Employing core regulatory circuits to define cell identity
Open accessAbstract
The interplay between extrinsic signaling and downstream gene networks controls the establishment of cell identity during development and its maintenance in adult life. Advances in next-generation sequencing and single-cell technologies have revealed additional layers of complexity in cell identity. Here, we review our current understanding of transcription factor (TF) networks as key determinants of cell identity. We discuss the concept of the core regulatory circuit as a set of TFs and interacting factors that together define the gene expression profile of the cell. We propose the core regulatory circuit as a comprehensive conceptual framework for defining cellular identity and discuss its connections to cell function in different contexts.
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?
A limited set of identity transcription factors engaging in auto- and cross-regulatory loops typically defines the core transcriptional regulatory circuitry (CoRC).
“A limited set of identity TFs engaging into auto‐ and cross‐regulatory loops typically defines the core transcriptional regulatory circuitry (CoRC; Arendt et al, 2016; Almeida et al, 2021).”
From An extended transcription factor regulatory network controls hepatocyte identity (2023) · cites this paper as Almeida et al, 2021
The Introduction assigns the small set of transcription factors and their auto- and cross-regulatory loops to core regulatory circuitry (CRC). It defines CoRC separately as a core regulatory complex involving the physical cooperativity of terminal selectors. The citing sentence conflates these distinct terms. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredCell-specific transcription factors directly control the expression of non-transcription-factor genes that exert activities/functions characterizing individual cell types (identity effector genes).
“cell‐specific TFs directly control the expression of non‐TF genes exerting activities/functions characterizing individual cell‐types, alternatively known as identity effector genes (Arendt et al, 2016; Almeida et al, 2021).”
From An extended transcription factor regulatory network controls hepatocyte identity (2023) · cites this paper as Almeida et al, 2021
The moderate transcriptional changes most probably relate to the intrinsic role of identity transcription factor networks, which are built up to allow robustness of individual cell-type transcriptional programs.
“This most probably relates to the intrinsic role of identity TF networks, which are built‐up to allow robustness of individual cell‐type transcriptional programs (Kyrmizi et al, 2006; Almeida et al, 2021).”
From An extended transcription factor regulatory network controls hepatocyte identity (2023) · cites this paper as Almeida et al, 2021
Core transcriptional regulatory circuitries are considered cornerstones for establishment and maintenance of cell identities.
“CoRCs are considered cornerstones for establishment and maintenance of cell identities (Arendt et al, 2016; Almeida et al, 2021).”
From An extended transcription factor regulatory network controls hepatocyte identity (2023) · cites this paper as Almeida et al, 2021
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
Direct conversion of fibroblasts to functional neurons by defined factors
Vierbuchen, T., Ostermeier, A., Pang, Z. P., Kokubu, Y., Südhof, T. C., & Wernig, M. (2010) · Nature · doi:10.1038/nature08797 · Cited by 3,017 · see citing works
A unique chromatin signature uncovers early developmental enhancers in humans
Rada-Iglesias, A., Bajpai, R., Swigut, T., Brugmann, S. A., Flynn, R. A., & Wysocka, J. (2011) · Nature · doi:10.1038/nature09692 · Cited by 2,233 · see citing works
Regev, A., Teichmann, S. A., Lander, E. S., Amit, I., Benoist, C., Birney, E., Bodenmiller, B., Campbell, P., Carninci, P., Clatworthy, M., et al. (2017) · eLife · doi:10.7554/elife.27041 · Cited by 2,232 · see citing works
Self-citationInferring Regulatory Networks from Expression Data Using Tree-Based Methods
Huynh-Thu, V. A., Irrthum, A., Wehenkel, L., & Geurts, P. (2010) · PLoS ONE · doi:10.1371/journal.pone.0012776 · Cited by 2,131 · see citing works
Adult mouse cortical cell taxonomy revealed by single cell transcriptomics
Tasic, B., Menon, V., Nguyen, T. N., Kim, T. K., Jarsky, T., Yao, Z., Levi, B., Gray, L. T., Sorensen, S. A., Dolbeare, T., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4216 · Cited by 1,714 · see citing works
Pioneer transcription factors: establishing competence for gene expression
Zaret, K. S., & Carroll, J. S. (2011) · Genes & Development · doi:10.1101/gad.176826.111 · Cited by 1,589 · see citing works
Gene Regulatory Networks and the Evolution of Animal Body Plans
Davidson, E. H., & Erwin, D. H. (2006) · Science · doi:10.1126/science.1113832 · Cited by 1,207 · cited 2× · see citing works
“Adult mouse brain (Davidson & Erwin, 2006).”
