Quantification of Differential Transcription Factor Activity and Multiomics-Based Classification into Activators and Repressors: diffTF
Open accessPublished version of a preprint
Abstract
Transcription factor (TF) activity is an important read-out of cellular signalling pathways and thus to assess regulatory differences across conditions. However, current technologies lack the ability to simultaneously assess activity changes for multiple TFs and in particular to determine whether a specific TF acts globally as transcriptional repressor or activator. To this end, we introduce a widely applicable genome-wide method diffTF to assess differential TF activity and to classify TFs as activator or repressor (available at https://git.embl.de/grp-zaugg/diffTF ). This is done by integrating any type of genome-wide chromatin accessibility data with RNA-Seq data and in-silico predicted TF binding sites. We corroborated the classification of TFs into repressors and activators by three independent analyses based on enrichments of active/repressive chromatin states, correlation of TF activity with gene expression, and activator-and repressor-specific chromatin footprints. To show the power of diffTF , we present two case studies: First, we applied diffTF in to a large ATAC-Seq/RNA-Seq dataset comparing mutated and unmutated chronic lymphocytic leukemia samples, where we identified dozens of known (40%) and potentially novel (60%) TFs that are differentially active. We were also able to classify almost half of them as either repressor and activator. Second, we applied diffTF to a small ATAC-Seq/RNA-Seq data set comparing two cell types along the hematopoietic differentiation trajectory (multipotent progenitors – MPP – versus granulocyte-macrophage progenitors – GMP). Here we identified the known drivers of differentiation and found that the majority of the differentially active TFs are transcriptional activators. Overall, diffTF was able to recover the known TFs in both case studies, additionally identified TFs that have been less well characterized in the given condition, and provides a classification of the TFs into transcriptional activators and repressors.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
TF footprinting suggests that direct repressor binding may occur within nucleosome-occupied regions, while activator binding is strongly associated with nucleosome depletion.
“TF footprinting suggests that direct repressor binding may occur within nucleosome-occupied regions, while activator binding is strongly associated with nucleosome depletion54.”
From Single-cell spatial multi-omics and deep learning dissect enhancer-driven gene regulatory networks in liver zonation (2024) · cites this paper as [54]
In “Determination of the molecular function of TFs: transcriptional repressors and activators” (page unavailable), the REST footprint shows accessibility at the binding motif but compact surrounding chromatin, whereas the STAT2 footprint shows increased accessibility around the binding site. This supports the repressor–activator contrast, but the paper does not establish that repressors bind within nucleosome-occupied regions or directly measure nucleosome depletion in this comparison. (LLM, conf=0.88)
Experimental — accuracy not yet measuredTF footprinting suggests that direct repressor binding may occur within nucleosome-occupied regions, while activator binding is strongly associated with nucleosome depletion.
“As a potential mechanism, how repressor binding could result in the absence of an ATAC peak, TF footprinting indeed suggests that direct repressor binding may occur within nucleosome-occupied regions, while activator binding is strongly associated with nucleosome depletion64.”
From Enhancer grammar of liver cell types and hepatocyte zonation states (2022) · cites this paper as [64]
In “Determination of the molecular function of TFs” (Fig. 4a; page not available), REST’s footprint shows locally increased accessibility with compact surrounding chromatin, whereas STAT2’s shows increased accessibility across the surrounding region. This supports the contrast between repressor and activator footprints, but the paper does not establish binding within nucleosome-occupied regions or directly measure nucleosome depletion. The figure caption also says the analyzed binding sites overlapped open chromatin. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works
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
Self-citationTrimmomatic: a flexible trimmer for Illumina sequence data
Bolger, A. M., Lohse, M., & Usadel, B. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu170 · Cited by 65,548 · see citing works
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041 · see citing works
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400 · see citing works
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709 · see citing works
limma powers differential expression analyses for RNA-sequencing and microarray studies
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv007 · Cited by 40,458 · see citing works
The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., et al. (2010) · Genome Research · doi:10.1101/gr.107524.110 · Cited by 27,895 · see citing works
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437 · see citing works
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386 · 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
MEME SUITE: tools for motif discovery and searching
Bailey, T. L., Boden, M., Buske, F. A., Frith, M., Grant, C. E., Clementi, L., Ren, J., Li, W. W., & Noble, W. S. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp335 · Cited by 10,648 · see citing works
MultiQC: summarize analysis results for multiple tools and samples in a single report
Ewels, P., Magnusson, M., Lundin, S., & Käller, M. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw354 · Cited by 10,143 · see citing works
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., & Greenleaf, W. J. (2013) · Nature Methods · doi:10.1038/nmeth.2688 · Cited by 6,422 · see citing works
Integrative analysis of 111 reference human epigenomes
