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  • 3
    Publication Date: 2013-12-11
    Description: The signal transducer and activator of transcription 3 (STAT3) is a transcription factor that, when dysregulated, becomes a powerful oncogene found in many human cancers, including diffuse large B-cell lymphoma. Diffuse large B-cell lymphoma is the most common form of non-Hodgkin’s lymphoma and has two major subtypes: germinal center B-cell–like and activated B–cell—like. Compared with the germinal center B-cell–like form, activated B-cell–like lymphomas respond much more poorly to current therapies and often exhibit overexpression or overactivation of STAT3. To investigate how STAT3 might contribute to this aggressive phenotype, we have integrated genome-wide studies of STAT3 DNA binding using chromatin immunoprecipitation-sequencing with whole-transcriptome profiling using RNA-sequencing. STAT3 binding sites are present near almost a third of all genes that differ in expression between the two subtypes, and examination of the affected genes identified previously undetected and clinically significant pathways downstream of STAT3 that drive oncogenesis. Novel treatments aimed at these pathways may increase the survivability of activated B-cell–like diffuse large B-cell lymphoma.
    Electronic ISSN: 2160-1836
    Topics: Biology
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  • 4
    Publication Date: 2014-04-30
    Description: With the completion of the human genome sequence, attention turned to identifying and annotating its functional DNA elements. As a complement to genetic and comparative genomics approaches, the Encyclopedia of DNA Elements Project was launched to contribute maps of RNA transcripts, transcriptional regulator binding sites, and chromatin states in many...
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
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  • 5
    Publication Date: 2014-10-11
    Description: Transcription of mitochondrial DNA (mtDNA)-encoded genes is thought to be regulated by a handful of dedicated transcription factors (TFs), suggesting that mtDNA genes are separately regulated from the nucleus. However, several TFs, with known nuclear activities, were found to bind mtDNA and regulate mitochondrial transcription. Additionally, mtDNA transcriptional regulatory elements, which were proved important in vitro, were harbored by a deletion that normally segregated among healthy individuals. Hence, mtDNA transcriptional regulation is more complex than once thought. Here, by analyzing ENCODE chromatin immunoprecipitation sequencing (ChIP-seq) data, we identified strong binding sites of three bona fide nuclear TFs (c-Jun, Jun-D, and CEBPb) within human mtDNA protein-coding genes. We validated the binding of two TFs by ChIP-quantitative polymerase chain reaction (c-Jun and Jun-D) and showed their mitochondrial localization by electron microscopy and subcellular fractionation. As a step toward investigating the functionality of these TF-binding sites (TFBS), we assessed signatures of selection. By analyzing 9,868 human mtDNA sequences encompassing all major global populations, we recorded genetic variants in tips and nodes of mtDNA phylogeny within the TFBS. We next calculated the effects of variants on binding motif prediction scores. Finally, the mtDNA variation pattern in predicted TFBS, occurring within ChIP-seq negative-binding sites, was compared with ChIP-seq positive-TFBS (CPR). Motifs within CPRs of c-Jun, Jun-D, and CEBPb harbored either only tip variants or their nodal variants retained high motif prediction scores. This reflects negative selection within mtDNA CPRs, thus supporting their functionality. Hence, human mtDNA-coding sequences may have dual roles, namely coding for genes yet possibly also possessing regulatory potential.
    Electronic ISSN: 1759-6653
    Topics: Biology
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  • 6
    Publication Date: 2014-02-20
    Description: ChIP-seq has become the primary method for identifying in vivo protein–DNA interactions on a genome-wide scale, with nearly 800 publications involving the technique appearing in PubMed as of December 2012. Individually and in aggregate, these data are an important and information-rich resource. However, uncertainties about data quality confound their use by the wider research community. Recently, the Encyclopedia of DNA Elements (ENCODE) project developed and applied metrics to objectively measure ChIP-seq data quality. The ENCODE quality analysis was useful for flagging datasets for closer inspection, eliminating or replacing poor data, and for driving changes in experimental pipelines. There had been no similarly systematic quality analysis of the large and disparate body of published ChIP-seq profiles. Here, we report a uniform analysis of vertebrate transcription factor ChIP-seq datasets in the Gene Expression Omnibus (GEO) repository as of April 1, 2012. The majority (55%) of datasets scored as being highly successful, but a substantial minority (20%) were of apparently poor quality, and another ~25% were of intermediate quality. We discuss how different uses of ChIP-seq data are affected by specific aspects of data quality, and we highlight exceptional instances for which the metric values should not be taken at face value. Unexpectedly, we discovered that a significant subset of control datasets ( i.e. , no immunoprecipitation and mock immunoprecipitation samples) display an enrichment structure similar to successful ChIP-seq data. This can, in turn, affect peak calling and data interpretation. Published datasets identified here as high-quality comprise a large group that users can draw on for large-scale integrated analysis. In the future, ChIP-seq quality assessment similar to that used here could guide experimentalists at early stages in a study, provide useful input in the publication process, and be used to stratify ChIP-seq data for different community-wide uses.
