Occupancy maps of 208 chromatin-associated proteins in one human cell type.
Chromatin
/ genetics
Chromatin Immunoprecipitation Sequencing
DNA-Binding Proteins
/ metabolism
Datasets as Topic
Enhancer Elements, Genetic
/ genetics
Hep G2 Cells
Humans
Molecular Sequence Annotation
Nucleotide Motifs
/ genetics
Promoter Regions, Genetic
/ genetics
Protein Binding
Regulatory Sequences, Nucleic Acid
/ genetics
Transcription Factors
/ metabolism
Journal
Nature
ISSN: 1476-4687
Titre abrégé: Nature
Pays: England
ID NLM: 0410462
Informations de publication
Date de publication:
07 2020
07 2020
Historique:
received:
04
10
2017
accepted:
09
01
2020
entrez:
31
7
2020
pubmed:
31
7
2020
medline:
12
1
2021
Statut:
ppublish
Résumé
Transcription factors are DNA-binding proteins that have key roles in gene regulation
Identifiants
pubmed: 32728244
doi: 10.1038/s41586-020-2023-4
pii: 10.1038/s41586-020-2023-4
pmc: PMC7398277
mid: NIHMS1549226
doi:
Substances chimiques
Chromatin
0
DNA-Binding Proteins
0
Transcription Factors
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
720-728Subventions
Organisme : NHGRI NIH HHS
ID : U54 HG006998
Pays : United States
Organisme : NHGRI NIH HHS
ID : UM1 HG009411
Pays : United States
Références
Vaquerizas, J. M., Kummerfeld, S. K., Teichmann, S. A. & Luscombe, N. M. A census of human transcription factors: function, expression and evolution. Nat. Rev. Genet. 10, 252–263 (2009).
pubmed: 19274049
Lambert, S. A. et al. The human transcription factors. Cell 172, 650–665 (2018).
pubmed: 29425488
pmcid: 29425488
Yosef, N. et al. Dynamic regulatory network controlling T
pubmed: 23467089
pmcid: 3637864
Busskamp, V. et al. Rapid neurogenesis through transcriptional activation in human stem cells. Mol. Syst. Biol. 10, 760 (2014).
pubmed: 25403753
pmcid: 4299601
Chen, X. et al. Integration of external signaling pathways with the core transcriptional network in embryonic stem cells. Cell 133, 1106–1117 (2008).
pubmed: 18555785
Iwafuchi-Doi, M. & Zaret, K. S. Pioneer transcription factors in cell reprogramming. Genes Dev. 28, 2679–2692 (2014).
pubmed: 25512556
pmcid: 4265672
Wingender, E., Schoeps, T. & Dönitz, J. TFClass: an expandable hierarchical classification of human transcription factors. Nucleic Acids Res. 41, D165–D170 (2013).
pubmed: 23180794
Weirauch, M. T. et al. Determination and inference of eukaryotic transcription factor sequence specificity. Cell 158, 1431–1443 (2014).
pubmed: 25215497
pmcid: 4163041
Cowper-Sal-lari, R. et al. Breast cancer risk-associated SNPs modulate the affinity of chromatin for FOXA1 and alter gene expression. Nat. Genet. 44, 1191–1198 (2012).
Dror, I., Golan, T., Levy, C., Rohs, R. & Mandel-Gutfreund, Y. A widespread role of the motif environment in transcription factor binding across diverse protein families. Genome Res. 25, 1268–1280 (2015).
pubmed: 26160164
pmcid: 4561487
Dasen, J. S., Tice, B. C., Brenner-Morton, S. & Jessell, T. M. A Hox regulatory network establishes motor neuron pool identity and target-muscle connectivity. Cell 123, 477–491 (2005).
pubmed: 16269338
Black, J. B. et al. Targeted epigenetic remodeling of endogenous loci by CRISPR/Cas9-based transcriptional activators directly converts fibroblasts to neuronal cells. Cell Stem Cell 19, 406–414 (2016).
pubmed: 27524438
pmcid: 5010447
Visel, A. et al. ChIP–seq accurately predicts tissue-specific activity of enhancers. Nature 457, 854–858 (2009).