Roadmap Epigenomics Consortium, Kundaje, A., Meuleman, W., Ernst, J., Bilenky, M., Yen, A., Heravi-Moussavi, A., Kheradpour, P., Zhang, Z., Wang, J., et al. (2015) · Nature · doi:10.1038/nature14248 · Cited by 6,368 · see citing works
GENCODE: The reference human genome annotation for The ENCODE Project
Harrow, J., Frankish, A., Gonzalez, J. M., Tapanari, E., Diekhans, M., Kokocinski, F., Aken, B. L., Barrell, D., Zadissa, A., Searle, S., et al. (2012) · Genome Research · doi:10.1101/gr.135350.111 · Cited by 4,585 · see citing works
ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization
Yu, G., Wang, L.-G., & He, Q. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv145 · Cited by 4,399 · see citing works
Master Transcription Factors and Mediator Establish Super-Enhancers at Key Cell Identity Genes
Whyte, W. A., Orlando, D. A., Hnisz, D., Abraham, B. J., Lin, C. Y., Kagey, M. H., Rahl, P. B., Lee, T. I., & Young, R. A. (2013) · Cell · doi:10.1016/j.cell.2013.03.035 · Cited by 4,143 · see citing works
deepTools: a flexible platform for exploring deep-sequencing data
Ramírez, F., Dündar, F., Diehl, S., Grüning, B. A., & Manke, T. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku365 · Cited by 3,738 · see citing works
Orchestrating high-throughput genomic analysis with Bioconductor
Huber, W. K., Carey, V. J., Gentleman, R. C., Anders, S., Carlson, M. R. J., Carvalho, B. S., Bravo, H. C., Davis, S. R., Gatto, L., Girke, T., et al. (2015) · Nature Methods · doi:10.1038/nmeth.3252 · Cited by 3,499 · see citing works
Self-citationThe Subread aligner: fast, accurate and scalable read mapping by seed-and-vote
Liao, Y., Smyth, G. K., & Shi, W. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt214 · Cited by 3,064 · see citing works
GENCODE reference annotation for the human and mouse genomes
Frankish, A., Diekhans, M., Ferreira, A.-M., Johnson, R., Jungreis, I., Loveland, J. E., Mudge, J. M., Sisu, C., Wright, J. C., Armstrong, J. C., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky955 · Cited by 2,929 · see citing works
Snakemake—a scalable bioinformatics workflow engine
Köster, J., & Rahmann, S. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts480 · Cited by 2,780 · see citing works
ChromHMM: automating chromatin-state discovery and characterization
Ernst, J., & Kellis, M. (2012) · Nature Methods · doi:10.1038/nmeth.1906 · Cited by 2,489 · see citing works
Komatsu, M., Kurokawa, H., Waguri, S., Taguchi, K., Kobayashi, A., Ichimura, Y., Sou, Y., Ueno, I., Sakamoto, A., Tong, K. I., et al. (2010) · Nature Cell Biology · doi:10.1038/ncb2021 · Cited by 2,422 · see citing works
Differential oestrogen receptor binding is associated with clinical outcome in breast cancer
Ross-Innes, C. S., Stark, R., Teschendorff, A. E., Holmes, K. A., Ali, H. R., Dunning, M., Brown, G. D., Gojiš, O., Ellis, I. O., Green, A. R., et al. (2012) · Nature · doi:10.1038/nature10730 · Cited by 2,182 · 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
TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions
Han, H., Cho, J.-W., Lee, S., Yun, A., Kim, H., Bae, D., Yang, S., Kim, C. Y., Lee, M., Kim, E., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1013 · Cited by 1,983 · see citing works
Idelalisib and Rituximab in Relapsed Chronic Lymphocytic Leukemia
Furman, R. R., Sharman, J. P., Coutre, S. E., Cheson, B. D., Pagel, J. M., Hillmen, P., Barrientos, J. C., Zelenetz, A. D., Kipps, T. J., Flinn, I. W., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1315226 · Cited by 1,711 · see citing works
chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data
Schep, A. N., Wu, B., Buenrostro, J. D., & Greenleaf, W. J. (2017) · Nature Methods · doi:10.1038/nmeth.4401 · Cited by 1,680 · see citing works
Bioconda: sustainable and comprehensive software distribution for the life sciences
Grüning, B., Dale, R., Sjödin, A., Chapman, B., Rowe, J., Tomkins-Tinch, C. H., Valieris, R., Caprez, A., Batut, B., Haudgaard, M., et al. (2018) · Nature Methods · doi:10.1038/s41592-018-0046-7 · Cited by 1,653 · see citing works
Differential Oestrogen Receptor Binding is Associated with Clinical Outcome in Breast Cancer
Stark, R. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-29627-7_30 · Cited by 1,403 · see citing works
Cancer immunoediting from immune surveillance to immune escape
Kim, R., Emi, M., & Tanabe, K. (2007) · Immunology · doi:10.1111/j.1365-2567.2007.02587.x · Cited by 1,078 · see citing works
Mutations driving CLL and their evolution in progression and relapse
Landau, D. A., Tausch, E., Taylor-Weiner, A. N., Stewart, C., Reiter, J. G., Bahlo, J., Kluth, S., Božić, I., Lawrence, M. S., Böttcher, S., et al. (2015) · Nature · doi:10.1038/nature15395 · Cited by 1,065 · see citing works
Mathelier, A., Fornes, O., Arenillas, D. J., Chen, C.-Y., Denay, G., Lee, J., Shi, W., Shyr, C., Tan, G., Worsley-Hunt, R., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1176 · Cited by 937 · see citing works
Summarizing and correcting the GC content bias in high-throughput sequencing
Benjamini, Y., & Speed, T. P. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks001 · Cited by 913 · see citing works
Clonal dynamics of native haematopoiesis
Sun, J., Ramos, A., Chapman, B., Johnnidis, J. B., Le, L., Ho, Y.-J., Klein, A. M., Hofmann, O., & Camargo, F. D. (2014) · Nature · doi:10.1038/nature13824 · Cited by 803 · see citing works
Chromatin state dynamics during blood formation
Lara-Astiaso, D., Weiner, A., Lorenzo-Vivas, E., Zaretsky, I., Jaitin, D. A., David, E., Keren-Shaul, H., Mildner, A., Winter, D., Jung, S., et al. (2014) · Science · doi:10.1126/science.1256271 · Cited by 776 · see citing works
Regulatory element detection using correlation with expression
Bussemaker, H. J., Li, H., & Siggia, E. D. (2001) · Nature Genetics · doi:10.1038/84792 · Cited by 721 · see citing works
Lun, A. T. L., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1191 · Cited by 510 · see citing works
TRRUST: a reference database of human transcriptional regulatory interactions
Han, H., Shim, H., Shin, D., Shim, J. E., Ko, Y., Shin, J., Kim, H., Cho, A., Kim, E., Lee, T., et al. (2015) · Scientific Reports · doi:10.1038/srep11432 · Cited by 462 · see citing works
