Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Keywords: RISK ; ALLELES ; GENETIC SUSCEPTIBILITY ; LOCI ; GENOME-WIDE ASSOCIATION ; CONFER SUSCEPTIBILITY ; COMMON VARIANTS ; EPISTASIS ; IDENTIFIES 2 ; ERAP1
    Abstract: Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70 917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46 450 breast cancer cases and 42 461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P 〈 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P 〈 10(-4)) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P 〈 10(-8). Results from the second analytic approach were consistent with those from the first (P 〉 10(-10)). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome.
    Type of Publication: Journal article published
    PubMed ID: 24242184
    Signatur Availability
    BibTip Others were also interested in ...
  • 2
    Keywords: RISK ; OVARIAN-CANCER ; BRCA2 MUTATIONS ; SINGLE-NUCLEOTIDE POLYMORPHISMS ; ALLELES ; LOCI ; GENOME-WIDE ASSOCIATION ; CONFER SUSCEPTIBILITY ; COMMON VARIANTS ; IDENTIFIES 2
    Abstract: Background: Breast cancer is one of the most common malignancies in women. Genome-wide association studies have identified FGFR2 as a breast cancer susceptibility gene. Common variation in other fibroblast growth factor (FGF) receptors might also modify risk. We tested this hypothesis by studying genotyped single-nucleotide polymorphisms (SNPs) and imputed SNPs in FGFR1, FGFR3, FGFR4 and FGFRL1 in the Breast Cancer Association Consortium. Methods: Data were combined from 49 studies, including 53 835 cases and 50 156 controls, of which 89 050 (46 450 cases and 42 600 controls) were of European ancestry, 12 893 (6269 cases and 6624 controls) of Asian and 2048 (1116 cases and 932 controls) of African ancestry. Associations with risk of breast cancer, overall and by disease sub-type, were assessed using unconditional logistic regression. Results: Little evidence of association with breast cancer risk was observed for SNPs in the FGF receptor genes. The strongest evidence in European women was for rs743682 in FGFR3; the estimated per-allele odds ratio was 1.05 (95% confidence interval 1.02-1.09, P=0.0020), which is substantially lower than that observed for SNPs in FGFR2. Conclusion: Our results suggest that common variants in the other FGF receptors are not associated with risk of breast cancer to the degree observed for FGFR2.
    Type of Publication: Journal article published
    PubMed ID: 24548884
    Signatur Availability
    BibTip Others were also interested in ...
  • 3
    Keywords: RISK ; ALLELES ; SUBTYPES ; GENOME-WIDE ASSOCIATION ; CONFER SUSCEPTIBILITY ; COMMON VARIANTS
    Abstract: BACKGROUND: The single-nucleotide polymorphism (SNP) 5p12-rs10941679 has been found to be associated with risk of breast cancer, particularly estrogen receptor (ER)-positive disease. We aimed to further explore this association overall, and by tumor histopathology, in the Breast Cancer Association Consortium. METHODS: Data were combined from 37 studies, including 40,972 invasive cases, 1,398 cases of ductal carcinoma in situ (DCIS), and 46,334 controls, all of white European ancestry, as well as 3,007 invasive cases and 2,337 controls of Asian ancestry. Associations overall and by tumor invasiveness and histopathology were assessed using logistic regression. RESULTS: For white Europeans, the per-allele OR associated with 5p12-rs10941679 was 1.11 (95% CI = 1.08-1.14, P = 7 x 10(-18)) for invasive breast cancer and 1.10 (95% CI = 1.01-1.21, P = 0.03) for DCIS. For Asian women, the estimated OR for invasive disease was similar (OR = 1.07, 95%CI = 0.99-1.15, P = 0.09). Further analyses suggested that the association in white Europeans was largely limited to progesterone receptor (PR)-positive disease (per-allele OR = 1.16, 95% CI = 1.12-1.20, P = 1 x 10(-18) vs. OR = 1.03, 95% CI = 0.99-1.07, P = 0.2 for PR-negative disease; P(heterogeneity) = 2 x 10(-7)); heterogeneity by ER status was not observed (P = 0.2) once PR status was accounted for. The association was also stronger for lower grade tumors [per-allele OR (95% CI) = 1.20 (1.14-1.25), 1.13 (1.09-1.16), and 1.04 (0.99-1.08) for grade 1, 2, and 3/4, respectively; P(trend) = 5 x 10(-7)]. CONCLUSION: 5p12 is a breast cancer susceptibility locus for PR-positive, lower grade breast cancer. IMPACT: Multicenter fine-mapping studies of this region are needed as a first step to identifying the causal variant or variants.
