
Selective mediator dependence of cell-type-specifying transcription
- Select a language for the TTS:
- UK English Female
- UK English Male
- US English Female
- US English Male
- Australian Female
- Australian Male
- Language selected: (auto detect) - EN
Play all audios:
ABSTRACT The Mediator complex directs signals from DNA-binding transcription factors to RNA polymerase II (Pol II). Despite this pivotal position, mechanistic understanding of Mediator in
human cells remains incomplete. Here we quantified Mediator-controlled Pol II kinetics by coupling rapid subunit degradation with orthogonal experimental readouts. In agreement with a model
of condensate-driven transcription initiation, large clusters of hypophosphorylated Pol II rapidly disassembled upon Mediator degradation. This was accompanied by a selective and pronounced
disruption of cell-type-specifying transcriptional circuits, whose constituent genes featured exceptionally high rates of Pol II turnover. Notably, the transcriptional output of most other
genes was largely unaffected by acute Mediator ablation. Maintenance of transcriptional activity at these genes was linked to an unexpected CDK9-dependent compensatory feedback loop that
elevated Pol II pause release rates across the genome. Collectively, our work positions human Mediator as a globally acting coactivator that selectively safeguards the functionality of
cell-type-specifying transcriptional networks. Access through your institution Buy or subscribe This is a preview of subscription content, access via your institution ACCESS OPTIONS Access
through your institution Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription $32.99 / 30 days cancel any time Learn more Subscribe to
this journal Receive 12 print issues and online access $209.00 per year only $17.42 per issue Learn more Buy this article * Purchase on SpringerLink * Instant access to full article PDF Buy
now Prices may be subject to local taxes which are calculated during checkout ADDITIONAL ACCESS OPTIONS: * Log in * Learn about institutional subscriptions * Read our FAQs * Contact customer
support SIMILAR CONTENT BEING VIEWED BY OTHERS THE MEDIATOR COMPLEX AS A MASTER REGULATOR OF TRANSCRIPTION BY RNA POLYMERASE II Article 20 June 2022 REGULATION OF THE RNA POLYMERASE II
PRE-INITIATION COMPLEX BY ITS ASSOCIATED COACTIVATORS Article 02 August 2023 H3K4ME3 REGULATES RNA POLYMERASE II PROMOTER-PROXIMAL PAUSE-RELEASE Article Open access 01 March 2023 DATA
AVAILABILITY Next-generation sequencing data are available through the NCBI Gene Expression Omnibus under accession code GSE139468. Chromatin proteomics data have been deposited at PRIDE
under dataset identifier PXD017611. Source data for Figs. 1 and 4 and Extended Data Figs. 1–4 and 6 are presented with the paper. CODE AVAILABILITY Custom code used to analyze the data in
this study is available at https://github.com/GWinterLab/Jaeger_Mediator_NatureGenetics_2020. REFERENCES * Kelleher, R. J. 3rd, Flanagan, P. M. & Kornberg, R. D. A novel mediator between
activator proteins and the RNA polymerase II transcription apparatus. _Cell_ 61, 1209–1215 (1990). CAS PubMed Google Scholar * Kornberg, R. D. Mediator and the mechanism of
transcriptional activation. _Trends Biochem. Sci._ 30, 235–239 (2005). CAS PubMed Google Scholar * Thompson, C. M., Koleske, A. J., Chao, D. M. & Young, R. A. A multisubunit complex
associated with the RNA polymerase II CTD and TATA-binding protein in yeast. _Cell_ 73, 1361–1375 (1993). CAS PubMed Google Scholar * Kim, Y. J., Bjorklund, S., Li, Y., Sayre, M. H. &
Kornberg, R. D. A multiprotein mediator of transcriptional activation and its interaction with the C-terminal repeat domain of RNA polymerase II. _Cell_ 77, 599–608 (1994). CAS PubMed
Google Scholar * Fondell, J. D., Ge, H. & Roeder, R. G. Ligand induction of a transcriptionally active thyroid hormone receptor coactivator complex. _Proc. Natl Acad. Sci. USA_ 93,
8329–8333 (1996). CAS PubMed PubMed Central Google Scholar * Jiang, Y. W. et al. Mammalian mediator of transcriptional regulation and its possible role as an end-point of signal
transduction pathways. _Proc. Natl Acad. Sci. USA_ 95, 8538–8543 (1998). CAS PubMed PubMed Central Google Scholar * Malik, S. & Roeder, R. G. Dynamic regulation of Pol II
transcription by the mammalian Mediator complex. _Trends Biochem. Sci._ 30, 256–263 (2005). CAS PubMed Google Scholar * Conaway, R. C., Sato, S., Tomomori-Sato, C., Yao, T. & Conaway,
J. W. The mammalian Mediator complex and its role in transcriptional regulation. _Trends Biochem. Sci._ 30, 250–255 (2005). CAS PubMed Google Scholar * Kim, Y. J. & Lis, J. T.
