Cited by 114Genomics and Chromatin DynamicsEpigenetics and DNA MethylationChromatin Remodeling and Cancer

Occupancy by key transcription factors is a more accurate predictor of enhancer activity than histone modifications or chromatin accessibility

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Dogan, Nergiz, Wu, Weisheng, Morrissey, Christapher S, Chen, Kuan-Bei, Stonestrom, Aaron, Long, Maria, Keller, Cheryl A, Cheng, Yong +6 more·2015·Epigenetics & Chromatin

Abstract

BACKGROUND: Regulated gene expression controls organismal development, and variation in regulatory patterns has been implicated in complex traits. Thus accurate prediction of enhancers is important for further understanding of these processes. Genome-wide measurement of epigenetic features, such as histone modifications and occupancy by transcription factors, is improving enhancer predictions, but the contribution of these features to prediction accuracy is not known. Given the importance of the hematopoietic transcription factor TAL1 for erythroid gene activation, we predicted candidate enhancers based on genomic occupancy by TAL1 and measured their activity. Contributions of multiple features to enhancer prediction were evaluated based on the results of these and other studies. RESULTS: TAL1-bound DNA segments were active enhancers at a high rate both in transient transfections of cultured cells (39 of 79, or 56%) and transgenic mice (43 of 66, or 65%). The level of binding signal for TAL1 or GATA1 did not help distinguish TAL1-bound DNA segments as active versus inactive enhancers, nor did the density of regulation-related histone modifications. A meta-analysis of results from this and other studies (273 tested predicted enhancers) showed that the presence of TAL1, GATA1, EP300, SMAD1, H3K4 methylation, H3K27ac, and CAGE tags at DNase hypersensitive sites gave the most accurate predictors of enhancer activity, with a success rate over 80% and a median threefold increase in activity. Chromatin accessibility assays and the histone modifications H3K4me1 and H3K27ac were sensitive for finding enhancers, but they have high false positive rates unless transcription factor occupancy is also included. CONCLUSIONS: Occupancy by key transcription factors such as TAL1, GATA1, SMAD1, and EP300, along with evidence of transcription, improves the accuracy of enhancer predictions based on epigenetic features.

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  • The observation that p300 catalytic activity does not contribute to destabilization is inconsistent with a model by which histone acetylation reduces nucleosome-DNA affinity to facilitate TF binding.

    “appears inconsistent with a model by which histone acetylation reduces nucleosome-DNA affinity to facilitate TF binding29,49,50”

    From Single-molecule states link transcription factor binding to gene expression (2024) · cites this paper as [50]

    The Background describes TF-bound enhancers as flanked by nucleosomes bearing H3K27ac, and the Results and Discussion compare TF occupancy and histone marks as predictors of enhancer activity. No passage found addresses the cited model that acetylation reduces nucleosome–DNA affinity to facilitate TF binding; searches for nucleosome affinity, acetylation-mediated binding, and p300 catalytic activity did not resolve it. (LLM, conf=0.73)

