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      ATAC-seq footprinting unravels kinetics of transcription factor binding during zygotic genome activation

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          Abstract

          While footprinting analysis of ATAC-seq data can theoretically enable investigation of transcription factor (TF) binding, the lack of a computational tool able to conduct different levels of footprinting analysis has so-far hindered the widespread application of this method. Here we present TOBIAS, a comprehensive, accurate, and fast footprinting framework enabling genome-wide investigation of TF binding dynamics for hundreds of TFs simultaneously. We validate TOBIAS using paired ATAC-seq and ChIP-seq data, and find that TOBIAS outperforms existing methods for bias correction and footprinting. As a proof-of-concept, we illustrate how TOBIAS can unveil complex TF dynamics during zygotic genome activation in both humans and mice, and propose how zygotic Dux activates cascades of TFs, binds to repeat elements and induces expression of novel genetic elements.

          Abstract

          Footprinting analysis allows genome-wide investigation of transcription factor (TF) binding on chromatin. Here the authors developed a framework termed TOBIAS aimed at identifying footprints of chromatin-associated proteins from ATAC-seq accessibility profiles and apply it to zygotic development datasets.

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          Most cited references30

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          Identifying ChIP-seq enrichment using MACS.

          Model-based analysis of ChIP-seq (MACS) is a computational algorithm that identifies genome-wide locations of transcription/chromatin factor binding or histone modification from ChIP-seq data. MACS consists of four steps: removing redundant reads, adjusting read position, calculating peak enrichment and estimating the empirical false discovery rate (FDR). In this protocol, we provide a detailed demonstration of how to install MACS and how to use it to analyze three common types of ChIP-seq data sets with different characteristics: the sequence-specific transcription factor FoxA1, the histone modification mark H3K4me3 with sharp enrichment and the H3K36me3 mark with broad enrichment. We also explain how to interpret and visualize the results of MACS analyses. The algorithm requires ∼3 GB of RAM and 1.5 h of computing time to analyze a ChIP-seq data set containing 30 million reads, an estimate that increases with sequence coverage. MACS is open source and is available from http://liulab.dfci.harvard.edu/MACS/.
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            An expansive human regulatory lexicon encoded in transcription factor footprints

            Regulatory factor binding to genomic DNA protects the underlying sequence from cleavage by DNaseI, leaving nucleotide-resolution footprints. Using genomic DNaseI footprinting across 41 diverse cell and tissue types, we detected 45 million factor occupancy events within regulatory regions, representing differential binding to 8.4 million distinct short sequence elements. Here we show that this small genomic sequence compartment, roughly twice the size of the exome, encodes an expansive repertoire of conserved recognition sequences for DNA-binding proteins that nearly doubles the size of the human cis-regulatory lexicon. We find that genetic variants affecting allelic chromatin states are concentrated in footprints, and that these elements are preferentially sheltered from DNA methylation. High-resolution DNaseI cleavage patterns mirror nucleotide-level evolutionary conservation and track the crystallographic topography of protein-DNA interfaces, indicating that transcription factor structure has been evolutionarily imprinted on the human genome sequence. We identify a stereotyped 50 base-pair footprint that precisely defines the site of transcript origination within thousands of human promoters. Finally, we describe a large collection of novel regulatory factor recognition motifs that are highly conserved in both sequence and function, and exhibit cell-selective occupancy patterns that closely parallel major regulators of development, differentiation, and pluripotency.
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              Conserved roles for murine DUX and human DUX4 in activating cleavage stage genes and MERVL/HERVL retrotransposons

              To better understand transcriptional regulation during human oogenesis and pre-implantation development, we defined stage-specific transcription, which revealed the cleavage stage as highly distinctive. Here, we present multiple lines of evidence that a eutherian-specific, multi-copy retrogene, DUX4, encodes a transcription factor which activates hundreds of endogenous genes (e.g. ZSCAN4, ZFP352, KDM4E) and retroviral elements (MERVL/HERVL-family) that defines the cleavage-specific transcriptional programs in mouse and human. Remarkably, mouse Dux expression is both necessary and sufficient to convert mouse embryonic stem cells into two-cell embryo-like (‘2C-like’) cells, measured here by the reactivation of ‘2C’ genes and repeat elements, the loss of POU5F1 protein and chromocenters, and by the conversion of the chromatin landscape (assessed by ATAC-seq) to a state strongly resembling mouse two-cell embryos. Taken together, we propose mouse DUX and human DUX4 as major drivers of the cleavage/‘2C’ state.
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                Author and article information

                Contributors
                mario.looso@mpi-bn.mpg.de
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                26 August 2020
                26 August 2020
                2020
                : 11
                : 4267
                Affiliations
                [1 ]GRID grid.418032.c, ISNI 0000 0004 0491 220X, Bioinformatics Core Unit (BCU), Max Planck Institute for Heart and Lung Research, ; 61231 Bad Nauheim, Germany
                [2 ]GRID grid.452396.f, ISNI 0000 0004 5937 5237, German Centre for Cardiovascular Research (DZHK), Partner Site Rhine-Main, ; 60596 Frankfurt am Main, Germany
                [3 ]GRID grid.418032.c, ISNI 0000 0004 0491 220X, Department of Cardiac Development and Remodeling, , Max Planck Institute for Heart and Lung Research, ; 61231 Bad Nauheim, Germany
                Author information
                http://orcid.org/0000-0002-8016-0199
                http://orcid.org/0000-0001-5640-9356
                http://orcid.org/0000-0003-2408-1282
                http://orcid.org/0000-0002-5921-8413
                http://orcid.org/0000-0003-1927-3458
                http://orcid.org/0000-0001-8013-5906
                http://orcid.org/0000-0002-6165-4804
                http://orcid.org/0000-0002-5226-5460
                http://orcid.org/0000-0003-1495-9530
                Article
                18035
                10.1038/s41467-020-18035-1
                7449963
                32848148
                1904a56e-f2b3-427a-95ef-2ffece63294c
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 17 February 2020
                : 23 July 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft (German Research Foundation);
                Award ID: EXEC CPI
                Award ID: KFO309
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research);
                Award ID: DZHK
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                computational biology and bioinformatics,software,embryogenesis
                Uncategorized
                computational biology and bioinformatics, software, embryogenesis

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