Syntax compensates for poor binding sites to encode tissue specificity of developmental enhancers

Optimization of the Irf8 +32-kb enhancer disrupts dendritic cell lineage segregation

Autoactivation of lineage-determining transcription factors mediates bistable expression, generating distinct cell phenotypes essential for complex body plans. Classical type 1 dendritic cell (cDC1) and type 2 dendritic cell (cDC2) subsets provide nonredundant functions for defense against distinct immune challenges. Interferon regulatory factor 8 (IRF8), the cDC1 lineage-determining transcription factor, undergoes autoactivation in cDC1 progenitors to establish cDC1 identity, yet its expression is downregulated during cDC2 differentiation by an unknown mechanism. This study reveals that the Irf8 +32-kb enhancer, responsible for IRF8 autoactivation, is naturally suboptimized with low-affinity IRF8 binding sites. Introducing multiple high-affinity IRF8 sites into the Irf8 +32-kb enhancer causes a gain-of-function effect, leading to erroneous IRF8 autoactivation in specified cDC2 progenitors, redirecting them toward cDC1 and a novel hybrid DC subset with mixed-lineage phenotypes. Further, this also causes a loss-of-function effect, reducing Irf8 expression in cDC1s. These developmental alterations critically impair both cDC1-dependent and cDC2-dependent arms of immunity. Collectively, our findings underscore the significance of enhancer suboptimization in the developmental segregation of cDCs required for normal immune function.

Combinatorial transcription factor binding encodes cis-regulatory wiring of mouse forebrain GABAergic neurogenesis

Transcription factors (TFs) bind combinatorially to cis-regulatory elements, orchestrating transcriptional programs. Although studies of chromatin state and chromosomal interactions have demonstrated dynamic neurodevelopmental cis-regulatory landscapes, parallel understanding of TF interactions lags. To elucidate combinatorial TF binding driving mouse basal ganglia development, we integrated chromatin immunoprecipitation sequencing (ChIP-seq) for twelve TFs, H3K4me3-associated enhancer-promoter interactions, chromatin and gene expression data, and functional enhancer assays. We identified sets of putative regulatory elements with shared TF binding (TF-pRE modules) that orchestrate distinct processes of GABAergic neurogenesis and suppress other cell fates. The majority of pREs were bound by one or two TFs; however, a small proportion were extensively bound. These sequences had exceptional evolutionary conservation and motif density, complex chromosomal interactions, and activity as in vivo enhancers. Our results provide insights into the combinatorial TF-pRE interactions that activate and repress expression programs during telencephalon neurogenesis and demonstrate the value of TF binding toward modeling developmental transcriptional wiring.

A change in cis-regulatory logic underlying obligate versus facultative muscle multinucleation in chordates

Vertebrates and tunicates are sister groups that share a common fusogenic factor, Myomaker (Mymk), that drives myoblast fusion and muscle multinucleation. Yet they are divergent in when and where they express Mymk. In vertebrates, all developing skeletal muscles express Mymk and are obligately multinucleated. In tunicates, Mymk is expressed only in post-metamorphic multinucleated muscles, but is absent from mononucleated larval muscles. In this study, we demonstrate that cis-regulatory sequence differences in the promoter region of Mymk underlie the different spatiotemporal patterns of its transcriptional activation in tunicates and vertebrates. Although in vertebrates myogenic regulatory factors (MRFs) such as MyoD1 alone are required and sufficient for Mymk transcription in all skeletal muscles, we show that transcription of Mymk in post-metamorphic muscles of the tunicate Ciona requires the combinatorial activity of MRF, MyoD and Early B-cell Factor (Ebf). This macroevolutionary difference appears to be encoded in cis, likely due to the presence of a putative Ebf-binding site adjacent to predicted MRF binding sites in the Ciona Mymk promoter. We further discuss how Mymk and myoblast fusion might have been regulated in the last common ancestor of tunicates and vertebrates, for which we propose two models.

Protocol to electroporate DNA plasmids into Ciona robusta embryos at the 1-cell stage

Electroporation is a technique to introduce DNA constructs into cells using electric current. Here, we present a protocol to electroporate DNA plasmids into Ciona robusta embryos at the 1-cell stage. We describe steps for setting up and conducting electroporation. We then detail procedures for collecting, fixing, and mounting embryos and counting expression. This protocol can be used to study the expression of enhancers via reporter assays, manipulating cells using genes or modified genes such as dominant negatives, and genome editing. For complete details on the use and execution of this protocol, please refer to Song, et al.1.

Mutagenesis Sensitivity Mapping of Human Enhancers In Vivo

Distant-acting enhancers are central to human development. However, our limited understanding of their functional sequence features prevents the interpretation of enhancer mutations in disease. Here, we determined the functional sensitivity to mutagenesis of human developmental enhancers in vivo. Focusing on seven enhancers active in the developing brain, heart, limb and face, we created over 1700 transgenic mice for over 260 mutagenized enhancer alleles. Systematic mutation of 12-basepair blocks collectively altered each sequence feature in each enhancer at least once. We show that 69% of all blocks are required for normal in vivo activity, with mutations more commonly resulting in loss (60%) than in gain (9%) of function. Using predictive modeling, we annotated critical nucleotides at base-pair resolution. The vast majority of motifs predicted by these machine learning models (88%) coincided with changes to in vivo function, and the models showed considerable sensitivity, identifying 59% of all functional blocks. Taken together, our results reveal that human enhancers contain a high density of sequence features required for their normal in vivo function and provide a rich resource for further exploration of human enhancer logic.

Anatomy of a superenhancer

Interferon regulatory factor-8 (IRF8) is the lineage determining transcription factor for the type one classical dendritic cell (cDC1) subset, a terminal selector for plasmacytoid dendritic cells and important for the function of monocytes. Studies of Irf8 gene regulation have identified several enhancers controlling its activity during development of progenitors in the bone marrow that precisely regulate expression at distinct developmental stages. Each enhancer responds to distinct transcription factors that are expressed at each stage. IRF8 is first expressed in early progenitors that form the monocyte dendritic cell progenitor (MDP) in response to induction of the transcription factor CCAAT/enhancer-binding protein alpha (C/EBPα) acting at the Irf8 +56 kb enhancer. IRF8 levels increase further as the MDP transits into the common dendritic cell progenitor (CDP) in response to E protein activity at the Irf8 +41 kb enhancer. Upon Nfil3-induction in CDPs leading to specification of the cDC1 progenitor, abrupt induction of BATF3 forms the JUN/BATF3/IRF8 heterotrimer that activates the Irf8 +32 kb enhancer that sustains Irf8 autoactivation throughout the cDC1 lifetime. Deletions of each of these enhancers has revealed their stage dependent activation. Surprisingly, studies of compound heterozygotes for each combination of enhancer deletions revealed that activation of each subsequent enhancer requires the successful activation of the previous enhancer in strictly cis-dependent mechanism. Successful progression of enhancer activation is finely tuned to alter the functional accessibility of subsequent enhancers to factors active in the next stage of development. The molecular basis for these phenomenon is still obscure but could have implications for genomic regulation in a broader developmental context.