    Experimental — accuracy not yet measured

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  1. [1]Hardison RC Taylor J Genomic approaches towards finding cis-regulatory modules in animals Nat Rev Genet 2012 13 469 83 10.1038/nrg3242 22705667 PMC3541939 · DOI
  2. [2]Janky R van Helden J Evaluation of phylogenetic footprint discovery for predicting bacterial cis-regulatory elements and revealing their evolution BMC Bioinf 2008 9 37 10.1186/1471-2105-9-37 PMC2248561 18215291 · DOI
  3. [3]Hardison RC Conserved noncoding sequences are reliable guides to regulatory elements Trends Genet 2000 16 369 72 10.1016/S0168-9525(00)02081-3 10973062 · DOI
  4. [4]Aparicio S Chapman J Stupka E Putnam N Chia JM Dehal P Whole-genome shotgun assembly and analysis of the genome of Fugu rubripes Science 2002 297 1301 10 10.1126/science.1072104 12142439 · DOI · Paper page
  5. [5]Pennacchio LA Ahituv N Moses AM Prabhakar S Nobrega MA Shoukry M In vivo enhancer analysis of human conserved non-coding sequences Nature 2006 444 499 502 10.1038/nature05295 17086198 · DOI · Paper page
  6. [6]Woolfe A Goodson M Goode DK Snell P McEwen GK Vavouri T Highly conserved non-coding sequences are associated with vertebrate development PLoS Biol 2005 3 e7 10.1371/journal.pbio.0030007 15630479 PMC526512 · DOI · Paper page
  7. [7]Visel A Blow MJ Li Z Zhang T Akiyama JA Holt A ChIP-seq accurately predicts tissue-specific activity of enhancers Nature 2009 457 854 8 10.1038/nature07730 19212405 PMC2745234 · DOI · Paper page
  8. [8]Blow MJ McCulley DJ Li Z Zhang T Akiyama JA Holt A ChIP-seq identification of weakly conserved heart enhancers Nat Genet 2010 42 806 10 10.1038/ng.650 20729851 PMC3138496 · DOI
  9. [9]Schmidt D Wilson MD Ballester B Schwalie PC Brown GD Marshall A Five-vertebrate ChIP-seq reveals the evolutionary dynamics of transcription factor binding Science 2010 328 1036 40 10.1126/science.1186176 20378774 PMC3008766 · DOI · Paper page
  10. [10]Mouse ENCODE Consortium A comparative encyclopedia of DNA elements in the mouse genome Nature 2014 515 355 64 10.1038/nature13992 25409824 PMC4266106 · DOI · Paper page
  11. [11]Taylor J Tyekucheva S King DC Hardison RC Miller W Chiaromonte F ESPERR: learning strong and weak signals in genomic sequence alignments to identify functional elements Genome Res 2006 16 1596 604 10.1101/gr.4537706 17053093 PMC1665643 · DOI
  12. [12]Wang H Zhang Y Cheng Y Zhou Y King DC Taylor J Experimental validation of predicted mammalian erythroid cis-regulatory modules Genome Res 2006 16 1480 92 10.1101/gr.5353806 17038566 PMC1665632 · DOI
  13. [13]Göttgens B Ferreira R Sanchez MJ Ishibashi S Li J Spensberger D cis-regulatory remodeling of the SCL locus during vertebrate evolution Mol Cel Biol 2010 30 5741 51 10.1128/MCB.00870-10 PMC3004278 20956563 · DOI
  14. [14]Attanasio C Reymond A Humbert R Lyle R Kuehn MS Neph S Assaying the regulatory potential of mammalian conserved non-coding sequences in human cells Genome Biol 2008 9 R168 10.1186/gb-2008-9-12-r168 19055709 PMC2646272 · DOI
  15. [15]Maniatis T Goodbourn S Fischer JA Regulation of inducible and tissue-specific gene expression Science 1987 236 1237 45 10.1126/science.3296191 3296191 · DOI
  16. [16]Vo N Goodman RH CREB-binding protein and p300 in transcriptional regulation J Biol Chem 2001 276 13505 8 10.1074/jbc.R000025200 11279224 · DOI
