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      Design and analysis of ChIP-seq experiments for DNA-binding proteins

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          Abstract

          Recent progress in massively parallel sequencing platforms has allowed for genome-wide measurements of DNA-associated proteins using a combination of chromatin immunoprecipitation and sequencing (ChIP-seq). While a variety of methods exist for analysis of the established microarray alternative (ChIP-chip), few approaches have been described for processing ChIP-seq data. To fill this gap, we propose an analysis pipeline specifically designed to detect protein binding positions with high accuracy. Using three separate datasets, we illustrate new methods for improving tag alignment and correcting for background signals. We also compare sensitivity and spatial precision of several novel and previously described binding detection algorithms. Finally, we analyze the relationship between the depth of sequencing and characteristics of the detected binding positions, and provide a method for estimating the sequencing depth necessary for a desired coverage of protein binding sites.

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          Most cited references16

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          TRANSFAC: transcriptional regulation, from patterns to profiles.

          The TRANSFAC database on eukaryotic transcriptional regulation, comprising data on transcription factors, their target genes and regulatory binding sites, has been extended and further developed, both in number of entries and in the scope and structure of the collected data. Structured fields for expression patterns have been introduced for transcription factors from human and mouse, using the CYTOMER database on anatomical structures and developmental stages. The functionality of Match, a tool for matrix-based search of transcription factor binding sites, has been enhanced. For instance, the program now comes along with a number of tissue-(or state-)specific profiles and new profiles can be created and modified with Match Profiler. The GENE table was extended and gained in importance, containing amongst others links to LocusLink, RefSeq and OMIM now. Further, (direct) links between factor and target gene on one hand and between gene and encoded factor on the other hand were introduced. The TRANSFAC public release is available at http://www.gene-regulation.com. For yeast an additional release including the latest data was made available separately as TRANSFAC Saccharomyces Module (TSM) at http://transfac.gbf.de. For CYTOMER free download versions are available at http://www.biobase.de:8080/index.html.
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            DNA methylation profiling of human chromosomes 6, 20 and 22

            DNA methylation constitutes the most stable type of epigenetic modifications modulating the transcriptional plasticity of mammalian genomes. Using bisulfite DNA sequencing, we report high-resolution methylation reference profiles of human chromosomes 6, 20 and 22, providing a resource of about 1.9 million CpG methylation values derived from 12 different tissues. Analysis of 6 annotation categories, revealed evolutionary conserved regions to be the predominant sites for differential DNA methylation and a core region surrounding the transcriptional start site as informative surrogate for promoter methylation. We find 17% of the 873 analyzed genes differentially methylated in their 5′-untranslated regions (5′-UTR) and about one third of the differentially methylated 5′-UTRs to be inversely correlated with transcription. While our study was controlled for factors reported to affect DNA methylation such as sex and age, we did not find any significant attributable effects. Our data suggest DNA methylation to be ontogenetically more stable than previously thought.
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              Analysis of the vertebrate insulator protein CTCF-binding sites in the human genome.

              Insulator elements affect gene expression by preventing the spread of heterochromatin and restricting transcriptional enhancers from activation of unrelated promoters. In vertebrates, insulator's function requires association with the CCCTC-binding factor (CTCF), a protein that recognizes long and diverse nucleotide sequences. While insulators are critical in gene regulation, only a few have been reported. Here, we describe 13,804 CTCF-binding sites in potential insulators of the human genome, discovered experimentally in primary human fibroblasts. Most of these sequences are located far from the transcriptional start sites, with their distribution strongly correlated with genes. The majority of them fit to a consensus motif highly conserved and suitable for predicting possible insulators driven by CTCF in other vertebrate genomes. In addition, CTCF localization is largely invariant across different cell types. Our results provide a resource for investigating insulator function and possible other general and evolutionarily conserved activities of CTCF sites.
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                Author and article information

                Journal
                9604648
                20305
                Nat Biotechnol
                Nature biotechnology
                1087-0156
                1546-1696
                30 October 2008
                16 November 2008
                December 2008
                1 June 2009
                : 26
                : 12
                : 1351-1359
                Affiliations
                [1 ]Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck St, Boston, MA 02115 USA
                [2 ]Harvard-Partners Center for Genetics and Genomics, 77 Avenue Louis Pasteur, Boston, MA 02115 USA
                [3 ]Harvard-MIT Health Sciences and Technology Informatics Program at Children’s Hospital, 300 Longwood Ave., Boston, MA 02115 USA
                Author notes
                [§ ]The correspondence should be addressed to PJP ( peter_park@ 123456harvard.edu )
                Article
                nihpa76273
                10.1038/nbt.1508
                2597701
                19029915
                980bc869-41b1-40f4-a867-b021b6d496c3
                History
                Funding
                Funded by: National Center for Research Resources : NCRR
                Funded by: National Human Genome Research Institute : NHGRI
                Funded by: National Institute of General Medical Sciences : NIGMS
                Award ID: UL1 RR024920-01 ||RR
                Funded by: National Center for Research Resources : NCRR
                Funded by: National Human Genome Research Institute : NHGRI
                Funded by: National Institute of General Medical Sciences : NIGMS
                Award ID: U01 HG004258-01 ||HG
                Funded by: National Center for Research Resources : NCRR
                Funded by: National Human Genome Research Institute : NHGRI
                Funded by: National Institute of General Medical Sciences : NIGMS
                Award ID: R01 GM082798-03 ||GM
                Categories
                Article

                Biotechnology
                Biotechnology

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