Interactions between subunits of _Drosophila_ Mediator and activator proteins. _Trends Biochem. Sci._ 30, 245–249 (2005). CAS PubMed Google Scholar * Allen, B. L. & Taatjes, D. J. The
Mediator complex: a central integrator of transcription. _Nat. Rev. Mol. Cell Biol._ 16, 155–166 (2015). CAS PubMed PubMed Central Google Scholar * Soutourina, J. Transcription
regulation by the Mediator complex. _Nat. Rev. Mol. Cell Biol._ 19, 262–274 (2018). CAS PubMed Google Scholar * Jeronimo, C. & Robert, F. The Mediator complex: at the nexus of RNA
polymerase II transcription. _Trends Cell Biol._ 27, 765–783 (2017). CAS PubMed Google Scholar * Eychenne, T., Werner, M. & Soutourina, J. Toward understanding of the mechanisms of
Mediator function in vivo: focus on the preinitiation complex assembly. _Transcription_ 8, 328–342 (2017). CAS PubMed PubMed Central Google Scholar * Malik, S. & Roeder, R. G. The
metazoan Mediator co-activator complex as an integrative hub for transcriptional regulation. _Nat. Rev. Genet._ 11, 761–772 (2010). CAS PubMed PubMed Central Google Scholar * Holstege,
F. C. et al. Dissecting the regulatory circuitry of a eukaryotic genome. _Cell_ 95, 717–728 (1998). CAS PubMed Google Scholar * Petrenko, N., Jin, Y., Wong, K. H. & Struhl, K.
Evidence that Mediator is essential for Pol II transcription, but is not a required component of the preinitiation complex in vivo. _eLife_ 6, e28447 (2017). PubMed PubMed Central Google
Scholar * Jeronimo, C. et al. Tail and kinase modules differently regulate core Mediator recruitment and function in vivo. _Mol. Cell_ 64, 455–466 (2016). CAS PubMed PubMed Central
Google Scholar * Petrenko, N., Jin, Y., Wong, K. H. & Struhl, K. Mediator undergoes a compositional change during transcriptional activation. _Mol. Cell_ 64, 443–454 (2016). CAS PubMed
PubMed Central Google Scholar * Shlyueva, D., Stampfel, G. & Stark, A. Transcriptional enhancers: from properties to genome-wide predictions. _Nat. Rev. Genet._ 15, 272–286 (2014).
CAS PubMed Google Scholar * Whyte, W. A. et al. Master transcription factors and Mediator establish super-enhancers at key cell identity genes. _Cell_ 153, 307–319 (2013). CAS PubMed
PubMed Central Google Scholar * Loven, J. et al. Selective inhibition of tumor oncogenes by disruption of super-enhancers. _Cell_ 153, 320–334 (2013). CAS PubMed PubMed Central Google
Scholar * Spitz, F. & Furlong, E. E. Transcription factors: from enhancer binding to developmental control. _Nat. Rev. Genet._ 13, 613–626 (2012). CAS PubMed Google Scholar * Lee, T.
I. & Young, R. A. Transcriptional regulation and its misregulation in disease. _Cell_ 152, 1237–1251 (2013). CAS PubMed PubMed Central Google Scholar * Davidson, E. H. Emerging
properties of animal gene regulatory networks. _Nature_ 468, 911–920 (2010). CAS PubMed PubMed Central Google Scholar * Sabari, B. R. et al. Coactivator condensation at super-enhancers
links phase separation and gene control. _Science_ 361, eaar3958 (2018). PubMed PubMed Central Google Scholar * Cho, W.-K. et al. Mediator and RNA polymerase II clusters associate in
transcription-dependent condensates. _Science_ 361, 412 (2018). CAS PubMed PubMed Central Google Scholar * Levine, M., Cattoglio, C. & Tjian, R. Looping back to leap forward:
transcription enters a new era. _Cell_ 157, 13–25 (2014). CAS PubMed PubMed Central Google Scholar * Kim, S. & Shendure, J. Mechanisms of interplay between transcription factors and
the 3D genome. _Mol. Cell_ 76, 306–319 (2019). CAS PubMed Google Scholar * Kagey, M. H. et al. Mediator and cohesin connect gene expression and chromatin architecture. _Nature_ 467,
430–435 (2010). CAS PubMed PubMed Central Google Scholar * El Khattabi, L. et al. A pliable Mediator acts as a functional rather than an architectural bridge between promoters and
enhancers. _Cell_ 178, 1145–1158 (2019). CAS PubMed Google Scholar * Takahashi, H. et al. Human Mediator subunit MED26 functions as a docking site for transcription elongation factors.