  17. [17]He HH Meyer CA Shin H Bailey ST Wei G Wang Q Nucleosome dynamics define transcriptional enhancers Nat Genet 2010 42 343 7 10.1038/ng.545 20208536 PMC2932437 · DOI
  18. [18]Zentner GE Tesar PJ Scacheri PC Epigenetic signatures distinguish multiple classes of enhancers with distinct cellular functions Genome Res 2011 21 1273 83 10.1101/gr.122382.111 21632746 PMC3149494 · DOI · Paper page
  19. [19]Hoffman MM Ernst J Wilder SP Kundaje A Harris RS Libbrecht M Integrative annotation of chromatin elements from encode data Nucleic Acids Res 2013 41 827 41 10.1093/nar/gks1284 23221638 PMC3553955 · DOI
  20. [22]Creyghton MP Cheng AW Welstead GG Kooistra T Carey BW Steine EJ Histone H3K27ac separates active from poised enhancers and predicts developmental state Proc Natl Acad Sci 2010 107 21931 6 10.1073/pnas.1016071107 21106759 PMC3003124 · DOI · Paper page
  21. [23]Gorkin DU Lee D Reed X Fletez-Brant C Bessling SL Loftus SK Integration of ChIP-seq and machine learning reveals enhancers and a predictive regulatory sequence vocabulary in melanocytes Genome Res 2012 22 2290 301 10.1101/gr.139360.112 23019145 PMC3483558 · DOI
  22. [24]Cheng Y King DC Dore LC Zhang X Zhou Y Zhang Y Transcriptional enhancement by GATA1-occupied DNA segments is strongly associated with evolutionary constraint on the binding site motif Genome Res 2008 18 1896 905 10.1101/gr.083089.108 18818370 PMC2593580 · DOI
  23. [25]Cao Y Yao Z Sarkar D Lawrence M Sanchez GJ Parker MH Genome-wide MyoD binding in skeletal muscle cells: a potential for broad cellular reprogramming Dev Cell 2010 18 662 74 10.1016/j.devcel.2010.02.014 20412780 PMC2910615 · DOI
  24. [26]Ernst J Kellis M ChromHMM: automating chromatin-state discovery and characterization Nat Methods 2012 9 215 6 10.1038/nmeth.1906 22373907 PMC3577932 · DOI
  25. [27]Kheradpour P Ernst J Melnikov A Rogov P Wang L Zhang X Systematic dissection of regulatory motifs in 2000 predicted human enhancers using a massively parallel reporter assay Genome Res 2013 23 800 11 10.1101/gr.144899.112 23512712 PMC3638136 · DOI · Paper page
  26. [28]Kwasnieski JC Fiore C Chaudhari HG Cohen BA High-throughput functional testing of ENCODE segmentation predictions Genome Res 2014 24 1595 602 10.1101/gr.173518.114 25035418 PMC4199366 · DOI · Paper page
  27. [29]Erwin GD Oksenberg N Truty RM Kostka D Murphy KK Ahituv N Integrating diverse datasets improves developmental enhancer prediction PLoS Comput Biol 2014 10 e1003677 10.1371/journal.pcbi.1003677 24967590 PMC4072507 · DOI
  28. [30]Porcher C Swat W Rockwell K Fujiwara Y Alt FW Orkin SH The T cell leukemia oncoprotein SCL/tal-1 is essential for developmental of all hematopoietic lineages Cell 1996 86 47 57 10.1016/S0092-8674(00)80076-8 8689686 · DOI
  29. [31]Schlaeger TM Mikkola HK Gekas C Helgadottir HB Orkin SH Tie2Cre-mediated gene ablation defines the stem-cell leukemia gene (SCL/tal1)-dependent window during hematopoietic stem-cell development Blood 2005 105 3871 4 10.1182/blood-2004-11-4467 15677556 · DOI
  30. [32]Wozniak RJ Keles S Lugus JJ Young KH Boyer ME Tran TM Molecular hallmarks of endogenous chromatin complexes containing master regulators of hematopoiesis Mol Cell Biol 2008 28 6681 94 10.1128/MCB.01061-08 18779319 PMC2573226 · DOI
  31. [33]Tripic T Deng W Cheng Y Zhang Y Vakoc CR Gregory GD SCL and associated proteins distinguish active from repressive GATA transcription factor complexes Blood 2009 113 2191 201 10.1182/blood-2008-07-169417 19011221 PMC2652367 · DOI
