Active promoters give rise to false positive ‘Phantom Peaks’ in ChIP-seq experiments
Open accessAbstract
Chromatin immunoprecipitation (ChIP) is widely used to identify chromosomal binding sites. Chromatin proteins are cross-linked to their target sequences in living cells. The purified chromatin is sheared and the relevant protein is enriched by immunoprecipitation with specific antibodies. The co-purifying genomic DNA is then determined by massive parallel sequencing (ChIP-seq).We applied ChIP-seq to map the chromosomal binding sites for two ISWI-containing nucleosome remodeling factors, ACF and RSF, in Drosophila embryos. Employing several polyclonal and monoclonal antibodies directed against their signature subunits, ACF1 and RSF-1, robust profiles were obtained indicating that both remodelers co-occupied a large set of active promoters.Further validation included controls using chromatin of mutant embryos that do not express ACF1 or RSF-1. Surprisingly, the ChIP-seq profiles were unchanged, suggesting that they were not due to specific immunoprecipitation. Conservative analysis lists about 3000 chromosomal loci, mostly active promoters that are prone to non-specific enrichment in ChIP and appear as 'Phantom Peaks'. These peaks are not obtained with pre-immune serum and are not prominent in input chromatin.Mining the modENCODE ChIP-seq profiles identifies potential Phantom Peaks in many profiles of epigenetic regulators. These profiles and other ChIP-seq data featuring prominent Phantom Peaks must be validated with chromatin from cells in which the protein of interest has been depleted.
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It remains unknown what proportion of candidate enhancers identified solely by biochemical marks are technical false positives or have enhancer-like features but no meaningful impact on expression of cis-encoded genes.
“Although unquestionably useful, it remains unknown what proportion of candidate enhancers identified solely by biochemical marks are technical false positives130-132 or a product of having enhancer-like biochemical features but no meaningful impact on the expression of cis encoded genes133.”
From Towards a comprehensive catalogue of validated and target-linked human enhancers (2020) · cites this paper as [132]
The Discussion reports that some ChIP-seq enrichments may be false-positive Phantom Peaks and says it cannot determine which overlapping signals represent genuine binding. The cited paper does not assess candidate enhancers identified solely by biochemical marks or estimate what proportion of them are technical false positives. The separate claim about enhancer-like features without an effect on cis-gene expression is attached to citation 133, not this source. (LLM, conf=0.84)
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Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106 · see citing works
Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y. C., Laslo, P., Cheng, J. X., Murre, C., Singh, H., & Glass, C. K. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.05.004 · Cited by 13,382 · see citing works
Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration
Thorvaldsdottir, H., Robinson, J. T., & Mesirov, J. P. (2013) · Briefings in Bioinformatics · doi:10.1093/bib/bbs017 · Cited by 9,049 · see citing works
The biology of chromatin remodeling complexes.
Clapier, C. R., & Cairns, B. (2009) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.77.062706.153223 · Cited by 2,384 · see citing works
GMAP: A genomic mapping and alignment program for mRNA and EST sequences
Wu, T. D., & Watanabe, C. K. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti310 · Cited by 2,354 · see citing works
Intrinsically disordered protein
Dunker, A. K., Lawson, J. D., Brown, C. J., Williams, R. M., Romero, P., Oh, J. S., Oldfield, C. J., Campen, A. M., Ratliff, C. M., Hipps, K. W., et al. (2001) · Journal of Molecular Graphics and Modelling · doi:10.1016/s1093-3263(00)00138-8 · Cited by 2,272 · see citing works
ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia
Landt, S. G., Marinov, G. K., Kundaje, A., Kheradpour, P., Pauli, F., Batzoglou, S., Bernstein, B. E., Bickel, P., Brown, J. B., Cayting, P., et al. (2012) · Genome Research · doi:10.1101/gr.136184.111 · Cited by 2,033 · see citing works
Natively unfolded proteins: A point where biology waits for physics
Uversky, V. N. (2002) · Protein Science · doi:10.1110/ps.4210102 · Cited by 1,815 · see citing works
The CRAPome: a contaminant repository for affinity purification–mass spectrometry data
Mellacheruvu, D., Wright, Z., Couzens, A. L., Lambert, J.-P., St-Denis, N. A., Li, T., Miteva, Y. V., Hauri, S., Sardiu, M. E., Low, T. Y., et al. (2013) · Nature Methods · doi:10.1038/nmeth.2557 · Cited by 1,686 · see citing works