Synergistic activation by Glass and Pointed promotes neuronal identity in the Drosophila eye disc

The integration of extrinsic signaling with cell-intrinsic transcription factors can direct progenitor cells to differentiate into distinct cell fates. In the developing Drosophila eye, differentiation of photoreceptors R1-R7 requires EGFR signaling mediated by the transcription factor Pointed, and our single-cell RNA-Seq analysis shows that the same photoreceptors require the eye-specific transcription factor Glass. We find that ectopic expression of Glass and activation of EGFR signaling synergistically induce neuronal gene expression in the wing disc in a Pointed-dependent manner. Targeted DamID reveals that Glass and Pointed share many binding sites in the genome of developing photoreceptors. Comparison with transcriptomic data shows that Pointed and Glass induce photoreceptor differentiation through intermediate transcription factors, including the redundant homologs Scratch and Scrape, as well as directly activating neuronal effector genes. Our data reveal synergistic activation of a multi-layered transcriptional network as the mechanism by which EGFR signaling induces neuronal identity in Glass-expressing cells.

Gene regulation in regeneration after acute kidney injury

Acute kidney injury (AKI) is a common condition associated with significant morbidity, mortality, and cost. Injured kidney tissue can regenerate after many forms of AKI. However, there are no treatments in routine clinical practice to encourage recovery. In part, this shortcoming is due to an incomplete understanding of the genetic mechanisms that orchestrate kidney recovery. The advent of high-throughput sequencing technologies and genetic mouse models has opened an unprecedented window into the transcriptional dynamics that accompany both successful and maladaptive repair. AKI recovery shares similar cell-state transformations with kidney development, which can suggest common mechanisms of gene regulation. Several powerful bioinformatic strategies have been developed to infer the activity of gene regulatory networks by combining multiple forms of sequencing data at single-cell resolution. These studies highlight not only shared stress responses but also key changes in gene regulatory networks controlling metabolism. Furthermore, chromatin immunoprecipitation studies in injured kidneys have revealed dynamic epigenetic modifications at enhancer elements near target genes. This review will highlight how these studies have enhanced our understanding of gene regulation in injury response and regeneration.

Plant enhancers exhibit both cooperative and additive interactions among their functional elements

Enhancers are cis-regulatory elements that shape gene expression in response to numerous developmental and environmental cues. In animals, several models have been proposed to explain how enhancers integrate the activity of multiple transcription factors. However, it remains largely unclear how plant enhancers integrate transcription factor activity. Here, we use Plant STARR-seq to characterize 3 light-responsive plant enhancers-AB80, Cab-1, and rbcS-E9-derived from genes associated with photosynthesis. Saturation mutagenesis revealed mutations, many of which clustered in short regions, that strongly reduced enhancer activity in the light, in the dark, or in both conditions. When tested in the light, these mutation-sensitive regions did not function on their own; rather, cooperative interactions with other such regions were required for full activity. Epistatic interactions occurred between mutations in adjacent mutation-sensitive regions, and the spacing and order of mutation-sensitive regions in synthetic enhancers affected enhancer activity. In contrast, when tested in the dark, mutation-sensitive regions acted independently and additively in conferring enhancer activity. Taken together, this work demonstrates that plant enhancers show evidence for both cooperative and additive interactions among their functional elements. This knowledge can be harnessed to design strong, condition-specific synthetic enhancers.

Context dependent activity of p63-bound gene regulatory elements

The p53 family of transcription factors regulate numerous organismal processes including the development of skin and limbs, ciliogenesis, and preservation of genetic integrity and tumor suppression. p53 family members control these processes and gene expression networks through engagement with DNA sequences within gene regulatory elements. Whereas p53 binding to its cognate recognition sequence is strongly associated with transcriptional activation, p63 can mediate both activation and repression. How the DNA sequence of p63-bound gene regulatory elements is linked to these varied activities is not yet understood. Here, we use massively parallel reporter assays (MPRA) in a range of cellular and genetic contexts to investigate the influence of DNA sequence on p63-mediated transcription. Most regulatory elements with a p63 response element motif (p63RE) activate transcription, with those sites bound by p63 more frequently or adhering closer to canonical p53 family response element sequences driving higher transcriptional output. The most active regulatory elements are those also capable of binding p53. Elements uniquely bound by p63 have varied activity, with p63RE-mediated repression associated with lower overall GC content in flanking sequences. Comparison of activity across cell lines suggests differential activity of elements may be regulated by a combination of p63 abundance or context-specific cofactors. Finally, changes in p63 isoform expression dramatically alters regulatory element activity, primarily shifting inactive elements towards a strong p63-dependent activity. Our analysis of p63-bound gene regulatory elements provides new insight into how sequence, cellular context, and other transcription factors influence p63-dependent transcription. These studies provide a framework for understanding how p63 genomic binding locally regulates transcription. Additionally, these results can be extended to investigate the influence of sequence content, genomic context, chromatin structure on the interplay between p63 isoforms and p53 family paralogs.

Lineage-determining transcription factor-driven promoters regulate cell type-specific macrophage gene expression

Mammalian promoters consist of multifarious elements, which make them unique and support the selection of the proper transcript variants required under diverse conditions in distinct cell types. However, their direct DNA-transcription factor (TF) interactions are mostly unidentified. Murine bone marrow-derived macrophages (BMDMs) are a widely used model for studying gene expression regulation. Thus, this model serves as a rich source of various next-generation sequencing data sets, including a large number of TF cistromes. By processing and integrating the available cistromic, epigenomic and transcriptomic data from BMDMs, we characterized the macrophage-specific direct DNA-TF interactions, with a particular emphasis on those specific for promoters. Whilst active promoters are enriched for certain types of typically methylatable elements, more than half of them contain non-methylatable and prototypically promoter-distal elements. In addition, circa 14% of promoters-including that of Csf1r-are composed exclusively of 'distal' elements that provide cell type-specific gene regulation by specialized TFs. Similar to CG-rich promoters, these also contain methylatable CG sites that are demethylated in a significant portion and show high polymerase activity. We conclude that this unusual class of promoters regulates cell type-specific gene expression in macrophages, and such a mechanism might exist in other cell types too.

Cis-regulatory interfaces reveal the molecular mechanisms underlying the notochord gene regulatory network of Ciona

Tissue-specific gene expression is fundamental in development and evolution, and is mediated by transcription factors and by the cis-regulatory regions (enhancers) that they control. Transcription factors and their respective tissue-specific enhancers are essential components of gene regulatory networks responsible for the development of tissues and organs. Although numerous transcription factors have been characterized from different organisms, the knowledge of the enhancers responsible for their tissue-specific expression remains fragmentary. Here we use Ciona to study the enhancers associated with ten transcription factors expressed in the notochord, an evolutionary hallmark of the chordate phylum. Our results illustrate how two evolutionarily conserved transcription factors, Brachyury and Foxa2, coordinate the deployment of other notochord transcription factors. The results of these detailed cis-regulatory analyses delineate a high-resolution view of the essential notochord gene regulatory network of Ciona, and provide a reference for studies of transcription factors, enhancers, and their roles in development, disease, and evolution.