Single-nucleus and single-cell transcriptomes compared in matched cortical cell types
Bakken, T. E., Hodge, R. D., Miller, J. A., Yao, Z., Nguyen, T. N., Aevermann, B., Barkan, E., Bertagnolli, D., Casper, T., Dee, N., et al. (2018) · PLoS ONE · doi:10.1371/journal.pone.0209648 · Cited by 608 · see citing works
Single-cell methylomes identify neuronal subtypes and regulatory elements in mammalian cortex
Luo, C., Keown, C. L., Kurihara, L., Zhou, J., He, Y., Li, J., Castanon, R., Lucero, J., Nery, J. R., Sandoval, J. P., et al. (2017) · Science · doi:10.1126/science.aan3351 · Cited by 545 · see citing works
The evolution of cell types in animals: emerging principles from molecular studies
Arendt, D. (2008) · Nature Reviews Genetics · doi:10.1038/nrg2416 · Cited by 525 · see citing works
Single-Cell Transcriptomics Meets Lineage Tracing
Kester, L., & van Oudenaarden, A. (2018) · Cell Stem Cell · doi:10.1016/j.stem.2018.04.014 · Cited by 375 · cited 3× · see citing works
“In developmental systems, the concept of cell state refers to cell fate transition along a particular developmental trajectory (Kester & van Oudenaarden, 2018).”
Preissl, S., Fang, R., Huang, H., Zhao, Y., Raviram, R., Gorkin, D. U., Zhang, Y., Sos, B. C., Afzal, V., Dickel, D. E., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0079-3 · Cited by 332 · see citing works
Role of H3K9me3 heterochromatin in cell identity establishment and maintenance
Nicetto, D., & Zaret, K. S. (2019) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2019.04.013 · Cited by 312 · see citing works
Kelley, K. W., Nakao-Inoue, H., Molofsky, A. V., & Oldham, M. C. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0216-z · Cited by 198 · see citing works
Reconstruction of Cell-type-Specific Interactomes at Single-Cell Resolution
Mohammadi, S., Davila-Velderrain, J., & Kellis, M. (2019) · Cell Systems · doi:10.1016/j.cels.2019.10.007 · Cited by 73 · see citing works
Flagged first, then by citations
Research works printed but not linked: 113
- Aibar S, González‐Blas CB, Moerman T, Huynh‐Thu VA, Imrichova H, Hulselmans G, Rambow F, Marine JC, Geurts P, Aerts J et al (2017) SCENIC: Single‐cell regulatory network inference and clustering. Nat Methods 14: 1083– 1086 28991892 PMC5937676
- Arda HE, Benitez CM, Kim SK (2013) Gene regulatory networks governing pancreas development. Dev Cell 25: 5– 13 23597482 PMC3645877
- Arendt D, Musser JM, Baker CVH, Bergman A, Cepko C, Erwin DH, Pavlicev M, Schlosser G, Widder S, Laubichler MD et al (2016) The origin and evolution of cell types. Nat Rev Genet 17: 744– 757 27818507
- Arlotta P, Paşca SP (2019) Cell diversity in the human cerebral cortex: from the embryo to brain organoids. Curr Opin Neurobiol 56: 194– 198 31051421
- Baranello L, Kouzine F, Sanford S, Levens D (2016) ChIP bias as a function of cross‐linking time. Chromosom Res 24: 175– 181 PMC4860130 26685864
- Baron M, Veres A, Wolock SL, Faust AL, Gaujoux R, Vetere A, Ryu JH, Wagner BK, Shen‐Orr SS, Klein AM et al (2016) A single‐cell transcriptomic map of the human and mouse pancreas reveals inter‐ and intra‐cell population structure. Cell Syst 3: 346– 360.e4 27667365 PMC5228327
- Basso K, Margolin AA, Stolovitzky G, Klein U, Dalla‐Favera R, Califano A (2005) Reverse engineering of regulatory networks in human B cells. Nat Genet 37: 382– 390 15778709
- Belton JM, McCord RP, Gibcus JH, Naumova N, Zhan Y, Dekker J (2012) Hi‐C: A comprehensive technique to capture the conformation of genomes. Methods 58: 268– 276 22652625 PMC3874846
- Best M, Carroll M, Hanley NA, Piper Hanley K (2008) Embryonic stem cells to beta‐cells by understanding pancreas development. Mol Cell Endocrinol 288: 86– 94 18487011