  32. [34]Cheng Y Wu W Kumar SA Yu D Deng W Tripic T Erythroid GATA1 function revealed by genome-wide analysis of transcription factor occupancy, histone modifications, and mRNA expression Genome Res 2009 19 2172 84 10.1101/gr.098921.109 19887574 PMC2792182 · DOI · Paper page
  33. [37]Wu W Morrissey CS Keller CA Mishra T Pimkin M Blobel GA Dynamic shifts in occupancy by TAL1 are guided by GATA factors and drive large-scale reprogramming of gene expression during hematopoiesis Genome Res 2014 24 1945 62 10.1101/gr.164830.113 25319994 PMC4248312 · DOI
  34. [38]Trompouki E Bowman TV Lawton LN Fan ZP Wu DC DiBiase A Lineage regulators direct BMP and Wnt pathways to cell-specific programs during differentiation and regeneration Cell 2011 147 577 89 10.1016/j.cell.2011.09.044 22036566 PMC3219441 · DOI
  35. [39]Weiss MJ Yu C Orkin SH Erythroid-cell-specific properties of transcription factor GATA-1 revealed by phenotypic rescue of a gene-targeted cell line Mol Cell Biol 1997 17 1642 51 9032291 PMC231889
  36. [40]Gregory T Yu C Ma A Orkin SH Blobel GA Weiss MJ GATA-1 and erythropoietin cooperate to promote erythroid cell survival by regulating bcl-xL expression Blood 1999 94 87 96 10381501
  37. [41]Zhang Y Wu W Cheng Y King DC Harris RS Taylor J Primary sequence and epigenetic determinants of in vivo occupancy of genomic DNA by GATA1 Nucleic Acids Res 2009 37 7024 38 10.1093/nar/gkp747 19767611 PMC2790884 · DOI
  38. [42]Arvey A Agius P Noble WS Leslie C Sequence and chromatin determinants of cell-type-specific transcription factor binding Genome Res 2012 22 1723 34 10.1101/gr.127712.111 22955984 PMC3431489 · DOI
  39. [44]Morrissey CS. Understanding the epigenetics of erythroid differentiation through the power of deep sequencing. PhD thesis. The Pennsylvania State University, Bioinformatics and Genomics; 2013. 66–98.
  40. [45]Stonestrom AJ, Hsu SC, Jahn KS, Huang P, Kadauke S, Campbell AE, et al. Function of BET proteins in GATA1-mediated transcriptional activation. Blood. 2015. doi: http://dx.doi.org/10.1182/blood-2014-10-607309. PMC4424630 25696920 · DOI
  41. [46]Cheng Y Ma Z Kim B-H Wu W Cayting P Boyle AP Principles of regulatory information conservation between mouse and human Nature 2014 515 371 75 10.1038/nature13985 25409826 PMC4343047 · DOI
  42. [47]The ENCODE Project Consortium Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project Nature 2007 447 799 816 10.1038/nature05874 17571346 PMC2212820 · DOI · Paper page
  43. [48]Benz EJ Jr Murnane MJ Tonkonow BL Berman BW Mazur EM Cavallesco C Embryonic-fetal erythroid characteristics of a human leukemic cell line Proc Natl Acad Sci 1980 77 3509 13 10.1073/pnas.77.6.3509 6932034 PMC349646 · DOI
  44. [49]Elnitski L Li J Noguchi CT Miller W Hardison R A negative cis-element regulates the level of enhancement by hypersensitive site 2 of the beta-globin locus control region J Biol Chem 2001 276 6289 98 10.1074/jbc.M009624200 11092897 · DOI
  45. [50]Reeves R Gorman CM Howard B Minichromosome assembly of non-integrated plasmid DNA transfected into mammalian cells Nucleic Acids Res 1985 13 3599 615 10.1093/nar/13.10.3599 3859838 PMC341261 · DOI
  46. [51]ENCODE Project Consortium An integrated encyclopedia of DNA elements in the human genome Nature 2012 489 57 74 10.1038/nature11247 22955616 PMC3439153 · DOI · Paper page
