_U120097112/Medical Research Council/United Kingdom -- British Heart Foundation/United Kingdom -- Medical Research Council/United Kingdom -- Wellcome Trust/United Kingdom -- England -- Nature. 2011 Oct 5;478(7367):114-8. doi: 10.1038/nature10490.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Medical Research Council Clinical Sciences Centre, Faculty of Medicine, Imperial College London, Hammersmith Hospital, Du Cane Road, London W12 ONN, UK.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/21979051" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Apoptosis ; Body Weight/genetics ; Cardiomegaly/*enzymology/genetics/*pathology/physiopathology ; Cell Respiration ; Chromosomes, Mammalian/genetics ; Crosses, Genetic ; Endodeoxyribonucleases/deficiency/genetics/*metabolism ; Female ; Gene Expression Regulation ; Genes, Mitochondrial/genetics ; Hypertrophy, Left Ventricular/enzymology/genetics/pathology/physiopathology ; Lipid Metabolism ; Male ; Mitochondria/genetics/*metabolism/pathology ; Organ Size/genetics ; Quantitative Trait Loci/genetics ; RNA-Binding Proteins/metabolism ; Rats ; Rats, Inbred Strains ; Reactive Oxygen Species/metabolism ; Receptors, Estrogen/metabolism ; Transcription Factors/metabolism
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Published by Nature Publishing Group (NPG)
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  • 4
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    WGBSSuite: simulating whole-genome bisulphite sequencing data and benchmarking differential DNA methylation analysis tools (2015)
    Oxford University Press
    Details
    Publication Date: 2015-07-09
    Description: Motivation : As the number of studies looking at differences between DNA methylation increases, there is a growing demand to develop and benchmark statistical methods to analyse these data. To date no objective approach for the comparison of these methods has been developed and as such it remains difficult to assess which analysis tool is most appropriate for a given experiment. As a result, there is an unmet need for a DNA methylation data simulator that can accurately reproduce a wide range of experimental setups, and can be routinely used to compare the performance of different statistical models. Results : We have developed WGBSSuite, a flexible stochastic simulation tool that generates single-base resolution DNA methylation data genome-wide. Several simulator parameters can be derived directly from real datasets provided by the user in order to mimic real case scenarios. Thus, it is possible to choose the most appropriate statistical analysis tool for a given simulated design. To show the usefulness of our simulator, we also report a benchmark of commonly used methods for differential methylation analysis. Availability and implementation : WGBS code and documentation are available under GNU licence at http://www.wgbssuite.org.uk/ Contact : owen.rackham@imperial.ac.uk or l.bottolo@imperial.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 5
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    MT-HESS: an efficient Bayesian approach for simultaneous association detection in OMICS datasets, with application to eQTL mapping in multiple tissues (2016)
    Oxford University Press
    Details
    Publication Date: 2016-02-06
    Description: Motivation: Analysing the joint association between a large set of responses and predictors is a fundamental statistical task in integrative genomics, exemplified by numerous expression Quantitative Trait Loci (eQTL) studies. Of particular interest are the so-called ‘ hotspots ’ , important genetic variants that regulate the expression of many genes. Recently, attention has focussed on whether eQTLs are common to several tissues, cell-types or, more generally, conditions or whether they are specific to a particular condition. Results: We have implemented MT-HESS, a Bayesian hierarchical model that analyses the association between a large set of predictors, e.g. SNPs, and many responses, e.g. gene expression, in multiple tissues, cells or conditions. Our Bayesian sparse regression algorithm goes beyond ‘ one-at-a-time ’ association tests between SNPs and responses and uses a fully multivariate model search across all linear combinations of SNPs, coupled with a model of the correlation between condition/tissue-specific responses. In addition, we use a hierarchical structure to leverage shared information across different genes, thus improving the detection of hotspots. We show the increase of power resulting from our new approach in an extensive simulation study. Our analysis of two case studies highlights new hotspots that would remain undetected by standard approaches and shows how greater prediction power can be achieved when several tissues are jointly considered. Availability and implementation: C ++ source code and documentation including compilation instructions are available under GNU licence at http://www.mrc-bsu.cam.ac.uk/software/ . Contact: sylvia.richardson@mrc-bsu.cam.ac.uk or lb664@cam.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 6
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    Novel association approach for variable number tandem repeats (VNTRs) identifies DOCK5 as a susceptibility gene for severe obesity (2012)
    Oxford University Press
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    Publication Date: 2012-07-28
    Description: Variable number tandem repeats (VNTRs) constitute a relatively under-examined class of genomic variants in the context of complex disease because of their sequence complexity and the challenges in assaying them. Recent large-scale genome-wide copy number variant mapping and association efforts have highlighted the need for improved methodology for association studies using these complex polymorphisms. Here we describe the in-depth investigation of a complex region on chromosome 8p21.2 encompassing the dedicator of cytokinesis 5 ( DOCK5 ) gene. The region includes two VNTRs of complex sequence composition which flank a common 3975 bp deletion, all three of which were genotyped by polymerase chain reaction and fragment analysis in a total of 2744 subjects. We have developed a novel VNTR association method named VNTRtest , suitable for association analysis of multi-allelic loci with binary and quantitative outcomes, and have used this approach to show significant association of the DOCK5 VNTRs with childhood and adult severe obesity ( P empirical = 8.9 x 10 –8 and P = 3.1 x 10 –3 , respectively) which we estimate explains ~0.8% of the phenotypic variance. We also identified an independent association between the 3975 base pair (bp) deletion and obesity, explaining a further 0.46% of the variance ( P combined = 1.6 x 10 –3 ). Evidence for association between DOCK5 transcript levels and the 3975 bp deletion ( P = 0.027) and both VNTRs ( P empirical = 0.015) was also identified in adipose tissue from a Swedish family sample, providing support for a functional effect of the DOCK5 deletion and VNTRs. These findings highlight the potential role of DOCK5 in human obesity and illustrate a novel approach for analysis of the contribution of VNTRs to disease susceptibility through association studies.
    Print ISSN: 0964-6906
    Electronic ISSN: 1460-2083
    Topics: Biology , Medicine
    Published by Oxford University Press
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  • 7
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    Discussion of ‘Gene hunting with hidden Markov model knockoffs’ (2019)
    Oxford University Press
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    Publication Date: 2019-02-13
    Print ISSN: 0006-3444
    Electronic ISSN: 1464-3510
    Topics: Biology , Mathematics , Medicine
    Published by Oxford University Press
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