A change in cis-regulatory logic underlying obligate versus facultative muscle multinucleation in chordates

Vertebrates and tunicates are sister groups that share a common fusogenic factor, Myomaker (Mymk), that drives myoblast fusion and muscle multinucleation. Yet they are divergent in when and where they express Mymk. In vertebrates, all developing skeletal muscles express Mymk and are obligately multinucleated. In tunicates, Mymk is only expressed in post-metamorphic multinucleated muscles, but is absent from mononucleated larval muscles. In this study, we demonstrate that cis-regulatory sequence differences in the promoter region of Mymk underlie the different spatiotemporal patterns of its transcriptional activation in tunicates and vertebrates. While in vertebrates Myogenic Regulatory Factors (MRFs) like MyoD1 alone are required and sufficient for Mymk transcription in all skeletal muscles, we show that transcription of Mymk in post-metamorphic muscles of the tunicate Ciona requires the combinatorial activity of MRF/MyoD and Early B-Cell Factor (Ebf). This macroevolutionary difference appears to be encoded in cis, likely due to the presence of a putative Ebf binding site adjacent to predicted MRF binding sites in the Ciona Mymk promoter. We further discuss how Mymk and myoblast fusion might have been regulated in the last common ancestor of tunicates and vertebrates, for which we propose two models.

Affinity-optimizing enhancer variants disrupt development

Enhancers control the location and timing of gene expression and contain the majority of variants associated with disease1-3. The ZRS is arguably the most well-studied vertebrate enhancer and mediates the expression of Shh in the developing limb4. Thirty-one human single-nucleotide variants (SNVs) within the ZRS are associated with polydactyly4-6. However, how this enhancer encodes tissue-specific activity, and the mechanisms by which SNVs alter the number of digits, are poorly understood. Here we show that the ETS sites within the ZRS are low affinity, and identify a functional ETS site, ETS-A, with extremely low affinity. Two human SNVs and a synthetic variant optimize the binding affinity of ETS-A subtly from 15% to around 25% relative to the strongest ETS binding sequence, and cause polydactyly with the same penetrance and severity. A greater increase in affinity results in phenotypes that are more penetrant and more severe. Affinity-optimizing SNVs in other ETS sites in the ZRS, as well as in ETS, interferon regulatory factor (IRF), HOX and activator protein 1 (AP-1) sites within a wide variety of enhancers, cause gain-of-function gene expression. The prevalence of binding sites with suboptimal affinity in enhancers creates a vulnerability in genomes whereby SNVs that optimize affinity, even slightly, can be pathogenic. Searching for affinity-optimizing SNVs in genomes could provide a mechanistic approach to identify causal variants that underlie enhanceropathies.

Homeodomain complex formation and biomolecular condensates in Hox gene regulation

Hox genes are a family of homeodomain transcription factors that regulate specialized morphological structures along the anterior-posterior axis of metazoans. Over the past few decades, researchers have focused on defining how Hox factors with similar in vitro DNA binding activities achieve sufficient target specificity to regulate distinct cell fates in vivo. In this review, we highlight how protein interactions with other transcription factors, many of which are also homeodomain proteins, result in the formation of transcription factor complexes with enhanced DNA binding specificity. These findings suggest that Hox-regulated enhancers utilize distinct combinations of homeodomain binding sites, many of which are low-affinity, to recruit specific Hox complexes. However, low-affinity sites can only yield reproducible responses with high transcription factor concentrations. To overcome this limitation, recent studies revealed how transcription factors, including Hox factors, use intrinsically disordered domains (IDRs) to form biomolecular condensates that increase protein concentrations. Moreover, Hox factors with altered IDRs have been associated with altered transcriptional activity and human disease states, demonstrating the importance of IDRs in mediating essential Hox output. Collectively, these studies highlight how Hox factors use their DNA binding domains, protein-protein interaction domains, and IDRs to form specific transcription factor complexes that yield accurate gene expression.

A molecular toolbox to study progesterone receptor signaling

Progesterone receptor (PR) signaling is required for mammary gland development and homeostasis. A major bottleneck in studying PR signaling is the lack of sensitive assays to measure and visualize PR pathway activity both quantitatively and spatially. Here, we develop new tools to study PR signaling in human breast epithelial cells. First, we generate optimized Progesterone Responsive Element (PRE)-luciferase constructs and demonstrate that these new reporters are a powerful tool to quantify PR signaling activity across a wide range of progesterone concentrations in two luminal breast cancer cell lines, MCF7 and T47D. We also describe a fluorescent lentiviral PRE-GFP reporter as a novel tool to visualize PR signaling at the single-cell level. Our reporter constructs are sensitive to physiological levels of progesterone. Second, we show that low background signaling, and high levels of PR expression are a prerequisite for robustly measuring PR signaling. Increasing PR expression by transient transfection, stable overexpression in MCF7 or clonal selection in T47D, drastically improves both the dynamic range of luciferase reporter assays, and the induction of endogenous PR target genes as measured by qRT-PCR. We find that the PR signaling response differs per cell line, target gene and hormone concentration used. Taken together, our tools allow a more rationally designed approach for measuring PR signaling in breast epithelial cells.

Single-nucleotide variants within heart enhancers increase binding affinity and disrupt heart development

Transcriptional enhancers direct precise gene expression patterns during development and harbor the majority of variants associated with phenotypic diversity, evolutionary adaptations, and disease. Pinpointing which enhancer variants contribute to changes in gene expression and phenotypes is a major challenge. Here, we find that suboptimal or low-affinity binding sites are necessary for precise gene expression during heart development. Single-nucleotide variants (SNVs) can optimize the affinity of ETS binding sites, causing gain-of-function (GOF) gene expression, cell migration defects, and phenotypes as severe as extra beating hearts in the marine chordate Ciona robusta. In human induced pluripotent stem cell (iPSC)-derived cardiomyocytes, a SNV within a human GATA4 enhancer increases ETS binding affinity and causes GOF enhancer activity. The prevalence of suboptimal-affinity sites within enhancers creates a vulnerability whereby affinity-optimizing SNVs can lead to GOF gene expression, changes in cellular identity, and organismal-level phenotypes that could contribute to the evolution of novel traits or diseases.

Unique activities of two overlapping PAX6 retinal enhancers

Enhancers play a critical role in development by precisely modulating spatial, temporal, and cell type-specific gene expression. Sequence variants in enhancers have been implicated in diseases; however, establishing the functional consequences of these variants is challenging because of a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development, with a regulatory landscape containing multiple enhancers driving the expression in the eye. Whether these enhancers perform additive, redundant or distinct functions is unknown. Here, we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers, HS5 and NRE. Using a unique combination of live imaging and single-cell RNA sequencing in dual enhancer-reporter zebrafish embryos, we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping, these enhancers have distinct activities in different cell types and therefore likely nonredundant functions. This work demonstrates that unique cell type-specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo.