  47. [52]Visel A Minovitsky S Dubchak I Pennacchio LA VISTA Enhancer Browser - a database of tissue-specific human enhancers Nucleic Acids Res 2007 35 D88 92 10.1093/nar/gkl822 17130149 PMC1716724 · DOI · Paper page
  48. [54]Hsiung CC-S Morrissey CS Udugama M Frank CL Keller CA Baek S Genome accessibility is widely preserved and locally modulated during mitosis Genome Res 2015 25 213 25 10.1101/gr.180646.114 25373146 PMC4315295 · DOI
  49. [55]Smith AD Sumazin P Zhang MQ Identifying tissue-selective transcription factor binding sites in vertebrate promoters Proc Natl Acad Sci 2005 102 1560 5 10.1073/pnas.0406123102 15668401 PMC547828 · DOI
  50. [56]Mathelier A Zhao X Zhang AW Parcy F Worsley-Hunt R Arenillas DJ JASPAR 2014: an extensively expanded and updated open-access database of transcription factor binding profiles Nucleic Acids Res 2014 42 D142 7 10.1093/nar/gkt997 24194598 PMC3965086 · DOI
  51. [57]Newburger DE Bulyk ML UniPROBE: an online database of protein binding microarray data on protein-DNA interactions Nucleic Acids Res 2009 37 D77 82 10.1093/nar/gkn660 18842628 PMC2686578 · DOI
  52. [58]Gupta S Stamatoyannopoulos JA Bailey TL Noble WS Quantifying similarity between motifs Genome Biol 2007 8 R24 10.1186/gb-2007-8-2-r24 17324271 PMC1852410 · DOI · Paper page
  53. [59]Sánchez-Castillo M Ruau D Wilkinson AC Ng FSL Hannah R Diamanti E CODEX: a next-generation sequencing experiment database for the haematopoietic and embryonic stem cell communities Nucleic Acids Res 2014 43 D1117 23 10.1093/nar/gku895 25270877 PMC4384009 · DOI
  54. [60]Massagué J Seoane J Wotton D Smad transcription factors Genes Dev 2005 19 2783 810 10.1101/gad.1350705 16322555 · DOI
  55. [61]Seoane J Le HV Shen L Anderson SA Massagué J Integration of Smad and forkhead pathways in the control of neuroepithelial and glioblastoma cell proliferation Cell 2004 117 211 23 10.1016/S0092-8674(04)00298-3 15084259 · DOI
  56. [63]Xu J Shao Z Glass K Bauer DE Pinello L Van Handel B Combinatorial assembly of developmental stage-specific enhancers controls gene expression programs during human erythropoiesis Dev Cell 2012 23 796 811 10.1016/j.devcel.2012.09.003 23041383 PMC3477283 · DOI
  57. [64]Palii CG Perez-Iratxeta C Yao Z Cao Y Dai F Davison J Differential genomic targeting of the transcription factor TAL1 in alternate haematopoietic lineages EMBO J 2011 30 494 509 10.1038/emboj.2010.342 21179004 PMC3034015 · DOI
  58. [65]Ng SL Friedman BA Schmid S Gertz J Myers RM Tenoever BR IĸB kinase epsilon (IKK(epsilon)) regulates the balance between type I and type II interferon responses Proc Natl Acad Sci U S A 2011 108 21170 5 10.1073/pnas.1119137109 22171011 PMC3248534 · DOI
  59. [66]Vahedi G Takahashi H Nakayamada S Sun HW Sartorelli V Kanno Y STATs shape the active enhancer landscape of T cell populations Cell 2012 151 981 93 10.1016/j.cell.2012.09.044 23178119 PMC3509201 · DOI
  60. [67]Stone EL Pepper M Katayama CD Kerdiles YM Lai C-Y Emslie E ICOS coreceptor signaling inactivates the transcription factor FOXO1 to promote Tfh cell differentiation Immunity 2015 42 239 51 10.1016/j.immuni.2015.01.017 25692700 PMC4334393 · DOI
  61. [68]Mullen AC Orlando DA Newman JJ Lovén J Kumar RM Bilodeau S Master transcription factors determine cell-type-specific responses to TGF-β signaling Cell 2011 147 565 76 10.1016/j.cell.2011.08.050 22036565 PMC3212730 · DOI
