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      Acoel genome reveals the regulatory landscape of whole-body regeneration

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          Abstract

          Whole-body regeneration is accompanied by complex transcriptomic changes, yet the chromatin regulatory landscapes that mediate this dynamic response remain unexplored. To decipher the regulatory logic that orchestrates regeneration, we sequenced the genome of the acoel worm Hofstenia miamia, a highly regenerative member of the sister lineage of other bilaterians. Epigenomic profiling revealed thousands of regeneration-responsive chromatin regions and identified dynamically bound transcription factor motifs, with the early growth response (EGR) binding site as the most variably accessible during Hofstenia regeneration. Combining egr inhibition with chromatin profiling suggests that Egr functions as a pioneer factor to directly regulate early wound-induced genes. The genetic connections inferred by this approach allowed the construction of a gene regulatory network for whole-body regeneration, enabling genomics-based comparisons of regeneration across species.

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          Most cited references32

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          Is Open Access

          REAPR: a universal tool for genome assembly evaluation

          Methods to reliably assess the accuracy of genome sequence data are lacking. Currently completeness is only described qualitatively and mis-assemblies are overlooked. Here we present REAPR, a tool that precisely identifies errors in genome assemblies without the need for a reference sequence. We have validated REAPR on complete genomes or de novo assemblies from bacteria, malaria and Caenorhabditis elegans, and demonstrate that 86% and 82% of the human and mouse reference genomes are error-free, respectively. When applied to an ongoing genome project, REAPR provides corrected assembly statistics allowing the quantitative comparison of multiple assemblies. REAPR is available at http://www.sanger.ac.uk/resources/software/reapr/.
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            JASPAR 2018: update of the open-access database of transcription factor binding profiles and its web framework

            Nucleic Acids Research (2017), https://doi.org/10.1093/nar/gkx1126 The above paper was corrected to add a reference to its companion paper: Chèneby, J., Gheorghe, M., Artufel, M., Mathelier, A., Ballester, B. (2017) ReMap 2018: An updated atlas of regulatory regions from an integrative analysis of DNA-binding ChIP-seq experiments. Nucleic Acids Res., doi: 10.1093/nar/gkx1092.
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              Discovery of non-directional and directional pioneer transcription factors by modeling DNase profile magnitude and shape

              Here we describe Protein Interaction Quantitation (PIQ), a computational method that models the magnitude and shape of genome-wide DNase profiles to facilitate the identification of transcription factor (TF) binding sites. Through the use of machine learning techniques, PIQ identified binding sites for >700 TFs from one DNase-seq experiment with accuracy comparable to ChIP-seq for motif-associated TFs (median AUC=0.93 across 303 TFs). We applied PIQ to analyze DNase-seq data from mouse embryonic stem cells differentiating into pre-pancreatic and intestinal endoderm. We identified (n=120) and experimentally validated eight ‘pioneer’ TF families that dynamically open chromatin, enabling other TFs to bind to adjacent DNA. Four pioneer TF families only open chromatin in one direction from their motifs. Furthermore, we identified a class of ‘settler’ TFs whose genomic binding is principally governed by proximity to open chromatin. Our results support a model of hierarchical TF binding in which directional and non-directional pioneer activity shapes the chromatin landscape for population by settler TFs.
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                Author and article information

                Journal
                Science
                Science
                American Association for the Advancement of Science (AAAS)
                0036-8075
                1095-9203
                March 14 2019
                March 15 2019
                March 14 2019
                March 15 2019
                : 363
                : 6432
                : eaau6173
                Article
                10.1126/science.aau6173
                30872491
                0367fce3-74c9-40a6-82b3-095ac6febbb4
                © 2019

                http://www.sciencemag.org/about/science-licenses-journal-article-reuse

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