    Type of Publication: Journal article published
    PubMed ID: 21795498
    Signatur Availability
    BibTip Others were also interested in ...
  • 4
    Keywords: RISK ; VARIANTS ; METAANALYSIS ; ALLELES ; LOCI ; GENOME-WIDE ASSOCIATION ; CONFER SUSCEPTIBILITY ; IDENTIFIES 2 ; 5P12
    Abstract: Candidate variant association studies have been largely unsuccessful in identifying common breast cancer susceptibility variants, although most studies have been underpowered to detect associations of a realistic magnitude. We assessed 41 common non-synonymous single nucleotide polymorphisms (nsSNPs) for which evidence of association with breast cancer risk had been previously reported. Case-control data were combined from 38 studies of white European women (46,450 cases and 42,600 controls) and analysed using unconditional logistic regression. Strong evidence of association was observed for three nsSNPs: ATXN7-K264R at 3p21 (rs1053338, per-allele OR=1.07, 95%CI=1.04-1.10, P=2.9x10-6), AKAP9-M463I at 7q21 (rs6964587, OR=1.05, 95%CI=1.03-1.07, P=1.7x10-6) and NEK10-L513S at 3p24 (rs10510592, OR=1.10, 95%CI=1.07-1.12, P=5.1x10-17). The first two associations reached genome-wide statistical significance in a combined analysis of available data, including independent data from nine GWAS: for ATXN7-K264R, OR=1.07 (95%CI=1.05-1.10, P=1.0x10-8); for AKAP9-M463I, OR=1.05 (95%CI=1.04-1.07, P=2.0x10-10). Further analysis of other common variants in these two regions suggested that intronic SNPs nearby are more strongly associated with disease risk. We have thus identified a novel susceptibility locus at 3p21, and confirmed previous suggestive evidence that rs6964587 at 7q21 is associated with risk. The third locus, rs10510592, is located in an established breast cancer susceptibility region; the association was substantially attenuated after adjustment for the known genome-wide association study (GWAS) hit. Thus, each of the associated nsSNPs is likely to be a marker for another, non-coding, variant causally related to breast cancer risk. Further fine-mapping and functional studies are required to identify the underlying risk-modifying variants and the genes through which they act.
    Type of Publication: Journal article published
    PubMed ID: 24943594
    Signatur Availability
    BibTip Others were also interested in ...
  • 5
    Publication Date: 2011-01-15
    Description: Long-term population viability of Fraser River sockeye salmon (Oncorhynchus nerka) is threatened by unusually high levels of mortality as they swim to their spawning areas before they spawn. Functional genomic studies on biopsied gill tissue from tagged wild adults that were tracked through ocean and river environments revealed physiological profiles predictive of successful migration and spawning. We identified a common genomic profile that was correlated with survival in each study. In ocean-tagged fish, a mortality-related genomic signature was associated with a 13.5-fold greater chance of dying en route. In river-tagged fish, the same genomic signature was associated with a 50% increase in mortality before reaching the spawning grounds in one of three stocks tested. At the spawning grounds, the same signature was associated with 3.7-fold greater odds of dying without spawning. Functional analysis raises the possibility that the mortality-related signature reflects a viral infection.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Miller, Kristina M -- Li, Shaorong -- Kaukinen, Karia H -- Ginther, Norma -- Hammill, Edd -- Curtis, Janelle M R -- Patterson, David A -- Sierocinski, Thomas -- Donnison, Louise -- Pavlidis, Paul -- Hinch, Scott G -- Hruska, Kimberly A -- Cooke, Steven J -- English, Karl K -- Farrell, Anthony P -- New York, N.Y. -- Science. 2011 Jan 14;331(6014):214-7. doi: 10.1126/science.1196901.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Molecular Genetics Section, Pacific Biological Station, 3190 Hammond Bay Road, Fisheries and Oceans Canada, Nanaimo, BC V9T 6N7, Canada. kristi.miller@dfo-mpo.gc.ca〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/21233388" target="_blank"〉PubMed〈/a〉
    Keywords: *Animal Migration ; Animals ; Canada ; Female ; Fish Diseases/genetics/immunology/mortality ; *Gene Expression ; *Gene Expression Profiling ; Genome ; Gills ; Male ; Mortality ; Oligonucleotide Array Sequence Analysis ; Pacific Ocean ; Population Dynamics ; Principal Component Analysis ; Remote Sensing Technology ; *Reproduction ; Rivers ; Salmon/*genetics/*physiology ; Stress, Physiological ; Survival Analysis ; Virus Diseases/genetics/immunology/mortality/veterinary
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Signatur Availability
    BibTip Others were also interested in ...