- Biddy BA, Kong W, Kamimoto K, Guo C, Waye SE, Sun T, Morris SA (2018) Single‐cell mapping of lineage and identity in direct reprogramming. Nature 564: 219– 224 30518857 PMC6635140
- Blau HM, Baltimore D (1991) Differentiation requires continuous regulation. J Cell Biol 112: 781– 783 1999456 PMC2288865
- Blau HM, Chiu CP, Webster C (1983) Cytoplasmic activation of human nuclear genes in stable heterocaryons. Cell 32: 1171– 1180 6839359
- Boyer LA, Tong IL, Cole MF, Johnstone SE, Levine SS, Zucker JP, Guenther MG, Kumar RM, Murray HL, Jenner RG et al (2005) Core transcriptional regulatory circuitry in human embryonic stem cells. Cell 122: 947– 956 16153702 PMC3006442
- Boyle AP, Davis S, Shulha HP, Meltzer P, Margulies EH, Weng Z, Furey TS, Crawford GE (2008) High‐resolution mapping and characterization of open chromatin across the genome. Cell 132: 311– 322 18243105 PMC2669738
- Bradner JE, Hnisz D, Young RA (2017) Transcriptional addiction in cancer. Cell 168: 629– 643 28187285 PMC5308559
- Bramswig NC, Kaestner KH (2014) Transcriptional and epigenetic regulation in human islets. Diabetologia 57: 451– 454 24362728 PMC3945729
- Buenrostro JD, Wu B, Chang HY, Greenleaf WJ (2015) ATAC‐seq: a method for assaying chromatin accessibility genome‐wide. Curr Protoc Mol Biol 109: 1– 10 PMC4374986 25559105
- Cahan P, Li H, Morris SA, Lummertz Da Rocha E, Daley GQ, Collins JJ (2014) Cell net: network biology applied to stem cell engineering. Cell 158: 903– 915 25126793 PMC4233680
- Chen M, Zhou X (2017) Controlling for confounding effects in single cell RNA sequencing studies using both control and target genes. Sci Rep 7: 1– 14 29051597 PMC5648789
- Clark SJ, Lee HJ, Smallwood SA, Kelsey G, Reik W (2016) Single‐cell epigenomics: powerful new methods for understanding gene regulation and cell identity. Genome Biol 17: 72 27091476 PMC4834828
- Coppola CJ, Ramaker RC, Mendenhall EM (2016) Identification and function of enhancers in the human genome. Hum Mol Genet 25: R190– R197 27402881
- Creyghton MP, Cheng AW, Welstead GG, Kooistra T, Carey BW, Steine EJ, Hanna J, Lodato MA, Frampton GM, Sharp PA et al (2010) Histone H3K27ac separates active from poised enhancers and predicts developmental state. Proc Natl Acad Sci USA 107: 21931– 21936 21106759 PMC3003124
- D’Alessio AC, Fan ZP, Wert KJ, Baranov P, Cohen MA, Saini JS, Cohick E, Charniga C, Dadon D, Hannett NM et al (2015) A systematic approach to identify candidate transcription factors that control cell identity. Stem Cell Rep 5: 763– 775 PMC4649293 26603904
- Davidson EH (2010) Emerging properties of animal gene regulatory networks. Nature 468: 911– 920 21164479 PMC3967874
- Davis RL, Weintraub H, Lassar AB (1987) Expression of a single transfected cDNA converts fibroblasts to myoblasts. Cell 51: 987– 1000 3690668
- Dekker J, Rippe K, Dekker M, Kleckner N (2002) Capturing chromosome conformation. Science 295: 1306– 1311 11847345
- Doitsidou M, Flames N, Topalidou I, Abe N, Felton T, Remesal L, Popovitchenko T, Mann R, Chalfie M, Hobert O (2013) A combinatorial regulatory signature controls terminal differentiation of the dopaminergic nervous system in C. elegans. Genes Dev 27: 1391– 1405 23788625 PMC3701194
- Dominguez‐Gutierrez G, Xin Y, Gromada J (2019) Heterogeneity of human pancreatic β‐cells. Mol Metab 27: S7– S14 PMC6768494 31500834
- Dunham I, Kundaje A, Aldred SF, Collins PJ, Davis CA, Doyle F, Epstein CB, Frietze S, Harrow J, Kaul R et al (2012) An integrated encyclopedia of DNA elements in the human genome. Nature 489: 57– 74 22955616 PMC3439153