  62. [69]Ester M Kriegel H-P Sander J Xu X Simoudis E Han J Fayyad U A density-based algorithm for discovering clusters in large spatial databases with noise International conference on Knowledge Discovery and Data Mining (KDD-96) 1996 2 Palo Alto AAAI Press 226 31
  63. [71]Pollard KS Hubisz MJ Rosenbloom KR Siepel A Detection of non-neutral substitution rates on mammalian phylogenies Genome Res 2010 20 110 21 10.1101/gr.097857.109 19858363 PMC2798823 · DOI · Paper page
  64. [72]Kassouf MT Hughes JR Taylor S McGowan SJ Soneji S Green AL Genome-wide identification of TAL1’s functional targets: insights into its mechanisms of action in primary erythroid cells Genome Res 2010 20 1064 83 10.1101/gr.104935.110 20566737 PMC2909570 · DOI
  65. [73]Wang H Zang C Taing L Arnett KL Wong YJ Pear WS NOTCH1-RBPJ complexes drive target gene expression through dynamic interactions with superenhancers Proc Natl Acad Sci U S A 2014 111 705 10 10.1073/pnas.1315023111 24374627 PMC3896193 · DOI · Paper page
  66. [74]Ney PA Sorrentino BP McDonagh KT Nienhuis AW Tandem AP-1-binding sites within the human beta-globin dominant control region function as an inducible enhancer in erythroid cells Genes Dev 1990 4 993 1006 10.1101/gad.4.6.993 2116990 · DOI
  67. [75]Caterina JJ Ryan TM Pawlik KM Palmiter RD Brinster RL Behringer RR Human β-globin locus control region: analysis of the 5′ DNase I hypersensitive site HS 2 in transgenic mice Proc Natl Acad Sci U S A 1991 88 1626 30 10.1073/pnas.88.5.1626 2000371 PMC51077 · DOI
  68. [76]Morikawa M Koinuma D Tsutsumi S Vasilaki E Kanki Y Heldin C-H ChIP-seq reveals cell type-specific binding patterns of BMP-specific Smads and a novel binding motif Nucleic Acids Res 2011 39 8712 27 10.1093/nar/gkr572 21764776 PMC3203580 · DOI
  69. [77]Massagué J Wotton D Transcriptional control by the TGF-β/Smad signaling system EMBO J 2000 19 1745 54 10.1093/emboj/19.8.1745 10775259 PMC302010 · DOI
  70. [78]Sun Y Nadal-Vicens M Misono S Lin MZ Zubiaga A Hua X Neurogenin promotes neurogenesis and inhibits glial differentiation by independent mechanisms Cell 2001 104 365 76 10.1016/S0092-8674(01)00224-0 11239394 · DOI
  71. [79]Wang J Zhuang J Iyer S Lin X Whitfield TW Greven MC Sequence features and chromatin structure around the genomic regions bound by 119 human transcription factors Genome Res 2012 22 1798 812 10.1101/gr.139105.112 22955990 PMC3431495 · DOI
  72. [80]Au-Yeung N Mandhana R Horvath CM Transcriptional regulation by STAT1 and STAT2 in the interferon JAK-STAT pathway JAK-STAT 2013 2 e23931 10.4161/jkst.23931 24069549 PMC3772101 · DOI
  73. [81]Richmond TD Chohan M Barber D Turning cells red: signal transduction mediated by erythropoietin Trends Cell Biol 2005 15 146 55 10.1016/j.tcb.2005.01.007 15752978 · DOI
  74. [82]Kirito K Nakajima K Watanabe T Uchida M Tanaka M Ozawaka K Identification of the human erythropoietin receptor region required for Stat1 and Stat3 activation Blood 2002 99 102 10 10.1182/blood.V99.1.102 11756159 · DOI
  75. [83]Kaestner KH The FoxA factors in organogenesis and differentiation Curr Opin Genet Dev 2010 20 527 32 10.1016/j.gde.2010.06.005 20591647 PMC2943037 · DOI
  76. [85]Marinkovic D Zhang X Yalcin S Luciano JP Brugnara C Huber T Foxo3 is required for the regulation of oxidative stress in erythropoiesis J Clin Invest 2007 117 2133 44 10.1172/JCI31807 17671650 PMC1934587 · DOI