The basic leucine zipper transcription factor E4BP4 is essential for natural killer cell development
Gascoyne, D. M., Long, E., Veiga‐Fernandes, H., de Boer, J., Williams, O., Seddon, B. P., Coles, M. C., Kioussis, D., & Brady, H. J. M. (2009) · Nature Immunology · doi:10.1038/ni.1787 · Cited by 446 · see citing works
Liu, Z., Lee, J., Krummey, S. M., Lü, W., Cai, H., & Lenardo, M. J. (2011) · Nature Immunology · doi:10.1038/ni.2113 · Cited by 361 · see citing works
Immune-mediated dormancy: an equilibrium with cancer
Teng, M. W. L., Swann, J. B., Koebel, C. M., Schreiber, R. D., & Smyth, M. J. (2008) · Journal of Leukocyte Biology · doi:10.1189/jlb.1107774 · Cited by 360 · see citing works
Genetic Control of Chromatin States in Humans Involves Local and Distal Chromosomal Interactions
Grubert, F., Zaugg, J. B., Kasowski, M., Ursu, O., Spacek, D. V., Martin, A. R., Greenside, P., Srivas, R., Phanstiel, D. H., Pekowska, A., et al. (2015) · Cell · doi:10.1016/j.cell.2015.07.048 · Cited by 319 · see citing works
Self-citationKikushige, Y., Ishikawa, F., Miyamoto, T., Shima, T., Urata, S., Yoshimoto, G., Mori, Y., Iino, T., Yamauchi, T., Eto, T., et al. (2011) · Cancer Cell · doi:10.1016/j.ccr.2011.06.029 · Cited by 317 · see citing works
Molecular genetics and cellular features of TFE3 and TFEB fusion kidney cancers
KAUFFMAN, E. C., Ricketts, C. J., Rais‐Bahrami, S., Yang, Y., Merino, M. J., Bottaro, D. P., Srinivasan, R., & Linehan, W. M. (2014) · Nature Reviews Urology · doi:10.1038/nrurol.2014.162 · Cited by 309 · see citing works
Oakes, C. C., Seifert, M., Assenov, Y., Gu, L., Przekopowitz, M., Ruppert, A. S., Wang, Q., Imbusch, C. D., Serva, A., Koser, S. D., et al. (2016) · Nature Genetics · doi:10.1038/ng.3488 · Cited by 302 · see citing works
Chiorazzi, N., & Ferrarini, M. (2010) · Blood · doi:10.1182/blood-2010-07-155663 · Cited by 264 · see citing works
Precrec: fast and accurate precision–recall and ROC curve calculations in R
Saito, T., & Rehmsmeier, M. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw570 · Cited by 262 · see citing works
The IRF family of transcription factors: Inception, impact and implications in oncogenesis
Yanai, H., Negishi, H., & Taniguchi, T. (2012) · OncoImmunology · doi:10.4161/onci.22475 · Cited by 261 · see citing works
RSAT 2015: Regulatory Sequence Analysis Tools
Medina-Rivera, A., Defrance, M., Sand, O., Herrmann, C., Castro-Mondragon, J. A., Delerce, J., Jaeger, S., Blanchet, C., Vincens, P., Caron, C., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv362 · Cited by 246 · see citing works
Minami, Y., Oishi, I., Endo, M., & Nishita, M. (2009) · Developmental Dynamics · doi:10.1002/dvdy.21991 · Cited by 240 · see citing works
HOCOMOCO: a comprehensive collection of human transcription factor binding sites models
Kulakovskiy, I. V., Medvedeva, Y. A., Schaefer, U., Kasianov, A. S., Vorontsov, I. E., Bajić, V. B., & Makeev, V. J. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1089 · Cited by 230 · see citing works
Bonhoure, N., Bounova, G., Bernasconi, D., Praz, V., Lammers, F., Canella, D., Willis, I. M., Herr, W., Hernandez, N., Delorenzi, M., et al. (2014) · Genome Research · doi:10.1101/gr.168260.113 · Cited by 155 · see citing works
High-throughput chromatin accessibility profiling at single-cell resolution
Mezger, A., Klemm, S. L., Mann, I. K., Brower, K. K., Mir, A. A., Bostick, M. L., Farmer, A. A., Fordyce, P. M., Linnarsson, S., & Greenleaf, W. J. (2018) · Nature Communications · doi:10.1038/s41467-018-05887-x · Cited by 149 · see citing works
Drug-perturbation-based stratification of blood cancer
Dietrich, S., Oleś, M., Lu, J., Sellner, L., Anders, S., Velten, B., Wu, B., Hüllein, J., Liberio, M. D. S., Walther, T., et al. (2017) · Journal of Clinical Investigation · doi:10.1172/jci93801 · Cited by 147 · see citing works
Self-citationPWMScan: a fast tool for scanning entire genomes with a position-specific weight matrix
Ambrosini, G., Groux, R., & Bücher, P. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty127 · Cited by 147 · see citing works
Rendeiro, A. F., Schmidl, C., Strefford, J. C., Walewska, R., Davis, Z., Farlik, M., Oscier, D., & Bock, C. (2016) · Nature Communications · doi:10.1038/ncomms11938 · Cited by 146 · see citing works
Lin28b promotes fetal B lymphopoiesis through the transcription factor Arid3a
Zhou, Y., Li, Y., Bandi, S. R., Tang, L., Shinton, S. A., Hayakawa, K., & Hardy, R. R. (2015) · The Journal of Experimental Medicine · doi:10.1084/jem.20141510 · Cited by 128 · see citing works
Castro-Mondragon, J. A., Jaeger, S., Thieffry, D., Thomas‐Chollier, M., & van Helden, J. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx314 · Cited by 126 · see citing works
Griffon, A., Barbier, Q., Dalino, J., van Helden, J., Spicuglia, S., & Ballester, B. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1280 · Cited by 123 · see citing works
Kreslavsky, T., Vilagos, B., Tagoh, H., Kostanova‐Poliakova, D., Schwickert, T. A., Wöhner, M., Jaritz, M., Weiß, S., Taneja, R., Rossner, M. J., et al. (2017) · Nature Immunology · doi:10.1038/ni.3694 · Cited by 119 · see citing works
Chevrier, S., Emslie, D., Shi, W., Kratina, T., Wellard, C. J., Karnowski, A., Erikçi, E., Smyth, G. K., Chowdhury, K., Tarlinton, D. M., et al. (2014) · The Journal of Experimental Medicine · doi:10.1084/jem.20131831 · Cited by 118 · see citing works
Drug-perturbation-based stratification of blood cancer
Dietrich, S., Oleś, M., Lu, J., Sellner, L., Anders, S., Velten, B., Wu, B., Hüllein, J., Libério, M. S., Walther, T., et al. (2017) · Kölner Universitäts PublikationsServer (Universität zu Köln) · doi:10.17863/cam.20903 · Cited by 111 · see citing works
Self-citationBivariate Genomic Footprinting Detects Changes in Transcription Factor Activity
Baek, S., Goldstein, I., & Hager, G. L. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.05.003 · Cited by 105 · see citing works
Modeling the relationship of epigenetic modifications to transcription factor binding
Liu, L., Jin, G., & Zhou, X.-B. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv255 · Cited by 97 · see citing works
TET2 binding to enhancers facilitates transcription factor recruitment in hematopoietic cells
