Genome-Wide Mapping of in Vivo Protein-DNA Interactions

Department of Genetics, Stanford University School of Medicine, Stanford, CA, 94305-5120, USA.
Science (Impact Factor: 31.48). 07/2007; 316(5830):1497-502. DOI: 10.1126/science.1141319
Source: PubMed

ABSTRACT In vivo protein-DNA interactions connect each transcription factor with its direct targets to form a gene network scaffold.
To map these protein-DNA interactions comprehensively across entire mammalian genomes, we developed a large-scale chromatin
immunoprecipitation assay (ChIPSeq) based on direct ultrahigh-throughput DNA sequencing. This sequence census method was then
used to map in vivo binding of the neuron-restrictive silencer factor (NRSF; also known as REST, for repressor element–1 silencing
transcription factor) to 1946 locations in the human genome. The data display sharp resolution of binding position [±50 base
pairs (bp)], which facilitated our finding motifs and allowed us to identify noncanonical NRSF-binding motifs. These ChIPSeq
data also have high sensitivity and specificity [ROC (receiver operator characteristic) area ≥ 0.96] and statistical confidence
(P <10–4), properties that were important for inferring new candidate interactions. These include key transcription factors in the
gene network that regulates pancreatic islet cell development.

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Available from: Richard M Myers, Aug 27, 2015
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    • "Interestingly, in the K562 cell genome, 46% of the p300 enhancer marks (Heintzman et al., 2007) have at least one CBS located within 2 kb (Figure S4B). On the other hand, 54% of the marks of the silencer factor REST/NRSF (Johnson et al., 2007) have at least one CBS located within 2 kb (Figure S4C). These observations suggest that CTCF/cohesin-mediated DNA-looping interaction may enhance or inhibit gene expression, depending on the proximity of the CBS to p300 or REST/NRSF. "
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    ABSTRACT: Graphical Abstract Highlights d The orientation of Pcdh CBSs determines the direction of topological DNA looping d Directional CTCF binding to CBSs is crucial for loop topology and gene expression d The CTCF binding orientation functions similarly in b-globin and the whole genome d CTCF/cohesin-mediated directional DNA-looping determines chromosome architecture
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    • "As specified for a subset of other genes (Pullen et al., 2010; Quintens et al., 2008), REST is thus " disallowed " in beta cells, as it is in neurons (Atouf et al., 1997). The observation made by ChIP seq analysis that REST binds to the chromatin of drivers of islet cell development (Johnson et al., 2007), together with the fact that REST clearance in neural progenitors has been evoked as a trigger for neural differentiation (Ballas et al., 2005), prompted us to assess the role of REST in the developing pancreas. "
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    ABSTRACT: To contribute to devise successful beta-cell differentiation strategies for the cure of Type1 diabetes we sought to uncover barriers that restrict endocrine fate acquisition by studying the role of the transcriptional repressor REST in the developing pancreas. Rest expression is prevented in neurons and in endocrine cells, which is necessary for their normal function. During development, REST represses a subset of genes in the neuronal differentiation program and Rest is down-regulated as neurons differentiate. Here, we investigate the role of REST in the differentiation of pancreatic endocrine cells, which are molecularly close to neurons. We show that Rest is widely expressed in pancreas progenitors and that it is down-regulated in differentiated endocrine cells. Sustained expression of REST in Pdx1(+) progenitors impairs the differentiation of endocrine-committed Neurog3(+) progenitors, decreases beta and alpha cell mass by E18.5, and triggers diabetes in adulthood. Conditional inactivation of Rest in Pdx1(+) progenitors is not sufficient to trigger endocrine differentiation but up-regulates a subset of differentiation genes. Our results show that the transcriptional repressor REST is active in pancreas progenitors where it gates the activation of part of the beta cell differentiation program. Copyright © 2015. Published by Elsevier Inc.
    Developmental Biology 07/2015; DOI:10.1016/j.ydbio.2015.07.002 · 3.64 Impact Factor
    • "To determine where histone modifications or transcription factors are located in the DNA , chromatin immunoprecipita - tion combined with next generation sequencing ( ChIP - seq ) protocols were developed several years ago ( Barski et al . , 2007 ; Johnson et al . , 2007 ; Mikkelsen et al . , 2007 ) . In a typi - cal ChIP experiment , a chromatin fragment is precipitated using antibodies directed against a specific histone modifica - tion or DNA - binding protein . The DNA is isolated from the precipitated chromatin and sequenced using Next Generation Sequencing . A genome - wide profile is generated th"
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    ABSTRACT: Genome-wide expression profiling technology has resulted in detailed transcriptome data for a wide range of tissues, conditions and diseases. In neuroscience, expression datasets were mostly generated using whole brain tissue samples, resulting in data from a mixture of cell types, including glial cells and neurons. Over the past few years, a rapidly increasing number of expression profiling studies using isolated microglial cell populations have been reported. In these studies, the microglia transcriptome was compared to other cell types, such as other brain cells and peripheral tissue macrophages, and related to aging and neurodegenerative conditions. A commonality found in many of these studies was that microglia possess distinct gene expression signatures. This repertoire of selectively-expressed microglial genes highlight functions beyond immune responses, such as synaptic modulation and neurotrophic support, and open up avenues to explore as-yet-unexpected roles. These data provide improved understanding of disease pathology, and complement not only the aforementioned whole brain tissue transcriptome studies, but also genome- and epigenome-wide association studies. In this review, insights obtained from isolated microglia transcriptome studies are presented, and compared to studies using other genome-wide approaches. The relation of microglia to other tissue macrophages and glial cell populations, as well as the role of microglia in the aging brain and in neurodegenerative conditions, will be discussed. Many more of these types of studies are expected in the near future, hopefully leading to the identification of novel genes and targets for neurodegenerative conditions. GLIA 2015. © 2015 Wiley Periodicals, Inc.
    Glia 06/2015; DOI:10.1002/glia.22866 · 6.03 Impact Factor
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