Enhancer-promoter interactions become more instructive in the transition from cell-fate specification to tissue differentiation.

To regulate expression, enhancers must come in proximity to their target gene. However, the relationship between the timing of enhancer-promoter (E-P) proximity and activity remains unclear, with examples of uncoupled, anticorrelated and correlated interactions. To assess this, we selected 600 characterized enhancers or promoters with tissue-specific activity in Drosophila embryos and performed Capture-C in FACS-purified myogenic or neurogenic cells during specification and tissue differentiation. This enabled direct comparison between E-P proximity and activity transitioning from OFF-to-ON and ON-to-OFF states across developmental conditions. This showed remarkably similar E-P topologies between specified muscle and neuronal cells, which are uncoupled from activity. During tissue differentiation, many new distal interactions emerge where changes in E-P proximity reflect changes in activity. The mode of E-P regulation therefore appears to change as embryogenesis proceeds, from largely permissive topologies during cell-fate specification to more instructive regulation during terminal tissue differentiation, when E-P proximity is coupled to activation.

Targeted design of synthetic enhancers for selected tissues in the Drosophila embryo.

Enhancers control gene expression and have crucial roles in development and homeostasis1-3. However, the targeted de novo design of enhancers with tissue-specific activities has remained challenging. Here we combine deep learning and transfer learning to design tissue-specific enhancers for five tissues in the Drosophila melanogaster embryo: the central nervous system, epidermis, gut, muscle and brain. We first train convolutional neural networks using genome-wide single-cell assay for transposase-accessible chromatin with sequencing (ATAC-seq) datasets and then fine-tune the convolutional neural networks with smaller-scale data from in vivo enhancer activity assays, yielding models with 13% to 76% positive predictive value according to cross-validation. We designed and experimentally assessed 40 synthetic enhancers (8 per tissue) in vivo, of which 31 (78%) were active and 27 (68%) functioned in the target tissue (100% for central nervous system and muscle). The strategy of combining genome-wide and small-scale functional datasets by transfer learning is generally applicable and should enable the design of tissue-, cell type- and cell state-specific enhancers in any system.

Chromatin gene-gene loops support the cross-regulation of genes with related function.

Chromatin loops between gene pairs have been observed in diverse contexts in both flies and vertebrates. Combining high-resolution Capture-C, DNA fluorescence in situ hybridization, and genetic perturbations, we dissect the functional role of three loops between genes with related function during Drosophila embryogenesis. By mutating the loop anchor (but not the gene) or the gene (but not loop anchor), we disentangle loop formation and gene expression and show that the 3D proximity of paralogous gene loci supports their co-regulation. Breaking the loop leads to either an attenuation or enhancement of expression and perturbs their relative levels of expression and cross-regulation. Although many loops appear constitutive across embryogenesis, their function can change in different developmental contexts. Taken together, our results indicate that chromatin gene-gene loops act as architectural scaffolds that can be used in different ways in different contexts to fine-tune the coordinated expression of genes with related functions and sustain their cross-regulation.

CTCF, BEAF-32, and CP190 are not required for the establishment of TADs in early Drosophila embryos but have locus-specific roles.

The boundaries of topologically associating domains (TADs) are delimited by insulators and/or active promoters; however, how they are initially established during embryogenesis remains unclear. Here, we examined this during the first hours of Drosophila embryogenesis. DNA-FISH confirms that intra-TAD pairwise proximity is established during zygotic genome activation (ZGA) but with extensive cell-to-cell heterogeneity. Most newly formed boundaries are occupied by combinations of CTCF, BEAF-32, and/or CP190. Depleting each insulator individually from chromatin revealed that TADs can still establish, although with lower insulation, with a subset of boundaries (~10%) being more dependent on specific insulators. Some weakened boundaries have aberrant gene expression due to unconstrained enhancer activity. However, the majority of misexpressed genes have no obvious direct relationship to changes in domain-boundary insulation. Deletion of an active promoter (thereby blocking transcription) at one boundary had a greater impact than deleting the insulator-bound region itself. This suggests that cross-talk between insulators and active promoters and/or transcription might reinforce domain boundary insulation during embryogenesis.