Rasmussen, K. D., Berest, I., Keβler, S., Nishimura, K., Simón-Carrasco, L., Vassiliou, G. S., Pedersen, M. T., Christensen, J., Zaugg, J. B., & Helin, K. (2019) · Genome Research · doi:10.1101/gr.239277.118 · Cited by 95 · see citing works
Self-citationArvaniti, E., Ntoufa, S., Papakonstantinou, N., Touloumenidou, T., Laoutaris, N. P., Anagnostopoulos, Α., Lamnissou, K., Caligaris‐Cappio, F., Σταματόπουλος, Κ., Ghia, P., et al. (2011) · Haematologica · doi:10.3324/haematol.2011.044792 · Cited by 83 · see citing works
Yeomans, A., Thirdborough, S. M., Valle‐Argos, B., Linley, A. J., Krysov, S. V., Sánchéz‐Hidalgo, M., Leonard, E., Ishfaq, M., Wagner, S. D., Willis, A. E., et al. (2015) · Blood · doi:10.1182/blood-2015-07-660969 · Cited by 66 · see citing works
Coscia, M., Pantaleoni, F., Riganti, C., Vitale, C., Rigoni, M. M., Peola, S., Castella, B., Foglietta, M., Griggio, V., Drandi, D., et al. (2011) · Leukemia · doi:10.1038/leu.2011.12 · Cited by 61 · see citing works
Hedgehog/GLI and PI3K signaling in the initiation and maintenance of chronic lymphocytic leukemia
Kern, D., Regl, G., Hofbauer, S. W., Altenhofer, P., Achatz, G., Dlugosz, A. A., Schnidar, H., Greil, R., Hartmann, T. N., & Aberger, F. (2015) · Oncogene · doi:10.1038/onc.2014.450 · Cited by 60 · see citing works
IRF4 mutations in chronic lymphocytic leukemia
Havelange, V., Pekarsky, Y., Nakamura, T., Palamarchuk, A., Alder, H., Rassenti, L. Z., Kipps, T. J., & Croce, C. M. (2011) · Blood · doi:10.1182/blood-2011-04-350579 · Cited by 59 · see citing works
Worsley-Hunt, R., Mathelier, A., del Peso, L., & Wasserman, W. W. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-472 · Cited by 56 · see citing works
Role of CTLA4 in the Proliferation and Survival of Chronic Lymphocytic Leukemia
Mittal, A. K., Chaturvedi, N. K., Rohlfsen, R. A., Gupta, P., Joshi, A. D., Hegde, G. V., Bociek, R. G., & Joshi, S. S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0070352 · Cited by 50 · see citing works
B- myb is an essential regulator of hematopoietic stem cell and myeloid progenitor cell development
Baker, S. J., Ma’ayan, A., Lieu, Y. K., John, P., Reddy, M. V. R., Chen, E. Y., Duan, Q., Snoeck, H., & Reddy, E. P. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1315464111 · Cited by 50 · see citing works
Piper, J., Assi, S. A., Cauchy, P., Ladroue, C., Cockerill, P. N., Bonifer, C., & Ott, S. (2015) · BMC Genomics · doi:10.1186/s12864-015-2081-4 · Cited by 43 · see citing works
Yasuda, T., Hayakawa, F., Kurahashi, S., Sugimoto, K., Minami, Y., Tomita, A., & Naoe, T. (2012) · The Journal of Immunology · doi:10.4049/jimmunol.1103039 · Cited by 43 · see citing works
Heckman, C. A., Duan, H., Garcia, P. B., & Boxer, L. M. (2005) · Oncogene · doi:10.1038/sj.onc.1209127 · Cited by 41 · see citing works
Boorsma, A., Lu, X., Zakrzewska, A., Klis, F. M., & Bussemaker, H. J. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003112 · Cited by 38 · see citing works
Li, Y.-J., Sun, L., Shi, Y., Wang, G., Wang, X., Dunn, S. E., Iorio, C., Screaton, R. A., & Spaner, D. (2017) · Leukemia · doi:10.1038/leu.2016.395 · Cited by 32 · see citing works
Genetic Susceptibility to Chronic Lymphocytic Leukemia
Slager, S. L., Caporaso, N. E., de Sanjosé, S., & Goldin, L. R. (2013) · Seminars in Hematology · doi:10.1053/j.seminhematol.2013.09.007 · Cited by 32 · see citing works
Transcription factor Yin Yang 2 is a novel regulator of the p53/p21 axis
Kasim, V., Xie, Y., Wang, H., Huang, C., Yan, X., Nian, W., Zheng, X., Miyagishi, M., & Wu, S. (2017) · Oncotarget · doi:10.18632/oncotarget.18005 · Cited by 29 · see citing works
Targeting self-renewal pathways in myeloid malignancies
Sands, W. A., Copland, M., & Wheadon, H. (2013) · Cell Communication and Signaling · doi:10.1186/1478-811x-11-33 · Cited by 27 · see citing works
Escaping Circadian Regulation: An Emerging Hallmark of Cancer?
El‐Athman, R., & Relógio, A. (2018) · Cell Systems · doi:10.1016/j.cels.2018.03.006 · Cited by 27 · see citing works
D’Annibale, S., Kim, J., Magliozzi, R., Low, T. Y., Mohammed, S., Heck, A. J. R., & Guardavaccaro, D. (2014) · Journal of Biological Chemistry · doi:10.1074/jbc.m114.549535 · Cited by 26 · see citing works
Ghamlouch, H., Darwiche, W., Hodroge, A., Ouled‐Haddou, H., Dupont, S., Singh, A. R., Guignant, C., Trudel, S., Royer, B., Gubler, B., et al. (2015) · OncoTarget · doi:10.18632/oncotarget.3941 · Cited by 9 · see citing works
TET2 binding to enhancers facilitates transcription factor recruitment in hematopoietic cellsPreprint
Rasmussen, K. D., Berest, I., Kessler, S., Nishimura, K., Simón-Carrasco, L., Vassilou, G. S., Pedersen, M. T., Christensen, J. F., Zaugg, J. B., & Helin, K. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/336008 · Cited by 9 · see citing works
Self-citationTaking the Broad View on B Cell Affinity Maturation
Neu, K. E., & Wilson, P. C. (2016) · Immunity · doi:10.1016/j.immuni.2016.03.001 · Cited by 9 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Bentsen, M. S., Goymann, P., Schultheis, H., Klee, K., Petrova, A., Wiegandt, R., Fust, A., Preussner, J., Kuenne, C. T., Braun, T. W., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18035-1 · Cited by 649 · see citing works
Chromatin accessibility profiling by ATAC-seq
Grandi, F. C., Modi, H., Kampman, L., & Corces, M. R. (2022) · Nature Protocols · doi:10.1038/s41596-022-00692-9 · Cited by 557 · see citing works
From reads to insight: a hitchhiker’s guide to ATAC-seq data analysis
Yan, F., Powell, D., Curtis, D. J., & Wong, N. C. (2020) · Genome biology · doi:10.1186/s13059-020-1929-3 · Cited by 467 · see citing works
Transcription factors: Bridge between cell signaling and gene regulation
Weidemüller, P., Kholmatov, M. M., Petsalaki, E., & Zaugg, J. B. (2021) · PROTEOMICS · doi:10.1002/pmic.202000034 · Cited by 282 · see citing works
Self-citationChromatin accessibility profiling methods
Minnoye, L., Marinov, G. K., Krausgruber, T., Pan, L., Marand, A. P., Secchia, S., Greenleaf, W. J., Furlong, E. E. M., Zhao, K., Schmitz, R. J., et al. (2021) · Nature Reviews Methods Primers · doi:10.1038/s43586-020-00008-9 · Cited by 206 · see citing works