- Ecker JR, Geschwind DH, Kriegstein AR, Ngai J, Osten P, Polioudakis D, Regev A, Sestan N, Wickersham IR, Zeng H (2017) The BRAIN initiative cell census consortium: lessons learned toward generating a comprehensive brain cell Atlas. Neuron 96: 542– 557 29096072 PMC5689454
- Etchberger JF, Lorch A, Sleumer MC, Zapf R, Jones SJ, Marra MA, Holt RA, Moerman DG, Hobert O (2007) The molecular signature and cis‐regulatory architecture of a C. elegans gustatory neuron. Genes Dev 21: 1653– 1674 17606643 PMC1899474
- Fernandes HJR, Patikas N, Foskolou S, Field SF, Park JE, Byrne ML, Bassett AR, Metzakopian E (2020) Single‐cell transcriptomics of Parkinson’s disease human in vitro models reveals dopamine neuron‐specific stress responses. Cell Rep 33: 108263 33053338
- Fishilevich S, Nudel R, Rappaport N, Hadar R, Plaschkes I, Iny Stein T, Rosen N, Kohn A, Twik M, Safran M et al (2017) GeneHancer: genome‐wide integration of enhancers and target genes in GeneCards. Database (Oxford) 2017: 1– 17 PMC5467550 28605766
- Fullard JF, Hauberg ME, Bendl J, Egervari G, Cirnaru MD, Reach SM, Motl J, Ehrlich ME, Hurd YL, Roussos P (2018) An atlas of chromatin accessibility in the adult human brain. Genome Res 28: 1243– 1252 29945882 PMC6071637
- Graf T, Enver T (2009) Forcing cells to change lineages. Nature 462: 587– 594 19956253
- Grebbin BM, Hau AC, Groß A, Anders‐Maurer M, Schramm J, Koss M, Wille C, Mittelbronn M, Selleri L, Schulte D (2016) PBX1 is required for adult subventricular zone neurogenesis. Dev. 143: 2281– 2291 PMC4958316 27226325
- Guenther MG, Levine SS, Boyer LA, Jaenisch R, Young RA (2007) A chromatin landmark and transcription initiation at most promoters in human cells. Cell 130: 77– 88 17632057 PMC3200295
- Hawrylycz MJ, Lein ES, Guillozet‐Bongaarts AL, Shen EH, Ng L, Miller JA, Van De Lagemaat LN, Smith KA, Ebbert A, Riley ZL et al (2012) An anatomically comprehensive atlas of the adult human brain transcriptome. Nature 489: 391– 399 22996553 PMC4243026
- Heinrich C, Spagnoli FM, Berninger B (2015) In vivo reprogramming for tissue repair. Nat Cell Biol 17: 204– 211 25720960
- Hnisz D, Abraham BJ, Lee TI, Lau A, Saint‐André V, Sigova AA, Hoke HA, Young RA (2013) Transcriptional super‐enhancers connected to cell identity and disease. Cell 155: 934– 947 24119843 PMC3841062
- Hobert O (2008) Regulatory logic of neuronal diversity: Terminal selector genes and selector motifs. Proc Natl Acad Sci USA 105: 20067– 20071 19104055 PMC2629285
- Hobert O (2011) Regulation of terminal differentiation programs in the nervous system. Annu Rev Cell Dev Biol 27: 681– 696 21985672
- Hobert O (2016) Terminal selectors of neuronal identity. Curr Top Dev Biol 116: 455– 475 26970634
- Holmberg J, Perlmann T (2012) Maintaining differentiated cellular identity. Nat Rev Genet 13: 429– 439 22596319
- Huynh‐Thu VA, Geurts P (2018) dynGENIE3: dynamical GENIE3 for the inference of gene networks from time series expression data. Sci Rep 8: 3384 29467401 PMC5821733
- Jennings RE, Berry AA, Strutt JP, Gerrard DT, Hanley NA (2015) Human pancreas development. Development 142: 3126– 3137 26395141
- Jiang M, Azevedo‐Pouly AC, Deering TG, Hoang CQ, DiRenzo D, Hess DA, Konieczny SF, Swift GH, MacDonald RJ (2016) MIST1 and PTF1 collaborate in feed‐forward regulatory loops that maintain the pancreatic Acinar phenotype in adult mice. Mol Cell Biol 36: 2945– 2955 27644326 PMC5108882
- Jiang Y, Qian F, Bai X, Liu Y, Wang Q, Ai B, Han X, Shi S, Zhang J, Li X et al (2019) SEdb: a comprehensive human super‐enhancer database. Nucleic Acids Res 47: D235– D243 30371817 PMC6323980
- Jung S, del Sol A (2020) Multiomics data integration unveils core transcriptional regulatory networks governing cell‐type identity. npj Syst Biol Appl 6: 1– 4 32839455 PMC7445234