Emerging insights into enhancer biology and function

Cell type-specific gene expression is coordinated by DNA-encoded enhancers and the transcription factors (TFs) that bind to them in a sequence-specific manner. As such, these enhancers and TFs are critical mediators of normal development and altered enhancer or TF function is associated with the development of diseases such as cancer. While initially defined by their ability to activate gene transcription in reporter assays, putative enhancer elements are now frequently defined by their unique chromatin features including DNase hypersensitivity and transposase accessibility, bidirectional enhancer RNA (eRNA) transcription, CpG hypomethylation, high H3K27ac and H3K4me1, sequence-specific transcription factor binding, and co-factor recruitment. Identification of these chromatin features through sequencing-based assays has revolutionized our ability to identify enhancer elements on a genome-wide scale, and genome-wide functional assays are now capitalizing on this information to greatly expand our understanding of how enhancers function to provide spatiotemporal coordination of gene expression programs. Here, we highlight recent technological advances that are providing new insights into the molecular mechanisms by which these critical cis-regulatory elements function in gene control. We pay particular attention to advances in our understanding of enhancer transcription, enhancer-promoter syntax, 3D organization and biomolecular condensates, transcription factor and co-factor dependencies, and the development of genome-wide functional enhancer screens.

Conserved enhancers control notochord expression of vertebrate Brachyury

The cell type-specific expression of key transcription factors is central to development and disease. Brachyury/T/TBXT is a major transcription factor for gastrulation, tailbud patterning, and notochord formation; however, how its expression is controlled in the mammalian notochord has remained elusive. Here, we identify the complement of notochord-specific enhancers in the mammalian Brachyury/T/TBXT gene. Using transgenic assays in zebrafish, axolotl, and mouse, we discover three conserved Brachyury-controlling notochord enhancers, T3, C, and I, in human, mouse, and marsupial genomes. Acting as Brachyury-responsive, auto-regulatory shadow enhancers, in cis deletion of all three enhancers in mouse abolishes Brachyury/T/Tbxt expression selectively in the notochord, causing specific trunk and neural tube defects without gastrulation or tailbud defects. The three Brachyury-driving notochord enhancers are conserved beyond mammals in the brachyury/tbxtb loci of fishes, dating their origin to the last common ancestor of jawed vertebrates. Our data define the vertebrate enhancers for Brachyury/T/TBXTB notochord expression through an auto-regulatory mechanism that conveys robustness and adaptability as ancient basis for axis development.

PorcineAI-Enhancer: Prediction of Pig Enhancer Sequences Using Convolutional Neural Networks

Understanding the mechanisms of gene expression regulation is crucial in animal breeding. Cis-regulatory DNA sequences, such as enhancers, play a key role in regulating gene expression. Identifying enhancers is challenging, despite the use of experimental techniques and computational methods. Enhancer prediction in the pig genome is particularly significant due to the costliness of high-throughput experimental techniques. The study constructed a high-quality database of pig enhancers by integrating information from multiple sources. A deep learning prediction framework called PorcineAI-enhancer was developed for the prediction of pig enhancers. This framework employs convolutional neural networks for feature extraction and classification. PorcineAI-enhancer showed excellent performance in predicting pig enhancers, validated on an independent test dataset. The model demonstrated reliable prediction capability for unknown enhancer sequences and performed remarkably well on tissue-specific enhancer sequences.The study developed a deep learning prediction framework, PorcineAI-enhancer, for predicting pig enhancers. The model demonstrated significant predictive performance and potential for tissue-specific enhancers. This research provides valuable resources for future studies on gene expression regulation in pigs.

Machine-guided design of synthetic cell type-specific cis-regulatory elements

Cis-regulatory elements (CREs) control gene expression, orchestrating tissue identity, developmental timing, and stimulus responses, which collectively define the thousands of unique cell types in the body. While there is great potential for strategically incorporating CREs in therapeutic or biotechnology applications that require tissue specificity, there is no guarantee that an optimal CRE for an intended purpose has arisen naturally through evolution. Here, we present a platform to engineer and validate synthetic CREs capable of driving gene expression with programmed cell type specificity. We leverage innovations in deep neural network modeling of CRE activity across three cell types, efficient in silico optimization, and massively parallel reporter assays (MPRAs) to design and empirically test thousands of CREs. Through in vitro and in vivo validation, we show that synthetic sequences outperform natural sequences from the human genome in driving cell type-specific expression. Synthetic sequences leverage unique sequence syntax to promote activity in the on-target cell type and simultaneously reduce activity in off-target cells. Together, we provide a generalizable framework to prospectively engineer CREs and demonstrate the required literacy to write regulatory code that is fit-for-purpose in vivo across vertebrates.

DNA selection by the master transcription factor PU.1

The master transcriptional regulator PU.1/Spi-1 engages DNA sites with affinities spanning multiple orders of magnitude. To elucidate this remarkable plasticity, we have characterized 22 high-resolution co-crystallographic PU.1/DNA complexes across the addressable affinity range in myeloid gene transactivation. Over a purine-rich core (such as 5'-GGAA-3') flanked by variable sequences, affinity is negotiated by direct readout on the 5' flank via a critical glutamine (Q226) sidechain and by indirect readout on the 3' flank by sequence-dependent helical flexibility. Direct readout by Q226 dynamically specifies PU.1's characteristic preference for purines and explains the pathogenic mutation Q226E in Waldenström macroglobulinemia. The structures also reveal how disruption of Q226 mediates strand-specific inhibition by DNA methylation and the recognition of non-canonical sites, including the authentic binding sequence at the CD11b promoter. A re-synthesis of phylogenetic and structural data on the ETS family, considering the centrality of Q226 in PU.1, unifies the model of DNA selection by ETS proteins.

Decoding enhancer complexity with machine learning and high-throughput discovery

Enhancers are genomic DNA elements controlling spatiotemporal gene expression. Their flexible organization and functional redundancies make deciphering their sequence-function relationships challenging. This article provides an overview of the current understanding of enhancer organization and evolution, with an emphasis on factors that influence these relationships. Technological advancements, particularly in machine learning and synthetic biology, are discussed in light of how they provide new ways to understand this complexity. Exciting opportunities lie ahead as we continue to unravel the intricacies of enhancer function.