  • 6
    Publication Date: 2014-08-29
    Description: The transcriptome is the readout of the genome. Identifying common features in it across distant species can reveal fundamental principles. To this end, the ENCODE and modENCODE consortia have generated large amounts of matched RNA-sequencing data for human, worm and fly. Uniform processing and comprehensive annotation of these data allow comparison across metazoan phyla, extending beyond earlier within-phylum transcriptome comparisons and revealing ancient, conserved features. Specifically, we discover co-expression modules shared across animals, many of which are enriched in developmental genes. Moreover, we use expression patterns to align the stages in worm and fly development and find a novel pairing between worm embryo and fly pupae, in addition to the embryo-to-embryo and larvae-to-larvae pairings. Furthermore, we find that the extent of non-canonical, non-coding transcription is similar in each organism, per base pair. Finally, we find in all three organisms that the gene-expression levels, both coding and non-coding, can be quantitatively predicted from chromatin features at the promoter using a 'universal model' based on a single set of organism-independent parameters.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4155737/" 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/PMC4155737/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Gerstein, Mark B -- Rozowsky, Joel -- Yan, Koon-Kiu -- Wang, Daifeng -- Cheng, Chao -- Brown, James B -- Davis, Carrie A -- Hillier, LaDeana -- Sisu, Cristina -- Li, Jingyi Jessica -- Pei, Baikang -- Harmanci, Arif O -- Duff, Michael O -- Djebali, Sarah -- Alexander, Roger P -- Alver, Burak H -- Auerbach, Raymond -- Bell, Kimberly -- Bickel, Peter J -- Boeck, Max E -- Boley, Nathan P -- Booth, Benjamin W -- Cherbas, Lucy -- Cherbas, Peter -- Di, Chao -- Dobin, Alex -- Drenkow, Jorg -- Ewing, Brent -- Fang, Gang -- Fastuca, Megan -- Feingold, Elise A -- Frankish, Adam -- Gao, Guanjun -- Good, Peter J -- Guigo, Roderic -- Hammonds, Ann -- Harrow, Jen -- Hoskins, Roger A -- Howald, Cedric -- Hu, Long -- Huang, Haiyan -- Hubbard, Tim J P -- Huynh, Chau -- Jha, Sonali -- Kasper, Dionna -- Kato, Masaomi -- Kaufman, Thomas C -- Kitchen, Robert R -- Ladewig, Erik -- Lagarde, Julien -- Lai, Eric -- Leng, Jing -- Lu, Zhi -- MacCoss, Michael -- May, Gemma -- McWhirter, Rebecca -- Merrihew, Gennifer -- Miller, David M -- Mortazavi, Ali -- Murad, Rabi -- Oliver, Brian -- Olson, Sara -- Park, Peter J -- Pazin, Michael J -- Perrimon, Norbert -- Pervouchine, Dmitri -- Reinke, Valerie -- Reymond, Alexandre -- Robinson, Garrett -- Samsonova, Anastasia -- Saunders, Gary I -- Schlesinger, Felix -- Sethi, Anurag -- Slack, Frank J -- Spencer, William C -- Stoiber, Marcus H -- Strasbourger, Pnina -- Tanzer, Andrea -- Thompson, Owen A -- Wan, Kenneth H -- Wang, Guilin -- Wang, Huaien -- Watkins, Kathie L -- Wen, Jiayu -- Wen, Kejia -- Xue, Chenghai -- Yang, Li -- Yip, Kevin -- Zaleski, Chris -- Zhang, Yan -- Zheng, Henry -- Brenner, Steven E -- Graveley, Brenton R -- Celniker, Susan E -- Gingeras, Thomas R -- Waterston, Robert -- 1U01HG007031-01/HG/NHGRI NIH HHS/ -- 5U01HG004695-04/HG/NHGRI NIH HHS/ -- 5U54HG004555/HG/NHGRI NIH HHS/ -- HG007000/HG/NHGRI NIH HHS/ -- HG007355/HG/NHGRI NIH HHS/ -- K99 HG006698/HG/NHGRI NIH HHS/ -- P30 CA045508/CA/NCI NIH HHS/ -- R01 GM076655/GM/NIGMS NIH HHS/ -- RC2-HG005639/HG/NHGRI NIH HHS/ -- T15 LM007056/LM/NLM NIH HHS/ -- T32 HD060555/HD/NICHD NIH HHS/ -- U01 HG 004263/HG/NHGRI NIH HHS/ -- U01 HG004261/HG/NHGRI NIH HHS/ -- U01 HG004271/HG/NHGRI NIH HHS/ -- U01 HG007031/HG/NHGRI NIH HHS/ -- U01-HG004261/HG/NHGRI NIH HHS/ -- U01HG004258/HG/NHGRI NIH HHS/ -- U41 HG007000/HG/NHGRI NIH HHS/ -- U41 HG007234/HG/NHGRI NIH HHS/ -- U41 HG007355/HG/NHGRI NIH HHS/ -- U54 HG004555/HG/NHGRI NIH HHS/ -- U54 HG006944/HG/NHGRI NIH HHS/ -- U54 HG006994/HG/NHGRI NIH HHS/ -- U54 HG007004/HG/NHGRI NIH HHS/ -- U54 HG007005/HG/NHGRI NIH HHS/ -- U54HG007005/HG/NHGRI NIH HHS/ -- WT098051/Wellcome Trust/United Kingdom -- ZIA DK015600-18/Intramural NIH HHS/ -- Howard Hughes Medical Institute/ -- England -- Nature. 