pubmed: 19212405
pmcid: 2745234
Johnson, D. S., Mortazavi, A., Myers, R. M. & Wold, B. Genome-wide mapping of in vivo protein-DNA interactions. Science 316, 1497–1502 (2007).
pubmed: 17540862
Mikkelsen, T. S. et al. Genome-wide maps of chromatin state in pluripotent and lineage-committed cells. Nature 448, 553–560 (2007).
pubmed: 17603471
pmcid: 2921165
Robertson, G. et al. Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing. Nat. Methods 4, 651–657 (2007).
pubmed: 17558387
Savic, D. et al. CETCh–seq: CRISPR epitope tagging ChIP–seq of DNA-binding proteins. Genome Res. 25, 1581–1589 (2015).
pubmed: 26355004
pmcid: 4579343
Partridge, E. C., Watkins, T. A. & Mendenhall, E. M. Every transcription factor deserves its map: scaling up epitope tagging of proteins to bypass antibody problems. BioEssays 38, 801–811 (2016).
pubmed: 27311628
Zhang, Y., An, L., Yue, F. & Hardison, R. C. Jointly characterizing epigenetic dynamics across multiple human cell types. Nucleic Acids Res. 44, 6721–6731 (2016).
pubmed: 27095202
pmcid: 5772166
Gerstein, M. B. et al. Architecture of the human regulatory network derived from ENCODE data. Nature 489, 91–100 (2012).
pubmed: 22955619
pmcid: 4154057
Mendenhall, E. M. et al. GC-rich sequence elements recruit PRC2 in mammalian ES cells. PLoS Genet. 6, e1001244 (2010).
pubmed: 21170310
pmcid: 3000368
Kowalczyk, M. S. et al. Intragenic enhancers act as alternative promoters. Mol. Cell 45, 447–458 (2012).
pubmed: 22264824
Dao, L. T. M. et al. Genome-wide characterization of mammalian promoters with distal enhancer functions. Nat. Genet. 49, 1073–1081 (2017).
pubmed: 28581502
Andersson, R., Sandelin, A. & Danko, C. G. A unified architecture of transcriptional regulatory elements. Trends Genet. 31, 426–433 (2015).
pubmed: 26073855
Sandelin, A., Alkema, W., Engström, P., Wasserman, W. W. & Lenhard, B. JASPAR: an open-access database for eukaryotic transcription factor binding profiles. Nucleic Acids Res. 32, D91–D94 (2004).
pubmed: 14681366
pmcid: 308747
Mathelier, A. et al. JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles. Nucleic Acids Res. 44, D110–D115 (2016).
pubmed: 26531826
Oliphant, A. R., Brandl, C. J. & Struhl, K. Defining the sequence specificity of DNA-binding proteins by selecting binding sites from random-sequence oligonucleotides: analysis of yeast GCN4 protein. Mol. Cell. Biol. 9, 2944–2949 (1989).
pubmed: 2674675
pmcid: 362762
Worsley Hunt, R. & Wasserman, W. W. Non-targeted transcription factors motifs are a systemic component of ChIP–seq datasets. Genome Biol. 15, 412 (2014).
pubmed: 25070602
pmcid: 4165360
Jolma, A. et al. DNA-binding specificities of human transcription factors. Cell 152, 327–339 (2013).
pubmed: 23332764
Morgunova, E. & Taipale, J. Structural perspective of cooperative transcription factor binding. Curr. Opin. Struct. Biol. 47, 1–8 (2017).
pubmed: 28349863
Wei, B. et al. A protein activity assay to measure global transcription factor activity reveals determinants of chromatin accessibility. Nat. Biotechnol. 36, 521–529 (2018).
pubmed: 29786094
Mortazavi, A. et al. Integrating and mining the chromatin landscape of cell-type specificity using self-organizing maps. Genome Res. 23, 2136–2148 (2013).
pubmed: 24170599
pmcid: 3847782
Longabaugh, W. J. R. et al. Bcl11b and combinatorial resolution of cell fate in the T-cell gene regulatory network. Proc. Natl Acad. Sci. USA 114, 5800–5807 (2017).
pubmed: 28584128
Whyte, W. A. et al. Enhancer decommissioning by LSD1 during embryonic stem cell differentiation. Nature 482, 221–225 (2012).