Intrinsically Disordered Proteins
Uversky, V. N. (2013) · Elsevier eBooks · doi:10.1016/b978-0-12-374984-0.01698-3 · Cited by 1,646 · see citing works
The developmental transcriptome of Drosophila melanogaster
Graveley, B. R., Brooks, A. N., Carlson, J. W., Duff, M. O., Landolin, J. M., Yang, L. C., Artieri, C. G., van Baren, M. J., Boley, N. P., Booth, B. W., et al. (2010) · Nature · doi:10.1038/nature09715 · Cited by 1,487 · see citing works
Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries
Aird, D., Ross, M. G., Chen, W.-S., Danielsson, M., Fennell, T., Russ, C., Jaffe, D. B., Nusbaum, C., & Gnirke, A. (2011) · Genome Biology · doi:10.1186/gb-2011-12-2-r18 · Cited by 1,174 · see citing works
ChIPpeakAnno: a Bioconductor package to annotate ChIP-seq and ChIP-chip data
Zhu, L., Gazin, C., Lawson, N., Pagès, H., Lin, S. M., Lapointe, D. S., & Green, M. R. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-237 · Cited by 1,144 · see citing works
Systematic Protein Location Mapping Reveals Five Principal Chromatin Types in Drosophila Cells
Filion, G. J. P., van Bemmel, J. G., Braunschweig, U., Talhout, W., Kind, J., Ward, L. D., Brugman, W., de Castro, I. J., Kerkhoven, R. M., Bussemaker, H. J., et al. (2010) · Cell · doi:10.1016/j.cell.2010.09.009 · Cited by 963 · see citing works
Design and analysis of ChIP-seq experiments for DNA-binding proteins
Kharchenko, P., Tolstorukov, M., & Park, P. J. (2008) · Nature Biotechnology · doi:10.1038/nbt.1508 · Cited by 950 · see citing works
ATP-dependent chromatin remodeling: genetics, genomics and mechanisms
Hargreaves, D. C., & Crabtree, G. R. (2011) · Cell Research · doi:10.1038/cr.2011.32 · Cited by 923 · see citing works
Comprehensive analysis of the chromatin landscape in Drosophila melanogaster
Kharchenko, P. V., Alekseyenko, A. A., Schwartz, Y. B., Minoda, A., Riddle, N. C., Ernst, J., Sabo, P. J., Larschan, E., Gorchakov, A. A., Gu, T., et al. (2010) · Nature · doi:10.1038/nature09725 · Cited by 853 · see citing works
A large genome center's improvements to the Illumina sequencing system
Quail, M. A., Kozarewa, I., Smith, F., Scally, A., Stephens, P. J., Durbin, R. M., Swerdlow, H., & Turner, D. (2008) · Nature Methods · doi:10.1038/nmeth.1270 · Cited by 732 · see citing works
Betulin Is a Potent Anti-Tumor Agent that Is Enhanced by Cholesterol
Mullauer, F. B., Kessler, J. H., & Medema, J. P. (2009) · PLoS ONE · doi:10.1371/journal.pone.0005361 · Cited by 688 · see citing works
Reproducibility: Standardize antibodies used in research
Bradbury, A., & Plückthun, A. (2015) · Nature · doi:10.1038/518027a · Cited by 647 · see citing works
ACF, an ISWI-Containing and ATP-Utilizing Chromatin Assembly and Remodeling Factor
Ito, T., Bulger, M., Pazin, M. J., Kobayashi, R., & Kadonaga, J. T. (1997) · Cell · doi:10.1016/s0092-8674(00)80321-9 · Cited by 633 · see citing works
Identification of in vivo DNA targets of chromatin proteins using tethered Dam methyltransferase
van Steensel, B., & Henikoff, S. (2000) · Nature Biotechnology · doi:10.1038/74487 · Cited by 629 · see citing works
Nicol, J. W., Helt, G. A., Blanchard, S. G., Raja, A. N., & Loraine, A. E. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp472 · Cited by 623 · see citing works
Phosphorylation-Regulated Binding of RNA Polymerase II to Fibrous Polymers of Low-Complexity Domains
Kwon, I., Kato, M., Xiang, S., Wu, L. C., Theodoropoulos, P., Mirzaei, H., Han, T. W., Xie, S., Corden, J. L., & McKnight, S. L. (2013) · Cell · doi:10.1016/j.cell.2013.10.033 · Cited by 541 · see citing works
A cis-regulatory map of the Drosophila genome
Negre, N. N., Brown, C. D., Ma, L., Bristow, C. A., Miller, S. W., Wagner, U., Kheradpour, P., Eaton, M. L., Loriaux, P. M., Sealfon, R. S. G., et al. (2011) · Nature · doi:10.1038/nature09990 · Cited by 500 · see citing works
The molten globule state of α‐lactalbumin
Kuwajima, K. (1996) · The FASEB Journal · doi:10.1096/fasebj.10.1.8566530 · Cited by 458 · see citing works
Chromatin remodelling at promoters suppresses antisense transcription
Whitehouse, I., Rando, O. J., Delrow, J., & Tsukiyama, T. (2007) · Nature · doi:10.1038/nature06391 · Cited by 456 · see citing works
Highly expressed loci are vulnerable to misleading ChIP localization of multiple unrelated proteins
Teytelman, L., Thurtle, D. M., Rine, J., & van Oudenaarden, A. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1316064110 · Cited by 389 · see citing works
Genome-wide copy number analysis of single cells
Baslan, T., Kendall, J., Rodgers, L., Cox, H., Riggs, M., Stepansky, A., Troge, J. E., Ravi, K., Esposito, D., Lakshmi, B. V., et al. (2012) · Nature Protocols · doi:10.1038/nprot.2012.039 · Cited by 373 · see citing works
Längst, G., Bonte, E. J., Corona, D. F. V., & Becker, P. B. (1999) · Cell · doi:10.1016/s0092-8674(00)80797-7 · Cited by 355 · see citing works