2014 Aug 28;512(7515):445-8. doi: 10.1038/nature13424.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉1] Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA [2] Department of Molecular Biophysics and Biochemistry, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA [3] Department of Computer Science, Yale University, 51 Prospect Street, New Haven, Connecticut 06511, USA [4] [5]. ; 1] Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA [2] Department of Molecular Biophysics and Biochemistry, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA [3]. ; 1] Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire 03755, USA [2] Institute for Quantitative Biomedical Sciences, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire 03766, USA [3]. ; 1] Department of Genome Dynamics, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA [2] Department of Statistics, University of California, Berkeley, 367 Evans Hall, Berkeley, California 94720-3860, USA [3]. ; 1] Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA [2]. ; 1] Department of Genome Sciences and University of Washington School of Medicine, William H. Foege Building S350D, 1705 Northeast Pacific Street, Box 355065 Seattle, Washington 98195-5065, USA [2]. ; 1] Department of Statistics, University of California, Berkeley, 367 Evans Hall, Berkeley, California 94720-3860, USA [2] Department of Statistics, University of California, Los Angeles, California 90095-1554, USA [3] Department of Human Genetics, University of California, Los Angeles, California 90095-7088, USA [4]. ; 1] Department of Genetics and Developmental Biology, Institute for Systems Genomics, University of Connecticut Health Center, 400 Farmington Avenue, Farmington, Connecticut 06030, USA [2]. ; 1] Centre for Genomic Regulation, Doctor Aiguader 88, 08003 Barcelona, Catalonia, Spain [2] Departament de Ciencies Experimentals i de la Salut, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain [3]. ; 1] Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA [2] Department of Molecular Biophysics and Biochemistry, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA. ; Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, Massachusetts 02115, USA. ; Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA. ; Department of Statistics, University of California, Berkeley, 367 Evans Hall, Berkeley, California 94720-3860, USA. ; Department of Genome Sciences and University of Washington School of Medicine, William H. Foege Building S350D, 1705 Northeast Pacific Street, Box 355065 Seattle, Washington 98195-5065, USA. ; 1] Department of Genome Dynamics, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA [2] Department of Biostatistics, University of California, Berkeley, 367 Evans Hall, Berkeley, California 94720-3860, USA. ; Department of Genome Dynamics, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA. ; 1] Department of Biology, Indiana University, 1001 East 3rd Street, Bloomington, Indiana 47405-7005, USA [2] Center for Genomics and Bioinformatics, Indiana University, 1001 East 3rd Street, Bloomington, Indiana 47405-7005, USA. ; MOE Key Lab of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China. ; National Human Genome Research Institute, National Institutes of Health, 5635 Fishers Lane, Bethesda, Maryland 20892-9307, USA. ; Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK. ; 1] Centre for Genomic Regulation, Doctor Aiguader 88, 08003 Barcelona, Catalonia, Spain [2] Departament de Ciencies Experimentals i de la Salut, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain. ; 