Enhancers have more cofactor specificity than we think: A potential new way to classify enhancers based on their functional cofactor requirements.

By systematically assessing the effects of depleting eight cofactors on enhancer activity, Neumayr et al. (2022) found that different enhancers have different requirements for some perceived universal cofactors. While some cofactors influence enhancer strength, others affect enhancer-promoter specificity.

The continuum of Drosophila embryonic development at single-cell resolution.

Drosophila melanogaster is a powerful, long-standing model for metazoan development and gene regulation. We profiled chromatin accessibility in almost 1 million and gene expression in half a million nuclei from overlapping windows spanning the entirety of embryogenesis. Leveraging developmental asynchronicity within embryo collections, we applied deep neural networks to infer the age of each nucleus, resulting in continuous, multimodal views of molecular and cellular transitions in absolute time. We identify cell lineages; infer their developmental relationships; and link dynamic changes in enhancer usage, transcription factor (TF) expression, and the accessibility of TFs' cognate motifs. With these data, the dynamics of enhancer usage and gene expression can be explored within and across lineages at the scale of minutes, including for precise transitions like zygotic genome activation.

Regulating specificity in enhancer-promoter communication.

Enhancers are cis-regulatory elements that can activate transcription remotely to regulate a specific pattern of a gene's expression. Genes typically have many enhancers that are often intermingled in the loci of other genes. To regulate expression, enhancers must therefore activate their correct promoter while ignoring others that may be in closer linear proximity. In this review, we discuss mechanisms by which enhancers engage with promoters, including recent findings on the role of cohesin and the Mediator complex, and how this specificity in enhancer-promoter communication is encoded. Genetic dissection of model loci, in addition to more recent findings using genome-wide approaches, highlight the core promoter sequence, its accessibility, cofactor-promoter preference, in addition to the surrounding genomic context, as key components.

Simultaneous cellular and molecular phenotyping of embryonic mutants using single-cell regulatory trajectories.

Developmental progression and cellular diversity are largely driven by transcription factors (TFs); yet, characterizing their loss-of-function phenotypes remains challenging and often disconnected from their underlying molecular mechanisms. Here, we combine single-cell regulatory genomics with loss-of-function mutants to jointly assess both cellular and molecular phenotypes. Performing sci-ATAC-seq at eight overlapping time points during Drosophila mesoderm development could reconstruct the developmental trajectories of all major muscle types and reveal the TFs and enhancers involved. To systematically assess mutant phenotypes, we developed a single-nucleus genotyping strategy to process embryo pools of mixed genotypes. Applying this to four TF mutants could identify and quantify their characterized phenotypes de novo and discover new ones, while simultaneously revealing their regulatory input and mode of action. Our approach is a general framework to dissect the functional input of TFs in a systematic, unbiased manner, identifying both cellular and molecular phenotypes at a scale and resolution that has not been feasible before.

scDALI: modeling allelic heterogeneity in single cells reveals context-specific genetic regulation.

While it is established that the functional impact of genetic variation can vary across cell types and states, capturing this diversity remains challenging. Current studies using bulk sequencing either ignore this heterogeneity or use sorted cell populations, reducing discovery and explanatory power. Here, we develop scDALI, a versatile computational framework that integrates information on cellular states with allelic quantifications of single-cell sequencing data to characterize cell-state-specific genetic effects. We apply scDALI to scATAC-seq profiles from developing F1 Drosophila embryos and scRNA-seq from differentiating human iPSCs, uncovering heterogeneous genetic effects in specific lineages, developmental stages, or cell types.

Extremely rapid and reversible optogenetic perturbation of nuclear proteins in living embryos.