    Electronic ISSN: 2160-1836
    Topics: Biology
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  • 7
    Publication Date: 2014-08-20
    Description: We agree with Brunet and Doolittle (1) on the utility of distinguishing the evolutionarily selected effects (SE) of some genomic elements from the causal roles (CR) of other elements that lack signatures of selection (1–4). DNA sequences identified by biochemical approaches include both SE and CR elements, and genetic variation...
    Keywords: Letters
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
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  • 8
    Publication Date: 2013-10-19
    Description: The majority of disease-associated variants lie outside protein-coding regions, suggesting a link between variation in regulatory regions and disease predisposition. We studied differences in chromatin states using five histone modifications, cohesin, and CTCF in lymphoblastoid lines from 19 individuals of diverse ancestry. We found extensive signal variation in regulatory regions, which often switch between active and repressed states across individuals. Enhancer activity is particularly diverse among individuals, whereas gene expression remains relatively stable. Chromatin variability shows genetic inheritance in trios, correlates with genetic variation and population divergence, and is associated with disruptions of transcription factor binding motifs. Overall, our results provide insights into chromatin variation among humans.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4075767/" 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/PMC4075767/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Kasowski, Maya -- Kyriazopoulou-Panagiotopoulou, Sofia -- Grubert, Fabian -- Zaugg, Judith B -- Kundaje, Anshul -- Liu, Yuling -- Boyle, Alan P -- Zhang, Qiangfeng Cliff -- Zakharia, Fouad -- Spacek, Damek V -- Li, Jingjing -- Xie, Dan -- Olarerin-George, Anthony -- Steinmetz, Lars M -- Hogenesch, John B -- Kellis, Manolis -- Batzoglou, Serafim -- Snyder, Michael -- R01 HG004037/HG/NHGRI NIH HHS/ -- T32 GM007205/GM/NIGMS NIH HHS/ -- T32 HG000044/HG/NHGRI NIH HHS/ -- T32GM07205/GM/NIGMS NIH HHS/ -- U01 HL107393/HL/NHLBI NIH HHS/ -- New York, N.Y. -- Science. 2013 Nov 8;342(6159):750-2. doi: 10.1126/science.1242510. Epub 2013 Oct 17.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/24136358" target="_blank"〉PubMed〈/a〉
    Keywords: Binding Sites ; Cell Cycle Proteins/genetics/metabolism ; Cell Line, Tumor ; Chromatin/*genetics/*metabolism ; Chromosomal Proteins, Non-Histone/genetics/metabolism ; Enhancer Elements, Genetic/genetics ; *Gene Expression Regulation ; Genetic Predisposition to Disease/*genetics ; Genetic Variation ; Histones/genetics/metabolism ; Humans ; Repressor Proteins/genetics/metabolism ; Transcription Factors/genetics/metabolism
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 9
    Publication Date: 2014-08-29
    Description: Despite the large evolutionary distances between metazoan species, they can show remarkable commonalities in their biology, and this has helped to establish fly and worm as model organisms for human biology. Although studies of individual elements and factors have explored similarities in gene regulation, a large-scale comparative analysis of basic principles of transcriptional regulatory features is lacking. Here we map the genome-wide binding locations of 165 human, 93 worm and 52 fly transcription regulatory factors, generating a total of 1,019 data sets from diverse cell types, developmental stages, or conditions in the three species, of which 498 (48.9%) are presented here for the first time. We find that structural properties of regulatory networks are remarkably conserved and that orthologous regulatory factor families recognize similar binding motifs in vivo and show some similar co-associations. Our results suggest that gene-regulatory properties previously observed for individual factors are general principles of metazoan regulation that are remarkably well-preserved despite extensive functional divergence of individual network connections. The comparative maps of regulatory circuitry provided here will drive an improved understanding of the regulatory underpinnings of model organism biology and how these relate to human biology, development and disease.