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      Global mapping of protein-DNA interactions in vivo by digital genomic footprinting

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          Abstract

          The orchestrated binding of transcriptional activators and repressors to specific DNA sequences in the context of chromatin defines the regulatory program of eukaryotic genomes. We developed a digital approach to assay regulatory protein occupancy on genomic DNA in vivo by dense mapping of individual DNase I cleavages from intact nuclei using massively parallel DNA sequencing. Analysis of > 23 million cleavages across the Saccharomyces cerevisiae genome revealed thousands of protected regulatory protein footprints, enabling de novo derivation of factor binding motifs as well as the identification of hundreds of novel binding sites for major regulators. We observed striking correspondence between nucleotide-level DNase I cleavage patterns and protein-DNA interactions determined by crystallography. The data also yielded a detailed view of larger chromatin features including positioned nucleosomes flanking factor binding regions. Digital genomic footprinting provides a powerful approach to delineate the cis-regulatory framework of any organism with an available genome sequence.

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          Most cited references21

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          Sequencing and comparison of yeast species to identify genes and regulatory elements.

          Identifying the functional elements encoded in a genome is one of the principal challenges in modern biology. Comparative genomics should offer a powerful, general approach. Here, we present a comparative analysis of the yeast Saccharomyces cerevisiae based on high-quality draft sequences of three related species (S. paradoxus, S. mikatae and S. bayanus). We first aligned the genomes and characterized their evolution, defining the regions and mechanisms of change. We then developed methods for direct identification of genes and regulatory motifs. The gene analysis yielded a major revision to the yeast gene catalogue, affecting approximately 15% of all genes and reducing the total count by about 500 genes. The motif analysis automatically identified 72 genome-wide elements, including most known regulatory motifs and numerous new motifs. We inferred a putative function for most of these motifs, and provided insights into their combinatorial interactions. The results have implications for genome analysis of diverse organisms, including the human.
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            Genome-scale identification of nucleosome positions in S. cerevisiae.

            G.-C. Yuan (2005)
            The positioning of nucleosomes along chromatin has been implicated in the regulation of gene expression in eukaryotic cells, because packaging DNA into nucleosomes affects sequence accessibility. We developed a tiled microarray approach to identify at high resolution the translational positions of 2278 nucleosomes over 482 kilobases of Saccharomyces cerevisiae DNA, including almost all of chromosome III and 223 additional regulatory regions. The majority of the nucleosomes identified were well-positioned. We found a stereotyped chromatin organization at Pol II promoters consisting of a nucleosome-free region approximately 200 base pairs upstream of the start codon flanked on both sides by positioned nucleosomes. The nucleosome-free sequences were evolutionarily conserved and were enriched in poly-deoxyadenosine or poly-deoxythymidine sequences. Most occupied transcription factor binding motifs were devoid of nucleosomes, strongly suggesting that nucleosome positioning is a global determinant of transcription factor access.
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              A high-resolution atlas of nucleosome occupancy in yeast.

              We present the first complete high-resolution map of nucleosome occupancy across the whole Saccharomyces cerevisiae genome, identifying over 70,000 positioned nucleosomes occupying 81% of the genome. On a genome-wide scale, the persistent nucleosome-depleted region identified previously in a subset of genes demarcates the transcription start site. Both nucleosome occupancy signatures and overall occupancy correlate with transcript abundance and transcription rate. In addition, functionally related genes can be clustered on the basis of the nucleosome occupancy patterns observed at their promoters. A quantitative model of nucleosome occupancy indicates that DNA structural features may account for much of the global nucleosome occupancy.
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                Author and article information

                Journal
                101215604
                32338
                Nat Methods
                Nature methods
                1548-7091
                1548-7105
                2 March 2009
                22 March 2009
                April 2009
                1 October 2009
                : 6
                : 4
                : 283-289
                Affiliations
                [1 ] Dept. of Genome Sciences, University of Washington, Seattle, WA 98195
                [2 ] Dept. of Computer Science, University of Washington, Seattle, WA 98195
                [3 ] Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195
                [4 ] Dept. of Medicine, University of Washington, Seattle, WA 98195
                Author notes
                [5]

                Present address: Illumina, Inc., San Diego, CA

                [6]

                equal contribution

                [# ] Correspondence: jstam@ 123456u.washington.edu
                Article
                nihpa97769
                10.1038/nmeth.1313
                2668528
                19305407
                d6fc3079-069a-40c3-b9f4-3f13c7b6bd87
                History
                Funding
                Funded by: National Center for Research Resources : NCRR
                Funded by: Howard Hughes Medical Institute
                Award ID: P41 RR011823-135975 ||RR
                Funded by: National Center for Research Resources : NCRR
                Funded by: Howard Hughes Medical Institute
                Award ID: ||HHMI_
                Categories
                Article

                Life sciences
                Life sciences

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