Many developmental regulators have complex and context-specific roles in different tissues and stages, making the dissection of their function extremely challenging. As regulatory processes often occur within minutes, perturbation methods that match these dynamics are needed. Here, we present the improved light-inducible nuclear export system (iLEXY), an optogenetic loss-of-function approach that triggers translocation of proteins from the nucleus to the cytoplasm. By introducing a series of mutations, we substantially increased LEXY's efficiency and generated variants with different recovery times. iLEXY enables rapid (t1/2 < 30 s), efficient, and reversible nuclear protein depletion in embryos, and is generalizable to proteins of diverse sizes and functions. Applying iLEXY to the Drosophila master regulator Twist, we phenocopy loss-of-function mutants, precisely map the Twist-sensitive embryonic stages, and investigate the effects of timed Twist depletions. Our results demonstrate the power of iLEXY to dissect the function of pleiotropic factors during embryogenesis with unprecedented temporal precision.

The hourglass model of evolutionary conservation during embryogenesis extends to developmental enhancers with signatures of positive selection.

Inter-species comparisons of both morphology and gene expression within a phylum have revealed a period in the middle of embryogenesis with more similarity between species compared with earlier and later time points. This "developmental hourglass" pattern has been observed in many phyla, yet the evolutionary constraints on gene expression, as well as the underlying mechanisms of how this is regulated, remain elusive. Moreover, the role of positive selection on gene regulation in the more diverged earlier and later stages of embryogenesis remains unknown. Here, using DNase-seq to identify regulatory regions in two distant Drosophila species (D. melanogaster and D. virilis), we assessed the evolutionary conservation and adaptive evolution of enhancers throughout multiple stages of embryogenesis. This revealed a higher proportion of conserved enhancers at the phylotypic period, providing a regulatory basis for the hourglass expression pattern. Using an in silico mutagenesis approach, we detect signatures of positive selection on developmental enhancers at early and late stages of embryogenesis, with a depletion at the phylotypic period, suggesting positive selection as one evolutionary mechanism underlying the hourglass pattern of animal evolution.

Cis-acting variation is common across regulatory layers but is often buffered during embryonic development.

Precise patterns of gene expression are driven by interactions between transcription factors, regulatory DNA sequences, and chromatin. How DNA mutations affecting any one of these regulatory "layers" are buffered or propagated to gene expression remains unclear. To address this, we quantified allele-specific changes in chromatin accessibility, histone modifications, and gene expression in F1 embryos generated from eight Drosophila crosses at three embryonic stages, yielding a comprehensive data set of 240 samples spanning multiple regulatory layers. Genetic variation (allelic imbalance) impacts gene expression more frequently than chromatin features, with metabolic and environmental response genes being most often affected. Allelic imbalance in cis-regulatory elements (enhancers) is common and highly heritable, yet its functional impact does not generally propagate to gene expression. When it does, genetic variation impacts RNA levels through two alternative mechanisms involving either H3K4me3 or chromatin accessibility and H3K27ac. Changes in RNA are more predictive of variation in H3K4me3 than vice versa, suggesting a role for H3K4me3 downstream from transcription. The impact of a substantial proportion of genetic variation is consistent across embryonic stages, with 50% of allelic imbalanced features at one stage being also imbalanced at subsequent developmental stages. Crucially, buffering, as well as the magnitude and evolutionary impact of genetic variants, is influenced by regulatory complexity (i.e., number of enhancers regulating a gene), with transcription factors being most robust to cis-acting, but most influenced by trans-acting, variation.

Chromatin accessibility profiling methods.

Chromatin accessibility, or the physical access to chromatinized DNA, is a widely studied characteristic of the eukaryotic genome. As active regulatory DNA elements are generally 'accessible', the genome-wide profiling of chromatin accessibility can be used to identify candidate regulatory genomic regions in a tissue or cell type. Multiple biochemical methods have been developed to profile chromatin accessibility, both in bulk and at the single-cell level. Depending on the method, enzymatic cleavage, transposition or DNA methyltransferases are used, followed by high-throughput sequencing, providing a view of genome-wide chromatin accessibility. In this Primer, we discuss these biochemical methods, as well as bioinformatics tools for analysing and interpreting the generated data, and insights into the key regulators underlying developmental, evolutionary and disease processes. We outline standards for data quality, reproducibility and deposition used by the genomics community. Although chromatin accessibility profiling is invaluable to study gene regulation, alone it provides only a partial view of this complex process. Orthogonal assays facilitate the interpretation of accessible regions with respect to enhancer-promoter proximity, functional transcription factor binding and regulatory function. We envision that technological improvements including single-molecule, multi-omics and spatial methods will bring further insight into the secrets of genome regulation.

Lineage-Resolved Enhancer and Promoter Usage during a Time Course of Embryogenesis.

Enhancers are essential drivers of cell states, yet the relationship between accessibility, regulatory activity, and in vivo lineage commitment during embryogenesis remains poorly understood. Here, we measure chromatin accessibility in isolated neural and mesodermal lineages across a time course of Drosophila embryogenesis. Promoters, including tissue-specific genes, are often constitutively open, even in contexts where the gene is not expressed. In contrast, the majority of distal elements have dynamic, tissue-specific accessibility. Enhancer priming appears rarely within a lineage, perhaps reflecting the speed of Drosophila embryogenesis. However, many tissue-specific enhancers are accessible in other lineages early on and become progressively closed as embryogenesis proceeds. We demonstrate the usefulness of this tissue- and time-resolved resource to definitively identify single-cell clusters, to uncover predictive motifs, and to identify many regulators of tissue development. For one such predicted neural regulator, l(3)neo38, we generate a loss-of-function mutant and uncover an essential role for neuromuscular junction and brain development.

The road ahead in genetics and genomics.

In celebration of the 20th anniversary of Nature Reviews Genetics, we asked 12 leading researchers to reflect on the key challenges and opportunities faced by the field of genetics and genomics. Keeping their particular research area in mind, they take stock of the current state of play and emphasize the work that remains to be done over the next few years so that, ultimately, the benefits of genetic and genomic research can be felt by everyone.

Characterization of Button Loci that Promote Homologous Chromosome Pairing and Cell-Type-Specific Interchromosomal Gene Regulation.

Homologous chromosomes colocalize to regulate gene expression in processes including genomic imprinting, X-inactivation, and transvection. In Drosophila, homologous chromosomes pair throughout development, promoting transvection. The "button" model of pairing proposes that specific regions along chromosomes pair with high affinity. Here, we identify buttons interspersed across the fly genome that pair with their homologous sequences, even when relocated to multiple positions in the genome. A majority of transgenes that span a full topologically associating domain (TAD) function as buttons, but not all buttons contain TADs. Additionally, buttons are enriched for insulator protein clusters. Fragments of buttons do not pair, suggesting that combinations of elements within a button are required for pairing. Pairing is necessary but not sufficient for transvection. Additionally, pairing and transvection are stronger in some cell types than in others, suggesting that pairing strength regulates transvection efficiency between cell types. Thus, buttons pair homologous chromosomes to facilitate cell-type-specific interchromosomal gene regulation.

Chromatin topology, condensates and gene regulation: shifting paradigms or just a phase?

In the past decade, two major advances in our understanding of nuclear organization have taken the field of gene regulation by storm. First, technologies that can analyze the three-dimensional conformation of chromatin have revealed how the genome is organized and have provided novel insights into how regulatory regions in the genome interact. Second, the recognition that many proteins can form membraneless compartments through liquid-liquid phase separation (LLPS) has challenged long-standing notions of how proteins within the nucleus are organized and has offered a tantalizing general mechanism by which many aspects of nuclear function may be regulated. However, the functional roles of chromatin topology and LLPS in regulating gene expression remain poorly understood. These topics were discussed with great fervor during an open discussion held at a recent workshop titled 'Chromatin-based regulation of development' organized by The Company of Biologists. Here, we summarize the major points covered during this debate and discuss how they tie into current thinking in the field of gene regulation.