1] Center for Integrative Genomics, University of Lausanne, Genopode building, Lausanne 1015, Switzerland [2] Swiss Institute of Bioinformatics, Genopode building, Lausanne 1015, Switzerland. ; 1] Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK [2] Medical and Molecular Genetics, King's College London, London WC2R 2LS, UK. ; Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06520-8005, USA. ; Department of Molecular, Cellular and Developmental Biology, PO Box 208103, Yale University, New Haven, Connecticut 06520, USA. ; Department of Biology, Indiana University, 1001 East 3rd Street, Bloomington, Indiana 47405-7005, USA. ; Sloan-Kettering Institute, 1275 York Avenue, Box 252, New York, New York 10065, USA. ; 1] Department of Genetics and Developmental Biology, Institute for Systems Genomics, University of Connecticut Health Center, 400 Farmington Avenue, Farmington, Connecticut 06030, USA [2] Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213 USA. ; Department of Cell and Developmental Biology, Vanderbilt University, 465 21st Avenue South, Nashville, Tennessee 37232-8240, USA. ; 1] Developmental and Cell Biology, University of California, Irvine, California 92697, USA [2] Center for Complex Biological Systems, University of California, Irvine, California 92697, USA. ; Section of Developmental Genomics, Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892, USA. ; Department of Genetics and Developmental Biology, Institute for Systems Genomics, University of Connecticut Health Center, 400 Farmington Avenue, Farmington, Connecticut 06030, USA. ; 1] Department of Genetics and Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, Massachusetts 02115, USA [2] Howard Hughes Medical Institute, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, Massachusetts 02115, USA. ; Center for Integrative Genomics, University of Lausanne, Genopode building, Lausanne 1015, Switzerland. ; 1] Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK [2] European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK. ; 1] Bioinformatics and Genomics Programme, Center for Genomic Regulation, Universitat Pompeu Fabra (CRG-UPF), 08003 Barcelona, Catalonia, Spain [2] Institute for Theoretical Chemistry, Theoretical Biochemistry Group (TBI), University of Vienna, Wahringerstrasse 17/3/303, A-1090 Vienna, Austria. ; 1] Department of Genetics and Developmental Biology, Institute for Systems Genomics, University of Connecticut Health Center, 400 Farmington Avenue, Farmington, Connecticut 06030, USA [2] Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China. ; 1] Hong Kong Bioinformatics Centre, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong [2] 5 CUHK-BGI Innovation Institute of Trans-omics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong. ; 1] Department of Molecular and Cell Biology, University of California, Berkeley, California 94720, USA [2] Department of Plant and Microbial Biology, University of California, Berkeley, California 94720, USA [3]. ; 1] Department of Genome Dynamics, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA [2].〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25164755" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Caenorhabditis elegans/embryology/*genetics/growth & development ; Chromatin/genetics ; Cluster Analysis ; Drosophila melanogaster/*genetics/growth & development ; *Gene Expression Profiling ; Gene Expression Regulation, Developmental/genetics ; Histones/metabolism ; Humans ; Larva/genetics/growth & development ; Models, Genetic ; Molecular Sequence Annotation ; Promoter Regions, Genetic/genetics ; Pupa/genetics/growth & development ; RNA, Untranslated/genetics ; Sequence Analysis, RNA ; Transcriptome/*genetics
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Signatur Availability
    BibTip Others were also interested in ...
