Enhancers display constrained sequence flexibility and context-specific modulation of motif function.

The information about when and where each gene is to be expressed is mainly encoded in the DNA sequence of enhancers, sequence elements that comprise binding sites (motifs) for different transcription factors (TFs). Most of the research on enhancer sequences has been focused on TF motif presence, whereas the enhancer syntax, that is, the flexibility of important motif positions and how the sequence context modulates the activity of TF motifs, remains poorly understood. Here, we explore the rules of enhancer syntax by a two-pronged approach in Drosophila melanogaster S2 cells: we (1) replace important TF motifs by all possible 65,536 eight-nucleotide-long sequences and (2) paste eight important TF motif types into 763 positions within 496 enhancers. These complementary strategies reveal that enhancers display constrained sequence flexibility and the context-specific modulation of motif function. Important motifs can be functionally replaced by hundreds of sequences constituting several distinct motif types, but these are only a fraction of all possible sequences and motif types. Moreover, TF motifs contribute with different intrinsic strengths that are strongly modulated by the enhancer sequence context (the flanking sequence, the presence and diversity of other motif types, and the distance between motifs), such that not all motif types can work in all positions. The context-specific modulation of motif function is also a hallmark of human enhancers, as we demonstrate experimentally. Overall, these two general principles of enhancer sequences are important to understand and predict enhancer function during development, evolution, and in disease.

Transcriptional regulators form diverse groups with context-dependent regulatory functions.

One of the most important questions in biology is how transcription factors (TFs) and cofactors control enhancer function and thus gene expression. Enhancer activation usually requires combinations of several TFs, indicating that TFs function synergistically and combinatorially. However, while TF binding has been extensively studied, little is known about how combinations of TFs and cofactors control enhancer function once they are bound. It is typically unclear which TFs participate in combinatorial enhancer activation, whether different TFs form functionally distinct groups, or if certain TFs might substitute for each other in defined enhancer contexts. Here we assess the potential regulatory contributions of TFs and cofactors to combinatorial enhancer control with enhancer complementation assays. We recruited GAL4-DNA-binding-domain fusions of 812 Drosophila TFs and cofactors to 24 enhancer contexts and measured enhancer activities by 82,752 luciferase assays in S2 cells. Most factors were functional in at least one context, yet their contributions differed between contexts and varied from repression to activation (up to 289-fold) for individual factors. Based on functional similarities across contexts, we define 15 groups of TFs that differ in developmental functions and protein sequence features. Similar TFs can substitute for each other, enabling enhancer re-engineering by exchanging TF motifs, and TF-cofactor pairs cooperate during enhancer control and interact physically. Overall, we show that activators and repressors can have diverse regulatory functions that typically depend on the enhancer context. The systematic functional characterization of TFs and cofactors should further our understanding of combinatorial enhancer control and gene regulation.

DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers.

Enhancer sequences control gene expression and comprise binding sites (motifs) for different transcription factors (TFs). Despite extensive genetic and computational studies, the relationship between DNA sequence and regulatory activity is poorly understood, and de novo enhancer design has been challenging. Here, we built a deep-learning model, DeepSTARR, to quantitatively predict the activities of thousands of developmental and housekeeping enhancers directly from DNA sequence in Drosophila melanogaster S2 cells. The model learned relevant TF motifs and higher-order syntax rules, including functionally nonequivalent instances of the same TF motif that are determined by motif-flanking sequence and intermotif distances. We validated these rules experimentally and demonstrated that they can be generalized to humans by testing more than 40,000 wildtype and mutant Drosophila and human enhancers. Finally, we designed and functionally validated synthetic enhancers with desired activities de novo.

Migratory and anti-fibrotic programmes define the regenerative potential of human cardiac progenitors.

Heart regeneration is an unmet clinical need, hampered by limited renewal of adult cardiomyocytes and fibrotic scarring. Pluripotent stem cell-based strategies are emerging, but unravelling cellular dynamics of host-graft crosstalk remains elusive. Here, by combining lineage tracing and single-cell transcriptomics in injured non-human primate heart biomimics, we uncover the coordinated action modes of human progenitor-mediated muscle repair. Chemoattraction via CXCL12/CXCR4 directs cellular migration to injury sites. Activated fibroblast repulsion targets fibrosis by SLIT2/ROBO1 guidance in organizing cytoskeletal dynamics. Ultimately, differentiation and electromechanical integration lead to functional restoration of damaged heart muscle. In vivo transplantation into acutely and chronically injured porcine hearts illustrated CXCR4-dependent homing, de novo formation of heart muscle, scar-volume reduction and prevention of heart failure progression. Concurrent endothelial differentiation contributed to graft neovascularization. Our study demonstrates that inherent developmental programmes within cardiac progenitors are sequentially activated in disease, enabling the cells to sense and counteract acute and chronic injury.

Combinatorial function of transcription factors and cofactors.

Differential gene expression gives rise to the many cell types of complex organisms. Enhancers regulate transcription by binding transcription factors (TFs), which in turn recruit cofactors to activate RNA Polymerase II at core promoters. Transcriptional regulation is typically mediated by distinct combinations of TFs, enabling a relatively small number of TFs to generate a large diversity of cell types. However, how TFs achieve combinatorial enhancer control and how enhancers, enhancer-bound TFs, and the cofactors they recruit regulate RNA Polymerase II activity is not entirely clear. Here, we review how TF synergy is mediated at the level of DNA binding and after binding, the role of cofactors and the post-translational modifications they catalyze, and discuss different models of enhancer-core-promoter communication.