pubmed: 22297846
pmcid: 4144424
Liang, Z. et al. A high-resolution map of transcriptional repression. eLife 6, e22767 (2017).
pubmed: 28318487
pmcid: 5373822
Zhang, Y. et al. Analysis of the NuRD subunits reveals a histone deacetylase core complex and a connection with DNA methylation. Genes Dev. 13, 1924–1935 (1999).
pubmed: 10444591
pmcid: 316920
Ramírez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 44, W160–W165 (2016).
doi: 10.1093/nar/gkw257
pubmed: 27079975
pmcid: 27079975
Huttlin, E. L. et al. The BioPlex Network: a systematic exploration of the human interactome. Cell 162, 425–440 (2015).
pubmed: 26186194
pmcid: 4617211
Faherty, N. et al. Negative autoregulation of BMP dependent transcription by SIN3B splicing reveals a role for RBM39. Sci. Rep. 6, 28210 (2016).
pubmed: 27324164
pmcid: 4914931
Choi, W. I. et al. Promyelocytic leukemia zinc finger-retinoic acid receptor α (PLZF-RARα), an oncogenic transcriptional repressor of cyclin-dependent kinase inhibitor 1A (p21WAF/CDKN1A) and tumor protein p53 (TP53) genes. J. Biol. Chem. 289, 18641–18656 (2014).
pubmed: 24821728
pmcid: 4081909
Hnisz, D. et al. Super-enhancers in the control of cell identity and disease. Cell 155, 934–947 (2013).
pubmed: 24119843
pmcid: 24119843
Günther, K. et al. Differential roles for MBD2 and MBD3 at methylated CpG islands, active promoters and binding to exon sequences. Nucleic Acids Res. 41, 3010–3021 (2013).
pubmed: 23361464
pmcid: 3597697
Zaret, K. S. & Carroll, J. S. Pioneer transcription factors: establishing competence for gene expression. Genes Dev. 25, 2227–2241 (2011).
pubmed: 22056668
pmcid: 3219227
Conacci-Sorrell, M., McFerrin, L. & Eisenman, R. N. An overview of MYC and its interactome. Cold Spring Harb. Perspect. Med. 4, a014357 (2014).
pubmed: 24384812
pmcid: 3869278
Hervouet, E., Vallette, F. M. & Cartron, P. F. Dnmt3/transcription factor interactions as crucial players in targeted DNA methylation. Epigenetics 4, 487–499 (2009).
pubmed: 19786833
Boyle, A. P. et al. Comparative analysis of regulatory information and circuits across distant species. Nature 512, 453–456 (2014).
pubmed: 25164757
pmcid: 4336544
Gerstein, M. B. et al. Integrative analysis of the Caenorhabditis elegans genome by the modENCODE project. Science 330, 1775–1787 (2010).
pubmed: 21177976
pmcid: 3142569
Moorman, C. et al. Hotspots of transcription factor colocalization in the genome of Drosophila melanogaster. Proc. Natl Acad. Sci. USA 103, 12027–12032 (2006).
pubmed: 16880385
Wreczycka, K. et al. HOT or not: examining the basis of high-occupancy target regions. Nucleic Acids Res. 47, 5735–5745 (2019).
pubmed: 31114922
pmcid: 6582337
Shin, H., Liu, T., Duan, X., Zhang, Y. & Liu, X. S. Computational methodology for ChIP–seq analysis. Quant. Biol. 1, 54–70 (2013).
pubmed: 25741452
pmcid: 4346130
Teytelman, L., Thurtle, D. M., Rine, J. & van Oudenaarden, A. Highly expressed loci are vulnerable to misleading ChIP localization of multiple unrelated proteins. Proc. Natl Acad. Sci. USA 110, 18602–18607 (2013).
pubmed: 24173036
Sherwood, R. I. et al. Discovery of directional and nondirectional pioneer transcription factors by modeling DNase profile magnitude and shape. Nat. Biotechnol. 32, 171–178 (2014).
pubmed: 24441470
pmcid: 3951735
Panne, D., Maniatis, T. & Harrison, S. C. An atomic model of the interferon-β enhanceosome. Cell 129, 1111–1123 (2007).
pubmed: 17574024
pmcid: 2020837
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
pubmed: 19451168
pmcid: 19451168
Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
pubmed: 2723002
pmcid: 2723002
Landt, S. G. et al. ChIP–seq guidelines and practices of the ENCODE and modENCODE consortia. Genome Res. 22, 1813–1831 (2012).
pubmed: 22955991
pmcid: 3431496
Kharchenko, P. V., Tolstorukov, M. Y. & Park, P. J. Design and analysis of ChIP–seq experiments for DNA-binding proteins. Nat. Biotechnol. 26, 1351–1359 (2008).
pubmed: 19029915
pmcid: 2597701
Worsley Hunt, R., Mathelier, A., Del Peso, L. & Wasserman, W. W. Improving analysis of transcription factor binding sites within ChIP–seq data based on topological motif enrichment. BMC Genomics 15, 472 (2014).
pubmed: 24927817
pmcid: 4082612
Teng, M. & Irizarry, R. A. Accounting for GC-content bias reduces systematic errors and batch effects in ChIP–seq data. Genome Res. 27, 1930–1938 (2017).
pubmed: 29025895
pmcid: 5668949
Machanick, P. & Bailey, T. L. MEME-ChIP: motif analysis of large DNA datasets. Bioinformatics 27, 1696–1697 (2011).
pubmed: 21486936
pmcid: 3106185
Ma, W., Noble, W. S. & Bailey, T. L. Motif-based analysis of large nucleotide data sets using MEME-ChIP. Nat. Protocols 9, 1428–1450 (2014).
pubmed: 24853928
Bailey, T. L. & Machanick, P. Inferring direct DNA binding from ChIP–seq. Nucleic Acids Res. 40, e128 (2012).
pubmed: 22610855
pmcid: 3458523
Gupta, S., Stamatoyannopoulos, J. A., Bailey, T. L. & Noble, W. S. Quantifying similarity between motifs. Genome Biol. 8, R24 (2007).
pubmed: 17324271
pmcid: 1852410
Uhlén, M. et al. Proteomics. Tissue-based map of the human proteome. Science 347, 1260419 (2015).
pubmed: 25613900
Dale, R. K., Pedersen, B. S. & Quinlan, A. R. Pybedtools: a flexible Python library for manipulating genomic datasets and annotations. Bioinformatics 27, 3423–3424 (2011).
pubmed: 21949271
pmcid: 3232365
Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).
pubmed: 2832824
pmcid: 2832824
Fletez-Brant, C., Lee, D., McCallion, A. S. & Beer, M. A. kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets. Nucleic Acids Res. 41, W544–W556 (2013).
pubmed: 23771147
pmcid: 3692045
McLean, C. Y. et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 28, 495–501 (2010).
pubmed: 4840234
pmcid: 4840234
Liberzon, A. et al. The molecular signatures database (MSigDB) hallmark gene set collection. Cell Syst. 1, 417–425 (2015).
pubmed: 26771021
pmcid: 4707969
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).
pubmed: 16199517
Quinlan, A. R. BEDTools: the swiss-army tool for genome feature analysis. Curr. Protoc. Bioinformatics 47, 11.12.11–11.12.34 (2014).
Ghandi, M. et al. gkmSVM: an R package for gapped-kmer SVM. Bioinformatics 32, 2205–2207 (2016).
pubmed: 27153639
pmcid: 4937197
Pedregosa, F. et al. Scikit-learn: machine learning in Python. JMLR 12, 2825–2830 (2011).
Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, New York, 2016).
Gu, Z., Eils, R. & Schlesner, M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics 32, 2847–2849 (2016).
pubmed: 27207943
Wright, M. N. & Ziegler, A. ranger: a fast implementation of random forests for high dimensional data in C++ and R. J. Stat. Softw. 77, 1–17 (2017).
Mellacheruvu, D. et al. The CRAPome: a contaminant repository for affinity purification-mass spectrometry data. Nat. Methods 10, 730–736 (2013).
pubmed: 23921808
pmcid: 3773500
Akaike, H. Information theory and an extension of the maximum likelihood principle. Intl Symp. Information Theory 267–281 (1973).