Brown, M. S., Abdollahi, B., Wilkins, O. M., Lu, H., Chakraborty, P., Ognjenovic, N. B., Muller, K. E., Jolly, M. K., Christensen, B. C., Hassanpour, S., et al. (2022) · Science Advances · doi:10.1126/sciadv.abj8002 · Cited by 153 · see citing works
Epigenetic regulation of innate immune memory in microglia
Zhang, X., Kracht, L., Lerário, A. M., Dubbelaar, M. L., Brouwer, N., Wesseling, E. M., Boddeke, E., Eggen, B. J. L., & Kooistra, S. M. (2022) · Journal of Neuroinflammation · doi:10.1186/s12974-022-02463-5 · Cited by 113 · see citing works
TET2 binding to enhancers facilitates transcription factor recruitment in hematopoietic cells
Rasmussen, K. D., Berest, I., Keβler, S., Nishimura, K., Simón-Carrasco, L., Vassiliou, G. S., Pedersen, M. T., Christensen, J., Zaugg, J. B., & Helin, K. (2019) · Genome Research · doi:10.1101/gr.239277.118 · Cited by 95 · see citing works
Self-citationBravo González-Blas, C., Matetovici, I., Hillen, H., Taskiran, I. I., Vandepoel, R., Christiaens, V., Sansores-García, L., Verboven, E., Hulselmans, G., Poovathingal, S., et al. (2024) · Nature Cell Biology · doi:10.1038/s41556-023-01316-4 · Cited by 85 · see citing works
Developmental and evolutionary dynamics of cis-regulatory elements in mouse cerebellar cells
Sarropoulos, I., Sepp, M., Frömel, R., Leiss, K., Trost, N., Leushkin, E. V., Okonechnikov, K., Joshi, P. K., Giere, P., Kutscher, L. M., et al. (2021) · Science · doi:10.1126/science.abg4696 · Cited by 77 · see citing works
Reyes‐Palomares, A., Gu, M., Grubert, F., Berest, I., Sa, S., Kasowski, M. M., Arnold, C., Mao, S., Srivas, R., Miao, S., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15463-x · Cited by 81 · see citing works
Self-citationHey, J., Paulsen, M., Tóth, R., Weichenhan, D., Butz, S., Schatterny, J., Liebers, R., Lutsik, P., Plass, C., & Mall, M. A. (2021) · Nature Communications · doi:10.1038/s41467-021-26777-9 · Cited by 77 · see citing works
Decoding gene regulation in the mouse embryo using single-cell multi-omicsPreprint
Argelaguet, R., Lohoff, T., Li, J., Nakhuda, A., Drage, D., Krueger, F., Velten, L., Clark, S. J., & Reik, W. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.15.496239 · Cited by 62 · see citing works
Rubin, J. D., Stanley, J. T., Sigauke, R. F., Levandowski, C. B., Maas, Z. L., Westfall, J., Taatjes, D. J., & Dowell, R. D. (2021) · Communications Biology · doi:10.1038/s42003-021-02153-7 · Cited by 63 · see citing works
GRaNIE and GRaNPA: inference and evaluation of enhancer‐mediated gene regulatory networks
Kamal, A., Arnold, C., Claringbould, A., Moussa, R., Servaas, N. H., Kholmatov, M. M., Daga, N., Nogina, D., Müller‐Dott, S., Reyes‐Palomares, A., et al. (2023) · Molecular Systems Biology · doi:10.15252/msb.202311627 · Cited by 63 · see citing works
Self-citationBibliometric review of ATAC-Seq and its application in gene expression
Luo, L.-H., Gribskov, M., & Wang, S. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac061 · Cited by 58 · see citing works
Enhancer–silencer transitions in the human genomePreprint
Huang, D., & Ovcharenko, I. (2022) · Genome Research · doi:10.1101/gr.275992.121 · Cited by 57 · see citing works
Pluripotency factors are repurposed to shape the epigenomic landscape of neural crest cells
Hovland, A. S., Bhattacharya, D., Azambujá, A. P., Pramio, D. T., Copeland, J., Rothstein, M., & Simões-Costa, M. (2022) · Developmental Cell · doi:10.1016/j.devcel.2022.09.006 · Cited by 56 · see citing works
Wang, Y., Liu, L., Song, Y., Yu, X., & Deng, H. (2022) · Protein & Cell · doi:10.1007/s13238-021-00894-z · Cited by 52 · see citing works
Liu, X., Rulina, A., Choi, M. H., Pedersen, L., Lepland, J., Takle, S. T., Madeleine, N., Peters, S. D., Wogsland, C. E., Grøndal, S. M., et al. (2022) · Nature Communications · doi:10.1038/s41467-021-27734-2 · Cited by 53 · see citing works
Cell-type-specific Hox regulatory strategies orchestrate tissue identity
Loker, R., Sanner, J. E., & Mann, R. S. (2021) · Current Biology · doi:10.1016/j.cub.2021.07.030 · Cited by 48 · see citing works
Constructing gene regulatory networks using epigenetic data
Sonawane, A. R., DeMeo, D. L., Quackenbush, J. F., & Glass, K. (2021) · npj Systems Biology and Applications · doi:10.1038/s41540-021-00208-3 · Cited by 40 · see citing works
Bunina, D., Abazova, N., Diaz, N. S., Noh, K., Krijgsveld, J., & Zaugg, J. (2020) · Cell Systems · doi:10.1016/j.cels.2020.05.003 · Cited by 40 · see citing works
Self-citationLoss of colonic fidelity enables multilineage plasticity and metastasis
Cammareri, P., Raponi, M., Hong, Y., Billard, C. V., Peckett, N., Zhu, Y., Velez-Bravo, F. D., Younger, N. T., Dunican, D. S., Pohl, S., et al. (2025) · Nature · doi:10.1038/s41586-025-09125-5 · Cited by 35 · see citing works
Ranking reprogramming factors for cell differentiation
Hammelman, J., Patel, T., Closser, M., Wichterle, H., & Gifford, D. K. (2022) · Nature Methods · doi:10.1038/s41592-022-01522-2 · Cited by 34 · see citing works
Álvarez, V., Bandau, S., Jiang, H., Rios-Szwed, D. O., Hukelmann, J. L., Garcia-Wilson, E., Wiechens, N., Griesser, E., ten Have, S., Owen‐Hughes, T., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.111996 · Cited by 27 · see citing works
Lobato-Moreno, S., Yildiz, U., Claringbould, A., Servaas, N. H., Vlachou, E. P., Arnold, C., Bauersachs, H. G., Campos-Fornés, V., Kim, M., Berest, I., et al. (2025) · Nature Methods · doi:10.1038/s41592-025-02700-8 · Cited by 34 · see citing works
Self-citationBasis of gene-specific transcription regulation by the Integrator complex
Sabath, K., Nabih, A., Arnold, C., Moussa, R., Domjan, D., Zaugg, J. B., & Jonas, S. (2024) · Molecular Cell · doi:10.1016/j.molcel.2024.05.027 · Cited by 29 · see citing works
Self-citationLu, Y., Peng, R., Dong, L., Xia, K., Wu, R., Xu, S., & Wang, J. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad378 · Cited by 26 · see citing works
Choi, W., Choe, M. S., Kim, S. M., Kim, S. J., Lee, J., Lee, Y., Lee, S.-M., Dho, S. H., Lee, M. Y., & Kim, L. K. (2024) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-024-05129-y · Cited by 26 · see citing works
ChIATAC is an efficient strategy for multi-omics mapping of 3D epigenomes from low-cell inputs