  • 7
    Publication Date: 2014-05-07
    Description: In the adult central nervous system, the vasculature of the neurogenic niche regulates neural stem cell behavior by providing circulating and secreted factors. Age-related decline of neurogenesis and cognitive function is associated with reduced blood flow and decreased numbers of neural stem cells. Therefore, restoring the functionality of the niche should counteract some of the negative effects of aging. We show that factors found in young blood induce vascular remodeling, culminating in increased neurogenesis and improved olfactory discrimination in aging mice. Further, we show that GDF11 alone can improve the cerebral vasculature and enhance neurogenesis. The identification of factors that slow the age-dependent deterioration of the neurogenic niche in mice may constitute the basis for new methods of treating age-related neurodegenerative and neurovascular diseases.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4123747/" 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/PMC4123747/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Katsimpardi, Lida -- Litterman, Nadia K -- Schein, Pamela A -- Miller, Christine M -- Loffredo, Francesco S -- Wojtkiewicz, Gregory R -- Chen, John W -- Lee, Richard T -- Wagers, Amy J -- Rubin, Lee L -- 1DP2 OD004345/OD/NIH HHS/ -- 1R01 AG033053/AG/NIA NIH HHS/ -- 1R01 AG040019/AG/NIA NIH HHS/ -- 5U01 HL100402/HL/NHLBI NIH HHS/ -- DP2 OD004345/OD/NIH HHS/ -- R01 AG032977/AG/NIA NIH HHS/ -- R01 AG033053/AG/NIA NIH HHS/ -- R01 AG040019/AG/NIA NIH HHS/ -- R01 NS070835/NS/NINDS NIH HHS/ -- R01 NS072167/NS/NINDS NIH HHS/ -- R01NS070835/NS/NINDS NIH HHS/ -- R01NS072167/NS/NINDS NIH HHS/ -- U01 HL100402/HL/NHLBI NIH HHS/ -- Howard Hughes Medical Institute/ -- New York, N.Y. -- Science. 2014 May 9;344(6184):630-4. doi: 10.1126/science.1251141. Epub 2014 May 5.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/24797482" target="_blank"〉PubMed〈/a〉
    Keywords: Aging/*drug effects ; Animals ; Bone Morphogenetic Proteins/*administration & dosage/blood/physiology ; Brain/blood supply/*drug effects ; Cerebrovascular Circulation/*drug effects ; Cognition/drug effects ; Endothelium, Vascular/cytology/drug effects ; Growth Differentiation Factors/*administration & dosage/blood/physiology ; Male ; Mice ; Mice, Inbred C57BL ; Neural Stem Cells/cytology/*drug effects ; Neurogenesis/*drug effects ; Olfactory Bulb/cytology/drug effects ; Parabiosis ; Recombinant Proteins/administration & dosage ; *Rejuvenation
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Signatur Availability
    BibTip Others were also interested in ...
  • 8
    Publication Date: 2015-02-03
    Description: The alternative non-homologous end-joining (NHEJ) machinery facilitates several genomic rearrangements, some of which can lead to cellular transformation. This error-prone repair pathway is triggered upon telomere de-protection to promote the formation of deleterious chromosome end-to-end fusions. Using next-generation sequencing technology, here we show that repair by alternative NHEJ yields non-TTAGGG nucleotide insertions at fusion breakpoints of dysfunctional telomeres. Investigating the enzymatic activity responsible for the random insertions enabled us to identify polymerase theta (Poltheta; encoded by Polq in mice) as a crucial alternative NHEJ factor in mammalian cells. Polq inhibition suppresses alternative NHEJ at dysfunctional telomeres, and hinders chromosomal translocations at non-telomeric loci. In addition, we found that loss of Polq in mice results in increased rates of homology-directed repair, evident by recombination of dysfunctional telomeres and accumulation of RAD51 at double-stranded breaks. Lastly, we show that depletion of Poltheta has a synergistic effect on cell survival in the absence of BRCA genes, suggesting that the inhibition of this mutagenic polymerase represents a valid therapeutic avenue for tumours carrying mutations in homology-directed repair genes.