Differential cofactor dependencies define distinct types of human enhancers

Neumayr, Christoph; Haberle, Vanja; Serebreni, Leonid; Karner, Katharina; Hendy, Oliver; Boija, Ann; Henninger, Jonathan E.; Li, Charles Han; Stejskal, Karel; Lin, Gen; Bergauer, Katharina; Pagani, Michaela; Rath, Martina; Mechtler, Karl; Arnold, Cosmas D.; Stark, Alexander

doi:10.1038/s41586-022-04779-x

Cited by 65 publications

(71 citation statements)

References 74 publications

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“…The current paradigm of how enhancers yield spatiotemporal gene expression is that they act as binding platforms for specific combinations of transcription factors (TF), that can be activators, repressors, or neutral/pioneering TFs. Cooperative or hierarchical binding of multiple TFs results in nucleosome eviction at the enhancer, followed by cofactor recruitment and interaction with other enhancers, with the proximal promoter, and with RNA polymerase, through which the rate of transcription initiation is modulated [1][2][3][4] . Cell type specific expression of a target gene is achieved when a unique combination of TFs activates a specific enhancer; while this enhancer remains either passively ("default-off" 5,6 ) or actively repressed in other cell types (e.g., via repressor binding 7 or co-repressor/polycomb recruitment).…”

Section: Introductionmentioning

confidence: 99%

Cell type directed design of synthetic enhancers

Taskiran

Spanier

Christiaens

et al. 2022

Preprint

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Transcriptional enhancers act as docking stations for combinations of transcription factors and thereby regulate spatiotemporal activation of their target genes. A single enhancer, of a few hundred base pairs in length, can autonomously and independently of its location and orientation drive cell-type specific expression of a gene or transgene. It has been a long-standing goal in the field to decode the regulatory logic of an enhancer and to understand the details of how spatiotemporal gene expression is encoded in an enhancer sequence. Recently, deep learning models have yielded unprecedented insight into the enhancer code, and well-trained models are reaching a level of understanding that may be close to complete. As a consequence, we hypothesized that deep learning models can be used to guide the directed design of synthetic, cell type specific enhancers, and that this process would allow for a detailed tracing of all enhancer features at nucleotide-level resolution. Here we implemented and compared three different design strategies, each built on a deep learning model: (1) directed sequence evolution; (2) directed iterative motif implanting; and (3) generative design. We evaluated the function of fully synthetic enhancers to specifically target Kenyon cells in the fruit fly brain using transgenic animals. We then exploited this concept further by creating "dual-code" enhancers that target two cell types, and minimal enhancers smaller than 50 base pairs that are fully functional. By examining the trajectories followed during state space searches towards functional enhancers, we could accurately define the enhancer code as the optimal strength, combination, and relative distance of TF activator motifs, and the absence of TF repressor motifs. Finally, we applied the same three strategies to successfully design human enhancers. In conclusion, enhancer design guided by deep learning leads to better understanding of how enhancers work and shows that their code can be exploited to manipulate cell states.

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Section: Introductionmentioning

confidence: 99%

Cell type directed design of synthetic enhancers

Taskiran

Spanier

Christiaens

et al. 2022

Preprint

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“…We hypothesize that the effects of MED12 and CCNC deletion are highly context dependent, because we observed increased glycolytic rates in MED12 - and CCNC -deficient effector T cells, consistent with enhanced effector activity, whereas previous studies in cancer have demonstrated diminished glycolytic activity in several cancers following small-molecule mediated inhibition of CDK8 ( 62 ). The selectivity of the effects is not fully understood, but may be explained in part by the newly reported finding that enhancers have varying degrees of dependence on Mediator for transcriptional activation, determined by the presence of sequence-specific transcription factors and other chromatin characteristics ( 63 ).…”

Section: Discussionmentioning

confidence: 99%

Enhanced T cell effector activity by targeting the Mediator kinase module

Freitas

Sotillo

Quinn

et al. 2022

Science

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T cells are the major arm of the immune system responsible for controlling and regressing cancers. To identify genes limiting T cell function, we conducted genome-wide CRISPR knockout screens in human chimeric antigen receptor (CAR) T cells. Top hits were MED12 and CCNC , components of the Mediator kinase module. Targeted MED12 deletion enhanced antitumor activity and sustained the effector phenotype in CAR- and T cell receptor–engineered T cells, and inhibition of CDK8/19 kinase activity increased expansion of nonengineered T cells. MED12 -deficient T cells manifested increased core Meditator chromatin occupancy at transcriptionally active enhancers—most notably for STAT and AP-1 transcription factors—and increased IL2RA expression and interleukin-2 sensitivity. These results implicate Mediator in T cell effector programming and identify the kinase module as a target for enhancing potency of antitumor T cell responses.

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“…Recently it was shown that different groups of human enhancers require different COFs 21 . To evaluate the requirement of CBP/p300 enhancer activity in STARR-seq, we re-analyzed the published data.…”

Section: Discussionmentioning

confidence: 99%

“…COF-AID STARR-seq regions were downloaded from the supplemental information of Neumayr et.al. 21 . HCT116 ATAC-seq data were downloaded from the GEO portal (GSE97889).…”

Section: Evaluating Chromatin Accessibility Of Cof-aid Starr-seq Regionsmentioning

confidence: 99%

“…In massively parallel reporter assays (MPRAs), a majority of Drosophila and mouse enhancers show promoter specificity 18, 19 , and the compatibility information appears to be sequence-encoded in the enhancers and promoters 18, 20 . Supporting E-P specificity, different groups of human enhancers use different cofactors (COFs) 21 , and different COFs activate different promoters in Drosophila 22 . These findings present two seemingly diverging models of enhancer specificity.…”

Section: Introductionmentioning

confidence: 99%

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The logic of native enhancer-promoter compatibility and cell-type-specific gene expression variation

Narita

Higashijima

Kilic

et al. 2022

Preprint

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Cis-regulatory enhancers are essential for differential expression of developmental and housekeeping genes. However, the specificity of native mammalian enhancers and how it shapes cell-type-specific gene expression landscapes remain largely unknown. We show that endogenous enhancers are broadly compatible with the promoters of developmental and housekeeping genes. Broad enhancer compatibility affords ‘retrofitting’ new regulatory capabilities to housekeeping genes that evolved before the advent of enhancers. This enables cell-type-specific tuning of ubiquitously expressed genes. Segregation between enhancer-dependent and –independent type regulation is blurred. Within the same cell type, a single promoter can be activated by enhancers and non-enhancer promoter-regulatory elements (PREs). It is the tunable and integrated strengths of enhancers and PREs that quantitatively shape gene expression landscapes, within and across cell types. Our findings have broad implications for understanding cell-type-specific quantitative gene expression variation, as well as the emergence and rewiring of gene regulatory networks in disease and organismal evolution.

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Differential cofactor dependencies define distinct types of human enhancers

Cited by 65 publications

References 74 publications

Cell type directed design of synthetic enhancers

Cell type directed design of synthetic enhancers

Enhanced T cell effector activity by targeting the Mediator kinase module

The logic of native enhancer-promoter compatibility and cell-type-specific gene expression variation

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