Self-citationIdentifying and mitigating bias in next-generation sequencing methods for chromatin biology
Meyer, C. A., & Liu, X. S. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3788 · Cited by 329 · see citing works
Genome-wide Nucleosome Specificity and Directionality of Chromatin Remodelers
Yen, K., Vinayachandran, V., Batta, K., Koerber, R. T., & Pugh, B. F. (2012) · Cell · doi:10.1016/j.cell.2012.04.036 · Cited by 327 · see citing works
Smolle, M., Venkatesh, S., Gogol, M., Li, H., Zhang, Y., Florens, L. A., Washburn, M. P., & Workman, J. L. (2012) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.2312 · Cited by 305 · see citing works
Nucleosome mobilization and positioning by ISWI-containing chromatin-remodeling factors
Längst, G., & Becker, P. B. (2001) · Journal of Cell Science · doi:10.1242/jcs.114.14.2561 · Cited by 201 · see citing works
Self-citationHigh-resolution mapping of transcription factor binding sites on native chromatin
Kasinathan, S., Orsi, G. A., Zentner, G. E., Ahmad, K., & Henikoff, S. (2013) · Nature Methods · doi:10.1038/nmeth.2766 · Cited by 183 · see citing works
The molten globule is a third thermodynamical state of protein molecules
Ptitsyn, O. B., & Uversky, V. N. (1994) · FEBS Letters · doi:10.1016/0014-5793(94)80231-9 · Cited by 178 · see citing works
Fyodorov, D. V., Blower, M. D., Karpen, G. H., & Kadonaga, J. T. (2004) · Genes & Development · doi:10.1101/gad.1139604 · Cited by 177 · see citing works
Locus-Specific Targeting to the X Chromosome Revealed by the RNA Interactome of CTCF
Kung, J. T., Kesner, B., An, J. Y., Ahn, J. Y., Cifuentes‐Rojas, C., Colognori, D., Jeon, Y., Szántó, A., Rosario, B. C. D., Pinter, S. F., et al. (2015) · Molecular Cell · doi:10.1016/j.molcel.2014.12.006 · Cited by 167 · see citing works
Systematic evaluation of factors influencing ChIP-seq fidelity
Chen, Y., Negre, N. N., Li, Q., Mieczkowska, J. O., Slattery, M. G., Liu, T., Zhang, Y., Kim, T.-K., He, H. H., Zieba, J. T., et al. (2012) · Nature Methods · doi:10.1038/nmeth.1985 · Cited by 164 · see citing works
Chromosome-wide gene-specific targeting of theDrosophiladosage compensation complexPreprint
Gilfillan, G. D., Straub, T., de Wit, E., Greil, F., Lamm, R., van Steensel, B., & Becker, P. B. (2006) · Genes & Development · doi:10.1101/gad.1399406 · Cited by 163 · see citing works
Self-citationOverlapping chromatin-remodeling systems collaborate genome wide at dynamic chromatin transitions
Morris, S. A., Baek, S., Sung, M., John, S., Wiench, M., Johnson, T. A., Schiltz, R. L., & Hager, G. L. (2013) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.2718 · Cited by 156 · see citing works
Widespread Misinterpretable ChIP-seq Bias in Yeast
Park, D., Lee, Y., Bhupindersingh, G., & Iyer, V. R. (2013) · PLoS ONE · doi:10.1371/journal.pone.0083506 · Cited by 144 · see citing works
Liang, J., Lacroix, L., Gamot, A., Cuddapah, S., Queillé, S., Lhoumaud, P., Lepetit, P., Martin, P. G. P., Vogelmann, J., Court, F., et al. (2014) · Molecular Cell · doi:10.1016/j.molcel.2013.12.029 · Cited by 113 · see citing works
Erdel, F., Schubert, T. E. O., Marth, C., Längst, G., & Rippe, K. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1003438107 · Cited by 104 · see citing works
Taliaferro, J. M., Aspden, J. L., Bradley, T., Marwha, D., Blanchette, M., & Rio, D. C. (2013) · Genes & Development · doi:10.1101/gad.210708.112 · Cited by 102 · see citing works
Torigoe, S. E., Urwin, D., Ishii, H., Smith, D. E., & Kadonaga, J. T. (2011) · Molecular Cell · doi:10.1016/j.molcel.2011.07.017 · Cited by 89 · see citing works
Straub, T., Zabel, A., Gilfillan, G. D., Feller, C., & Becker, P. B. (2012) · Genome Research · doi:10.1101/gr.146407.112 · Cited by 88 · see citing works
Self-citationMoshkin, Y. M., Chalkley, G. E., Kan, T. W., Reddy, B. A., Özgür, Z., van IJcken, W. F. J., Dekkers, D. H. W., Demmers, J., TRAVERS, A. A., & Verrijzer, C. P. (2011) · Molecular and Cellular Biology · doi:10.1128/mcb.06365-11 · Cited by 86 · see citing works
ISWI and CHD Chromatin Remodelers Bind Promoters but Act in Gene Bodies
Zentner, G. E., Tsukiyama, T., & Henikoff, S. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003317 · Cited by 86 · see citing works
ISWI and CHD chromatin remodelers bind to promoters but act in gene bodies
Zentner, G. E., Tsukiyama, T., & Henikoff, S. (2013) · Epigenetics & Chromatin · doi:10.1186/1756-8935-6-s1-o29 · Cited by 85 · see citing works
Pickrell, J. K., Gaffney, D. J., Gilad, Y., & Pritchard, J. K. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr354 · Cited by 82 · see citing works
ChIP on Chip: surprising results are often artifacts
Waldminghaus, T., & Skarstad, K. (2010) · BMC Genomics · doi:10.1186/1471-2164-11-414 · Cited by 72 · see citing works
Where Does Mediator Bind In Vivo?