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4336544/" 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/PMC4336544/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Boyle, Alan P -- Araya, Carlos L -- Brdlik, Cathleen -- Cayting, Philip -- Cheng, Chao -- Cheng, Yong -- Gardner, Kathryn -- Hillier, LaDeana W -- Janette, Judith -- Jiang, Lixia -- Kasper, Dionna -- Kawli, Trupti -- Kheradpour, Pouya -- Kundaje, Anshul -- Li, Jingyi Jessica -- Ma, Lijia -- Niu, Wei -- Rehm, E Jay -- Rozowsky, Joel -- Slattery, Matthew -- Spokony, Rebecca -- Terrell, Robert -- Vafeados, Dionne -- Wang, Daifeng -- Weisdepp, Peter -- Wu, Yi-Chieh -- Xie, Dan -- Yan, Koon-Kiu -- Feingold, Elise A -- Good, Peter J -- Pazin, Michael J -- Huang, Haiyan -- Bickel, Peter J -- Brenner, Steven E -- Reinke, Valerie -- Waterston, Robert H -- Gerstein, Mark -- White, Kevin P -- Kellis, Manolis -- Snyder, Michael -- F32GM101778/GM/NIGMS NIH HHS/ -- P50GM081892/GM/NIGMS NIH HHS/ -- R01 HG004037/HG/NHGRI NIH HHS/ -- RC2HG005679/HG/NHGRI NIH HHS/ -- U01 HG004267/HG/NHGRI NIH HHS/ -- U01HG004264/HG/NHGRI NIH HHS/ -- U01HG004267/HG/NHGRI NIH HHS/ -- U54 HG004558/HG/NHGRI NIH HHS/ -- U54 HG006996/HG/NHGRI NIH HHS/ -- U54HG004558/HG/NHGRI NIH HHS/ -- U54HG006996/HG/NHGRI NIH HHS/ -- UL1 TR000430/TR/NCATS NIH HHS/ -- England -- Nature. 2014 Aug 28;512(7515):453-6. doi: 10.1038/nature13668.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉1] Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA [2]. ; Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA. ; Program of Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520, USA. ; Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06520, USA. ; Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA. ; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. ; 1] Department of Computer Science, Stanford University, Stanford, California 94305, USA [2] Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. ; 1] Department of Statistics, University of California, Berkeley, California 94720, USA [2] Department of Statistics, University of California, Los Angeles, California 90095, USA. ; Institute for Genomics and Systems Biology, University of Chicago, Chicago, Ilinois 60637, USA. ; National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, 20892, USA. ; Department of Statistics, University of California, Berkeley, California 94720, USA. ; 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.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25164757" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Binding Sites ; Caenorhabditis elegans/*genetics/growth & development ; Chromatin Immunoprecipitation ; Conserved Sequence/genetics ; Drosophila melanogaster/*genetics/growth & development ; *Evolution, Molecular ; Gene Expression Regulation/*genetics ; Gene Expression Regulation, Developmental/genetics ; Gene Regulatory Networks/*genetics ; Genome/genetics ; Humans ; Molecular Sequence Annotation ; Nucleotide Motifs/genetics ; Organ Specificity/genetics ; Transcription Factors/genetics/*metabolism
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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  • 10
    Publication Date: 2014-11-21