Chai, H.-X., Tjong, H., Li, P., Liao, W., Wang, P., Wong, C.-H., Ngan, C., Leonard, W., Wei, C.-L., & Ruan, Y. (2023) · Nature Communications · doi:10.1038/s41467-023-35879-5 · Cited by 23 · see citing works
Computational tools for inferring transcription factor activity
Hecker, D., Lauber, M., Ardakani, F. B., Ashrafiyan, S., Manz, Q., Kersting, J., Hoffmann, M., Schulz, M. H., & List, M. (2023) · PROTEOMICS · doi:10.1002/pmic.202200462 · Cited by 25 · see citing works
Türk, L., Filippov, I. V., Arnold, C., Zaugg, J. B., Tserel, L., Kisand, K. E., & Peterson, P. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1285798 · Cited by 25 · see citing works
Self-citationNair, V. D., Vasoya, M., Nair, V., Smith, G. R., Pinças, H., Ge, Y., Douglas, C. M., Esser, K. A., & Sealfon, S. C. (2021) · Genomics · doi:10.1016/j.ygeno.2021.09.013 · Cited by 25 · see citing works
Jauregui-Lozano, J. P. P., Hall, H., Stanhope, S. C., Bakhle, K. M., Marlin, M. N., & Weake, V. M. (2022) · PLoS Genetics · doi:10.1371/journal.pgen.1010021 · Cited by 25 · see citing works
Analytical Approaches for ATAC‐seq Data Analysis
Smith, J. P., & Sheffield, N. C. (2020) · Current Protocols in Human Genetics · doi:10.1002/cphg.101 · Cited by 22 · see citing works
SWI/SNF-type complexes–transcription factor interplay: a key regulatory interaction
Maassen, A., Steciuk, J., Wilga, M., Szurmak, J., Garbicz, D., Sarnowska, E. A., & Sarnowski, T. J. (2025) · Cellular & Molecular Biology Letters · doi:10.1186/s11658-025-00704-y · Cited by 23 · see citing works
He, L., Arnold, C., Thoma, J., Rohde, C., Kholmatov, M. M., Garg, S., Hsiao, C., Viol, L., Zhang, K., Sun, R., et al. (2022) · EMBO Molecular Medicine · doi:10.15252/emmm.202114990 · Cited by 20 · see citing works
Self-citationBakr, A., Hey, J., Sigismondo, G., Liu, C.-S., Sadik, A., Goyal, A., Cross, A., Iyer, R. L., Müller, P., Trauernicht, M., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab964 · Cited by 21 · see citing works
Mapping the regulatory landscape of auditory hair cells from single-cell multi-omics dataPreprint
Wang, S., Lee, M. P., Jones, S., Liu, J., & Waldhaus, J. (2021) · Genome Research · doi:10.1101/gr.271080.120 · Cited by 21 · see citing works
Valdes, P., Caldwell, A. B., Liu, Q., Fitzgerald, M. Q., Ramachandran, S., Karch, C. M. M., Dominantly Inherited Alzheimer Network (DIAN), Adams, S., Allegri, R., Araki, A., et al. (2025) · Alzheimer s Research & Therapy · doi:10.1186/s13195-024-01659-6 · Cited by 21 · see citing works
Trovato, M., Bunina, D., Yildiz, U., Marx, N. F.-N., Uckelmann, M., Levina, V., Perez, Y., Janeva, A., Garcia, B. A., Davidovich, C., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-51785-w · Cited by 19 · see citing works
Self-citationBagheri, M., Mohamed, G. A., Saleem, M. A. M., Ognjenovic, N. B., Lu, H., Kolling, F., Wilkins, O. M., Das, S., LaCroix, I. S., Nagaraj, S. H., et al. (2024) · Cell Reports Medicine · doi:10.1016/j.xcrm.2024.101504 · Cited by 19 · see citing works
p300 suppresses the transition of myelodysplastic syndromes to acute myeloid leukemia
Man, N., Martín, G. M., Karl, D. L., Sun, J., Liu, F., Yang, Q., Torres‐Martín, M., Itonaga, H., Martínez, C., Shi, C., et al. (2021) · JCI Insight · doi:10.1172/jci.insight.138478 · Cited by 19 · see citing works
Drug‐microenvironment perturbations reveal resistance mechanisms and prognostic subgroups in CLL
Bruch, P., Giles, H. A. R., Kolb, C., Herbst, S., Becirovic, T., Roider, T., Lu, J.-Y., Scheinost, S., Wagner, L., Huellein, J., et al. (2022) · Molecular Systems Biology · doi:10.15252/msb.202110855 · Cited by 13 · see citing works
Self-citationEmerging insights into enhancer biology and function
Arnold, M., & Stengel, K. R. (2023) · Transcription · doi:10.1080/21541264.2023.2222032 · Cited by 18 · see citing works
Lim, B., Kamal, A., Gomez Ramos, B., Adrian Segarra, J. M., Ibarra, I. L., Dignas, L., Kindinger, T., Volz, K., Rahbari, M., Rahbari, N., et al. (2025) · Nature Genetics · doi:10.1038/s41588-025-02081-w · Cited by 17 · see citing works
Self-citationShaban, H. A., Friman, E. T., Deluz, C., Tollenaere, A., Katanayeva, N., & Suter, D. M. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2311374121 · Cited by 16 · see citing works
Perspective on recent developments and challenges in regulatory and systems genomics
Zeitlinger, J., Roy, S., Ay, F., Mathelier, A., Medina-Rivera, A., Mahony, S., Sinha, S. K., & Ernst, J. (2024) · Bioinformatics Advances · doi:10.1093/bioadv/vbaf106 · Cited by 14 · see citing works
Chromatin Landscape Governing Murine Epidermal Differentiation
Nayak, S., Jiang, K., Hope, E., Cross, M., Overmiller, A. M., Naz, F., Worrell, S. D., Bajpai, D., Hasneen, K., Brooks, S. R., et al. (2023) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2022.12.020 · Cited by 13 · see citing works
Shevade, K., Yang, Y. A., Feng, K., Mader, K., Sevi̇m, V., Parsons, J., Arora, G., Elfawy, H. A., Mace, R., Federman, S., et al. (2025) · Cell Reports Methods · doi:10.1016/j.crmeth.2025.101222 · Cited by 15 · see citing works
Stem cell–like reprogramming is required for leukemia-initiating activity in B-ALL
Fregona, V., Bayet, M., Bouttier, M., Largeaud, L., Hamelle, C., Jamrog, L. A., Prade, N., Lagarde, S., Hébrard, S., Luquet, I., et al. (2023) · The Journal of Experimental Medicine · doi:10.1084/jem.20230279 · Cited by 12 · see citing works
Kamal, A., Arnold, C., Claringbould, A., Moussa, R., Servaas, N. H., Kholmatov, M., Daga, N., Nogina, D., Mueller-Dott, S., Reyes-Palomares, A., et al. (2021) · doi:10.1101/2021.12.18.473290 · Cited by 12 · see citing works
Self-citationDaga, N., Servaas, N. H., Kisand, K. E., Moonen, D. P. I., Arnold, C., Reyes‐Palomares, A., Kaleviste, E., Kingo, K., Kuuse, R., Ulst, K., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114810 · Cited by 11 · see citing works
Self-citationSecanechia, Y. N. S., Bergiers, I., Rogon, Z., Arnold, C., Descostes, N., Le, S., López-Anguita, N., Ganter, K., Kapsali, C., Bouilleau, L., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-20906-0 · Cited by 11 · see citing works
Self-citationOptimized reporters for multiplexed detection of transcription factor activity
Trauernicht, M., Filipovska, T., Rastogi, C., & van Steensel, B. (2024) · Cell Systems · doi:10.1016/j.cels.2024.11.003 · Cited by 10 · see citing works
Zhou, A., Xie, S., Feng, Y., Sun, D., Liu, S., Sun, Z., Li, M., Zhang, C., & Zou, J. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00830 · Cited by 10 · see citing works
Saelens, W., Pushkarev, O., & Deplancke, B. (2025) · Nature Communications · doi:10.1038/s41467-024-55447-9 · Cited by 9 · see citing works
On the identification of differentially-active transcription factors from ATAC-seq data
Gerbaldo, F. E., Sonder, E., Fischer, V., Frei, S., Wang, J., Gapp, K., Robinson, M. D., & Germain, P. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1011971 · Cited by 7 · see citing works
Kidani, Y., Kitagawa, Y., Hagiwara, M., Kawashima, A., Kanazawa, T., Wada, H., Uemura, M., Nonomura, N., Motooka, D., Nakamura, S., et al. (2024) · International Immunology · doi:10.1093/intimm/dxad053 · Cited by 6 · see citing works
Moscona, R., Janssen, S. M., Elchebly, M., Papadakis, A. I., Rubin, E., & Spatz, A. (2023) · Pigment Cell & Melanoma Research · doi:10.1111/pcmr.13089 · Cited by 6 · see citing works
TF-Prioritizer: a Java pipeline to prioritize condition-specific transcription factors
Hoffmann, M., Trummer, N., Schwartz, L., Jankowski, J., Lee, H., Willruth, L.-L., Lazareva, O., Yuan, K. Z., Baumgarten, N., Schmidt, F., et al. (2022) · GigaScience · doi:10.1093/gigascience/giad026 · Cited by 6 · see citing works
Enhancer-priming in ageing human bone marrow mesenchymal stromal cells contributes to immune traitsPreprint
Lai, M. C., Ruiz-Velasco, M., Arnold, C., Sigalova, O. M., Bunina, D., Berest, I., Ding, X., Hennrich, M. L., Poisa-Beiro, L., Claringbould, A., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.09.03.458728 · Cited by 6 · see citing works
Self-citationEnhancer grammar of liver cell types and hepatocyte zonation states
González-Blas, C. B., Matetovici, I., Hillen, H., Taskiran, I. I., Vandepoel, R., Christiaens, V., Sansores-García, L., Verboven, E., Hulselmans, G., Poovathingal, S., et al. (2022) · doi:10.1101/2022.12.08.519575 · Cited by 5 · see citing works
Machine-guided cell-fate engineering
Appleton, E., Tao, J., Liu, S., Glass, C. K., Fonseca, G. J., & Church, G. M. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.115726 · Cited by 5 · see citing works
Argonaute proteins regulate a specific network of genes through KLF4 in mouse embryonic stem cells
Müller, M., Schaefer, M., Fäh, T., Spies, D., Hermes, V., Ngondo, R. P., Peña‐Hernández, R., Santoro, R., & Ciaudo, C. (2022) · Stem Cell Reports · doi:10.1016/j.stemcr.2022.03.014 · Cited by 5 · see citing works
Ranking Reprogramming Factors for Directed DifferentiationPreprint
Hammelman, J., Patel, T., Closser, M., Wichterle, H., & Gifford, D. K. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.14.444080 · Cited by 5 · see citing works
SOX transcription factors direct TCF-independent WNT/beta-catenin transcriptionPreprint
Mukherjee, S., Luedeke, D. M., Brown, L., & Zorn, A. M. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.08.25.457694 · Cited by 5 · see citing works
Bagheri, M., Mohamed, G. A., Saleem, M. A. M., Saleem, M.-A. M., Ognjenovic, N. B., Lu, H., Kolling, F., Wilkins, O. M., Das, S., LaCroix, I. S., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.19.537586 · Cited by 5 · see citing works
Lobato-Moreno, S., Yildiz, U., Claringbould, A., Servaas, N. H., Vlachou, E. P., Arnold, C., Bauersachs, H. G., Campos-Fornés, V., Prummel, K. D., Noh, K., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.26.573253 · Cited by 5 · see citing works
Self-citationCharacterization of an eye field-like state during optic vesicle organoid development
Owen, L. J., Rainger, J. K., Bengani, H., Kilanowski, F. M., FitzPatrick, D. R., & Papanastasiou, A. S. (2023) · Development · doi:10.1242/dev.201432 · Cited by 4 · see citing works
Raposo, A. A. S. F., Rosmaninho, P., Silva, S. L., Paço, S., Brazão, M. E., Godinho‐Santos, A., Tokunaga-Mizoro, Y., Nunes‐Cabaço, H., Serra‐Caetano, A., Almeida, A. R. M., et al. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1458581 · Cited by 4 · see citing works
Alzubaidi, A., & Tepper, J. A. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-2095-3_15 · Cited by 4 · see citing works
Mechanistic basis of gene-specific transcription regulation by the Integrator complexPreprint
Sabath, K., Nabih, A., Arnold, C., Moussa, R., Domjan, D., Zaugg, J. B., & Jonas, S. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.24.576984 · Cited by 4 · see citing works
Self-citationChromatin accessibility regulates age-dependent nuclear mechanotransduction
Liao, Y., Yuan, L., Sornapudi, T. R., Land, M., Gupta, R., & Shivashankar, G. V. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2522217123 · Cited by 3 · see citing works
Natural Killer Cell–Mediated Cytotoxicity Shapes the Clonal Evolution of B-cell Leukemia
Buri, M. C., Shoeb, M. R., Bykov, A., Repiščák, P., Baik, H., Dupanovic, A., David, F. O., Kovačic, B., Hall‐Glenn, F., Dopa, S., et al. (2024) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-24-0189 · Cited by 3 · see citing works
Zibetti, C. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26125817 · Cited by 3 · see citing works
Liu, X.-Z., Rulina, A., Choi, M. H., Pedersen, L., Lepland, J., Takle, S. T., Madeleine, N., Peters, S. D., Wogsland, C. E., Grøndal, S. M., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.08.11.244509 · Cited by 3 · see citing works
Gene-regulatory programs that specify age-related differences during thymocyte development
Sankaran, D. G., Zhu, H., Maymí, V. I., Forlastro, I. M., Jiang, Y., Laniewski, N. G., Scheible, K. M., Rudd, B. D., & Grimson, A. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.115903 · Cited by 2 · see citing works
Sun, F., Zhao, Y., Do, J., Cheng, P., Li, E., Liu, Y., Shirazi, S. P., Sucre, J. M. S., Kalin, T. V., He, H., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-69525-7 · Cited by 2 · see citing works
Decoding Arabidopsis growth-defense trade-offs through ADR1-associated transcriptional networks
Hu, D., Wang, J., Lee, R. R. Q., Su, Z., Zhu, W., Kim, S.-T., & Chae, E. (2026) · Cell Reports · doi:10.1016/j.celrep.2026.117030 · Cited by 2 · see citing works