Fan, X., & Struhl, K. (2009) · PLoS ONE · doi:10.1371/journal.pone.0005029 · Cited by 69 · see citing works
Two Distinct Mechanisms of Chromatin Interaction by the Isw2 Chromatin Remodeling Complex In Vivo
Fazzio, T. G., Gelbart, M. E., & Tsukiyama, T. (2005) · Molecular and Cellular Biology · doi:10.1128/mcb.25.21.9165-9174.2005 · Cited by 62 · see citing works
RSF Governs Silent Chromatin Formation via Histone H2Av Replacement
Hanai, K., Furuhashi, H., Yamamoto, T., Akasaka, K., & Hirose, S. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000011 · Cited by 62 · see citing works
An effective statistical evaluation of ChIPseq dataset similarity
Chikina, M. D., & Troyanskaya, O. G. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts009 · Cited by 60 · see citing works
A Network Model of the Molecular Organization of Chromatin in Drosophila
van Bemmel, J. G., Filion, G. J. P., Rosado, A., Talhout, W., de Haas, M., van Welsem, T., van Leeuwen, F., & van Steensel, B. (2013) · Molecular Cell · doi:10.1016/j.molcel.2013.01.040 · Cited by 58 · see citing works
Sala, A., Toto, M., Pinello, L., Gabriele, A., Benedetto, V. D., Ingrassia, A. M. R., Bosco, G. L., Gesù, V. D., Giancarlo, R., & Corona, D. F. V. (2011) · The EMBO Journal · doi:10.1038/emboj.2011.98 · Cited by 58 · see citing works
Calling Cards enable multiplexed identification of the genomic targets of DNA-binding proteinsPreprint
Wang, H., Mayhew, D. N., Chen, X., Johnston, M., & Mitra, R. D. (2011) · Genome Research · doi:10.1101/gr.114850.110 · Cited by 50 · see citing works
Erdel, F., & Rippe, K. (2011) · Nucleus · doi:10.4161/nucl.2.2.15209 · Cited by 46 · see citing works
Detection of bladder, breast and prostate cancer using serum and tissue miRNA profiling
Porter-Gill, P. A., Fu, Y., Kaushiva, A., Price, D. K., Dahut, W., Figg, W. D., & Prokunina‐Olsson, L. (2011) · Genome biology · doi:10.1186/gb-2011-12-s1-p18 · Cited by 31 · see citing works
Optimization of transcription factor binding map accuracy utilizing knockout-mouse models
Krebs, W., Schmidt, S. V., Goren, A., Nardo, D. D., Labzin, L. I., Bovier, A., Ulas, T., Theis, H., Kraut, M., Latz, E., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1078 · Cited by 27 · see citing works
Developmental role for ACF1-containing nucleosome remodellers in chromatin organisation
Chioda, M., Vengadasalam, S., Kremmer, E., Eberharter, A., & Becker, P. B. (2010) · Development · doi:10.1242/dev.048405 · Cited by 26 · see citing works
Self-citationSolution-based targeted genomic enrichment for precious DNA samples
Shearer, A. E., Hildebrand, M. S., & Smith, R. J. (2012) · BMC Biotechnology · doi:10.1186/1472-6750-12-20 · Cited by 20 · see citing works
Erdel, F., & Rippe, K. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1209579109 · Cited by 12 · see citing works
Flagged first, then by citations
Research works printed but not linked: 2
- [51]Kuwajima K. The molten state of a-lactalhunun FASEB J. 1996 10 102 109 8566530
- [60]Bradbury A. Plückthun A. Standarize antibodies Used in Research Nature 2015 518 27 29 25652980
Cited by
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Skene, P. J., & Henikoff, S. (2017) · eLife · doi:10.7554/elife.21856 · Cited by 1,737 · see citing works
Role of TET enzymes in DNA methylation, development, and cancer
Rasmussen, K. D., & Helin, K. (2016) · Genes & Development · doi:10.1101/gad.276568.115 · Cited by 1,040 · see citing works
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Ramírez, F., Bhardwaj, V., Arrigoni, L., Lam, K. C., Grüning, B. A., Villaveces, J. M., Habermann, B. H., Akhtar, A., & Manke, T. (2018) · Nature Communications · doi:10.1038/s41467-017-02525-w · Cited by 974 · see citing works
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Skene, P. J., Henikoff, J. G., & Henikoff, S. (2018) · Nature Protocols · doi:10.1038/nprot.2018.015 · Cited by 803 · see citing works
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Meers, M. P., Tenenbaum, D., & Henikoff, S. (2019) · Epigenetics & Chromatin · doi:10.1186/s13072-019-0287-4 · Cited by 556 · see citing works
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Meers, M. P., Bryson, T. D., Henikoff, J. G., & Henikoff, S. (2019) · eLife · doi:10.7554/elife.46314 · Cited by 474 · see citing works
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Gasperini, M., Tome, J. M., & Shendure, J. (2020) · Nature Reviews Genetics · doi:10.1038/s41576-019-0209-0 · Cited by 396 · see citing works
Predicting mRNA Abundance Directly from Genomic Sequence Using Deep Convolutional Neural Networks
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Hainer, S. J., Boskovic, A., McCannell, K. N., Rando, O. J., & Fazzio, T. (2019) · Cell · doi:10.1016/j.cell.2019.03.014 · Cited by 171 · see citing works