De novo distillation of thermodynamic affinity from deep learning regulatory sequence models of in vivo protein-DNA binding

Transcription factors (TF) are proteins that bind DNA in a sequence-specific manner to regulate gene transcription. Despite their unique intrinsic sequence preferences, in vivo genomic occupancy profiles of TFs differ across cellular contexts. Hence, deciphering the sequence determinants of TF binding, both intrinsic and context-specific, is essential to understand gene regulation and the impact of regulatory, non-coding genetic variation. Biophysical models trained on in vitro TF binding assays can estimate intrinsic affinity landscapes and predict occupancy based on TF concentration and affinity. However, these models cannot adequately explain context-specific, in vivo binding profiles. Conversely, deep learning models, trained on in vivo TF binding assays, effectively predict and explain genomic occupancy profiles as a function of complex regulatory sequence syntax, albeit without a clear biophysical interpretation. To reconcile these complementary models of in vitro and in vivo TF binding, we developed Affinity Distillation (AD), a method that extracts thermodynamic affinities de-novo from deep learning models of TF chromatin immunoprecipitation (ChIP) experiments by marginalizing away the influence of genomic sequence context. Applied to neural networks modeling diverse classes of yeast and mammalian TFs, AD predicts energetic impacts of sequence variation within and surrounding motifs on TF binding as measured by diverse in vitro assays with superior dynamic range and accuracy compared to motif-based methods. Furthermore, AD can accurately discern affinities of TF paralogs. Our results highlight thermodynamic affinity as a key determinant of in vivo binding, suggest that deep learning models of in vivo binding implicitly learn high-resolution affinity landscapes, and show that these affinities can be successfully distilled using AD. This new biophysical interpretation of deep learning models enables high-throughput in silico experiments to explore the influence of sequence context and variation on both intrinsic affinity and in vivo occupancy.

Conserved enhancer logic controls the notochord expression of vertebrate Brachyury

The cell type-specific expression of key transcription factors is central to development. Brachyury/T/TBXT is a major transcription factor for gastrulation, tailbud patterning, and notochord formation; however, how its expression is controlled in the mammalian notochord has remained elusive. Here, we identify the complement of notochord-specific enhancers in the mammalian Brachyury/T/TBXT gene. Using transgenic assays in zebrafish, axolotl, and mouse, we discover three Brachyury-controlling notochord enhancers T3, C, and I in human, mouse, and marsupial genomes. Acting as Brachyury-responsive, auto-regulatory shadow enhancers, deletion of all three enhancers in mouse abolishes Brachyury/T expression selectively in the notochord, causing specific trunk and neural tube defects without gastrulation or tailbud defects. Sequence and functional conservation of Brachyury-driving notochord enhancers with the brachyury/tbxtb loci from diverse lineages of fishes dates their origin to the last common ancestor of jawed vertebrates. Our data define the enhancers for Brachyury/T/TBXTB notochord expression as ancient mechanism in axis development.

Transcriptional kinetic synergy: A complex landscape revealed by integrating modeling and synthetic biology

Transcription factors (TFs) control gene expression, often acting synergistically. Classical thermodynamic models offer a biophysical explanation for synergy based on binding cooperativity and regulated recruitment of RNA polymerase. Because transcription requires polymerase to transition through multiple states, recent work suggests that "kinetic synergy" can arise through TFs acting on distinct steps of the transcription cycle. These types of synergy are not mutually exclusive and are difficult to disentangle conceptually and experimentally. Here, we model and build a synthetic circuit in which TFs bind to a single shared site on DNA, such that TFs cannot synergize by simultaneous binding. We model mRNA production as a function of both TF binding and regulation of the transcription cycle, revealing a complex landscape dependent on TF concentration, DNA binding affinity, and regulatory activity. We use synthetic TFs to confirm that the transcription cycle must be integrated with recruitment for a quantitative understanding of gene regulation.

Diverse logics and grammar encode notochord enhancers

The notochord is a defining feature of all chordates. The transcription factors Zic and ETS regulate enhancer activity within the notochord. We conduct high-throughput screens of genomic elements within developing Ciona embryos to understand how Zic and ETS sites encode notochord activity. Our screen discovers an enhancer located near Lama, a gene critical for notochord development. Reversing the orientation of an ETS site within this enhancer abolishes expression, indicating that enhancer grammar is critical for notochord activity. Similarly organized clusters of Zic and ETS sites occur within mouse and human Lama1 introns. Within a Brachyury (Bra) enhancer, FoxA and Bra, in combination with Zic and ETS binding sites, are necessary and sufficient for notochord expression. This binding site logic also occurs within other Ciona and vertebrate Bra enhancers. Collectively, this study uncovers the importance of grammar within notochord enhancers and discovers signatures of enhancer logic and grammar conserved across chordates.

Computational approaches to understand transcription regulation in development

Gene regulatory networks (GRNs) serve as useful abstractions to understand transcriptional dynamics in developmental systems. Computational prediction of GRNs has been successfully applied to genome-wide gene expression measurements with the advent of microarrays and RNA-sequencing. However, these inferred networks are inaccurate and mostly based on correlative rather than causative interactions. In this review, we highlight three approaches that significantly impact GRN inference: (1) moving from one genome-wide functional modality, gene expression, to multi-omics, (2) single cell sequencing, to measure cell type-specific signals and predict context-specific GRNs, and (3) neural networks as flexible models. Together, these experimental and computational developments have the potential to significantly impact the quality of inferred GRNs. Ultimately, accurately modeling the regulatory interactions between transcription factors and their target genes will be essential to understand the role of transcription factors in driving developmental gene expression programs and to derive testable hypotheses for validation.

Transcriptional and post-transcriptional controls for tuning gene expression in plants

Plant biotechnologists seek to modify plants through genetic reprogramming, but our ability to precisely control gene expression in plants is still limited. Here, we review transcription and translation in the model plants Arabidopsis thaliana and Nicotiana benthamiana with an eye toward control points that may be used to predictably modify gene expression. We highlight differences in gene expression requirements between these plants and other species, and discuss the ways in which our understanding of gene expression has been used to engineer plants. This review is intended to serve as a resource for plant scientists looking to achieve precise control over gene expression.

MEPP: more transparent motif enrichment by profiling positional correlations

Score-based motif enrichment analysis (MEA) is typically applied to regulatory DNA to infer transcription factors (TFs) that may modulate transcription and chromatin state in different conditions. Most MEA methods determine motif enrichment independent of motif position within a sequence, even when those sequences harbor anchor points that motifs and their bound TFs may functionally interact with in a distance-dependent fashion, such as other TF binding motifs, transcription start sites (TSS), sequencing assay cleavage sites, or other biologically meaningful features. We developed motif enrichment positional profiling (MEPP), a novel MEA method that outputs a positional enrichment profile of a given TF's binding motif relative to key anchor points (e.g. transcription start sites, or other motifs) within the analyzed sequences while accounting for lower-order nucleotide bias. Using transcription initiation and TF binding as test cases, we demonstrate MEPP's utility in determining the sequence positions where motif presence correlates with measures of biological activity, inferring positional dependencies of binding site function. We demonstrate how MEPP can be applied to interpretation and hypothesis generation from experiments that quantify transcription initiation, chromatin structure, or TF binding measurements. MEPP is available for download from https://github.com/npdeloss/mepp.