_Cell_ 146, 92–104 (2011). CAS PubMed PubMed Central Google Scholar * Wang, W. et al. Mediator MED23 regulates basal transcription in vivo via an interaction with P-TEFb. _Transcription_
4, 39–51 (2013). CAS PubMed PubMed Central Google Scholar * Dahlberg, O., Shilkova, O., Tang, M., Holmqvist, P. H. & Mannervik, M. P-TEFb, the super elongation complex and Mediator
regulate a subset of non-paused genes during early _Drosophila_ embryo development. _PLoS Genet._ 11, e1004971 (2015). PubMed PubMed Central Google Scholar * Conaway, R. C. & Conaway,
J. W. The Mediator complex and transcription elongation. _Biochim. Biophys. Acta_ 1829, 69–75 (2013). CAS PubMed Google Scholar * Erb, M. A. et al. Transcription control by the ENL YEATS
domain in acute leukaemia. _Nature_ 543, 270–274 (2017). CAS PubMed PubMed Central Google Scholar * Nabet, B. et al. The dTAG system for immediate and target-specific protein
degradation. _Nat. Chem. Biol._ 14, 431–441 (2018). CAS PubMed PubMed Central Google Scholar * Cevher, M. A. et al. Reconstitution of active human core Mediator complex reveals a
critical role of the MED14 subunit. _Nat. Struct. Mol. Biol._ 21, 1028–1034 (2014). CAS PubMed PubMed Central Google Scholar * Winter, G. E. et al. BET bromodomain proteins function as
master transcription elongation factors independent of CDK9 recruitment. _Mol. Cell_ 67, 5–18 (2017). CAS PubMed PubMed Central Google Scholar * Olson, C. M. et al. Pharmacological
perturbation of CDK9 using selective CDK9 inhibition or degradation. _Nat. Chem. Biol._ 14, 163–170 (2018). CAS PubMed Google Scholar * Muhar, M. et al. SLAM-seq defines direct
gene-regulatory functions of the BRD4–MYC axis. _Science_ 360, 800–805 (2018). CAS PubMed PubMed Central Google Scholar * Plaschka, C. et al. Architecture of the RNA polymerase
II–Mediator core initiation complex. _Nature_ 518, 376–380 (2015). CAS PubMed Google Scholar * Nozawa, K., Schneider, T. R. & Cramer, P. Core Mediator structure at 3.4 Å extends model
of transcription initiation complex. _Nature_ 545, 248–251 (2017). CAS PubMed Google Scholar * Tsai, K. L. et al. Mediator structure and rearrangements required for holoenzyme formation.
_Nature_ 544, 196–201 (2017). CAS PubMed PubMed Central Google Scholar * Kato, M. et al. Cell-free formation of RNA granules: low complexity sequence domains form dynamic fibers within
hydrogels. _Cell_ 149, 753–767 (2012). CAS PubMed PubMed Central Google Scholar * Schwalb, B. et al. TT-seq maps the human transient transcriptome. _Science_ 352, 1225–1228 (2016). CAS
PubMed Google Scholar * Saint-Andre, V. et al. Models of human core transcriptional regulatory circuitries. _Genome Res._ 26, 385–396 (2016). CAS PubMed PubMed Central Google Scholar *
Nabet, B. et al. Rapid and direct control of target protein levels with VHL-recruiting dTAG molecules. Preprint at _bioRxiv_ https://doi.org/10.1101/2020.03.13.980946 (2020). * Mumbach, M.
R. et al. HiChIP: efficient and sensitive analysis of protein-directed genome architecture. _Nat. Methods_ 13, 919–922 (2016). CAS PubMed PubMed Central Google Scholar * Weintraub, A. S.
et al. YY1 is a structural regulator of enhancer–promoter loops. _Cell_ 171, 1573–1588 (2017). CAS PubMed PubMed Central Google Scholar * Li, W., Notani, D. & Rosenfeld, M. G.
Enhancers as non-coding RNA transcription units: recent insights and future perspectives. _Nat. Rev. Genet._ 17, 207–223 (2016). CAS PubMed Google Scholar * Kwak, H., Fuda, N. J., Core,
L. J. & Lis, J. T. Precise maps of RNA polymerase reveal how promoters direct initiation and pausing. _Science_ 339, 950–953 (2013). CAS PubMed PubMed Central Google Scholar *
Wissink, E. M., Vihervaara, A., Tippens, N. D. & Lis, J. T. Nascent RNA analyses: tracking transcription and its regulation. _Nat. Rev.Genet._ 20, 705–723 (2019). * Cramer, P.