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Chang, C.-H., Chavan, A., Palladino, J., Wei, X., Martins, N. M. C., Santinello, B., Chen, C.-C., Erceg, J., Beliveau, B. J., Wu, C.-T., et al. (2019) · PLoS Biology · doi:10.1371/journal.pbio.3000241 · Cited by 154 · see citing works
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Shin, S.-I., Ham, S., Park, J., Seo, S. H., Lim, C. H., Jeon, H., Huh, J., & Roh, T. (2016) · DNA Research · doi:10.1093/dnares/dsw031 · Cited by 109 · see citing works
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Boija, A., Mahat, D. B., Zare, A., Holmqvist, P.-H., Philip, P., Meyers, D. J., Cole, P. A., Lis, J. T., Stenberg, P., & Mannervik, M. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.09.031 · Cited by 83 · see citing works
LIM domain–binding 1 maintains the terminally differentiated state of pancreatic &bgr; cells
Ediger, B. N., Lim, H., Juliana, C., Groff, D., Williams, L. T., Dominguez, G., Liu, J.-H., Taylor, B., Walp, E., Kameswaran, V., et al. (2017) · Journal of Clinical Investigation · doi:10.1172/jci88016 · Cited by 55 · see citing works
Genome-wide measurement of local nucleosome array regularity and spacing by nanopore sequencing
Baldi, S., Krebs, S., Blum, H., & Becker, P. B. (2018) · Nature Structural & Molecular Biology · doi:10.1038/s41594-018-0110-0 · Cited by 74 · see citing works
Self-citationIn vivo binding of PRDM9 reveals interactions with noncanonical genomic sitesPreprint
Grey, C., Clément, J. A. J., Buard, J., Leblanc, B., Gut, I. G., Gut, M. O., Duret, L., & de Massy, B. (2017) · Genome Research · doi:10.1101/gr.217240.116 · Cited by 74 · see citing works
Automated in situ chromatin profiling efficiently resolves cell types and gene regulatory programs
Janssens, D. H., Wu, S. J., Sarthy, J. F., Meers, M. P., Myers, C. H., Olson, J. M., Ahmad, K., & Henikoff, S. (2018) · Epigenetics & Chromatin · doi:10.1186/s13072-018-0243-8 · Cited by 73 · see citing works
Kwon, S. Y., Grisan, V., Jang, B., Herbert, J. M. J., & Badenhorst, P. W. (2016) · PLoS Genetics · doi:10.1371/journal.pgen.1005969 · Cited by 71 · see citing works
HOT or not: examining the basis of high-occupancy target regions
Wreczycka, K., Franke, V., Uyar, B., Wurmus, R., Bulut, S., Tursun, B., & Akalin, A. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz460 · Cited by 66 · see citing works
Genome-Scale Mapping of Escherichia coli σ54 Reveals Widespread, Conserved Intragenic Binding
Bonocora, R. P., Smith, C., Lapierre, P., & Wade, J. T. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005552 · Cited by 60 · see citing works
Cofactor squelching: Artifact or fact?
Schmidt, S. F., Larsen, B. D., Loft, A., & Mandrup, S. (2016) · BioEssays · doi:10.1002/bies.201600034 · Cited by 56 · see citing works
DamID as a versatile tool for understanding gene regulation
Aughey, G., Cheetham, S. W., & Southall, T. D. (2019) · Development · doi:10.1242/dev.173666 · Cited by 54 · see citing works
Mapping transcription factor occupancy using minimal numbers of cells in vitro and in vivoPreprint
Tosti, L., Ashmore, J., Tan, B. S. N., Carbone, B., Mistri, T. K., Wilson, V. A., Tomlinson, S. R., & Kaji, K. (2018) · Genome Research · doi:10.1101/gr.227124.117 · Cited by 54 · see citing works
NF-Y and SP transcription factors — New insights in a long-standing liaison
Suske, G. (2016) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2016.08.011 · Cited by 52 · see citing works
Shen, N., Zhao, J., Schipper, J. L., Zhang, Y., Bepler, T., Leehr, D., Bradley, J., Horton, J., Lapp, H., & Gordân, R. (2018) · Cell Systems · doi:10.1016/j.cels.2018.02.009 · Cited by 50 · see citing works
Transcriptional repression by FEZF2 restricts alternative identities of cortical projection neurons
Tsyporin, J., Tastad, D., Ma, X., Nehme, A., Finn, T. S., Huebner, L., Liu, G., Gallardo, D., Makhamreh, A. K., Roberts, J. M., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109269 · Cited by 50 · see citing works
Sasse, S. K., Gruca, M., Allen, M. A., Kadiyala, V., Song, T., Gally, F., Gupta, A., Pufall, M. A., Dowell, R. D., & Gerber, A. N. (2019) · Genome Research · doi:10.1101/gr.248187.119 · Cited by 44 · see citing works
Yus, E., Lloréns‐Rico, V., Martínez, S., Gallo, C., Eilers, H., Blötz, C., Stülke, J., Lluch‐Senar, M., & Serrano, L. G. (2019) · Cell Systems · doi:10.1016/j.cels.2019.07.001 · Cited by 48 · see citing works
Identification of plant transcription factor target sequences
Franco‐Zorrilla, J. M., & Solano, R. (2016) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2016.05.001 · Cited by 44 · see citing works
Valsecchi, C. I. K., Basilicata, M. F., Semplicio, G., Georgiev, P., Gutierrez, N. M., & Akhtar, A. (2018) · Nature Communications · doi:10.1038/s41467-018-05642-2 · Cited by 40 · see citing works
Kasinathan, B., Colmenares, S. U., McConnell, H., Young, J. M., Karpen, G. H., & Malik, H. S. (2020) · eLife · doi:10.7554/elife.63368 · Cited by 41 · see citing works
High-intensity UV laser ChIP-seq for the study of protein-DNA interactions in living cells
Steube, A., Schenk, T., Tretyakov, A. N., & Saluz, H. P. (2017) · Nature Communications · doi:10.1038/s41467-017-01251-7 · Cited by 39 · see citing works
Feng, D., Chen, Y., Dai, R., Bian, S., Xue, W., Zhu, Y., Li, Z., Yang, Y., Zhang, Y., Zhang, J., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-33333-6 · Cited by 38 · see citing works
Gally, F., Sasse, S. K., Kurche, J. S., Gruca, M. A., Cardwell, J., Okamoto, T., Chu, H. W., Hou, X., Poirion, O., Buchanan, J., et al. (2020) · JCI Insight · doi:10.1172/jci.insight.144294 · Cited by 36 · see citing works
Regulation of the BMP Signaling-Responsive Transcriptional Network in the Drosophila Embryo
Deignan, L., Pinheiro, M. T., Sutcliffe, C., Saunders, A., Wilcockson, S. G., Zeef, L. A. H., Donaldson, I. J., & Ashe, H. L. (2016) · PLoS Genetics · doi:10.1371/journal.pgen.1006164 · Cited by 38 · see citing works
CHRAC/ACF contribute to the repressive ground state of chromatin
Scacchetti, A., Brueckner, L., Jain, D. S., Schauer, T., Zhang, X., Schnorrer, F., van Steensel, B., Straub, T., & Becker, P. B. (2018) · Life Science Alliance · doi:10.26508/lsa.201800024 · Cited by 35 · see citing works
Self-citationUnexpected conformational variations of the human centromeric chromatin complexPreprint
Thakur, J., & Henikoff, S. (2018) · Genes & Development · doi:10.1101/gad.307736.117 · Cited by 34 · see citing works
Central control of dynamic gene circuits governs T cell rest and activation
Arce, M. M., Umhoefer, J. M., Arang, N., Kasinathan, S., Freimer, J. W., Steinhart, Z., Shen, H., Pham, M. T. N., Ota, M., Wadhera, A., et al. (2024) · Nature · doi:10.1038/s41586-024-08314-y · Cited by 31 · see citing works
Past Roadblocks and New Opportunities in Transcription Factor Network Mapping
Brent, M. R. (2016) · Trends in Genetics · doi:10.1016/j.tig.2016.08.009 · Cited by 32 · see citing works
Binding of high mobility group A proteins to the mammalian genome occurs as a function of AT-content
Colombo, D., Burger, L., Baubec, T., & Schübeler, D. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1007102 · Cited by 32 · see citing works
Ramaker, R. C., Hardigan, A. A., Goh, S.-T., Partridge, E. C., Wold, B. J., Cooper, S. J., & Myers, R. (2020) · Genome Research · doi:10.1101/gr.260463.119 · Cited by 30 · see citing works
Gawky modulates MTF-1-mediated transcription activation and metal discrimination
Jia, R., Song, Z., Lin, J., Li, Z., Shan, G., & Huang, C. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab474 · Cited by 29 · see citing works
Establishment of H3K9me3-dependent heterochromatin during embryogenesis in Drosophila miranda
Wei, K. H.-C., Chan, C., & Bachtrog, D. (2021) · eLife · doi:10.7554/elife.55612 · Cited by 29 · see citing works
Putative Causal Variants Are Enriched in Annotated Functional Regions From Six Bovine Tissues
Prowse-Wilkins, C., Wang, J., Xiang, R., Garner, J. B., Goddard, M., & Chamberlain, A. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.664379 · Cited by 29 · see citing works
McGann, J. C., Spinner, M. A., Garg†, S. K., Müllendorff, K., Woltjer, R. L., & Mandel, G. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.2059-20.2021 · Cited by 27 · see citing works
Genome-wide studies reveal novel and distinct biological pathways regulated by SIN3 isoforms
Saha, N., Liu, M., Gajan, A., & Pile, L. A. (2016) · BMC Genomics · doi:10.1186/s12864-016-2428-5 · Cited by 27 · see citing works
Biswas, J., Rahman, R., Gupta, V., Rosbash, M., & Singer, R. H. (2020) · iScience · doi:10.1016/j.isci.2020.101318 · Cited by 27 · see citing works
A large-scale benchmark for network inference from single-cell perturbation data
Chevalley, M., Roohani, Y. H., Mehrjou, A., Leskovec, J., & Schwab, P. (2025) · Communications Biology · doi:10.1038/s42003-025-07764-y · Cited by 26 · see citing works
Lessons from eRNAs: understanding transcriptional regulation through the lens of nascent RNAs
Cardiello, J. F., Sanchez, G. J., Allen, M. A., & Dowell, R. D. (2019) · Transcription · doi:10.1080/21541264.2019.1704128 · Cited by 24 · see citing works
Dynamic enhancer function in the chromatin context
Goldstein, I., & Hager, G. L. (2018) · WIREs Systems Biology and Medicine · doi:10.1002/wsbm.1390 · Cited by 25 · see citing works
Assaying epigenome functions of PRMTs and their substrates
Rakow, S., Pullamsetti, S. S., Bauer, U., & Bouchard, C. (2019) · Methods · doi:10.1016/j.ymeth.2019.09.014 · Cited by 24 · see citing works
Genome-wide variability in recombination activity is associated with meiotic chromatin organizationPreprint
Jin, X., Fudenberg, G., & Pollard, K. (2021) · bioRxiv · doi:10.1101/gr.275358.121 · Cited by 16 · see citing works
What to do about those immunoprecipitation blues
Marx, V. (2019) · Nature Methods · doi:10.1038/s41592-019-0365-3 · Cited by 23 · see citing works
Implications of CpG islands on chromosomal architectures and modes of global gene regulation
Beck, S., Rhee, C., Song, J., Lee, B., LeBlanc, L., Cannon, L., & Kim, J. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky147 · Cited by 22 · see citing works
Chromatin reprogramming in breast cancer
Swinstead, E. E., Paakinaho, V., & Hager, G. L. (2018) · Endocrine Related Cancer · doi:10.1530/erc-18-0033 · Cited by 23 · see citing works
Differential cytokine sensitivities of STAT5-dependent enhancers rely onStat5autoregulation
Willi, M., Yoo, K. H., Wang, C., Trajanoski, Z., & Hennighausen, L. G. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw844 · Cited by 22 · see citing works
Enzymatic methods for genome-wide profiling of protein binding sites
Policastro, R. A., & Zentner, G. E. (2017) · Briefings in Functional Genomics · doi:10.1093/bfgp/elx030 · Cited by 22 · see citing works
DIVERSITY in binding, regulation, and evolution revealed from high-throughput ChIP
Mitra, S., Biswas, A., & Narlikar, L. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006090 · Cited by 19 · see citing works
To mock or not: a comprehensive comparison of mock IP and DNA input for ChIP-seq
Xu, J., Kudron, M. M., Victorsen, A., Gao, J., Ammouri, H., Navarro, F. C. P., Gevirtzman, L., Waterston, R., White, K. P., Reinke, V., et al. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa1155 · Cited by 19 · see citing works
Lee, H., Willi, M., Liu, C., & Hennighausen, L. G. (2023) · Nature Communications · doi:10.1038/s41467-023-40712-0 · Cited by 18 · see citing works
Retrieving Chromatin Patterns from Deep Sequencing Data Using Correlation Functions
Molitor, J., Mallm, J., Rippe, K., & Erdel, F. (2017) · Biophysical Journal · doi:10.1016/j.bpj.2017.01.001 · Cited by 17 · see citing works
Dissecting chromatin-mediated gene regulation and epigenetic memory through mathematical modelling
Ringrose, L., & Howard, M. (2017) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2017.02.003 · Cited by 17 · see citing works
CUT&RUN Profiling of the Budding Yeast Epigenome
Brahma, S., & Henikoff, S. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-2257-5_9 · Cited by 15 · see citing works
Zeng, X., Willi, M., Shin, H. Y., Hennighausen, L. G., & Wang, C. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.11.079 · Cited by 16 · see citing works
Genome-Scale Mapping Reveals Complex Regulatory Activities of RpoN in Yersinia pseudotuberculosis
Mahmud, A. K. M. F., Nilsson, K. L., Fahlgren, A., Navais, R., Choudhury, R., Avican, K., & Fällman, M. (2020) · mSystems · doi:10.1128/msystems.01006-20 · Cited by 16 · see citing works
normR: Regime enrichment calling for ChIP-seq dataPreprint
Helmuth, J., Li, N., Arrigoni, L., Gianmoena, K., Cadenas, C., Gasparoni, G., Sinha, A. N., Rosenstiel, P. C., Walter, J., Hengstler, J. G., et al. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/082263 · Cited by 15 · see citing works
Cell-type specific profiling of histone post-translational modifications in the adult mouse striatum
Carpenter, M. D., Fischer, D. K., Zhang, S., Bond, A. M., Czarnecki, K. S., Woolf, M. T., Song, H., & Heller, E. A. (2022) · Nature Communications · doi:10.1038/s41467-022-35384-1 · Cited by 14 · see citing works
A role for tuned levels of nucleosome remodeler subunit ACF1 during Drosophila oogenesis
Börner, K., Jain, D. S., Vázquez‐Pianzola, P., Vengadasalam, S., Steffen, N., Fyodorov, D. V., Tomančák, P., Konev, A. Y., Suter, B., & Becker, P. B. (2016) · Developmental Biology · doi:10.1016/j.ydbio.2016.01.039 · Cited by 14 · see citing works
Self-citationA Quantitative Proteomic Analysis of In Vitro Assembled Chromatin
Völker-Albert, M. C., Pusch, M. C., Fedisch, A., Schilcher, P., Schmidt, A., & Imhof, A. (2016) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m115.053553 · Cited by 14 · see citing works
ChIPulate: A comprehensive ChIP-seq simulation pipeline
Datta, V., Hannenhalli, S. S., & Siddharthan, R. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006921 · Cited by 13 · see citing works
Qi, Z., Smith, K. M., Bredeweg, E. L., Bosnjak, N., Freitag, M., & Nargang, F. E. (2017) · G3 Genes|Genomes|Genetics · doi:10.1534/g3.116.035402 · Cited by 12 · see citing works
Factors and Methods for the Detection of Gene Expression Regulation
Wang, M., Li, Q., & Liu, L. (2023) · Biomolecules · doi:10.3390/biom13020304 · Cited by 12 · see citing works
Catizone, A. N., Good, C. R., Alexander, K. A., Berger, S. L., & Sammons, M. A. (2019) · Cell Cycle · doi:10.1080/15384101.2019.1593643 · Cited by 12 · see citing works
Genome-wide Mapping of Protein-DNA Interactions with ChEC-seq in Saccharomyces cerevisiae
Grünberg, S., & Zentner, G. E. (2017) · Journal of Visualized Experiments · doi:10.3791/55836 · Cited by 10 · see citing works
Wei, Y., Luo, D., Xiong, X., Huang, Y., Xie, M., Lu, W., & Li, D. (2022) · Chemical Science · doi:10.1039/d2sc00188h · Cited by 9 · see citing works
Bai, H., Lin, M., Meng, Y., Bai, H., & Cai, S. (2022) · Cellular Signalling · doi:10.1016/j.cellsig.2022.110361 · Cited by 8 · see citing works
Anomaly detection in genomic catalogues using unsupervised multi-view autoencoders
Ferré, Q., Chèneby, J., Puthier, D., Capponi, C., & Ballester, B. (2021) · BMC Bioinformatics · doi:10.1186/s12859-021-04359-2 · Cited by 8 · see citing works
Ferraioli, S., Sarigol, F., Prakash, C., Filipczak, D., Foisner, R., & Naetar, N. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae752 · Cited by 7 · see citing works
Computational identification of cell-specific variable regions in ChIP-seq data
Andreani, T., Albrecht, S., Fontaine, J., & Andrade-Navarro, M. A. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa180 · Cited by 7 · see citing works
Conserved dual-mode gene regulation programs in higher eukaryotes
Lee, J.-Y., Song, J., LeBlanc, L., Davis, I., Kim, J., & Beck, S. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab108 · Cited by 7 · see citing works
Less-is-more: selecting transcription factor binding regions informative for motif inference
Xu, J., Gao, J., Ni, P., & Gerstein, M. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkad1240 · Cited by 7 · see citing works
Prediction of the transcription factor binding sites with meta-learning
Jing, F., Zhang, S., & Zhang, S. (2022) · Methods · doi:10.1016/j.ymeth.2022.04.010 · Cited by 7 · see citing works
Trizzino, M., Park, Y., Beltrame, M. H., Aracena, K. A., Mika, K. M., Çalışkan, M., Perry, G. H., Lynch, V. J., & Brown, C. D. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/083980 · Cited by 7 · see citing works
Improved CUT&RUN chromatin profiling and analysis toolsPreprint
Meers, M. P., Bryson, T. D., & Henikoff, S. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/569129 · Cited by 7 · see citing works
ISW1a modulates cohesin distribution in centromeric and pericentromeric regions
Litwin, I., Nowicka, M., Markowska, K., Maciaszczyk-Dziubińska, E., Tomaszewska, P., Wysocki, R., & Kramarz, K. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad612 · Cited by 6 · see citing works
Saleh, M. M., Tourigny, J. P., & Zentner, G. E. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1597-3_16 · Cited by 6 · see citing works
Building integrative functional maps of gene regulation
Xu, J., Pratt, H., Moore, J. E., Gerstein, M., & Weng, Z. (2022) · Human Molecular Genetics · doi:10.1093/hmg/ddac195 · Cited by 6 · see citing works
Mod(mdg4) variants repress telomeric retrotransposon HeT-A by blocking subtelomeric enhancers
Takeuchi, C., Yokoshi, M., Kondo, S., Shibuya, A., Saito, K., Fukaya, T., Siomi, H., & Iwasaki, Y. W. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac1034 · Cited by 6 · see citing works
Detecting and correcting the binding-affinity bias in ChIP-seq data using inter-species information
Nettling, M., Treutler, H., Cerquides, J., & Große, I. (2016) · BMC Genomics · doi:10.1186/s12864-016-2682-6 · Cited by 5 · see citing works
Sprang, M., Möllmann, J. S., Andrade-Navarro, M. A., & Fontaine, J. (2024) · Genome biology · doi:10.1186/s13059-024-03331-6 · Cited by 4 · see citing works
- Authors
- Jain, D., Baldi, S., Zabel, A., Straub, T., & Becker, P. B.
- Affiliations
- Center for Integrated Protein Science Munich (DE)
- Corresponding author
- Becker, Peter B.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-06-27
- Volume
- 43
- Issue
- 14
- Pages
- 6959-6968
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC4538825
- OpenAlex
- W1610193264
- Cited by
- 156
- References
- 65
- Citations by year
- 2026: 6 · 2025: 12 · 2024: 13 · 2023: 10 · 2022: 8 · 2021: 16 · 2020: 13 · 2019: 20 · 2018: 19 · 2017: 15 · 2016: 22 · 2015: 2
- FWCI
- 8.40
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nucleic Acids Research (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Open access LMU (Ludwid Maxmilian's Universitat Munchen) (submittedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Keywords
- ACF, Drosophila embryo, chromatin immunoprecipitation, modENCODE
- MeSH terms
- RNA Splicing Factors, Animals, Binding Sites, Drosophila, Promoter Regions, Genetic, Repressor Proteins, Transcription Factors, Artifacts, RNA-Binding Proteins, Sequence Analysis, DNA, Drosophila Proteins, Databases, Genetic, Chromatin Immunoprecipitation, Chromosomes, Insect, High-Throughput Nucleotide Sequencing
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