  77. [86]Yang GH Wang F Yu J Wang XS Yuan JY Zhang JW MicroRNAs are involved in erythroid differentiation control J Biol Chem 2009 107 548 56 19350553
  78. [88]King DC Taylor J Zhang Y Cheng Y Lawson HA Martin J ENCODE groups for Transcriptional Regulation and Multispecies Sequence Analysis, Chiaromonte F, Miller W, Hardison RC. Finding cis-regulatory elements using comparative genomics: some lessons from ENCODE data Genome Res 2007 17 775 86 10.1101/gr.5592107 17567996 PMC1891337 · DOI
  79. [89]Denas O Sandstrom R Cheng Y Beal K Herrero J Hardison RC Genome-wide comparative analysis reveals human-mouse regulatory landscape and evolution BMC Genomics 2015 16 87 10.1186/s12864-015-1245-6 25765714 PMC4333152 · DOI
  80. [90]Melnikov A Murugan A Zhang X Tesileanu T Wang L Rogov P Systematic dissection and optimization of inducible enhancers in human cells using a massively parallel reporter assay Nat Biotechnol 2012 30 271 7 10.1038/nbt.2137 22371084 PMC3297981 · DOI · Paper page
  81. [91]White MA Myers CA Corbo JC Cohen BA Massively parallel in vivo enhancer assay reveals that highly local features determine the cis-regulatory function of ChIP-seq peaks Proc Natl Acad Sci U S A 2013 110 11952 7 10.1073/pnas.1307449110 23818646 PMC3718143 · DOI
  82. [92]Smith RP Taher L Patwardhan RP Kim MJ Inoue F Shendure J Massively parallel decoding of mammalian regulatory sequences supports a flexible organizational model Nat Genet 2013 45 1021 8 10.1038/ng.2713 23892608 PMC3775494 · DOI · Paper page
  83. [94]Murtha M Tokcaer-Keskin Z Tang Z Strino F Chen X Wang Y FIREWACh: high-throughput functional detection of transcriptional regulatory modules in mammalian cells Nat Methods 2014 11 559 65 10.1038/nmeth.2885 24658142 PMC4020622 · DOI
  84. [95]Dickel DE Zhu Y Nord AS Wylie JN Akiyama JA Afzal V Function-based identification of mammalian enhancers using site-specific integration Nat Methods 2014 11 566 71 10.1038/nmeth.2886 24658141 PMC4008384 · DOI
  85. [96]Huang S Brandt SJ mSin3A regulates murine erythroleukemia cell differentiation through association with the TAL1 (or SCL) transcription factor Mol Cell Biol 2000 20 2248 59 10.1128/MCB.20.6.2248-2259.2000 10688671 PMC110841 · DOI
  86. [97]Wu C Orozco C Boyer J Leglise M Goodale J Batalov S BioGPS: an extensible and customizable portal for querying and organizing gene annotation resources Genome Biol 2009 10 R130 10.1186/gb-2009-10-11-r130 19919682 PMC3091323 · DOI
  87. [99]Baron MH Isern J Fraser ST The embryonic origins of erythropoiesis in mammals Blood 2012 119 4828 37 10.1182/blood-2012-01-153486 22337720 PMC3367890 · DOI · Paper page
  88. [100]Achim K Peltopuro P Lahti L Tsai H-H Zachariah A Åstrand M The role of Tal2 and Tal1 in the differentiation of midbrain GABAergic neuron precursors Open Biol J 2013 2 990 7 10.1242/bio.20135041 PMC3798194 24167708 · DOI
  89. [101]Dzierzak E Speck NA Of lineage and legacy - the development of mammalian hematopoietic stem cells Nat Immunol 2008 9 129 36 10.1038/ni1560 18204427 PMC2696344 · DOI · Paper page
  90. [102]Masino AM Gallardo TD Wilcox CA Olson EN Williams RS Garry DJ Transcriptional regulation of cardiac progenitor cell populations Circ Res 2004 95 389 97 10.1161/01.RES.0000138302.02691.be 15242968 · DOI
  91. [103]Nakano H Liu X Arshi A Nakashima Y van Handel B Sasidharan R Haemogenic endocardium contributes to transient definitive hematopoiesis Nat Commun 2013 4 1564 10.1038/ncomms2569 23463007 PMC3612528 · DOI
  92. [104]Org T Duan D Ferrari R Montel-Hagen A Handel BV Kerényi MA Scl binds to primed enhancers in mesoderm to regulate hematopoietic and cardiac fate divergence EMBO J 2015 34 759 77 10.15252/embj.201490542 25564442 PMC4369313 · DOI
  93. [105]Ng CE Yokomizo T Yamashita N Cirovic B Jin H Wen Z A Runx1 intronic enhancer marks hemogenic endothelial cells and hematopoietic stem cells Stem Cells 2010 28 1869 81 10.1002/stem.507 20799333 · DOI
  94. [106]Nord AS Blow MJ Attanasio C Akiyama JA Holt A Hosseini R Rapid and pervasive changes in genome-wide enhancer usage during mammalian development Cell 2013 155 1521 31 10.1016/j.cell.2013.11.033 24360275 PMC3989111 · DOI · Paper page
  95. [107]MacQueen JB Le Cam LM Neyman J Some methods for classification and analysis of multivariate observations Proceedings of 5th Symposium on Mathematical Statistics and Probability 1967 1 Berkeley University of California Press 281 97
  96. [108]King DC. Phylogenetic conservation of cis-regulatory regions using sequence alignability and cladistic motifs. PhD thesis. The Pennsylvania State University, Integrative Biosciences; 2009. p. 40–59.
  97. [109]Kent WJ Sugnet CW Furey TS Roskin KM Pringle TH Zahler AM The human genome browser at UCSC Genome Res 2002 12 996 1006 10.1101/gr.229102.ArticlepublishedonlinebeforeprintinMay2002 12045153 PMC186604 · DOI

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Authors
Dogan, N., Wu, W., Morrissey, C. S., Chen, K.-B., Stonestrom, A., Long, M., Keller, C. A., Cheng, Y., Jain, D., Visel, A., Pennacchio, L. A., Weiss, M. J., Blobel, G. A., & Hardison, R. C.
Affiliations
  • Pennsylvania State University (US)
  • Children's Hospital of Philadelphia (US)
  • Stanford University (US)
  • Lawrence Berkeley National Laboratory (US)
  • St. Jude Children's Research Hospital (US)
Corresponding author
Hardison, Ross C
Venue
Epigenetics & Chromatin
Published
2015-04-23
Volume
8
Issue
1
Pages
16-16
ISSN
1756-8935 (ISSN-L)
OpenAlex
W1988760117
Cited by
114
References
12
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FWCI
6.81
Type
journal article
Language
en
Open access
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  • Epigenetics & Chromatin (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion, other-oa)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
Funders
  • National Science Foundation (0821527)
  • University of Pennsylvania
  • Pennsylvania State University (OCI-0821527)
  • National Institutes of Health (R01DK58044)
  • National Heart, Lung, and Blood Institute (U01HL099656)
  • National Human Genome Research Institute (RC2HG005573, U54HG006998, R01HG003988)
  • National Institute of Diabetes and Digestive and Kidney Diseases (R37DK058044, P30DK090969, R01DK065806, R56DK065806, R01DK058044, R01DK054937)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
Keywords
enhancer prediction, transcription factor occupancy, TAL1, GATA-1, Smad1, EP300, histone modifications, H3K4me1, H3K27ac, chromatin accessibility, DNase I hypersensitive sites, hematopoietic transcription factors, enhancer activity

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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