Organization and regulation of gene transcription. _Nature_ 573, 45–54 (2019). CAS PubMed Google Scholar * Hnisz, D., Shrinivas, K., Young, R. A., Chakraborty, A. K. & Sharp, P. A. A
phase separation model for transcriptional control. _Cell_ 169, 13–23 (2017). CAS PubMed PubMed Central Google Scholar * Guo, Y. E. et al. Pol II phosphorylation regulates a switch
between transcriptional and splicing condensates. _Nature_ 572, 543–548 (2019). CAS PubMed PubMed Central Google Scholar * Gressel, S. et al. CDK9-dependent RNA polymerase II pausing
controls transcription initiation. _eLife_ 6, e29736 (2017). * Shao, W. & Zeitlinger, J. Paused RNA polymerase II inhibits new transcriptional initiation. _Nat. Genet._ 49, 1045–1051
(2017). CAS PubMed Google Scholar * Adelman, K. & Lis, J. T. Promoter-proximal pausing of RNA polymerase II: emerging roles in metazoans. _Nat. Rev. Genet._ 13, 720–731 (2012). CAS
PubMed PubMed Central Google Scholar * Ehrensberger, A. H., Kelly, G. P. & Svejstrup, J. Q. Mechanistic interpretation of promoter-proximal peaks and RNAPII density maps. _Cell_ 154,
713–715 (2013). CAS PubMed Google Scholar * Szklarczyk, D. et al. STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide
experimental datasets. _Nucleic Acids Res._ 47, D607–D613 (2019). CAS PubMed Google Scholar * Zhou, Q., Li, T. & Price, D. H. RNA polymerase II elongation control. _Annu. Rev.
Biochem._ 81, 119–143 (2012). CAS PubMed PubMed Central Google Scholar * Sanso, M. et al. P-TEFb regulation of transcription termination factor Xrn2 revealed by a chemical genetic screen
for Cdk9 substrates. _Genes Dev._ 30, 117–131 (2016). CAS PubMed PubMed Central Google Scholar * Parua, P. K. et al. A Cdk9–PP1 switch regulates the elongation–termination transition of
RNA polymerase II. _Nature_ 558, 460–464 (2018). CAS PubMed PubMed Central Google Scholar * Bradner, J. E., Hnisz, D. & Young, R. A. Transcriptional addiction in cancer. _Cell_ 168,
629–643 (2017). CAS PubMed PubMed Central Google Scholar * Krebs, A. R. et al. Genome-wide single-molecule footprinting reveals high RNA polymerase II turnover at paused promoters.
_Mol. Cell_ 67, 411–422 (2017). CAS PubMed PubMed Central Google Scholar * Li, Y., Liu, M., Chen, L. F. & Chen, R. P-TEFb: finding its ways to release promoter-proximally paused RNA
polymerase II. _Transcription_ 9, 88–94 (2018). CAS PubMed PubMed Central Google Scholar * Mir, M., Bickmore, W., Furlong, E. E. M. & Narlikar, G. Chromatin topology, condensates and
gene regulation: shifting paradigms or just a phase? _Development_ 146, dev182766 (2019). * Chong, S. et al. Imaging dynamic and selective low-complexity domain interactions that control
gene transcription. _Science_ 361, eaar2555 (2018). PubMed PubMed Central Google Scholar * Roeder, R. G. 50+ years of eukaryotic transcription: an expanding universe of factors and
mechanisms. _Nat. Struct. Mol. Biol._ 26, 783–791 (2019). CAS PubMed PubMed Central Google Scholar * Sakuma, T., Nakade, S., Sakane, Y., Suzuki, K.-I. T. & Yamamoto, T. MMEJ-assisted
gene knock-in using TALENs and CRISPR–Cas9 with the PITCh systems. _Nat. Protoc._ 11, 118–133 (2016). CAS PubMed Google Scholar * Brand, M. & Winter, G. E. Locus-specific knock-in of
a degradable tag for target validation studies. _Methods Mol. Biol._ 1953, 105–119 (2019). CAS PubMed Google Scholar * Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner.
_Bioinformatics_ 29, 15–21 (2013). CAS PubMed Google Scholar * Anders, S., Pyl, P. T. & Huber, W. HTSeq—a Python framework to work with high-throughput sequencing data.
