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      Genome-wide identification and characterisation of human DNA replication origins by initiation site sequencing (ini-seq)

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          Abstract

          Next-generation sequencing has enabled the genome-wide identification of human DNA replication origins. However, different approaches to mapping replication origins, namely (i) sequencing isolated small nascent DNA strands (SNS-seq); (ii) sequencing replication bubbles (bubble-seq) and (iii) sequencing Okazaki fragments (OK-seq), show only limited concordance. To address this controversy, we describe here an independent high-resolution origin mapping technique that we call initiation site sequencing (ini-seq). In this approach, newly replicated DNA is directly labelled with digoxigenin-dUTP near the sites of its initiation in a cell-free system. The labelled DNA is then immunoprecipitated and genomic locations are determined by DNA sequencing. Using this technique we identify >25,000 discrete origin sites at sub-kilobase resolution on the human genome, with high concordance between biological replicates. Most activated origins identified by ini-seq are found at transcriptional start sites and contain G-quadruplex (G4) motifs. They tend to cluster in early-replicating domains, providing a correlation between early replication timing and local density of activated origins. Origins identified by ini-seq show highest concordance with sites identified by SNS-seq, followed by OK-seq and bubble-seq. Furthermore, germline origins identified by positive nucleotide distribution skew jumps overlap with origins identified by ini-seq and OK-seq more frequently and more specifically than do sites identified by either SNS-seq or bubble-seq.

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          Most cited references56

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          A clustering approach for identification of enriched domains from histone modification ChIP-Seq data.

          Chromatin states are the key to gene regulation and cell identity. Chromatin immunoprecipitation (ChIP) coupled with high-throughput sequencing (ChIP-Seq) is increasingly being used to map epigenetic states across genomes of diverse species. Chromatin modification profiles are frequently noisy and diffuse, spanning regions ranging from several nucleosomes to large domains of multiple genes. Much of the early work on the identification of ChIP-enriched regions for ChIP-Seq data has focused on identifying localized regions, such as transcription factor binding sites. Bioinformatic tools to identify diffuse domains of ChIP-enriched regions have been lacking. Based on the biological observation that histone modifications tend to cluster to form domains, we present a method that identifies spatial clusters of signals unlikely to appear by chance. This method pools together enrichment information from neighboring nucleosomes to increase sensitivity and specificity. By using genomic-scale analysis, as well as the examination of loci with validated epigenetic states, we demonstrate that this method outperforms existing methods in the identification of ChIP-enriched signals for histone modification profiles. We demonstrate the application of this unbiased method in important issues in ChIP-Seq data analysis, such as data normalization for quantitative comparison of levels of epigenetic modifications across cell types and growth conditions. http://home.gwu.edu/ approximately wpeng/Software.htm. Supplementary data are available at Bioinformatics online.
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            Sequencing newly replicated DNA reveals widespread plasticity in human replication timing.

            Faithful transmission of genetic material to daughter cells involves a characteristic temporal order of DNA replication, which may play a significant role in the inheritance of epigenetic states. We developed a genome-scale approach--Repli Seq--to map temporally ordered replicating DNA using massively parallel sequencing and applied it to study regional variation in human DNA replication time across multiple human cell types. The method requires as few as 8,000 cytometry-fractionated cells for a single analysis, and provides high-resolution DNA replication patterns with respect to both cell-cycle time and genomic position. We find that different cell types exhibit characteristic replication signatures that reveal striking plasticity in regional replication time patterns covering at least 50% of the human genome. We also identified autosomal regions with marked biphasic replication timing that include known regions of monoallelic expression as well as many previously uncharacterized domains. Comparison with high-resolution genome-wide profiles of DNaseI sensitivity revealed that DNA replication typically initiates within foci of accessible chromatin comprising clustered DNaseI hypersensitive sites, and that replication time is better correlated with chromatin accessibility than with gene expression. The data collectively provide a unique, genome-wide picture of the epigenetic compartmentalization of the human genome and suggest that cell-lineage specification involves extensive reprogramming of replication timing patterns.
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              Unraveling cell type-specific and reprogrammable human replication origin signatures associated with G-quadruplex consensus motifs.

              DNA replication is highly regulated, ensuring faithful inheritance of genetic information through each cell cycle. In metazoans, this process is initiated at many thousands of DNA replication origins whose cell type-specific distribution and usage are poorly understood. We exhaustively mapped the genome-wide location of replication origins in human cells using deep sequencing of short nascent strands and identified ten times more origin positions than we expected; most of these positions were conserved in four different human cell lines. Furthermore, we identified a consensus G-quadruplex-forming DNA motif that can predict the position of DNA replication origins in human cells, accounting for their distribution, usage efficiency and timing. Finally, we discovered a cell type-specific reprogrammable signature of cell identity that was revealed by specific efficiencies of conserved origin positions and not by the selection of cell type-specific subsets of origins.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                01 December 2016
                01 September 2016
                01 September 2016
                : 44
                : 21
                : 10230-10247
                Affiliations
                [1 ]Francis Crick Institute, Mill Hill Laboratory, The Ridgeway, London NW7 1AA, UK
                [2 ]Department of Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
                [3 ]Department of Haematology, University of Cambridge, Cambridge CB2 0PT, UK
                [4 ]Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +44 1223 330111; Email: tk218@ 123456cam.ac.uk
                []These authors contributed equally to this work as first authors.
                Article
                10.1093/nar/gkw760
                5137433
                27587586
                2883aecd-7604-4b49-b886-fbd2bee437a4
                © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 20 August 2016
                : 18 August 2016
                : 21 June 2016
                Page count
                Pages: 18
                Categories
                21
                28
                Genome Integrity, Repair and Replication
                Custom metadata
                01 December 2016

                Genetics
                Genetics

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