- Kataoka K, Han S, Shioda S, Hirai M, Nishizawa M, Handa H (2002) MafA is a glucose‐regulated and pancreatic beta‐cell‐specific transcriptional activator for the insulin gene. J Biol Chem 277: 49903– 49910 12368292
- Keil JM, Qalieh A, Kwan KY (2018) Brain transcriptome databases: a user’s guide. J Neurosci 38: 2399– 2412 29437890 PMC5858588
- Khan A, Zhang X (2016) DbSUPER: a database of Super‐enhancers in mouse and human genome. Nucleic Acids Res 44: D164– D171 26438538 PMC4702767
- Kiselev VY, Andrews TS, Hemberg M (2019) Challenges in unsupervised clustering of single‐cell RNA‐seq data. Nat Rev Genet 20: 273– 282 30617341
- Krapp A, Knöfler M, Frutiger S, Hughes GJ, Hagenbüchle O, Wellauer PK (1996) The p48 DNA‐binding subunit of transcription factor PTF1 is a new exocrine pancreas‐specific basic helix‐loop‐helix protein. EMBO J 15: 4317– 4329 8861960 PMC452157
- Lake BB, Ai R, Kaeser GE, Salathia NS, Yung YC, Liu R, Wildberg A, Gao D, Fung HL, Chen S et al (2016) Neuronal subtypes and diversity revealed by single‐nucleus RNA sequencing of the human brain. Science 352: 1586– 1590 27339989 PMC5038589
- Lawlor N, George J, Bolisetty M, Kursawe R, Sun L, Sivakamasundari V, Kycia I, Robson P, Stitzel ML (2017) Single‐cell transcriptomes identify human islet cell signatures and reveal cell‐type‐specific expression changes in type 2 diabetes. Genome Res 27: 208– 222 27864352 PMC5287227
- Lemercier C, To RQ, Swanson BJ, Lyons GE, Konieczny SF (1997) Mist1: a novel basic helix‐loop‐helix transcription factor exhibits a developmentally regulated expression pattern. Dev Biol 182: 101– 113 9073453
- Marioni JC, Arendt D (2017) How single‐cell genomics is changing evolutionary and developmental biology. Annu Rev Cell Dev Biol 33: 537– 553 28813177
- Martens JHA, Stunnenberg HG (2013) BLUEPRINT: mapping human blood cell epigenomes. Haematologica 98: 1487– 1489 24091925 PMC3789449
- Matsuoka TA, Artner I, Henderson E, Means A, Sander M, Stein R (2004) The MafA transcription factor appears to be responsible for tissue‐specific expression of insulin. Proc Natl Acad Sci USA 101: 2930– 2933 14973194 PMC365722
- Mawla AM, Huising MO (2019) Navigating the depths and avoiding the shallows of pancreatic islet cell transcriptomes. Diabetes 68: 1380– 1393 31221802 PMC6609986
- Menon V (2018) Extracting new insights from bulk transcriptomics. Nat Neurosci 21: 1142– 1144 30154506
- Moore JE, Purcaro MJ, Pratt HE, Epstein CB, Shoresh N, Adrian J, Kawli T, Davis CA, Dobin A, Kaul R et al (2020) Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature 583: 699– 710 32728249 PMC7410828
- Moorthy SD, Davidson S, Shchuka VM, Singh G, Malek‐Gilani N, Langroudi L, Martchenko A, So V, Macpherson NN, Mitchell JA (2017) Enhancers and super‐enhancers have an equivalent regulatory role in embryonic stem cells through regulation of single or multiple genes. Genome Res 27: 246– 258 27895109 PMC5287230
- Muraro MJ, Dharmadhikari G, Grün D, Groen N, Dielen T, Jansen E, van Gurp L, Engelse MA, Carlotti F, de Koning EJP et al (2016) A single‐cell transcriptome atlas of the human pancreas. Cell Syst 3: 385– 394.e3 27693023 PMC5092539
- Murtaugh LC (2007) Pancreas and beta‐cell development: from the actual to the possible. Development 134: 427– 438 17185316
- Neph S, Stergachis AB, Reynolds A, Sandstrom R, Borenstein E, Stamatoyannopoulos JA (2012) Circuitry and dynamics of human transcription factor regulatory networks. Cell 150: 1274– 1286 22959076 PMC3679407
- Nishimura W, Takahashi S, Yasuda K (2015) MafA is critical for maintenance of the mature beta cell phenotype in mice. Diabetologia 58: 566– 574 25500951