_Bioinformatics_ 31, 166–169 (2015). CAS PubMed Google Scholar * Pedregosa, F. et al. Scikit-learn: machine learning in Python. _J. Mach. Learn. Res._ 12, 2825–2830 (2011). Google Scholar
* Reich, M. et al. GenePattern 2.0. _Nat. Genet._ 38, 500–501 (2006). CAS PubMed Google Scholar * Gautier, L., Cope, L., Bolstad, B. M. & Irizarry, R. A. affy—analysis of Affymetrix
GeneChip data at the probe level. _Bioinformatics_ 20, 307–315 (2004). CAS PubMed Google Scholar * Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and
dispersion for RNA-seq data with DESeq2. _Genome Biol._ 15, 550 (2014). PubMed PubMed Central Google Scholar * Cui, Y. et al. BioCircos.js: an interactive Circos JavaScript library for
biological data visualization on web applications. _Bioinformatics_ 32, 1740–1742 (2016). CAS PubMed Google Scholar * Aranda-Orgilles, B. et al. MED12 regulates HSC-specific enhancers
independently of Mediator kinase activity to control hematopoiesis. _Cell Stem Cell_ 19, 784–799 (2016). CAS PubMed PubMed Central Google Scholar * Carpenter, A. E. et al. CellProfiler:
image analysis software for identifying and quantifying cell phenotypes. _Genome Biol._ 7, R100 (2006). PubMed PubMed Central Google Scholar * Peng, K., Radivojac, P., Vucetic, S.,
Dunker, A. K. & Obradovic, Z. Length-dependent prediction of protein intrinsic disorder. _BMC Bioinformatics_ 7, 208 (2006). PubMed PubMed Central Google Scholar * Virtanen, P. et al.
SciPy 1.0: fundamental algorithms for scientific computing in Python. _Nat. Methods_ 17, 261–272 (2020). CAS PubMed PubMed Central Google Scholar * Waskom, M. et al. mwaskom/seaborn:
v0.9.0. _Zenodo_ https://doi.org/10.5281/ZENODO.1313201 (2018). * Hunter, J. D. Matplotlib: a 2D graphics environment. _Comput. Sci. Eng._ 9, 90–95 (2007). Google Scholar * McNamara, R. P.
et al. KAP1 recruitment of the 7SK snRNP complex to promoters enables transcription elongation by RNA polymerase II. _Mol. Cell_ 61, 39–53 (2016). CAS PubMed Google Scholar Download
references ACKNOWLEDGEMENTS We thank R. Fisher (Icahn School of Medicine at Mount Sinai) for sharing antibody to SPT5 phosphorylated at Thr806. We thank the Biomedical Sequencing Facility at
CeMM and the MPIMG sequencing core for assistance with next-generation sequencing. We thank the imaging core facility of the Medical University of Vienna for assistance with microscopy. We
thank P. Lenart for critical review of the image quantification procedures. We thank A. Mayer and M. Erb for feedback on this manuscript. M.G.J. was supported by a Boehringer Ingelheim Fonds
PhD fellowship. T.V. was supported by the International Max Planck Research School for Genome Science, part of the Göttingen Graduate Center for Neurosciences, Biophysics and Molecular
Biosciences. B.A. is supported by the Austrian Science Fund (FWF) and the Medical University of Vienna’s joint PhD program in Inflammation and Immunity (FWF1212). C.B. is supported by a New
Frontiers Group award of the Austrian Academy of Sciences and by an ERC Starting Grant (European Union’s Horizon 2020 research and innovation programme, grant agreement 679146). B.N. was
supported by an American Cancer Society Postdoctoral Fellowship (PF-17-010-01-CDD). B.N. and N.S.G. were supported by the Katherine L. and Steven C. Pinard Research Fund. D.H. is supported
by the SPP2202 Priority Program Grant (HN 4/1-1) from the Deutsche Forschungsgemeinschaft (DFG). This project was further supported by an FWF Stand-Alone grant (P31690-B) awarded to the
Winter laboratory. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria Martin G. Jaeger, Alexander
Hanzl, Hana Imrichova, Matthias Brand, Benedikt Agerer, Someth Chorn, André C. Müller, Andreas Bergthaler, Christoph Bock & Georg E. Winter * Department of Molecular Biology, Max Planck
Institute for Biophysical Chemistry, Göttingen, Germany Björn Schwalb, Taras Velychko & Patrick Cramer * Department of Genome Regulation, Max Planck Institute for Molecular Genetics,
Berlin, Germany Sebastian D. Mackowiak & Denes Hnisz * Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA Behnam Nabet, Fleur M. Ferguson & Nathanael S.
Gray * Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA Behnam Nabet, Fleur M. Ferguson & Nathanael S. Gray * Novartis Institutes
for BioMedical Research, Cambridge, MA, USA James E. Bradner * Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria Christoph Bock Authors * Martin G. Jaeger View
author publications You can also search for this author inPubMed Google Scholar * Björn Schwalb View author publications You can also search for this author inPubMed Google Scholar *
Sebastian D. Mackowiak View author publications You can also search for this author inPubMed Google Scholar * Taras Velychko View author publications You can also search for this author
inPubMed Google Scholar * Alexander Hanzl View author publications You can also search for this author inPubMed Google Scholar * Hana Imrichova View author publications You can also search
for this author inPubMed Google Scholar * Matthias Brand View author publications You can also search for this author inPubMed Google Scholar * Benedikt Agerer View author publications You
can also search for this author inPubMed Google Scholar * Someth Chorn View author publications You can also search for this author inPubMed Google Scholar * Behnam Nabet View author
publications You can also search for this author inPubMed Google Scholar * Fleur M. Ferguson View author publications You can also search for this author inPubMed Google Scholar * André C.