    Description: To broaden our understanding of the evolution of gene regulation mechanisms, we generated occupancy profiles for 34 orthologous transcription factors (TFs) in human-mouse erythroid progenitor, lymphoblast and embryonic stem-cell lines. By combining the genome-wide transcription factor occupancy repertoires, associated epigenetic signals, and co-association patterns, here we deduce several evolutionary principles of gene regulatory features operating since the mouse and human lineages diverged. The genomic distribution profiles, primary binding motifs, chromatin states, and DNA methylation preferences are well conserved for TF-occupied sequences. However, the extent to which orthologous DNA segments are bound by orthologous TFs varies both among TFs and with genomic location: binding at promoters is more highly conserved than binding at distal elements. Notably, occupancy-conserved TF-occupied sequences tend to be pleiotropic; they function in several tissues and also co-associate with many TFs. Single nucleotide variants at sites with potential regulatory functions are enriched in occupancy-conserved TF-occupied sequences.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4343047/" 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/PMC4343047/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Cheng, Yong -- Ma, Zhihai -- Kim, Bong-Hyun -- Wu, Weisheng -- Cayting, Philip -- Boyle, Alan P -- Sundaram, Vasavi -- Xing, Xiaoyun -- Dogan, Nergiz -- Li, Jingjing -- Euskirchen, Ghia -- Lin, Shin -- Lin, Yiing -- Visel, Axel -- Kawli, Trupti -- Yang, Xinqiong -- Patacsil, Dorrelyn -- Keller, Cheryl A -- Giardine, Belinda -- Mouse ENCODE Consortium -- Kundaje, Anshul -- Wang, Ting -- Pennacchio, Len A -- Weng, Zhiping -- Hardison, Ross C -- Snyder, Michael P -- 1U54HG00699/HG/NHGRI NIH HHS/ -- 3RC2HG005602/HG/NHGRI NIH HHS/ -- 5U54HG006996/HG/NHGRI NIH HHS/ -- R01 DK065806/DK/NIDDK NIH HHS/ -- R01 DK096266/DK/NIDDK NIH HHS/ -- R01 ES024992/ES/NIEHS NIH HHS/ -- R01 EY021482/EY/NEI NIH HHS/ -- R01 GM083337/GM/NIGMS NIH HHS/ -- R01 HG003988/HG/NHGRI NIH HHS/ -- R01 HG004037/HG/NHGRI NIH HHS/ -- R01 HG007175/HG/NHGRI NIH HHS/ -- R01 HG007348/HG/NHGRI NIH HHS/ -- R01 HG007354/HG/NHGRI NIH HHS/ -- R01DK065806/DK/NIDDK NIH HHS/ -- R01HG003988/HG/NHGRI NIH HHS/ -- R37 DK044746/DK/NIDDK NIH HHS/ -- RC2 HG005573/HG/NHGRI NIH HHS/ -- RC2 HG005602/HG/NHGRI NIH HHS/ -- RC2HG005573/HG/NHGRI NIH HHS/ -- U01 DE024427/DE/NIDCR NIH HHS/ -- U41 HG007234/HG/NHGRI NIH HHS/ -- U54 HG006996/HG/NHGRI NIH HHS/ -- U54 HG006997/HG/NHGRI NIH HHS/ -- U54 HG006998/HG/NHGRI NIH HHS/ -- U54 HG007004/HG/NHGRI NIH HHS/ -- U54HG006997/HG/NHGRI NIH HHS/ -- England -- Nature. 2014 Nov 20;515(7527):371-5. doi: 10.1038/nature13985.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Genetics, Stanford University, Stanford, California 94305, USA. ; Program in Bioinformatics and Integrative Biology, Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, Massachusetts 01605, USA. ; 1] Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania 16802, USA [2] BRCF Bioinformatics Core, University of Michigan, Ann Arbor, Michigan 48105, USA. ; Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St Louis, Missouri 63108, USA. ; Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania 16802, USA. ; 1] Department of Genetics, Stanford University, Stanford, California 94305, USA [2] Division of Cardiovascular Medicine, Stanford University, Stanford, California 94304, USA. ; 1] Department of Genetics, Stanford University, Stanford, California 94305, USA [2] Department of Surgery, Washington University School of Medicine, St Louis, Missouri 63110, USA. ; 1] Lawrence Berkeley National Laboratory, Genomics Division, Berkeley, California 94701, USA [2] Department of Energy Joint Genome Institute, Walnut Creek, California 94598, USA [3] School of Natural Sciences, University of California, Merced, California 95343, USA. ; 1] Lawrence Berkeley National Laboratory, Genomics Division, Berkeley, California 94701, USA [2] Department of Energy Joint Genome Institute, Walnut Creek, California 94598, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25409826" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Cell Line ; Chromatin/genetics/metabolism ; Conserved Sequence/*genetics ; Enhancer Elements, Genetic/genetics ; Genome/*genetics ; *Genomics ; Humans ; Mice ; Polymorphism, Single Nucleotide/genetics ; Regulatory Sequences, Nucleic Acid/*genetics ; Transcription Factors/*metabolism
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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