A cis-regulatory lexicon of DNA motif combinations mediating cell-type-specific gene regulation

Gene expression is controlled by transcription factors (TFs) that bind cognate DNA motif sequences in cis-regulatory elements (CREs). The combinations of DNA motifs acting within homeostasis and disease, however, are unclear. Gene expression, chromatin accessibility, TF footprinting, and H3K27ac-dependent DNA looping data were generated and a random-forest-based model was applied to identify 7,531 cell-type-specific cis-regulatory modules (CRMs) across 15 diploid human cell types. A co-enrichment framework within CRMs nominated 838 cell-type-specific, recurrent heterotypic DNA motif combinations (DMCs), which were functionally validated using massively parallel reporter assays. Cancer cells engaged DMCs linked to neoplasia-enabling processes operative in normal cells while also activating new DMCs only seen in the neoplastic state. This integrative approach identifies cell-type-specific cis-regulatory combinatorial DNA motifs in diverse normal and diseased human cells and represents a general framework for deciphering cis-regulatory sequence logic in gene regulation.

TFSyntax: a database of transcription factors binding syntax in mammalian genomes

In mammals, transcriptional factors (TFs) drive gene expression by binding to regulatory elements in a cooperative manner. Deciphering the rules of such cooperation is crucial to obtain a full understanding of cellular homeostasis and development. Although this is a long-standing topic, there is no comprehensive database for biologists to access the syntax of TF binding sites. Here we present TFSyntax (https://tfsyntax.zhaopage.com), a database focusing on the arrangement of TF binding sites. TFSyntax maps the binding motif of 1299 human TFs and 890 mouse TFs across 382 cells and tissues, representing the most comprehensive TF binding map to date. In addition to location, TFSyntax defines motif positional preference, density and colocalization within accessible elements. Powered by a series of functional modules based on web interface, users can freely search, browse, analyze, and download data of interest. With comprehensive characterization of TF binding syntax across distinct tissues and cell types, TFSyntax represents a valuable resource and platform for studying the mechanism of transcriptional regulation and exploring how regulatory DNA variants cause disease.

A Bcl6 Intronic Element Regulates T Follicular Helper Cell Differentiation

In response to an intracellular infectious agent, the immune system produces a specific cellular response as well as a T cell–dependent Ab response. Precursor T cells differentiate into effector T cells, including Th1 cells, and T follicular helper (TFH) cells. The latter cooperate with B cells to form germinal centers and induce the formation of Ab-forming plasmacytes. One major focal point for control of T cell differentiation is the transcription factor BCL6. In this study, we demonstrated that the Bcl6 gene is regulated by FOXO1-binding, cis-acting sequences located in a highly conserved region of the first Bcl6 intron. In both mouse and human T cells, deletion of the tandem FOXO1 binding sites increased the expression of BCL6 and enhanced the proportion of TFH cells. These results reveal a fundamental control point for cellular versus humoral immunity.

Typical Enhancers, Super-Enhancers, and Cancers

Simple Summary

The cancer genome has been exhaustively studied upon the advent of Next-Generation Sequencing technologies. Coding and non-coding sequences have been defined as hotspots of genomic variations that affect the naïve gene expression programs established in normal cells, thus working as endogenous drivers of carcinogenesis. In this review, we comprehensively summarize fundamental aspects of gene expression regulation, with emphasis on the impact of sequence and structural variations mapped across non-coding cis-acting elements of genes encoding for tumor-related transcription factors. Chromatin architecture, epigenome reprogramming, transcriptional enhancers and Super-enhancers, oncogene regulation, cutting-edge technologies, and pharmacological treatment are substantially highlighted.

Abstract

Non-coding segments of the human genome are enriched in cis-regulatory modules that constitute functional elements, such as transcriptional enhancers and Super-enhancers. A hallmark of cancer pathogenesis is the dramatic dysregulation of the “archetype” gene expression profiles of normal human cells. Genomic variations can promote such deficiencies when occurring across enhancers and Super-enhancers, since they affect their mechanistic principles, their functional capacity and specificity, and the epigenomic features of the chromatin microenvironment across which these regulatory elements reside. Here, we comprehensively describe: fundamental mechanisms of gene expression dysregulation in cancers that involve genomic abnormalities within enhancers’ and Super-enhancers’ (SEs) sequences, which alter the expression of oncogenic transcription factors (TFs); cutting-edge technologies applied for the analysis of variation-enriched hotspots of the cancer genome; and pharmacological approaches for the treatment of Super-enhancers’ aberrant function. Finally, we provide an intratumor meta-analysis, which highlights that genomic variations in transcription-factor-driven tumors are accompanied overexpression of genes, a portion of which encodes for additional cancer-related transcription factors.

On the incongruence of genotype-phenotype and fitness landscapes

The mapping from genotype to phenotype to fitness typically involves multiple nonlinearities that can transform the effects of mutations. For example, mutations may contribute additively to a phenotype, but their effects on fitness may combine non-additively because selection favors a low or intermediate value of that phenotype. This can cause incongruence between the topographical properties of a fitness landscape and its underlying genotype-phenotype landscape. Yet, genotype-phenotype landscapes are often used as a proxy for fitness landscapes to study the dynamics and predictability of evolution. Here, we use theoretical models and empirical data on transcription factor-DNA interactions to systematically study the incongruence of genotype-phenotype and fitness landscapes when selection favors a low or intermediate phenotypic value. Using the theoretical models, we prove a number of fundamental results. For example, selection for low or intermediate phenotypic values does not change simple sign epistasis into reciprocal sign epistasis, implying that genotype-phenotype landscapes with only simple sign epistasis motifs will always give rise to single-peaked fitness landscapes under such selection. More broadly, we show that such selection tends to create fitness landscapes that are more rugged than the underlying genotype-phenotype landscape, but this increased ruggedness typically does not frustrate adaptive evolution because the local adaptive peaks in the fitness landscape tend to be nearly as tall as the global peak. Many of these results carry forward to the empirical genotype-phenotype landscapes, which may help to explain why low- and intermediate-affinity transcription factor-DNA interactions are so prevalent in eukaryotic gene regulation.

Characterization of sequence determinants of enhancer function using natural genetic variation

Sequence variation in enhancers that control cell-type-specific gene transcription contributes significantly to phenotypic variation within human populations. However, it remains difficult to predict precisely the effect of any given sequence variant on enhancer function due to the complexity of DNA sequence motifs that determine transcription factor (TF) binding to enhancers in their native genomic context. Using F₁-hybrid cells derived from crosses between distantly related inbred strains of mice, we identified thousands of enhancers with allele-specific TF binding and/or activity. We find that genetic variants located within the central region of enhancers are most likely to alter TF binding and enhancer activity. We observe that the AP-1 family of TFs (Fos/Jun) are frequently required for binding of TEAD TFs and for enhancer function. However, many sequence variants outside of core motifs for AP-1 and TEAD also impact enhancer function, including sequences flanking core TF motifs and AP-1 half sites. Taken together, these data represent one of the most comprehensive assessments of allele-specific TF binding and enhancer function to date and reveal how sequence changes at enhancers alter their function across evolutionary timescales.

Specificity of the Hox member Deformed is determined by transcription factor levels and binding site affinities

Hox proteins have similar binding specificities in vitro, yet they control different morphologies in vivo. This paradox has been partially solved with the identification of Hox low-affinity binding sites. However, anterior Hox proteins are more promiscuous than posterior Hox proteins, raising the question how anterior Hox proteins achieve specificity. We use the AP2x enhancer, which is activated in the maxillary head segment by the Hox TF Deformed (Dfd). This enhancer lacks canonical Dfd-Exd sites but contains several predicted low-affinity sites. Unexpectedly, these sites are strongly bound by Dfd-Exd complexes and their conversion into optimal Dfd-Exd sites results only in a modest increase in binding strength. These small variations in affinity change the sensitivity of the enhancer to different Dfd levels, resulting in perturbed AP-2 expression and maxillary morphogenesis. Thus, Hox-regulated morphogenesis seems to result from the co-evolution of Hox binding affinity and Hox dosage for precise target gene regulation.

Despite the central role of Hox genes in controlling morphogenesis, the DNA binding of different Hox members is relatively similar. Here they show that specificity of Hox member Dfd relies on a precise balance of transcription factors and binding site affinities.

Multi-layered transcriptional control of cranial neural crest development

The neural crest (NC) is an emblematic population of embryonic stem-like cells with remarkable migratory ability. These distinctive attributes have inspired the curiosity of developmental biologists for over 150 years, however only recently the regulatory mechanisms controlling the complex features of the NC have started to become elucidated at genomic scales. Regulatory control of NC development is achieved through combinatorial transcription factor binding and recruitment of associated transcriptional complexes to distal cis-regulatory elements. Together, they regulate when, where and to what extent transcriptional programmes are actively deployed, ultimately shaping ontogenetic processes. Here, we discuss how transcriptional networks control NC ontogeny, with a special emphasis on the molecular mechanisms underlying specification of the cephalic NC. We also cover emerging properties of transcriptional regulation revealed in diverse developmental systems, such as the role of three-dimensional conformation of chromatin, and how they are involved in the regulation of NC ontogeny. Finally, we highlight how advances in deciphering the NC transcriptional network have afforded new insights into the molecular basis of human diseases.

Two distinct evolutionary conserved neural degeneration pathways characterized in a colonial chordate

Colonial tunicates are marine organisms that possess multiple brains simultaneously during their colonial phase. While the cyclical processes of neurogenesis and neurodegeneration characterizing their life cycle have been documented previously, the cellular and molecular changes associated with such processes and their relationship with variation in brain morphology and individual (zooid) behavior throughout adult life remains unknown. Here, we introduce Botryllus schlosseri as an invertebrate model for neurogenesis, neural degeneration, and evolutionary neuroscience. Our analysis reveals that during the weekly colony budding (i.e., asexual reproduction), prior to programmed cell death and removal by phagocytes, decreases in the number of neurons in the adult brain are associated with reduced behavioral response and significant change in the expression of 73 mammalian homologous genes associated with neurodegenerative disease. Similarly, when comparing young colonies (1 to 2 y of age) to those reared in a laboratory for ∼20 y, we found that older colonies contained significantly fewer neurons and exhibited reduced behavioral response alongside changes in the expression of 148 such genes (35 of which were differentially expressed across both timescales). The existence of two distinct yet apparently related neurodegenerative pathways represents a novel platform to study the gene products governing the relationship between aging, neural regeneration and degeneration, and loss of nervous system function. Indeed, as a member of an evolutionary clade considered to be a sister group of vertebrates, this organism may be a fundamental resource in understanding how evolution has shaped these processes across phylogeny and obtaining mechanistic insight.

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.

Synthetic reconstruction of the hunchback promoter specifies the role of Bicoid, Zelda and Hunchback in the dynamics of its transcription

For over 40 years, the Bicoid-hunchback (Bcd-hb) system in the fruit fly embryo has been used as a model to study how positional information in morphogen concentration gradients is robustly translated into step-like responses. A body of quantitative comparisons between theory and experiment have since questioned the initial paradigm that the sharp hb transcription pattern emerges solely from diffusive biochemical interactions between the Bicoid transcription factor and the gene promoter region. Several alternative mechanisms have been proposed, such as additional sources of positional information, positive feedback from Hb proteins or out-of-equilibrium transcription activation. By using the MS2-MCP RNA-tagging system and analysing in real time, the transcription dynamics of synthetic reporters for Bicoid and/or its two partners Zelda and Hunchback, we show that all the early hb expression pattern features and temporal dynamics are compatible with an equilibrium model with a short decay length Bicoid activity gradient as a sole source of positional information. Meanwhile, Bicoid’s partners speed-up the process by different means: Zelda lowers the Bicoid concentration threshold required for transcriptional activation while Hunchback reduces burstiness and increases the polymerase firing rate.

Quantitative Dissection of the Proximal Ciona brachyury Enhancer

A major goal in biology is to understand the rules by which cis-regulatory sequences control spatially and temporally precise expression patterns. Here we present a systematic dissection of the proximal enhancer for the notochord-specific transcription factor brachyury in the ascidian chordate Ciona. The study uses a quantitative image-based reporter assay that incorporates a dual-reporter strategy to control for variable electroporation efficiency. We identified and mutated multiple predicted transcription factor binding sites of interest based on statistical matches to the JASPAR binding motif database. Most sites (Zic, Ets, FoxA, RBPJ) were selected based on prior knowledge of cell fate specification in both the primary and secondary notochord. We also mutated predicted Brachyury sites to investigate potential autoregulation as well as Fos/Jun (AP1) sites that had very strong matches to JASPAR. Our goal was to quantitatively define the relative importance of these different sites, to explore the importance of predicted high-affinity versus low-affinity motifs, and to attempt to design mutant enhancers that were specifically expressed in only the primary or secondary notochord lineages. We found that the mutation of all predicted high-affinity sites for Zic, FoxA or Ets led to quantifiably distinct effects. The FoxA construct caused a severe loss of reporter expression whereas the Ets construct had little effect. A strong Ets phenotype was only seen when much lower-scoring binding sites were also mutated. This supports the enhancer suboptimization hypothesis proposed by Farley and Levine but suggests that it may only apply to some but not all transcription factor families. We quantified reporter expression separately in the two notochord lineages with the expectation that Ets mutations and RBPJ mutations would have distinct effects given that primary notochord is induced by Ets-mediated FGF signaling whereas secondary notochord is induced by RBPJ/Su(H)-mediated Notch/Delta signaling. We found, however, that ETS mutations affected primary and secondary notochord expression relatively equally and that RBPJ mutations were only moderately more severe in their effect on secondary versus primary notochord. Our results point to the promise of quantitative reporter assays for understanding cis-regulatory logic but also highlight the challenge of arbitrary statistical thresholds for predicting potentially important sites.