Müller View author publications You can also search for this author inPubMed Google Scholar * Andreas Bergthaler View author publications You can also search for this author inPubMed Google
Scholar * Nathanael S. Gray View author publications You can also search for this author inPubMed Google Scholar * James E. Bradner View author publications You can also search for this
author inPubMed Google Scholar * Christoph Bock View author publications You can also search for this author inPubMed Google Scholar * Denes Hnisz View author publications You can also
search for this author inPubMed Google Scholar * Patrick Cramer View author publications You can also search for this author inPubMed Google Scholar * Georg E. Winter View author
publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS M.G.J. and G.E.W. conceptualized this project. M.G.J., T.V., A.H., M.B., B.A. and D.H. designed and
conducted experiments. M.G.J., B.S., S.D.M., A.H., H.I. and M.B. analyzed and interpreted original and published omics data. M.G.J., M.B., B.A. and S.C. generated cell lines. M.G.J., B.S.,
S.D.M. and M.B. visualized data. B.N. and F.M.F. synthesized the dTAGV-1 reagent. A.M., A.B., J.E.B., N.S.G., C.B., D.H., P.C. and G.E.W. supervised the work. M.G.J. and G.E.W. wrote the
manuscript with input from all authors. CORRESPONDING AUTHORS Correspondence to Patrick Cramer or Georg E. Winter. ETHICS DECLARATIONS COMPETING INTERESTS G.E.W., J.E.B. and B.N. are
inventors on patent applications related to the dTAG system (WO/2017/024318, WO/2017/024319, WO/2018/148443, WO/2018/148440). The dTAGV-1 molecule is the subject of a patent application
filed by Dana-Farber Cancer Institute. N.S.G. is a scientific founder, member of the scientific advisory board (SAB) and equity holder for C4 Therapeutics, Syros, Soltego, B2S, Gatekeeper
and Petra Pharmaceuticals. The Gray laboratory receives or has received research funding from Novartis, Takeda, Astellas, Taiho, Janssen, Kinogen, Voroni, Her2llc, Deerfield and Sanofi.
J.E.B. is now an executive and shareholder of Novartis and has been a founder and shareholder of SHAPE (acquired by Medivir), Acetylon (acquired by Celgene), Tensha (acquired by Roche),
Syros, Regenacy and C4 Therapeutics. ADDITIONAL INFORMATION PUBLISHER’S NOTE Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional
affiliations. EXTENDED DATA EXTENDED DATA FIG. 1 EXTENDED CHARACTERIZATION OF CHEMICALLY DEGRADABLE MED-DTAG ALLELES. a, MED-dTAG depletion mean of two independent image quantifications of
the Fig. 1b immunoblot. b, Degrader treatment selectively destabilizes the tagged Mediator subunit without affecting other complex members. c, Time-resolved immunoblot of MED10-dTAG and
direct pharmacologic degradation of CDK9 (dCDK9; THAL-SNS-032) or BRD4 (dBET6). d, Pearson correlation of average 3’ mRNA-seq log2 fold changes after 6 h (n = 3 independent drug treatments).