- Ocone A, Haghverdi L, Mueller NS, Theis FJ (2015) Reconstructing gene regulatory dynamics from high‐dimensional single‐cell snapshot data. Bioinformatics 31: i89– i96 26072513 PMC4765871
- Orchard S, Ammari M, Aranda B, Breuza L, Briganti L, Broackes‐Carter F, Campbell NH, Chavali G, Chen C, Del‐Toro N et al (2014) The MIntAct project‐IntAct as a common curation platform for 11 molecular interaction databases. Nucleic Acids Res 42: D358– D363 24234451 PMC3965093
- Oughtred R, Stark C, Breitkreutz B‐J, Rust J, Boucher L, Chang C, Kolas N, O’Donnell L, Leung G, McAdam R et al (2018) The BioGRID interaction database: 2019 update. Nucleic Acids Res 47: 529– 541 PMC6324058 30476227
- Park P (2009) Applications of next‐generation sequencing: ChIP–seq: advantages and challenges of a maturing technology. Nat Rev Genet 10: 669 19736561 PMC3191340
- Peter IS, Davidson EH (2016) Implications of developmental gene regulatory networks inside and outside developmental biology. Curr Top Dev Biol 117: 237– 251 26969981
- Philpott M, Cribbs AP, Brown T, Oppermann U (2020) Advances and challenges in epigenomic single‐cell sequencing applications. Curr Opin Chem Biol 57: 17– 26 32304986
- Pin CL, Michael Rukstalis J, Johnson C, Konieczny SF (2001) The bHLH transcription factor Mist1 is required to maintain exocrine pancreas cell organization and acinar cell identity. J Cell Biol 155: 519– 530 11696558 PMC2198859
- Pomerantz JH, Mukherjee S, Palermo AT, Blau HM (2009) Reprogramming to a muscle fate by fusion recapitulates differentiation. J Cell Sci 122: 1045– 1053 19295131 PMC2720934
- Qian FC, Li XC, Guo JC, Zhao JM, Li YY, Tang ZD, Zhou LW, Zhang J, Bai XF, Jiang Y et al (2019) SEanalysis: a web tool for super‐enhancer associated regulatory analysis. Nucleic Acids Res 47: W248– W255 31028388 PMC6602466
- Rackham OJL, Firas J, Fang H, Oates ME, Holmes ML, Knaupp AS, Suzuki H, Nefzger CM, Daub CO, Shin JW et al (2016) A predictive computational framework for direct reprogramming between human cell types. Nat Genet 48: 331– 335 26780608
- Remesal L, Roger‐Baynat I, Chirivella L, Maicas M, Brocal‐Ruiz R, Pérez‐Villalba A, Cucarella C, Casado M, Flames N (2020) PBX1 acts as terminal selector for olfactory bulb dopaminergic neurons. Development 147: dev186841 32156753
- 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) Integrative analysis of 111 reference human epigenomes. Nature 518: 317– 329 25693563 PMC4530010
- Rolland T, Taşan M, Charloteaux B, Pevzner SJ, Zhong Q, Sahni N, Yi S, Lemmens I, Fontanillo C, Mosca R et al (2014) A proteome‐scale map of the human interactome network. Cell 159: 1212– 1226 25416956 PMC4266588
- Romer AI, Sussel L (2015) Pancreatic islet cell development and regeneration. Curr Opin Endocrinol Diabetes Obes 22: 255– 264 26087337 PMC4660868
- Russell R, Carnese PP, Hennings TG, Walker EM, Russ HA, Liu JS, Giacometti S, Stein R, Hebrok M (2020) Loss of the transcription factor MAFB limits β‐cell derivation from human PSCs. Nat Commun 11: 1– 15 32488111 PMC7265500
- Saelens W, Cannoodt R, Todorov H, Saeys Y (2019) A comparison of single‐cell trajectory inference methods. Nat Biotechnol 37: 547– 554 30936559
- Saint‐André V, Federation AJ, Lin CY, Abraham BJ, Reddy J, Lee TI, Bradner JE, Young RA (2016) Models of human core transcriptional regulatory circuitries. Genome Res 26: 385– 396 26843070 PMC4772020
- Satterlee JS, Schübeler D, Ng HH (2010) Tackling the epigenome: challenges and opportunities for collaboration. Nat Biotechnol 28: 1039– 1044 20944594
- Scarl RT, Corbin KL, Vann NW, Smith HM, Satin LS, Sherman A, Nunemaker CS (2019) Intact pancreatic islets and dispersed beta‐cells both generate intracellular calcium oscillations but differ in their responsiveness to glucose. Cell Calcium 83: 102081 31563790 PMC6983470
- Schiebinger G, Shu J, Tabaka M, Cleary B, Subramanian V, Solomon A, Gould J, Liu S, Lin S, Berube P et al (2019) Optimal‐transport analysis of single‐cell gene expression identifies developmental trajectories in reprogramming. Cell 176: 928– 943.e22 30712874 PMC6402800
- Segerstolpe Å, Palasantza A, Eliasson P, Andersson EM, Andréasson AC, Sun X, Picelli S, Sabirsh A, Clausen M, Bjursell MK et al (2016) Single‐cell transcriptome profiling of human pancreatic islets in health and type 2 diabetes. Cell Metab 24: 593– 607 27667667 PMC5069352
- Selleri L, Zappavigna V, Ferretti E (2019) ‘Building a perfect body’: control of vertebrate organogenesis by PBX‐dependent regulatory networks. Genes Dev 33: 258– 275 30824532 PMC6411007
- Shlyueva D, Stampfel G, Stark A (2014) Transcriptional enhancers: from properties to genome‐wide predictions. Nat Rev Genet 15: 272– 286 24614317
- Spitz F, Furlong EEM (2012) Transcription factors: from enhancer binding to developmental control. Nat Rev Genet 13: 613– 626 22868264
- Sun Y, Miao N, Sun T (2019) Detect accessible chromatin using ATAC‐sequencing, from principle to applications. Hereditas 156: 29 31427911 PMC6696680
- Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta‐Cepas J, Simonovic M, Doncheva NT, Morris JH, Jensen LJ et al (2018) STRING v11: protein‐protein association networks with increased coverage, supporting functional discovery in genome‐wide experimental datasets. Nucleic Acids Res 47: 607– 613 PMC6323986 30476243
- Thibodeau A, Uyar A, Khetan S, Stitzel ML, Ucar D (2018) A neural network based model effectively predicts enhancers from clinical ATAC‐seq samples. Sci Rep 8: 1– 15 30375457 PMC6207744
- Tiwari N, Pataskar A, Péron S, Thakurela S, Sahu SK, Figueres‐Oñate M, Marichal N, López‐Mascaraque L, Tiwari VK, Berninger B (2018) Stage‐specific transcription factors drive astrogliogenesis by remodeling gene regulatory landscapes. Cell Stem Cell 23: 557– 571.e8 30290178 PMC6179960
- Tosti L, Hang Y, Trefzer T, Steiger K, Ten FW, Lukassen S, Ballke S, Kuehl A, Spieckermann S, Bottino R et al (2021) Single‐nucleus and in situ RNA–sequencing reveal cell topographies in the human pancreas. Gastroenterology 160: 1330– 1344.e11 33212097
- Trapnell C, Cacchiarelli D, Grimsby J, Pokharel P, Li S, Morse M, Lennon NJ, Livak KJ, Mikkelsen TS, Rinn JL (2014) The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat Biotechnol 32: 381– 386 24658644 PMC4122333
- Tritschler S, Büttner M, Fischer DS, Lange M, Bergen V, Lickert H, Theis FJ (2019) Concepts and limitations for learning developmental trajectories from single cell genomics. Development 146: dev170506 31249007
- Villaescusa JC, Li B, Toledo EM, di Val R, Cervo P, Yang S, Stott SR, Kaiser K, Islam S, Gyllborg D et al (2016) A PBX1 transcriptional network controls dopaminergic neuron development and is impaired in Parkinson’s disease. EMBO J 35: 1963– 1978 27354364 PMC5282836
- Wagner A, Regev A, Yosef N (2016) Revealing the vectors of cellular identity with single‐cell genomics. Nat Biotechnol 34: 1145– 1160 27824854 PMC5465644
- Wang J, Yuan R, Zhu X, Ao P (2020) Adaptive landscape shaped by core endogenous network coordinates complex early progenitor fate commitments in embryonic pancreas. Sci Rep 10: 1– 17 31980678 PMC6981170
- Wang L, Tan TK, Durbin AD, Zimmerman MW, Abraham BJ, Tan SH, Ngoc PCT, Weichert‐Leahey N, Akahane K, Lawton LN et al (2019) ASCL1 is a MYCN‐ and LMO1‐dependent member of the adrenergic neuroblastoma core regulatory circuitry. Nat Commun 10: 1– 15 31819055 PMC6901540