Mukund, K., Alva-Ornelas, J. A., Maddox, A. L., Murali, D., Veraksa, D., Saftics, A., Tomšič, J., Frankhouser, D. E., Razo, M., Jovanović‐Talisman, T., et al. (2024) · Cancers · doi:10.3390/cancers16030553 · Cited by 2 · see citing works
Bunina, D., Germain, P., Tobon, A., Marx, N. F.-N., Arnold, C., Ahern, A., Claringbould, A., Lai, M. C., Rangasamy, S., Narayanan, V., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.08.11.455900 · Cited by 1 · see citing works
Self-citationLi, C., Chen, S., Chen, Y., Bian, H., Hao, M., Wei, L., & Zhang, X. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.08.574757 · Cited by 2 · see citing works
PBRM1-dependent PBAF targeting is required for EMT and metastasis in breast cancer
Dhiman, A., Ayers, M. G., McCuiston, J. L., Shinde, A. B., Akhand, S. S., Jiao, G., Jauregui-Lozano, J. P. P., Hadisurya, M., Porter, E. G. P., Tao, W. A., et al. (2026) · Science Advances · doi:10.1126/sciadv.aed8038 · Cited by 1 · see citing works
Nothnagel, P. M. C., Meslin, P.-A., Wik, J. A., Dufour, D., Strøm, Y. E., Bjørås, M., Enserink, J., Skålhegg, B., Briand, N., Mathelier, A., et al. (2026) · Nucleic Acids Research · doi:10.1093/nar/gkag232
Trauernicht, M., Franceschini-Santos, V. H., Yücel, H., Filipovska, T., & van Steensel, B. (2026) · Molecular Systems Biology · doi:10.1038/s44320-026-00240-7 · Cited by 1 · see citing works
Best practices for the ATAC-seq assay and its data analysis
Liu, H., Li, R., Hu, K., Ou, J., Pak, M. L., Green, M. R., & Zhu, L. J. (2024) · Elsevier eBooks · doi:10.1016/b978-0-12-817218-6.00016-4 · Cited by 1 · see citing works
ATAC-seq and psychiatric disorders
Fullard, J. F., Bendl, J. M., & Roussos, P. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-823577-5.00036-2 · Cited by 1 · see citing works
Multiomics analysis reveals extensive epigenome remodeling during cortical developmentPreprint
Noack, F., Vangelisti, S., Carido, M., Chong, F., & Bonev, B. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.08.07.241828 · Cited by 1 · see citing works
Bruch, P., Giles, H. A. R., Kolb, C., Herbst, S. A., Becirovic, T., Roider, T., Lu, J., Scheinost, S., Wagner, L., Hüellein, J., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.07.23.453514 · Cited by 1 · see citing works
Self-citationSecanechia, Y. N. S., Bergiers, I., Rogon, Z., Arnold, C., Descostes, N., Le, S., López-Anguita, N., Ganter, K., Kapsali, C., Bouilleau, L., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.03.462906 · Cited by 1 · see citing works
Self-citationLargeaud, L., Fregona, V., Jamrog, L. A., Hamelle, C., Dufrechou, S., Prade, N., Sellam, E., Enfedaque, P., Bayet, M., Hebrard, S., et al. (2023) · bioRxiv · doi:10.1101/2023.08.07.551811 · Cited by 1 · see citing works
Daga, N., Servaas, N. H., Kisand, K. E., Moonen, D. P. I., Arnold, C., Reyes‐Palomares, A., Kaleviste, E., Kingo, K., Kuuse, R., Ulst, K., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.11.575022 · Cited by 1 · see citing works
Self-citationShevade, K., Yang, Y. A., Feng, K., Mader, K., Sevi̇m, V., Parsons, J., Arora, G., Elfawy, H. A., Mace, R., Federman, S., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.02.11.637716 · Cited by 1 · see citing works
Tse, J. K. Y., Liu, X., Eres, I. E., Yamawaki, T., Kanke, M., Killian, M. L., Amrute, J., Chaudhry, A., Sahoo, A., Liu, W., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.02.25.638325 · Cited by 1 · see citing works
β-catenin programs a tissue-specific epigenetic vulnerability in aggressive adrenocortical carcinomaPreprint
Mohan, D. R., Borges, K. S., Finco, I., LaPensee, C. R., Rege, J., Solon, A. L., Little, D. W., Else, T., Almeida, M. Q., Dang, D., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.07.02.497654
Transcription promotes the restoration of chromatin following DNA replicationPreprint
Bandau, S., Álvarez, V., Jiang, H., Graff, S., Sundaramoorthy, R., Toman, M., Owen‐Hughes, T., Sidoli, S., Lamond, A. I., & Alabert, C. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.19.537523
Mohan, D. R., Borges, K. S., Finco, I., LaPensee, C. R., Rege, J., Solon, A. L., Little, D. W., Else, T., Almeida, M. Q., Dang, D., et al. (2023) · doi:10.1158/0008-5472.23569577
- Authors
- Berest, I., Arnold, C., Reyes-Palomares, A., Palla, G., Rasmussen, K. D., Giles, H., Bruch, P.-M., Huber, W., Dietrich, S., Helin, K., & Zaugg, J. B.
- Affiliations
- Heidelberg University (DE)
- European Molecular Biology Laboratory (DE)
- University of Copenhagen (DK)
- University Hospital Heidelberg (DE)
- European Bioinformatics Institute (GB)
- Corresponding author
- Zaugg, Judith B.
- ORCID
- Venue
- Cell Reports
- Publisher
- Elsevier BV
- Published
- 2019-12
- Volume
- 29
- Issue
- 10
- Pages
- 3147-3159.e12
- ISSN
- 2211-1247 (ISSN-L)
- OpenAlex
- W2993816863
- Cited by
- 119
- References
- 89
- Citations by year
- 2026: 12 · 2025: 15 · 2024: 20 · 2023: 19 · 2022: 25 · 2021: 19 · 2020: 8 · 2019: 1
- FWCI
- 5.21
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Cell Reports (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Discovery Research Portal (University of Dundee) (publishedVersion, cc-by)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institutes of Health (P30 CA008748)
- Novo Nordisk Fonden (NNF17CC0027852)
- Fundación Ramón Areces
- Danmarks Frie Forskningsfond (8020-00044B)
- Sundhed og Sygdom, Det Frie Forskningsråd (FSS 1333-00120B)
- European Molecular Biology Laboratory
- European Research Council (294666_DNAMET)
- Bayer Foundation
- 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 › Bioinformatics and Genomic Networks
- Keywords
- transcription factor activity, transcriptional activator, transcriptional repressor, chromatin accessibility, transcription factor binding sites, RNA-seq, multi-omics integration, chronic lymphocytic leukemia, hematopoietic progenitor cells
- MeSH terms
- Binding Sites, Chromatin, Gene Expression Regulation, Hematopoietic Stem Cells, Humans, Protein Binding, Transcription Factors, Transcription, Genetic, Leukemia, Lymphocytic, Chronic, B-Cell, Transcriptional Activation, Genome
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 ›
Are you an author, or do you see a problem with this page? Request a review