For dTAG-carrying cell lines (only gene names shown), we compare dTAG7 vs. vehicle control in the same cell line. Other conditions represent drug vs. vehicle control in wild-type cells. e,
Gene ontology (GO) terms enriched among negative PC2 loadings in Fig. 1c. Enrichment was calculated using the GSEAPreranked tool75. Negative enrichment indicates a strong influence of these
terms on PC2 diversity and that the underlying genes are downregulated. f, Gene set enrichment analysis of top 100 core MYC target genes from (ref. 40) among PC2 loadings. g, Time-resolved
immunoblot of MED14-dTAG degradation kinetics and its influence on MYC protein levels. Unprocessed western blots shown in Source Data. Source Data EXTENDED DATA FIG. 2 MED14 DEGRADATION
DISRUPTS OVERALL MEDIATOR COMPLEX INTEGRITY. A, Influence of long-term MED14 degradation on cell growth. B, Size-exclusion chromatography and western blotting of nuclear extracts after MED14
degradation. Mediator subunits of each submodule shifted to lower apparent molecular weight, indicating complex disassembly. BAF complex member BRD9 serves as negative control. C, Image
quantification related to Fig. 1f. Pie chart: percent of n = 125 MED1 foci with overlapping MED14-dTAG foci. Middle dot plot: mean±s.e.m number of foci per cell. Swarm plot: mean±s.e.m
integrated nuclear fluorescence intensity. Unpaired, two-sided t-tests. 163 nuclei were quantified for DMSO and 105 for dTAG7. D, 20-residue running average-smoothed PONDR-VSL2 disorder
prediction for human Mediator. Subunits are ordered by ascending index numbers from MED1 to MED31, followed by CDK8, CDK19, and CCNC. E, Influence of MED14 or MED1 degradation on
co-precipitation of other Mediator subunits with biotinylated isoxazole pellets. MED14, but not MED1 degradation, prevents Mediator co-precipitation with IDR-enriching hydrogels. F, Cell
identity gene sets enriched among downregulated transcription units in TT-seq after 1 h MED14 degradation. Enrichment was calculated using the GSEAPreranked tool75. Unprocessed western blots
shown in Source Data. Source Data EXTENDED DATA FIG. 3 ACUTE TRANSCRIPTIONAL CONSEQUENCES OF MED14 DEGRADATION IN HCT-116 CELLS. A, CellTiter-Glo viability-based 72 h dose-response of dTAG7
and dTAGV-1 in HCT-116 MED14-dTAG cells. Mean±s.d. of n = 3 drug treatments. B, Time-resolved immunoblot of MED14-dTAG degradation. C, Differences in TT-seq nascent transcript levels (n = 2
independent treatments). Significantly deregulated (DESeq2 q < 0.01; dark grey), SE-proximal (blue), and auto-regulatory TF genes (red) are highlighted. Dark grey line: median log2 fold
change of all n = 21,629 transcription units. D, TT-seq signal of two auto-regulatory TFs, and an expression-matched control gene. H3K27ac and H3K4me3 ChIP-seq signals are from publically
available data (GSE72622; see Supplementary Table 7)85. E, Fold-change (color) and significance (size) of SE-driven HCT-116 cell identity and expression-matched control gene sets (data as in
C). F, Regulatory wiring of 17 auto-regulatory TFs in the HCT-116 cell type-specifying gene regulatory network. Arrows: the given TF has binding motifs in the target TF’s SE region(s). Edge
weight mirrors number of motifs. G, Overlap of KBM7 and HCT-116 auto-regulatory TFs. H, Cell type-specific impact of 1 h MED14 degradation. Auto-regulatory TFs in KBM7 (blue, for example
_MYB_), HCT-116 (orange, for example _TGIF1_), or _MYC_ (black) as the only shared TF are highlighted. Colored lines: median log2FC in the respective cell line. I, Mean steady state
expression of auto-regulatory TFs in merged 1 h and 2 h DMSO TT-seq conditions and transcriptional defects after 1 h MED14 degradation. Unprocessed western blot shown in Source Data. Source
Data EXTENDED DATA FIG. 4 IMPACT OF MED14 DEGRADATION ON OVERALL CHROMATIN ARCHITECTURE. A, Genomic feature classes at H3K27ac HiChIP contact anchors. Only significant interactions called by
hichipper/mango were used for anchor identification. Arcs indicate the percentage of anchor-anchor pairs annotated with the indicated feature in each of the samples. B, Total number of
interactions common to DMSO and dTAG7 samples, which were used for quantification (E: enhancer, P: promoter, SE: constituent). C, Impact of Mediator loss on CTCF-CTCF contact strength as
negative control. Bracket: number of quantified contacts. Violin plot elements: approximated density distribution with internal box plots showing medians with interquartile range and 1.5x
whiskers. D, Impact of MED14 degradation on H3K27 acetylation. E, Pulldown-independent 4C-seq analysis of MYB SE constituent viewpoint (VP) after 2 h MED14 degradation in triplicates. Top
track shows KBM7 wild-type H3K27ac ChIP-seq. TE: typical enhancer, SE: super-enhancer F, Analogous to (E) with a SATB1 SE viewpoint. Unprocessed western blot shown in Source Data. Source
Data EXTENDED DATA FIG. 5 IMPACT OF MED14 DEGRADATION ON POL II CLUSTERS AND NASCENT TRANSCRIPTION DYNAMICS. A, Image quantification related to Fig. 3c. Pie chart: percent of n = 100 large
Pol II foci, which overlap MED14-dTAG foci. Mean±s.e.m. with two-sided, unpaired t-test (n = 40 nuclei in DMSO; n = 36 nuclei in dTAG7 condition). B, Control imaging experiment related to
Fig. 3c, omitting anti-HA primary antibody to rule out that Pol II foci are an HA channel bleed through artifact. C, Immunofluorescence of large hypo-phosphorylated Pol II foci (8WG16;
arrows) in MED14-dTAG KBM7 cells. Maximum intensity projections of 3D images. Scale bars 1 µm. Pie chart: percent of n = 60 large Pol II foci, which overlap MED14-dTAG foci. Dot plots:
changes in number of large Pol II foci per cell and integrated nuclear fluorescence intensity. Mean±s.e.m. with unpaired, two-sided t-tests (n = 94 nuclei for DMSO; n = 89 for dTAG7). D,
PRO-seq signal of auto-regulatory TFs _MYC_ and _MYB_, and the expression-matched control gene _RAB3GAP1_ after 1 h MED14 degradation. Arrows highlight loss of promoter-proximal signal.