- Weiss MC, Green H (1967) Human‐mouse hybrid cell lines containing partial complements of human chromosomes and functioning human genes. Proc Natl Acad Sci USA 58: 1104– 1111 5233838 PMC335754
- Whyte WA, Orlando DA, Hnisz D, Abraham BJ, Lin CY, Kagey MH, Rahl PB, Lee TI, Young RA (2013) Master transcription factors and mediator establish super‐enhancers at key cell identity genes. Cell 153: 307– 319 23582322 PMC3653129
- Wilson S, Filipp FV (2018) A network of epigenomic and transcriptional cooperation encompassing an epigenomic master regulator in cancer. npj Syst Biol Appl 4: 24 29977600 PMC6026491
- Xia B, Yanai I (2019) A periodic table of cell types. Development 146: 1– 9 PMC6602355 31249003
- Xin Y, Kim J, Okamoto H, Ni M, Wei Y, Adler C, Murphy AJ, Yancopoulos GD, Lin C, Gromada J (2016) RNA sequencing of single human islet cells reveals type 2 diabetes genes. Cell Metab 24: 608– 615 27667665
- Xu J, Du Y, Deng H (2015) Direct lineage reprogramming: strategies, mechanisms, and applications. Cell Stem Cell 16: 119– 134 25658369
- Young RA (2011) Control of the embryonic stem cell state. Cell 144: 940– 954 21414485 PMC3099475
- Zaret KS, Mango SE (2016) Pioneer transcription factors, chromatin dynamics, and cell fate control. Curr Opin Genet Dev 37: 76– 81 26826681 PMC4914445
- Zhou Q, Brown J, Kanarek A, Rajagopal J, Melton DA (2008) In vivo reprogramming of adult pancreatic exocrine cells to β‐cells. Nature 455: 627– 632 18754011 PMC9011918
- Zhu Y, Liu Q, Zhou Z, Ikeda Y (2017) PDX1, Neurogenin‐3, and MAFA: critical transcription regulators for beta cell development and regeneration. Stem Cell Res Ther 8: 240 29096722 PMC5667467
Cited by
Sorted by citations
An extended transcription factor regulatory network controls hepatocyte identity
Dubois‐Chevalier, J., Gheeraert, C., Berthier, A., Boulet, C., Dubois, V., Guille, L., Fourcot, M., Marot, G., Gauthier, K., Dubuquoy, L., et al. (2023) · EMBO Reports · doi:10.15252/embr.202357020 · Cited by 6 · see citing works
“…to self-sustain high expression of identity TFs and their target effector genes in addition to being involved in the continuous modulation of the hepatic transcriptome in response to environmental stimuli (Boyer et al , 2005; Arendt et al , 2016; Wilkinson et al , 2017; Almeida et al , 2021).”
Influential
- Authors
- Almeida, N., Chung, M. W. H., Drudi, E. M., Engquist, E. N., Hamrud, E., Isaacson, A., Tsang, V. S. K., Watt, F. M., & Spagnoli, F. M.
- Affiliations
- Guy's Hospital (GB)
- Corresponding author
- Watt, Fiona M
- Spagnoli, Francesca M
- ORCID
- Venue
- The EMBO Journal
- Published
- 2021-05-02
- Volume
- 40
- Issue
- 10
- Pages
- e106785-e106785
- ISSN
- 0261-4189 (ISSN-L)
- 1460-2075
- PMC
- PMC8126924
- OpenAlex
- W3157806418
- Cited by
- 49
- References
- 15
- Citations by year
- 2026: 8 · 2025: 8 · 2024: 14 · 2023: 9 · 2022: 6 · 2021: 4
- FWCI
- 0.87
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- The EMBO Journal (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Portal (King's College London) (submittedVersion, cc-by)
- Funders
- Wellcome Trust (108874/Z/15/Z)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Developmental Biology and Gene Regulation
- Keywords
- cell identity, transcriptional regulatory networks, transcription factors, gene regulatory networks, extrinsic signaling, cell fate determination, gene expression profiles, single-cell technologies
- MeSH terms
- Humans, Transcription Factors, Regenerative Medicine
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