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4718306/" 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/PMC4718306/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Mateos-Gomez, Pedro A -- Gong, Fade -- Nair, Nidhi -- Miller, Kyle M -- Lazzerini-Denchi, Eros -- Sfeir, Agnel -- AG038677/AG/NIA NIH HHS/ -- P30 CA016087/CA/NCI NIH HHS/ -- R01 AG038677/AG/NIA NIH HHS/ -- England -- Nature. 2015 Feb 12;518(7538):254-7. doi: 10.1038/nature14157. Epub 2015 Feb 2.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Skirball Institute of Biomolecular Medicine, Department of Cell Biology, NYU School of Medicine, New York, New York 10016, USA. ; Department of Molecular Biosciences, Institute for Cellular and Molecular Biology, University of Texas at Austin. 2506 Speedway Stop A5000, Austin, Texas 78712, USA. ; Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, California 92037, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25642960" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Base Sequence ; Cell Death/genetics ; Cell Line ; Chromosome Aberrations ; Chromosomes, Mammalian/genetics/*metabolism ; *DNA Breaks, Double-Stranded ; *DNA End-Joining Repair ; DNA-Directed DNA Polymerase/deficiency/*metabolism ; Genes, BRCA1 ; Genes, BRCA2 ; HeLa Cells ; Humans ; Mice ; Poly(ADP-ribose) Polymerases/genetics/metabolism ; Rad51 Recombinase/metabolism ; *Recombination, Genetic/genetics ; Recombinational DNA Repair/genetics ; Telomere/*genetics/*metabolism ; Translocation, Genetic/genetics
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Signatur Availability
    BibTip Others were also interested in ...
  • 9
    Publication Date: 2016-03-19
    Description: Expansions of a hexanucleotide repeat (GGGGCC) in the noncoding region of the C9orf72 gene are the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia. Decreased expression of C9orf72 is seen in expansion carriers, suggesting that loss of function may play a role in disease. We found that two independent mouse lines lacking the C9orf72 ortholog (3110043O21Rik) in all tissues developed normally and aged without motor neuron disease. Instead, C9orf72 null mice developed progressive splenomegaly and lymphadenopathy with accumulation of engorged macrophage-like cells. C9orf72 expression was highest in myeloid cells, and the loss of C9orf72 led to lysosomal accumulation and altered immune responses in macrophages and microglia, with age-related neuroinflammation similar to C9orf72 ALS but not sporadic ALS human patient tissue. Thus, C9orf72 is required for the normal function of myeloid cells, and altered microglial function may contribute to neurodegeneration in C9orf72 expansion carriers.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉O'Rourke, J G -- Bogdanik, L -- Yanez, A -- Lall, D -- Wolf, A J -- Muhammad, A K M G -- Ho, R -- Carmona, S -- Vit, J P -- Zarrow, J -- Kim, K J -- Bell, S -- Harms, M B -- Miller, T M -- Dangler, C A -- Underhill, D M -- Goodridge, H S -- Lutz, C M -- Baloh, R H -- GM085796/GM/NIGMS NIH HHS/ -- NS069669/NS/NINDS NIH HHS/ -- NS078398/NS/NINDS NIH HHS/ -- NS087351/NS/NINDS NIH HHS/ -- UL1TR000124/TR/NCATS NIH HHS/ -- New York, N.Y. -- Science. 2016 Mar 18;351(6279):1324-9. doi: 10.1126/science.aaf1064.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA. ; The Jackson Laboratory, Bar Harbor, ME, USA. ; Division of Biomedical Sciences, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA. ; Department of Neurology, Washington University School of Medicine, 660 South Euclid Avenue, St. Louis, MO 63110, USA. ; Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA. Department of Neurology, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26989253" target="_blank"〉PubMed〈/a〉
    Keywords: Aging/immunology ; Amyotrophic Lateral Sclerosis/genetics/*immunology ; Animals ; Frontotemporal Dementia/genetics/*immunology ; Gene Knockdown Techniques ; Guanine Nucleotide Exchange Factors/genetics/*physiology ; Heterozygote ; Humans ; Lymphatic Diseases/genetics/immunology ; Macrophages/*immunology ; Mice ; Mice, Knockout ; Microglia/*immunology ; Myeloid Cells/*immunology ; Proteins/genetics/*physiology ; Rats ; Splenomegaly/genetics/immunology
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Signatur Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...