Accurate genome-wide predictions of spatio-temporal gene expression during embryonic development.

Comprehensive information on the timing and location of gene expression is fundamental to our understanding of embryonic development and tissue formation. While high-throughput in situ hybridization projects provide invaluable information about developmental gene expression patterns for model organisms like Drosophila, the output of these experiments is primarily qualitative, and a high proportion of protein coding genes and most non-coding genes lack any annotation. Accurate data-centric predictions of spatio-temporal gene expression will therefore complement current in situ hybridization efforts. Here, we applied a machine learning approach by training models on all public gene expression and chromatin data, even from whole-organism experiments, to provide genome-wide, quantitative spatio-temporal predictions for all genes. We developed structured in silico nano-dissection, a computational approach that predicts gene expression in >200 tissue-developmental stages. The algorithm integrates expression signals from a compendium of 6,378 genome-wide expression and chromatin profiling experiments in a cell lineage-aware fashion. We systematically evaluated our performance via cross-validation and experimentally confirmed 22 new predictions for four different embryonic tissues. The model also predicts complex, multi-tissue expression and developmental regulation with high accuracy. We further show the potential of applying these genome-wide predictions to extract tissue specificity signals from non-tissue-dissected experiments, and to prioritize tissues and stages for disease modeling. This resource, together with the exploratory tools are freely available at our webserver http://find.princeton.edu, which provides a valuable tool for a range of applications, from predicting spatio-temporal expression patterns to recognizing tissue signatures from differential gene expression profiles.

Highly rearranged chromosomes reveal uncoupling between genome topology and gene expression.

Chromatin topology is intricately linked to gene expression, yet its functional requirement remains unclear. Here, we comprehensively assessed the interplay between genome topology and gene expression using highly rearranged chromosomes (balancers) spanning ~75% of the Drosophila genome. Using transheterozyte (balancer/wild-type) embryos, we measured allele-specific changes in topology and gene expression in cis, while minimizing trans effects. Through genome sequencing, we resolved eight large nested inversions, smaller inversions, duplications and thousands of deletions. These extensive rearrangements caused many changes to chromatin topology, disrupting long-range loops, topologically associating domains (TADs) and promoter interactions, yet these are not predictive of changes in expression. Gene expression is generally not altered around inversion breakpoints, indicating that mis-appropriate enhancer-promoter activation is a rare event. Similarly, shuffling or fusing TADs, changing intra-TAD connections and disrupting long-range inter-TAD loops does not alter expression for the majority of genes. Our results suggest that properties other than chromatin topology ensure productive enhancer-promoter interactions.

The Role of Chromatin Accessibility in cis-Regulatory Evolution.

Transcription factor (TF) binding is determined by sequence as well as chromatin accessibility. Although the role of accessibility in shaping TF-binding landscapes is well recorded, its role in evolutionary divergence of TF binding, which in turn can alter cis-regulatory activities, is not well understood. In this work, we studied the evolution of genome-wide binding landscapes of five major TFs in the core network of mesoderm specification, between Drosophila melanogaster and Drosophila virilis, and examined its relationship to accessibility and sequence-level changes. We generated chromatin accessibility data from three important stages of embryogenesis in both Drosophila melanogaster and Drosophila virilis and recorded conservation and divergence patterns. We then used multivariable models to correlate accessibility and sequence changes to TF-binding divergence. We found that accessibility changes can in some cases, for example, for the master regulator Twist and for earlier developmental stages, more accurately predict binding change than is possible using TF-binding motif changes between orthologous enhancers. Accessibility changes also explain a significant portion of the codivergence of TF pairs. We noted that accessibility and motif changes offer complementary views of the evolution of TF binding and developed a combined model that captures the evolutionary data much more accurately than either view alone. Finally, we trained machine learning models to predict enhancer activity from TF binding and used these functional models to argue that motif and accessibility-based predictors of TF-binding change can substitute for experimentally measured binding change, for the purpose of predicting evolutionary changes in enhancer activity.