The Non-continuum Nature of Eukaryotic Transcriptional Regulation

Eukaryotic transcription factors are versatile mediators of specificity in gene regulation. This versatility is achieved through mutual specification by context-specific DNA binding on the one hand, and identity-specific protein-protein partnerships on the other. This interactivity, known as combinatorial control, enables a repertoire of complex transcriptional outputs that are qualitatively disjoint, or non-continuum, with respect to binding affinity. This feature contrasts starkly with prokaryotic gene regulators, whose activities in general vary quantitatively in step with binding affinity. Biophysical studies on prokaryotic model systems and more recent investigations on transcription factors highlight an important role for folded state dynamics and molecular hydration in protein/DNA recognition. Analysis of molecular models of combinatorial control and recent literature in low-affinity gene regulation suggest that transcription factors harbor unique conformational dynamics that are inaccessible or unused by prokaryotic DNA-binding proteins. Thus, understanding the intrinsic dynamics involved in DNA binding and co-regulator recruitment appears to be a key to understanding how transcription factors mediate non-continuum outcomes in eukaryotic gene expression, and how such capability might have evolved from ancient, structurally conserved counterparts.

COVID-19 genetic risk variants are associated with expression of multiple genes in diverse immune cell types

Common genetic polymorphisms associated with COVID-19 illness can be utilized for discovering molecular pathways and cell types driving disease pathogenesis. Given the importance of immune cells in the pathogenesis of COVID-19 illness, here we assessed the effects of COVID-19-risk variants on gene expression in a wide range of immune cell types. Transcriptome-wide association study and colocalization analysis revealed putative causal genes and the specific immune cell types where gene expression is most influenced by COVID-19-risk variants. Notable examples include OAS1 in non-classical monocytes, DTX1 in B cells, IL10RB in NK cells, CXCR6 in follicular helper T cells, CCR9 in regulatory T cells and ARL17A in TH2 cells. By analysis of transposase accessible chromatin and H3K27ac-based chromatin-interaction maps of immune cell types, we prioritized potentially functional COVID-19-risk variants. Our study highlights the potential of COVID-19 genetic risk variants to impact the function of diverse immune cell types and influence severe disease manifestations.

The dynamic, combinatorial cis-regulatory lexicon of epidermal differentiation

Transcription factors bind DNA sequence motif vocabularies in cis-regulatory elements (CREs) to modulate chromatin state and gene expression during cell state transitions. A quantitative understanding of how motif lexicons influence dynamic regulatory activity has been elusive due to the combinatorial nature of the cis-regulatory code. To address this, we undertook multiomic data profiling of chromatin and expression dynamics across epidermal differentiation to identify 40,103 dynamic CREs associated with 3,609 dynamically expressed genes, then applied an interpretable deep-learning framework to model the cis-regulatory logic of chromatin accessibility. This analysis framework identified cooperative DNA sequence rules in dynamic CREs regulating synchronous gene modules with diverse roles in skin differentiation. Massively parallel reporter assay analysis validated temporal dynamics and cooperative cis-regulatory logic. Variants linked to human polygenic skin disease were enriched in these time-dependent combinatorial motif rules. This integrative approach shows the combinatorial cis-regulatory lexicon of epidermal differentiation and represents a general framework for deciphering the organizational principles of the cis-regulatory code of dynamic gene regulation.

Deciphering enhancer sequence using thermodynamics-based models and convolutional neural networks

Deciphering the sequence-function relationship encoded in enhancers holds the key to interpreting non-coding variants and understanding mechanisms of transcriptomic variation. Several quantitative models exist for predicting enhancer function and underlying mechanisms; however, there has been no systematic comparison of these models characterizing their relative strengths and shortcomings. Here, we interrogated a rich data set of neuroectodermal enhancers in Drosophila, representing cis- and trans- sources of expression variation, with a suite of biophysical and machine learning models. We performed rigorous comparisons of thermodynamics-based models implementing different mechanisms of activation, repression and cooperativity. Moreover, we developed a convolutional neural network (CNN) model, called CoNSEPT, that learns enhancer 'grammar' in an unbiased manner. CoNSEPT is the first general-purpose CNN tool for predicting enhancer function in varying conditions, such as different cell types and experimental conditions, and we show that such complex models can suggest interpretable mechanisms. We found model-based evidence for mechanisms previously established for the studied system, including cooperative activation and short-range repression. The data also favored one hypothesized activation mechanism over another and suggested an intriguing role for a direct, distance-independent repression mechanism. Our modeling shows that while fundamentally different models can yield similar fits to data, they vary in their utility for mechanistic inference. CoNSEPT is freely available at: https://github.com/PayamDiba/CoNSEPT.

Information content differentiates enhancers from silencers in mouse photoreceptors

Enhancers and silencers often depend on the same transcription factors (TFs) and are conflated in genomic assays of TF binding or chromatin state. To identify sequence features that distinguish enhancers and silencers, we assayed massively parallel reporter libraries of genomic sequences targeted by the photoreceptor TF cone-rod homeobox (CRX) in mouse retinas. Both enhancers and silencers contain more TF motifs than inactive sequences, but relative to silencers, enhancers contain motifs from a more diverse collection of TFs. We developed a measure of information content that describes the number and diversity of motifs in a sequence and found that, while both enhancers and silencers depend on CRX motifs, enhancers have higher information content. The ability of information content to distinguish enhancers and silencers targeted by the same TF illustrates how motif context determines the activity of cis-regulatory sequences.

Different cell types are established by activating and repressing the activity of specific sets of genes, a process controlled by proteins called transcription factors. Transcription factors work by recognizing and binding short stretches of DNA in parts of the genome called cis-regulatory sequences. A cis-regulatory sequence that increases the activity of a gene when bound by transcription factors is called an enhancer, while a sequence that causes a decrease in gene activity is called a silencer.

To establish a cell type, a particular transcription factor will act on both enhancers and silencers that control the activity of different genes. For example, the transcription factor cone-rod homeobox (CRX) is critical for specifying different types of cells in the retina, and it acts on both enhancers and silencers. In rod photoreceptors, CRX activates rod genes by binding their enhancers, while repressing cone photoreceptor genes by binding their silencers. However, CRX always recognizes and binds to the same DNA sequence, known as its binding site, making it unclear why some cis-regulatory sequences bound to CRX act as silencers, while others act as enhancers.

Friedman et al. sought to understand how enhancers and silencers, both bound by CRX, can have different effects on the genes they control. Since both enhancers and silencers contain CRX binding sites, the difference between the two must lie in the sequence of the DNA surrounding these binding sites.

Using retinas that have been explanted from mice and kept alive in the laboratory, Friedman et al. tested the activity of thousands of CRX-binding sequences from the mouse genome. This showed that both enhancers and silencers have more copies of CRX-binding sites than sequences of the genome that are inactive. Additionally, the results revealed that enhancers have a diverse collection of binding sites for other transcription factors, while silencers do not. Friedman et al. developed a new metric they called information content, which captures the diverse combinations of different transcription binding sites that cis-regulatory sequences can have. Using this metric, Friedman et al. showed that it is possible to distinguish enhancers from silencers based on their information content.

It is critical to understand how the DNA sequences of cis-regulatory regions determine their activity, because mutations in these regions of the genome can cause disease. However, since every person has thousands of benign mutations in cis-regulatory sequences, it is a challenge to identify specific disease-causing mutations, which are relatively rare. One long-term goal of models of enhancers and silencers, such as Friedman et al.’s information content model, is to understand how mutations can affect cis-regulatory sequences, and, in some cases, lead to disease.