H3K4me3 and H3K27ac ChIP-seq signal from KBM7 wild-type cells. E, Aggregated PRO-seq coverage over an SE-proximal metagene. TSS, transcription start site; TES, transcription end site. F,
Changes in PRO-seq pausing index at n = 7,643 genes after 1 h MED14 degradation. G, Observed vs. expected median Euclidean distance of auto-regulatory TFs from the pause-initiation limit in
Fig. 3f. The expected distribution was generated by randomly selecting the same number of genes from bulk. H, Changes in productive initiation rate and pause duration of all 6,791 genes vs.
the 24 auto-regulatory TFs. Productive initiation rates selectively decrease for auto-regulatory TFs, while pause duration decreases globally. Box plot elements: medians with interquartile
range and 1.5x whiskers. EXTENDED DATA FIG. 6 UNBIASED PROTEOMICS REVEAL INCREASED P-TEFB LEVELS ON CHROMATIN. A, Overlap of three independent data analyses to detect high-confidence
differentially chromatin-bound proteins (p < 0.1; see Supplementary Note). B,C, Differential chromatin binding of transcription regulators. Class averages are shown in B. Scratched boxes
indicate missing values. GTFs: general transcription factors. D, Salt-based fractionation of 7SK- and chromatin-bound P-TEFb complexes. Unprocessed western blot shown in Source Data. Source
Data EXTENDED DATA FIG. 7 P-TEFB ACTIVATION SHAPES THE TRANSCRIPTIONAL RESPONSE TO MEDIATOR LOSS. A, PRO-seq read-through upon 2 h MED14 degradation. Additionally inhibiting CDK9 with 500 nM
NVP2 in the last 30 min reverses the read-through. Zoom-ins show 30 kb windows around the polyadenylation site. Arrows highlight transcription start site (TSS) regions shown in G. B,
Aggregated PRO-seq coverages show read-through even for long genes, where newly initiated Pol II has not yet reached the termination site. Mean±bootstrapped confidence region. C, Aggregated
TT-seq coverages show read-through transcription after MED14 degradation also in HCT-116 cells. D,E, Changes in PRO-seq pausing index of all n = 5,558 genes (D) and calculated pause duration
at all n = 6,954 transcription units (E) after MED14/CDK9 perturbation. F, Changes in productive initiation rates for all n = 6,954 transcription units. Box plot elements: medians with
interquartile range, 1.5x whiskers and confidence region notches. G, PRO-seq signal around transcription start sites (TSS) of two non-SE and one auto-regulatory TF gene. Paused polymerase
does not re-accumulate at the _MYB_ TSS upon combined MED14/CDK9 perturbation. H, TT-seq SE-gene set enrichment upon combined MED14/CDK9 perturbation. Less significant enrichment confirms
that CDK9 activity aggravated the SE-selectivity of Mediator disruption. SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION Supplementary Note REPORTING SUMMARY SUPPLEMENTARY TABLES
Supplementary Tables 1–8 SOURCE DATA SOURCE DATA FIG. 1 Unprocessed western blots for Fig. 1b. SOURCE DATA FIG. 4 Unprocessed western blots for Fig. 4b,c. SOURCE DATA EXTENDED DATA FIG. 1
Unprocessed western blots for Extended Data Fig. 1b,c,g. SOURCE DATA EXTENDED DATA FIG. 2 Unprocessed western blots for Extended Data Fig. 2b,e. SOURCE DATA EXTENDED DATA FIG. 3 Unprocessed
western blots for Extended Data Fig. 3b. SOURCE DATA EXTENDED DATA FIG. 4 Unprocessed western blots for Extended Data Fig. 4d. SOURCE DATA EXTENDED DATA FIG. 6 Unprocessed western blots for
Extended Data Fig. 6d. RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Jaeger, M.G., Schwalb, B., Mackowiak, S.D. _et al._ Selective Mediator dependence
of cell-type-specifying transcription. _Nat Genet_ 52, 719–727 (2020). https://doi.org/10.1038/s41588-020-0635-0 Download citation * Received: 02 December 2019 * Accepted: 24 April 2020 *
Published: 01 June 2020 * Issue Date: July 2020 * DOI: https://doi.org/10.1038/s41588-020-0635-0 SHARE THIS ARTICLE Anyone you share the following link with will be able to read this
content: Get shareable link Sorry, a shareable link is not currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative