Genome-scale functional characterization of Drosophila developmental enhancers in vivo

Developmental and housekeeping transcriptional programs display distinct modes of enhancer-enhancer cooperativity in Drosophila

Genomic enhancers are key transcriptional regulators which, upon the binding of sequence-specific transcription factors, activate their cognate target promoters. Although enhancers have been extensively studied in isolation, a substantial number of genes have more than one simultaneously active enhancer, and it remains unclear how these cooperate to regulate transcription. Using Drosophila melanogaster S2 cells as a model, we assay the activities of more than a thousand individual enhancers and about a million enhancer pairs toward housekeeping and developmental core promoters with STARR-seq. We report that housekeeping and developmental enhancers show distinct modes of enhancer-enhancer cooperativity: while housekeeping enhancers are additive such that their combined activity mirrors the sum of their individual activities, developmental enhancers are super-additive and combine multiplicatively. Super-additivity between developmental enhancers is promiscuous and neither depends on the enhancers' endogenous genomic contexts nor on specific transcription factor motif signatures. However, it can be further boosted by Twist and Trl motifs and saturates for the highest levels of enhancer activity. These results have important implications for our understanding of gene regulation in complex multi-enhancer developmental loci and genomically clustered housekeeping genes, providing a rationale to interpret the transcriptional impact of non-coding mutations at different loci.

Regulatory landscape of enhancer-mediated transcriptional activation

Enhancers are noncoding regulatory elements that instruct spatial and temporal specificity of gene transcription in response to a variety of intrinsic and extrinsic signals during development. Although it has long been postulated that enhancers physically interact with target promoters through the formation of stable loops, recent studies have changed this static view: sequence-specific transcription factors (TFs) and coactivators are dynamically recruited to enhancers and assemble so-called transcription hubs. Dynamic assembly of transcription hubs appears to serve as a key scaffold to integrate regulatory information encoded by surrounding genome and biophysical properties of transcription machineries. In this review, we outline emerging new models of transcriptional regulation by enhancers and discuss future perspectives.

Dynamic modulation of enhancer-promoter and promoter-promoter connectivity in gene regulation

Enhancers are short segments of regulatory DNA that control when and in which cell-type genes should be turned on in response to a variety of extrinsic and intrinsic signals. At the molecular level, enhancers serve as a genomic scaffold that recruits sequence-specific transcription factors and co-activators to facilitate transcription from linked promoters. However, it remains largely unclear how enhancers communicate with appropriate target promoters in the context of higher-order genome topology. In this review, we discuss recent progress in our understanding of the functional interplay between enhancers, genome topology, and the molecular properties of transcription machineries in gene regulation. We suggest that the activities of transcription hubs are highly regulated through the dynamic rearrangement of enhancer-promoter and promoter-promoter connectivity during animal development.

Transcriptional repression and enhancer decommissioning silence cell cycle genes in postmitotic tissues

The mechanisms that maintain a non-cycling status in postmitotic tissues are not well understood. Many cell cycle genes have promoters and enhancers that remain accessible even when cells are terminally differentiated and in a non-cycling state, suggesting their repression must be maintained long term. In contrast, enhancer decommissioning has been observed for rate-limiting cell cycle genes in the Drosophila wing, a tissue where the cells die soon after eclosion, but it has been unclear if this also occurs in other contexts of terminal differentiation. In this study, we show that enhancer decommissioning also occurs at specific, rate-limiting cell cycle genes in the long-lived tissues of the Drosophila eye and brain, and we propose this loss of chromatin accessibility may help maintain a robust postmitotic state. We examined the decommissioned enhancers at specific rate-limiting cell cycle genes and show that they encode for dynamic temporal and spatial expression patterns that include shared, as well as tissue-specific elements, resulting in broad gene expression with developmentally controlled temporal regulation. We extend our analysis to cell cycle gene expression and chromatin accessibility in the mammalian retina using a published dataset and find that the principles of cell cycle gene regulation identified in terminally differentiating Drosophila tissues are conserved in the differentiating mammalian retina. We propose a robust, non-cycling status is maintained in long-lived postmitotic tissues through a combination of stable repression at most cell cycle genes, alongside enhancer decommissioning at specific rate-limiting cell cycle genes.

Multiplex profiling of developmental cis-regulatory elements with quantitative single-cell expression reporters

The inability to scalably and precisely measure the activity of developmental cis-regulatory elements (CREs) in multicellular systems is a bottleneck in genomics. Here we develop a dual RNA cassette that decouples the detection and quantification tasks inherent to multiplex single-cell reporter assays. The resulting measurement of reporter expression is accurate over multiple orders of magnitude, with a precision approaching the limit set by Poisson counting noise. Together with RNA barcode stabilization via circularization, these scalable single-cell quantitative expression reporters provide high-contrast readouts, analogous to classic in situ assays but entirely from sequencing. Screening >200 regions of accessible chromatin in a multicellular in vitro model of early mammalian development, we identify 13 (8 previously uncharacterized) autonomous and cell-type-specific developmental CREs. We further demonstrate that chimeric CRE pairs generate cognate two-cell-type activity profiles and assess gain- and loss-of-function multicellular expression phenotypes from CRE variants with perturbed transcription factor binding sites. Single-cell quantitative expression reporters can be applied in developmental and multicellular systems to quantitatively characterize native, perturbed and synthetic CREs at scale, with high sensitivity and at single-cell resolution.

Systematical identification of key genes and regulatory genetic variants associated with prognosis of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) stands as a highly lethal malignancy characterized by pronounced recurrence and metastasis, resulting in a bleak 5-year survival rate. Despite extensive investigations, encompassing genome-wide association studies, the identification of robust prognostic markers has remained elusive. In this study, leveraging four independent data sets comprising 404 ESCC patients, we conducted a systematic analysis to unveil pivotal genes influencing overall survival. our meta-analysis identified 278 genes significantly associated with ESCC prognosis. Further exploration of the prognostic landscape involved an examination of expression quantitative trait loci for these genes, leading to the identification of six tag single nucleotide polymorphisms predictive of overall survival in a cohort of 904 ESCC patients. Notably, functional annotation spotlighted rs11227223, residing in the enhancer region of nuclear paraspeckle assembly transcript 1 (NEAT1), as a crucial variant likely exerting a substantive biological role. Through a series of biochemistry experiments, we conclusively demonstrated that the rs11227223-T allele, indicative of a poorer prognosis, augmented NEAT1 expression. Our results underscore the substantive role of NEAT1 and its regulatory variant in prognostic predictions for ESCC. This comprehensive analysis not only advances our comprehension of ESCC prognosis but also unveils a potential avenue for targeted interventions, offering promise for enhanced clinical outcomes.

Transcriptional repression and enhancer decommissioning silence cell cycle genes in postmitotic tissues

The mechanisms that maintain a non-cycling status in postmitotic tissues are not well understood. Many cell cycle genes have promoters and enhancers that remain accessible even when cells are terminally differentiated and in a non-cycling state, suggesting their repression must be maintained long term. In contrast, enhancer decommissioning has been observed for rate-limiting cell cycle genes in the Drosophila wing, a tissue where the cells die soon after eclosion, but it has been unclear if this also occurs in other contexts of terminal differentiation. In this study, we show that enhancer decommissioning also occurs at specific, rate-limiting cell cycle genes in the long-lived tissues of the Drosophila eye and brain, and we propose this loss of chromatin accessibility may help maintain a robust postmitotic state. We examined the decommissioned enhancers at specific rate-limiting cell cycle genes and show that they encode dynamic temporal and spatial expression patterns that include shared, as well as tissue-specific elements, resulting in broad gene expression with developmentally controlled temporal regulation. We extend our analysis to cell cycle gene expression and chromatin accessibility in the mammalian retina using a published dataset, and find that the principles of cell cycle gene regulation identified in terminally differentiating Drosophila tissues are conserved in the differentiating mammalian retina. We propose a robust, non-cycling status is maintained in long-lived postmitotic tissues through a combination of stable repression at most cell cycle gens, alongside enhancer decommissioning at specific rate-limiting cell cycle genes.

The BTB-ZF gene Bm-mamo regulates pigmentation in silkworm caterpillars

The color pattern of insects is one of the most diverse adaptive evolutionary phenotypes. However, the molecular regulation of this color pattern is not fully understood. In this study, we found that the transcription factor Bm-mamo is responsible for black dilute (bd) allele mutations in the silkworm. Bm-mamo belongs to the BTB zinc finger family and is orthologous to mamo in Drosophila melanogaster. This gene has a conserved function in gamete production in Drosophila and silkworms and has evolved a pleiotropic function in the regulation of color patterns in caterpillars. Using RNAi and clustered regularly interspaced short palindromic repeats (CRISPR) technology, we showed that Bm-mamo is a repressor of dark melanin patterns in the larval epidermis. Using in vitro binding assays and gene expression profiling in wild-type and mutant larvae, we also showed that Bm-mamo likely regulates the expression of related pigment synthesis and cuticular protein genes in a coordinated manner to mediate its role in color pattern formation. This mechanism is consistent with the dual role of this transcription factor in regulating both the structure and shape of the cuticle and the pigments that are embedded within it. This study provides new insight into the regulation of color patterns as well as into the construction of more complex epidermal features in some insects.

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.

Increased enhancer-promoter interactions during developmental enhancer activation in mammals

Remote enhancers are thought to interact with their target promoters via physical proximity, yet the importance of this proximity for enhancer function remains unclear. Here we investigate the three-dimensional (3D) conformation of enhancers during mammalian development by generating high-resolution tissue-resolved contact maps for nearly a thousand enhancers with characterized in vivo activities in ten murine embryonic tissues. Sixty-one percent of developmental enhancers bypass their neighboring genes, which are often marked by promoter CpG methylation. The majority of enhancers display tissue-specific 3D conformations, and both enhancer-promoter and enhancer-enhancer interactions are moderately but consistently increased upon enhancer activation in vivo. Less than 14% of enhancer-promoter interactions form stably across tissues; however, these invariant interactions form in the absence of the enhancer and are likely mediated by adjacent CTCF binding. Our results highlight the general importance of enhancer-promoter physical proximity for developmental gene activation in mammals.

Conserved and novel enhancers in the Aedes aegypti single-minded locus recapitulate embryonic ventral midline gene expression

Transcriptional cis-regulatory modules, e.g., enhancers, control the time and location of metazoan gene expression. While changes in enhancers can provide a powerful force for evolution, there is also significant deep conservation of enhancers for developmentally important genes, with function and sequence characteristics maintained over hundreds of millions of years of divergence. Not well understood, however, is how the overall regulatory composition of a locus evolves, with important outstanding questions such as how many enhancers are conserved vs. novel, and to what extent are the locations of conserved enhancers within a locus maintained? We begin here to address these questions with a comparison of the respective single-minded (sim) loci in the two dipteran species Drosophila melanogaster (fruit fly) and Aedes aegypti (mosquito). sim encodes a highly conserved transcription factor that mediates development of the arthropod embryonic ventral midline. We identify two enhancers in the A. aegypti sim locus and demonstrate that they function equivalently in both transgenic flies and transgenic mosquitoes. One A. aegypti enhancer is highly similar to known Drosophila counterparts in its activity, location, and autoregulatory capability. The other differs from any known Drosophila sim enhancers with a novel location, failure to autoregulate, and regulation of expression in a unique subset of midline cells. Our results suggest that the conserved pattern of sim expression in the two species is the result of both conserved and novel regulatory sequences. Further examination of this locus will help to illuminate how the overall regulatory landscape of a conserved developmental gene evolves.

Enhancer-promoter interactions can form independently of genomic distance and be functional across TAD boundaries

Topologically Associating Domains (TADs) have been suggested to facilitate and constrain enhancer-promoter interactions. However, the role of TAD boundaries in effectively restricting these interactions remains unclear. Here, we show that a significant proportion of enhancer-promoter interactions are established across TAD boundaries in Drosophila embryos, but that developmental genes are strikingly enriched in intra- but not inter-TAD interactions. We pursued this observation using the twist locus, a master regulator of mesoderm development, and systematically relocated one of its enhancers to various genomic locations. While this developmental gene can establish inter-TAD interactions with its enhancer, the functionality of these interactions remains limited, highlighting the existence of topological constraints. Furthermore, contrary to intra-TAD interactions, the formation of inter-TAD enhancer-promoter interactions is not solely driven by genomic distance, with distal interactions sometimes favored over proximal ones. These observations suggest that other general mechanisms must exist to establish and maintain specific enhancer-promoter interactions across large distances.

Cell-type-directed design of synthetic enhancers

Transcriptional enhancers act as docking stations for combinations of transcription factors and thereby regulate spatiotemporal activation of their target genes1. It has been a long-standing goal in the field to decode the regulatory logic of an enhancer and to understand the details of how spatiotemporal gene expression is encoded in an enhancer sequence. Here we show that deep learning models2-6, can be used to efficiently design synthetic, cell-type-specific enhancers, starting from random sequences, and that this optimization process allows detailed tracing of enhancer features at single-nucleotide resolution. We evaluate the function of fully synthetic enhancers to specifically target Kenyon cells or glial cells in the fruit fly brain using transgenic animals. We further exploit enhancer design to create 'dual-code' enhancers that target two cell types and minimal enhancers smaller than 50 base pairs that are fully functional. By examining the state space searches towards local optima, we characterize enhancer codes through the strength, combination and arrangement of transcription factor activator and transcription factor repressor motifs. Finally, we apply the same strategies to successfully design human enhancers, which adhere to enhancer rules similar to those of Drosophila enhancers. Enhancer design guided by deep learning leads to better understanding of how enhancers work and shows that their code can be exploited to manipulate cell states.

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.

The adhesion G-protein-coupled receptor mayo/CG11318 controls midgut development in Drosophila

Adhesion G-protein-coupled receptors (aGPCRs) form a large family of cell surface molecules with versatile tasks in organ development. Many aGPCRs still await their functional and pharmacological deorphanization. Here, we characterized the orphan aGPCR CG11318/mayo of Drosophila melanogaster and found it expressed in specific regions of the gastrointestinal canal and anal plates, epithelial specializations that control ion homeostasis. Genetic removal of mayo results in tachycardia, which is caused by hyperkalemia of the larval hemolymph. The hyperkalemic effect can be mimicked by a raise in ambient potassium concentration, while normal potassium levels in mayoKO mutants can be restored by pharmacological inhibition of potassium channels. Intriguingly, hyperkalemia and tachycardia are caused non-cell autonomously through mayo-dependent control of enterocyte proliferation in the larval midgut, which is the primary function of this aGPCR. These findings characterize the ancestral aGPCR Mayo as a homeostatic regulator of gut development.

Macrophage subpopulation identity in Drosophila is modulated by apoptotic cell clearance and related signalling pathways

In Drosophila blood, plasmatocytes of the haemocyte lineage represent the functional equivalent of vertebrate macrophages and have become an established in vivo model with which to study macrophage function and behaviour. However, the use of plasmatocytes as a macrophage model has been limited by a historical perspective that plasmatocytes represent a homogenous population of cells, in contrast to the high levels of heterogeneity of vertebrate macrophages. Recently, a number of groups have reported transcriptomic approaches which suggest the existence of plasmatocyte heterogeneity, while we identified enhancer elements that identify subpopulations of plasmatocytes which exhibit potentially pro-inflammatory behaviours, suggesting conservation of plasmatocyte heterogeneity in Drosophila. These plasmatocyte subpopulations exhibit enhanced responses to wounds and decreased rates of efferocytosis when compared to the overall plasmatocyte population. Interestingly, increasing the phagocytic requirement placed upon plasmatocytes is sufficient to decrease the size of these plasmatocyte subpopulations in the embryo. However, the mechanistic basis for this response was unclear. Here, we examine how plasmatocyte subpopulations are modulated by apoptotic cell clearance (efferocytosis) demands and associated signalling pathways. We show that loss of the phosphatidylserine receptor Simu prevents an increased phagocytic burden from modulating specific subpopulation cells, while blocking other apoptotic cell receptors revealed no such rescue. This suggests that Simu-dependent efferocytosis is specifically involved in determining fate of particular subpopulations. Supportive of our original finding, mutations in amo (the Drosophila homolog of PKD2), a calcium-permeable channel which operates downstream of Simu, phenocopy simu mutants. Furthermore, we show that Amo is involved in the acidification of the apoptotic cell-containing phagosomes, suggesting that this reduction in pH may be associated with macrophage reprogramming. Additionally, our results also identify Ecdysone receptor signalling, a pathway related to control of cell death during developmental transitions, as a controller of plasmatocyte subpopulation identity. Overall, these results identify fundamental pathways involved in the specification of plasmatocyte subpopulations and so further validate Drosophila plasmatocytes as a heterogeneous population of macrophage-like cells within this important developmental and immune model.

Tissue-specific RNA Polymerase II promoter-proximal pause release and burst kinetics in a Drosophila embryonic patterning network

BACKGROUND

Formation of tissue-specific transcriptional programs underlies multicellular development, including dorsoventral (DV) patterning of the Drosophila embryo. This involves interactions between transcriptional enhancers and promoters in a chromatin context, but how the chromatin landscape influences transcription is not fully understood.

RESULTS

Here we comprehensively resolve differential transcriptional and chromatin states during Drosophila DV patterning. We find that RNA Polymerase II pausing is established at DV promoters prior to zygotic genome activation (ZGA), that pausing persists irrespective of cell fate, but that release into productive elongation is tightly regulated and accompanied by tissue-specific P-TEFb recruitment. DV enhancers acquire distinct tissue-specific chromatin states through CBP-mediated histone acetylation that predict the transcriptional output of target genes, whereas promoter states are more tissue-invariant. Transcriptome-wide inference of burst kinetics in different cell types revealed that while DV genes are generally characterized by a high burst size, either burst size or frequency can differ between tissues.

CONCLUSIONS

The data suggest that pausing is established by pioneer transcription factors prior to ZGA and that release from pausing is imparted by enhancer chromatin state to regulate bursting in a tissue-specific manner in the early embryo. Our results uncover how developmental patterning is orchestrated by tissue-specific bursts of transcription from Pol II primed promoters in response to enhancer regulatory cues.

Cis-Regulatory Elements in Mammals

In cis-regulatory elements, enhancers and promoters with complex molecular interactions are used to coordinate gene transcription through physical proximity and chemical modifications. These processes subsequently influence the phenotypic characteristics of an organism. An in-depth exploration of enhancers and promoters can substantially enhance our understanding of gene regulatory networks, shedding new light on mammalian development, evolution and disease pathways. In this review, we provide a comprehensive overview of the intrinsic structural attributes, detection methodologies as well as the operational mechanisms of enhancers and promoters, coupled with the relevant novel and innovative investigative techniques used to explore their actions. We further elucidated the state-of-the-art research on the roles of enhancers and promoters in the realms of mammalian development, evolution and disease, and we conclude with forward-looking insights into prospective research avenues.

Neuronal calcium spikes enable vector inversion in the Drosophila brain

A typical neuron signals to downstream cells when it is depolarized and firing sodium spikes. Some neurons, however, also fire calcium spikes when hyperpolarized. The function of such bidirectional signaling remains unclear in most circuits. Here we show how a neuron class that participates in vector computation in the fly central complex employs hyperpolarization-elicited calcium spikes to invert two-dimensional mathematical vectors. When cells switch from firing sodium to calcium spikes, this leads to a ~180° realignment between the vector encoded in the neuronal population and the fly's internal heading signal, thus inverting the vector. We show that the calcium spikes rely on the T-type calcium channel Ca-α1T, and argue, via analytical and experimental approaches, that these spikes enable vector computations in portions of angular space that would otherwise be inaccessible. These results reveal a seamless interaction between molecular, cellular and circuit properties for implementing vector math in the brain.

MPRAbase: A Massively Parallel Reporter Assay Database

Massively parallel reporter assays (MPRAs) represent a set of high-throughput technologies that measure the functional effects of thousands of sequences/variants on gene regulatory activity. There are several different variations of MPRA technology and they are used for numerous applications, including regulatory element discovery, variant effect measurement, saturation mutagenesis, synthetic regulatory element generation or characterization of evolutionary gene regulatory differences. Despite their many designs and uses, there is no comprehensive database that incorporates the results of these experiments. To address this, we developed MPRAbase, a manually curated database that currently harbors 129 experiments, encompassing 17,718,677 elements tested across 35 cell types and 4 organisms. The MPRAbase web interface ( http://www.mprabase.com ) serves as a centralized user-friendly repository to download existing MPRA data for independent analysis and is designed with the ability to allow researchers to share their published data for rapid dissemination to the community.

Generation of Mutants from the 57B Region of Drosophila melanogaster

The 57B region of Drosophila melanogaster includes a cluster of the three homeobox genes orthopedia (otp), Drosophila Retinal homeobox (DRx), and homeobrain (hbn). In an attempt to isolate mutants for these genes, we performed an EMS mutagenesis and isolated lethal mutants from the 57B region, among them mutants for otp, DRx, and hbn. With the help of two newly generated deletions from the 57B region, we mapped additional mutants to specific chromosomal intervals and identified several of these mutants from the 57B region molecularly. In addition, we generated mutants for CG15651 and RIC-3 by gene targeting and mutants for the genes CG9344, CG15649, CG15650, and ND-B14.7 using the CRISPR/Cas9 system. We determined the lethality period during development for most isolated mutants. In total, we analysed alleles from nine different genes from the 57B region of Drosophila, which could now be used to further explore the functions of the corresponding genes in the future.

Dopaminergic systems create reward seeking despite adverse consequences

Resource-seeking behaviours are ordinarily constrained by physiological needs and threats of danger, and the loss of these controls is associated with pathological reward seeking1. Although dysfunction of the dopaminergic valuation system of the brain is known to contribute towards unconstrained reward seeking2,3, the underlying reasons for this behaviour are unclear. Here we describe dopaminergic neural mechanisms that produce reward seeking despite adverse consequences in Drosophila melanogaster. Odours paired with optogenetic activation of a defined subset of reward-encoding dopaminergic neurons become cues that starved flies seek while neglecting food and enduring electric shock punishment. Unconstrained seeking of reward is not observed after learning with sugar or synthetic engagement of other dopaminergic neuron populations. Antagonism between reward-encoding and punishment-encoding dopaminergic neurons accounts for the perseverance of reward seeking despite punishment, whereas synthetic engagement of the reward-encoding dopaminergic neurons also impairs the ordinary need-dependent dopaminergic valuation of available food. Connectome analyses reveal that the population of reward-encoding dopaminergic neurons receives highly heterogeneous input, consistent with parallel representation of diverse rewards, and recordings demonstrate state-specific gating and satiety-related signals. We propose that a similar dopaminergic valuation system dysfunction is likely to contribute to maladaptive seeking of rewards by mammals.

The evolution and mutational robustness of chromatin accessibility in Drosophila

BACKGROUND

The evolution of genomic regulatory regions plays a critical role in shaping the diversity of life. While this process is primarily sequence-dependent, the enormous complexity of biological systems complicates the understanding of the factors underlying regulation and its evolution. Here, we apply deep neural networks as a tool to investigate the sequence determinants underlying chromatin accessibility in different species and tissues of Drosophila.

RESULTS

We train hybrid convolution-attention neural networks to accurately predict ATAC-seq peaks using only local DNA sequences as input. We show that our models generalize well across substantially evolutionarily diverged species of insects, implying that the sequence determinants of accessibility are highly conserved. Using our model to examine species-specific gains in accessibility, we find evidence suggesting that these regions may be ancestrally poised for evolution. Using in silico mutagenesis, we show that accessibility can be accurately predicted from short subsequences in each example. However, in silico knock-out of these sequences does not qualitatively impair classification, implying that accessibility is mutationally robust. Subsequently, we show that accessibility is predicted to be robust to large-scale random mutation even in the absence of selection. Conversely, simulations under strong selection demonstrate that accessibility can be extremely malleable despite its robustness. Finally, we identify motifs predictive of accessibility, recovering both novel and previously known motifs.

CONCLUSIONS

These results demonstrate the conservation of the sequence determinants of accessibility and the general robustness of chromatin accessibility, as well as the power of deep neural networks to explore fundamental questions in regulatory genomics and evolution.

Chromatin accessibility in the Drosophila embryo is determined by transcription factor pioneering and enhancer activation

Chromatin accessibility is integral to the process by which transcription factors (TFs) read out cis-regulatory DNA sequences, but it is difficult to differentiate between TFs that drive accessibility and those that do not. Deep learning models that learn complex sequence rules provide an unprecedented opportunity to dissect this problem. Using zygotic genome activation in Drosophila as a model, we analyzed high-resolution TF binding and chromatin accessibility data with interpretable deep learning and performed genetic validation experiments. We identify a hierarchical relationship between the pioneer TF Zelda and the TFs involved in axis patterning. Zelda consistently pioneers chromatin accessibility proportional to motif affinity, whereas patterning TFs augment chromatin accessibility in sequence contexts where they mediate enhancer activation. We conclude that chromatin accessibility occurs in two tiers: one through pioneering, which makes enhancers accessible but not necessarily active, and the second when the correct combination of TFs leads to enhancer activation.

Mate copying requires the coincidence detector Rutabaga in the mushroom bodies of Drosophila melanogaster

Mate choice constitutes a major fitness-affecting decision often involving social learning leading to copying the preference of other individuals (i.e., mate copying). While mate copying exists in many taxa, its underlying neurobiological mechanisms remain virtually unknown. Here, we show in Drosophila melanogaster that the rutabaga gene is necessary to support mate copying. Rutabaga encodes an adenylyl cyclase (AC-Rut+) acting as a coincidence detector in associative learning. Since the brain localization requirements for AC-Rut+ expression differ in classical and operant learning, we determine the functional localization of AC-Rut+ for mate copying by artificially rescuing the expression of AC-Rut+ in neural subsets of a rutabaga mutant. We found that AC-Rut+ has to be expressed in the mushroom bodies' Kenyon cells (KCs), specifically in the γ-KCs subset. Thus, this form of discriminative social learning requires the same KCs as non-social Pavlovian learning, suggesting that pathways of social and asocial learning overlap significantly.

Shifting landscapes: the role of 3D genomic organizations in gene regulatory strategies

3D genome folding enables the physical storage of chromosomes into the compact volume of a cell's nucleus, allows for the accurate segregation of chromatin to daughter cells, and has been shown to be tightly coupled to the way in which genetic information is converted into transcriptional programs [1-3]. Importantly, this link between chromatin architecture and gene regulation is a selectable feature in which modifications to chromatin organization accompany, or perhaps even drive the establishment of new regulatory strategies with enduring impacts on animal body plan complexity. Here, we discuss the nature of different 3D genome folding systems found across the tree of life, with particular emphasis on metazoans, and the relative influence of these systems on gene regulation. We suggest how the properties of these folding systems have influenced regulatory strategies employed by different lineages and may have catalyzed the partitioning and specialization of genetic programs that enabled multicellularity and organ-grade body plan complexity.

Exploring the Role of Enhancer-Mediated Transcriptional Regulation in Precision Biology

The emergence of precision biology has been driven by the development of advanced technologies and techniques in high-resolution biological research systems. Enhancer-mediated transcriptional regulation, a complex network of gene expression and regulation in eukaryotes, has attracted significant attention as a promising avenue for investigating the underlying mechanisms of biological processes and diseases. To address biological problems with precision, large amounts of data, functional information, and research on the mechanisms of action of biological molecules is required to address biological problems with precision. Enhancers, including typical enhancers and super enhancers, play a crucial role in gene expression and regulation within this network. The identification and targeting of disease-associated enhancers hold the potential to advance precision medicine. In this review, we present the concepts, progress, importance, and challenges in precision biology, transcription regulation, and enhancers. Furthermore, we propose a model of transcriptional regulation for multi-enhancers and provide examples of their mechanisms in mammalian cells, thereby enhancing our understanding of how enhancers achieve precise regulation of gene expression in life processes. Precision biology holds promise in providing new tools and platforms for discovering insights into gene expression and disease occurrence, ultimately benefiting individuals and society as a whole.

The evolution and mutational robustness of chromatin accessibility in Drosophila

The evolution of regulatory regions in the genome plays a critical role in shaping the diversity of life. While this process is primarily sequence-dependent, the enormous complexity of biological systems has made it difficult to understand the factors underlying regulation and its evolution. Here, we apply deep neural networks as a tool to investigate the sequence determinants underlying chromatin accessibility in different tissues of Drosophila. We train hybrid convolution-attention neural networks to accurately predict ATAC-seq peaks using only local DNA sequences as input. We show that a model trained in one species has nearly identical performance when tested in another species, implying that the sequence determinants of accessibility are highly conserved. Indeed, model performance remains excellent even in distantly-related species. By using our model to examine species-specific gains in chromatin accessibility, we find that their orthologous inaccessible regions in other species have surprisingly similar model outputs, suggesting that these regions may be ancestrally poised for evolution. We then use in silico saturation mutagenesis to reveal evidence of selective constraint acting specifically on inaccessible chromatin regions. We further show that chromatin accessibility can be accurately predicted from short subsequences in each example. However, in silico knock-out of these sequences does not qualitatively impair classification, implying that chromatin accessibility is mutationally robust. Subsequently, we demonstrate that chromatin accessibility is predicted to be robust to large-scale random mutation even in the absence of selection. We also perform in silico evolution experiments under the regime of strong selection and weak mutation (SSWM) and show that chromatin accessibility can be extremely malleable despite its mutational robustness. However, selection acting in different directions in a tissue-specific manner can substantially slow adaptation. Finally, we identify motifs predictive of chromatin accessibility and recover motifs corresponding to known chromatin accessibility activators and repressors. These results demonstrate the conservation of the sequence determinants of accessibility and the general robustness of chromatin accessibility, as well as the power of deep neural networks as tools to answer fundamental questions in regulatory genomics and evolution.

Transitions in development - an interview with Evgeny Kvon

Evgeny Kvon is an Assistant Professor at the University of California, Irvine (UCI) in the Department of Developmental and Cell Biology, USA. His lab studies non-coding regulatory DNA and its mechanistic role in the control of gene expression to understand more about development, disease and evolution. Last year, Evgeny received the National Institutes of Health Director's New Innovator Award. We spoke to Evgeny over Zoom to learn more about his career and the silver lining to starting a lab during the COVID-19 lockdowns.

Transient photocurrents in a subthreshold evidence accumulator accelerate perceptual decisions

Perceptual decisions are complete when a continuously updated score of sensory evidence reaches a threshold. In Drosophila, αβ core Kenyon cells (αβc KCs) of the mushroom bodies integrate odor-evoked synaptic inputs to spike threshold at rates that parallel the speed of olfactory choices. Here we perform a causal test of the idea that the biophysical process of synaptic integration underlies the psychophysical process of bounded evidence accumulation in this system. Injections of single brief, EPSP-like depolarizations into the dendrites of αβc KCs during odor discrimination, using closed-loop control of a targeted opsin, accelerate decision times at a marginal cost of accuracy. Model comparisons favor a mechanism of temporal integration over extrema detection and suggest that the optogenetically evoked quanta are added to a growing total of sensory evidence, effectively lowering the decision bound. The subthreshold voltage dynamics of αβc KCs thus form an accumulator memory for sequential samples of information.

Genomic benchmarks: a collection of datasets for genomic sequence classification

BACKGROUND

Recently, deep neural networks have been successfully applied in many biological fields. In 2020, a deep learning model AlphaFold won the protein folding competition with predicted structures within the error tolerance of experimental methods. However, this solution to the most prominent bioinformatic challenge of the past 50 years has been possible only thanks to a carefully curated benchmark of experimentally predicted protein structures. In Genomics, we have similar challenges (annotation of genomes and identification of functional elements) but currently, we lack benchmarks similar to protein folding competition.

RESULTS

Here we present a collection of curated and easily accessible sequence classification datasets in the field of genomics. The proposed collection is based on a combination of novel datasets constructed from the mining of publicly available databases and existing datasets obtained from published articles. The collection currently contains nine datasets that focus on regulatory elements (promoters, enhancers, open chromatin region) from three model organisms: human, mouse, and roundworm. A simple convolution neural network is also included in a repository and can be used as a baseline model. Benchmarks and the baseline model are distributed as the Python package 'genomic-benchmarks', and the code is available at https://github.com/ML-Bioinfo-CEITEC/genomic_benchmarks .

CONCLUSIONS

Deep learning techniques revolutionized many biological fields but mainly thanks to the carefully curated benchmarks. For the field of Genomics, we propose a collection of benchmark datasets for the classification of genomic sequences with an interface for the most commonly used deep learning libraries, implementation of the simple neural network and a training framework that can be used as a starting point for future research. The main aim of this effort is to create a repository for shared datasets that will make machine learning for genomics more comparable and reproducible while reducing the overhead of researchers who want to enter the field, leading to healthy competition and new discoveries.

Ecdysone signaling determines lateral polarity and remodels neurites to form Drosophila's left-right brain asymmetry

Left-right (LR) asymmetry of the brain is fundamental to its higher-order functions. The Drosophila brain's asymmetrical body (AB) consists of a structural pair arborized from AB neurons and is larger on the right side than the left. We find that the AB initially forms LR symmetrically and then develops LR asymmetrically by neurite remodeling that is specific to the left AB and is dynamin dependent. Additionally, neuronal ecdysone signaling inhibition randomizes AB laterality, suggesting that ecdysone signaling determines AB's LR polarity. Given that AB's LR asymmetry relates to memory formation, our research establishes AB as a valuable model for studying LR asymmetry and higher-order brain function relationships.

A modERN resource: identification of Drosophila transcription factor candidate target genes using RNAi

Transcription factors (TFs) play a key role in development and in cellular responses to the environment by activating or repressing the transcription of target genes in precise spatial and temporal patterns. In order to develop a catalog of target genes of Drosophila melanogaster TFs, the modERN consortium systematically knocked down the expression of TFs using RNAi in whole embryos followed by RNA-seq. We generated data for 45 TFs which have 18 different DNA-binding domains and are expressed in 15 of the 16 organ systems. The range of inactivation of the targeted TFs by RNAi ranged from log2fold change -3.52 to +0.49. The TFs also showed remarkable heterogeneity in the numbers of candidate target genes identified, with some generating thousands of candidates and others only tens. We present detailed analysis from five experiments, including those for three TFs that have been the focus of previous functional studies (ERR, sens, and zfh2) and two previously uncharacterized TFs (sens-2 and CG32006), as well as short vignettes for selected additional experiments to illustrate the utility of this resource. The RNA-seq datasets are available through the ENCODE DCC (http://encodeproject.org) and the Sequence Read Archive (SRA). TF and target gene expression patterns can be found here: https://insitu.fruitfly.org. These studies provide data that facilitate scientific inquiries into the functions of individual TFs in key developmental, metabolic, defensive, and homeostatic regulatory pathways, as well as provide a broader perspective on how individual TFs work together in local networks during embryogenesis.

Cell-specific occupancy dynamics between the pioneer-like factor Opa/ZIC and Ocelliless/OTX regulate early head development in embryos

During development, embryonic patterning systems direct a set of initially uncommitted pluripotent cells to differentiate into a variety of cell types and tissues. A core network of transcription factors, such as Zelda/POU5F1, Odd-paired (Opa)/ZIC3 and Ocelliless (Oc)/OTX2, are conserved across animals. While Opa is essential for a second wave of zygotic activation after Zelda, it is unclear whether Opa drives head cell specification, in the Drosophila embryo. Our hypothesis is that Opa and Oc are interacting with distinct cis-regulatory regions for shaping cell fates in the embryonic head. Super-resolution microscopy and meta-analysis of single-cell RNAseq datasets show that opa’s and oc’s overlapping expression domains are dynamic in the head region, with both factors being simultaneously transcribed at the blastula stage. Additionally, analysis of single-embryo RNAseq data reveals a subgroup of Opa-bound genes to be Opa-independent in the cellularized embryo. Interrogation of these genes against Oc ChIPseq combined with in situ data, suggests that Opa is competing with Oc for the regulation of a subgroup of genes later in gastrulation. Specifically, we find that Oc binds to late, head-specific enhancers independently and activates them in a head-specific wave of zygotic transcription, suggesting distinct roles for Oc in the blastula and gastrula stages.

The abundances of LTF and SOD2 in amniotic fluid are potential biomarkers of gestational age and preterm birth

Neonates who are born preterm (PT) are usually characterized by immature physiological development, and preterm birth (PTB) is the leading cause of neonatal morbidity and mortality if intensive medical care is not available to PTB neonates. Early prediction of a PTB enables medical personnel to make preparations in advance, protecting the neonate from the subsequent health risks. Therefore, many studies have worked on identifying invasive or noninvasive PT biomarkers. In this study, we collected amniocentesis-derived (at the second trimester of gestation) amniotic fluid (AF) samples. At delivery, AF samples were classified into PTB or full-term birth (FTB). We first applied protein mass spectrometry technology to globally screen AF proteins, followed by specific protein validation with ELISA. We identified four protein biomarkers of PTB, including lactotransferrin (LTF), glutathione-disulfide reductase (GSR), myeloperoxidase (MPO) and superoxide dismutase 2 (SOD2). Further analyses demonstrated that their abundances were negatively correlated with neonatal weight and gestational age. In addition, by mimicking survival rate analysis widely used in tumor biology, we found that LTF and SOD2 were prognostic factors of gestational age, with higher levels denoting shorter gestational age. Finally, using the abundances of the four protein biomarkers, we developed a prediction model of PTB with an auROC value of 0.935 (sensitivity = 0.94, specificity = 0.89, p value = 0.0001). This study demonstrated that the abundances of specific proteins in amniotic fluid were not only the prognostic factors of gestational age but also the predictive biomarkers of PTB. These four AF proteins enable identification of PTB early in the second trimester of gestation, facilitating medical intervention to be applied in advance.

A toolkit for converting Gal4 into LexA and Flippase transgenes in Drosophila

Drosophila has been a powerful model system for biological studies due to the wide range of genetic tools established for it. Among these tools, Gal4 is the most abundant, offering unparalleled tissue and developmental stage specificity for gene manipulation. In comparison, other genetic reagents are far fewer in choices. Here we present a genetic toolkit for converting Gal4 strains into LexA and Flippase transgenes through simple genetic crosses and fluorescence screening. We demonstrate the proof-of-principle by converting ten Gal4 lines that exhibit diverse tissue specificities and examined the activity patterns of the converted LexA and Flippase lines. Gal4-to-LexA and Flp conversion is fast and convenient and should greatly expand the choices of LexA and Flp for binary expression and FRT-based mosaic analysis, respectively, in Drosophila.

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

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

Dynamic interplay between non-coding enhancer transcription and gene activity in development

Non-coding transcription at the intergenic regulatory regions is a prevalent feature of metazoan genomes, but its biological function remains uncertain. Here, we devise a live-imaging system that permits simultaneous visualization of gene activity along with intergenic non-coding transcription at single-cell resolution in Drosophila. Quantitative image analysis reveals that elongation of RNA polymerase II across the internal core region of enhancers leads to suppression of transcriptional bursting from linked genes. Super-resolution imaging and genome-editing analysis further demonstrate that enhancer transcription antagonizes molecular crowding of transcription factors, thereby interrupting the formation of a transcription hub at the gene locus. We also show that a certain class of developmental enhancers are structurally optimized to co-activate gene transcription together with non-coding transcription effectively. We suggest that enhancer function is flexibly tunable through the modulation of hub formation via surrounding non-coding transcription during development.

Using single-cell RNA sequencing to generate cell-type-specific split-GAL4 reagents throughout development

Cell-type-specific tools facilitate the identification and functional characterization of distinct cell types, which underly the complexity of neuronal circuits. A large collection of existing genetic tools in Drosophila relies on enhancer activity to label different subsets of cells. These enhancer-based GAL4 lines often fail to show a predicable expression pattern to reflect the expression of nearby gene(s), partly due to an incomplete capture of the full gene regulatory elements. While genetic intersectional technique such as the split-GAL4 system further improve cell-type-specificity, it requires significant time and resource to generate and screen through combinations of enhancer expression patterns. In addition, since existing enhancer-based split-GAL4 lines that show cell-type-specific labeling in adult are not necessarily active nor specific in early development, there is a relative lack of tools for the study of neural development. Here, we use an existing single-cell RNA sequencing (scRNAseq) dataset to select gene pairs and provide an efficient pipeline to generate cell-type-specific split-GAL4 lines based on the native genetic regulatory elements. These gene-specific split-GAL4 lines can be generated from a large collection of coding intronic MiMIC/CRIMIC lines either by embryo injection or in vivo cassette swapping crosses and/or CRISPR knock-in at the N or C terminal of the gene. We use the developing Drosophila visual system as a model to demonstrate the high prediction power of scRNAseq-guided gene specific split-GAL4 lines in targeting known cell types. The toolkit allows efficient cluster annotation in scRNAseq datasets but also the identification of novel cell types. Lastly, the gene-specific split-GAL4 lines are broadly applicable to Drosophila tissues. Our work opens new avenues for generating cell-type-specific tools for the targeted manipulation of distinct cell types throughout development and represents a valuable resource to the fly research community.

Significance Statement

Understanding the functional role of individual cell types in the nervous systems has remained a major challenge for neuroscience researchers, partly due to incomplete identification and characterization of underlying cell types. To study the development of individual cell types and their functional roles in health and disease, experimental access to a specific cell type is often a prerequisite. Here, we establish an experimental pipeline to generate gene-specific split-GAL4 guided by single-cell RNA sequencing datasets. These lines show high accuracy for labeling targeted cell types from early developmental stages to adulthood and can be applied to any tissues in Drosophila. The collection of gene-speicifc-split-GAL4 will provide a valuable resource to the entire fly research community.

Enhancer architecture and chromatin accessibility constrain phenotypic space during Drosophila development

Developmental enhancers bind transcription factors and dictate patterns of gene expression during development. Their molecular evolution can underlie phenotypical evolution, but the contributions of the evolutionary pathways involved remain little understood. Here, using mutation libraries in Drosophila melanogaster embryos, we observed that most point mutations in developmental enhancers led to changes in gene expression levels but rarely resulted in novel expression outside of the native pattern. In contrast, random sequences, often acting as developmental enhancers, drove expression across a range of cell types; random sequences including motifs for transcription factors with pioneer activity acted as enhancers even more frequently. Our findings suggest that the phenotypic landscapes of developmental enhancers are constrained by enhancer architecture and chromatin accessibility. We propose that the evolution of existing enhancers is limited in its capacity to generate novel phenotypes, whereas the activity of de novo elements is a primary source of phenotypic novelty.

Аpplication of massive parallel reporter analysis in biotechnology and medicine

The development and functioning of an organism relies on tissue-specific gene programs. Genome regulatory elements play a key role in the regulation of such programs, and disruptions in their function can lead to the development of various pathologies, including cancers, malformations and autoimmune diseases. The emergence of high-throughput genomic studies has led to massively parallel reporter analysis (MPRA) methods, which allow the functional verification and identification of regulatory elements on a genome-wide scale. Initially MPRA was used as a tool to investigate fundamental aspects of epigenetics, but the approach also has great potential for clinical and practical biotechnology. Currently, MPRA is used for validation of clinically significant mutations, identification of tissue-specific regulatory elements, search for the most promising loci for transgene integration, and is an indispensable tool for creating highly efficient expression systems, the range of application of which extends from approaches for protein development and design of next-generation therapeutic antibody superproducers to gene therapy. In this review, the main principles and areas of practical application of high-throughput reporter assays will be discussed.

CFA: An explainable deep learning model for annotating the transcriptional roles of cis-regulatory modules based on epigenetic codes

Metazoa gene expression is controlled by modular DNA segments called cis-regulatory modules (CRMs). CRMs can convey promoter/enhancer/insulator roles, generating additional regulation layers in transcription. Experiments for understanding CRM roles are low-throughput and costly. Large-scale CRM function investigation still depends on computational methods. However, existing in silico tools only recognize enhancers or promoters exclusively, thus accumulating errors when considering CRM promoter/enhancer/insulator roles altogether. Currently, no algorithm can concurrently consider these CRM roles. In this research, we developed the CRM Function Annotator (CFA) model. CFA provides complete CRM transcriptional role labeling based on epigenetic profiling interpretation. We demonstrated that CFA achieves high performance (test macro auROC/auPRC = 94.1%/90.3%) and outperforms existing tools in promoter/enhancer/insulator identification. CFA is also inspected to recognize explainable epigenetic codes consistent with previous findings when labeling CRM roles. By considering the higher-order combinations of the epigenetic codes, CFA significantly reduces false-positive rates in CRM transcriptional role annotation. CFA is available at https://github.com/cobisLab/CFA/.

Identification of a GABAergic neuroblast lineage modulating sweet and bitter taste sensitivity

In Drosophila melanogaster, processing of gustatory information and controlling feeding behavior are executed by neural circuits located in the subesophageal zone (SEZ) of the brain.1 Gustatory receptor neurons (GRNs) project their axons in the primary gustatory center (PGC), which is located in the SEZ.1,2,3,4 To address the function of the PGC, we need detailed information about the different classes of gustatory interneurons that frame the PGC. In this work, we screened large collections of driver lines for SEZ interneuron-specific labeling and subsequently used candidate lines to access the SEZ neuroblast lineages. We converted 130 Gal4 lines to LexA drivers and carried out functional screening using calcium imaging. We found one neuroblast lineage, TRdm, whose neurons responded to both sweet and bitter tastants, and formed green fluorescent protein (GFP) reconstitution across synaptic partners (GRASP)-positive synapses with sweet sensory neurons. TRdm neurons express the inhibitory transmitter GABA, and silencing these neurons increases appetitive feeding behavior. These results demonstrate that TRdm generates a class of inhibitory local neurons that control taste sensitivity in Drosophila.

Regeneration and developmental enhancers are differentially compatible with minimal promoters

Enhancers and promoters are cis-regulatory elements that control gene expression. Enhancers are activated in a cell type-, tissue-, and condition-specific manner to stimulate promoter function and transcription. Zebrafish have emerged as a powerful animal model for examining the activities of enhancers derived from various species through transgenic enhancer assays, in which an enhancer is coupled with a minimal promoter. However, the efficiency of minimal promoters and their compatibility with multiple developmental and regeneration enhancers have not been systematically tested in zebrafish. Thus, we assessed the efficiency of six minimal promoters and comprehensively interrogated the compatibility of the promoters with developmental and regeneration enhancers. We found that the fos minimal promoter and Drosophila synthetic core promoter (DSCP) yielded high rates of leaky expression that may complicate the interpretation of enhancer assays. Notably, the adenovirus E1b promoter, the zebrafish lepb 0.8-kb (P0.8) and lepb 2-kb (P2) promoters, and a new zebrafish synthetic promoter (ZSP) that combines elements of the E1b and P0.8 promoters drove little or no ectopic expression, making them suitable for transgenic assays. We also found significant differences in compatibility among specific combinations of promoters and enhancers, indicating the importance of promoters as key regulatory elements determining the specificity of gene expression. Our study provides guidelines for transgenic enhancer assays in zebrafish to aid in the discovery of functional enhancers regulating development and regeneration.

Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material

Background

Recent technological advances opened the opportunity to simultaneously study gene expression for thousands of individual cells on a genome-wide scale. The experimental accessibility of such single-cell RNA sequencing (scRNAseq) approaches allowed gaining insights into the cell type composition of heterogeneous tissue samples of animal model systems and emerging models alike. A major prerequisite for a successful application of the method is the dissociation of complex tissues into individual cells, which often requires large amounts of input material and harsh mechanical, chemical and temperature conditions. However, the availability of tissue material may be limited for small animals, specific organs, certain developmental stages or if samples need to be acquired from collected specimens. Therefore, we evaluated different dissociation protocols to obtain single cells from small tissue samples of Drosophila melanogaster eye-antennal imaginal discs.

Results

We show that a combination of mechanical and chemical dissociation resulted in sufficient high-quality cells. As an alternative, we tested protocols for the isolation of single nuclei, which turned out to be highly efficient for fresh and frozen tissue samples. Eventually, we performed scRNAseq and single-nuclei RNA sequencing (snRNAseq) to show that the best protocols for both methods successfully identified relevant cell types. At the same time, snRNAseq resulted in less artificial gene expression that is caused by rather harsh dissociation conditions needed to obtain single cells for scRNAseq. A direct comparison of scRNAseq and snRNAseq data revealed that both datasets share biologically relevant genes among the most variable genes, and we showed differences in the relative contribution of the two approaches to identified cell types.

Conclusion

We present two dissociation protocols that allow isolating single cells and single nuclei, respectively, from low input material. Both protocols resulted in extraction of high-quality RNA for subsequent scRNAseq or snRNAseq applications. If tissue availability is limited, we recommend the snRNAseq procedure of fresh or frozen tissue samples as it is perfectly suited to obtain thorough insights into cellular diversity of complex tissue.

Chromatin accessibility-based characterisation of brain gene regulatory networks in three distinct honey bee polyphenisms

The honey bee genome has the capacity to produce three phenotypically distinct organisms (two diploid female castes: queen and worker, and a haploid male drone). Previous studies have implicated metabolic flux acting via epigenetic regulation in directing nutrition-driven phenotypic plasticity in the honey bee. However, the cis-acting DNA regulatory elements that establish tissue and polyphenism -specific epigenomes and gene expression programmes, remain unclear. Using a high resolution multiomic approach including assay for transposase-accessible chromatin by sequencing (ATAC-seq), RNA-seq and ChIP-seq, we produce the first genome-wide maps of the regulatory landscape across all three adult honey bee phenotypes identifying > 5000 regulatory regions in queen, 7500 in worker and 6500 in drone, with the vast majority of these sites located within intronic regions. These regions are defined by positive enrichment of H3K27ac and depletion of H3K4me3 and show a positive correlation with gene expression. Using ATAC-seq footprinting we determine queen, worker and drone -specific transcription factor occupancy and uncover novel phenotype-specific regulatory networks identifying two key nuclear receptors that have previously been implicated in caste-determination and adult behavioural maturation in honey bees; ecdysone receptor and ultraspiracle. Collectively, this study provides novel insights into key gene regulatory networks that are associated with these distinct polyphenisms in the honey bee.

Unveiling dynamic enhancer–promoter interactions in Drosophila melanogaster

Proper enhancer–promoter interactions are essential to maintaining specific transcriptional patterns and preventing ectopic gene expression. Drosophila is an ideal model organism to study transcriptional regulation due to extensively characterized regulatory regions and the ease of implementing new genetic and molecular techniques for quantitative analysis. The mechanisms of enhancer–promoter interactions have been investigated over a range of length scales. At a DNA level, compositions of both enhancer and promoter sequences affect transcriptional dynamics, including duration, amplitude, and frequency of transcriptional bursting. 3D chromatin topology is also important for proper enhancer–promoter contacts. By working competitively or cooperatively with one another, multiple, simultaneous enhancer–enhancer, enhancer–promoter, and promoter–promoter interactions often occur to maintain appropriate levels of mRNAs. For some long-range enhancer–promoter interactions, extra regulatory elements like insulators and tethering elements are required to promote proper interactions while blocking aberrant ones. This review provides an overview of our current understanding of the mechanism of enhancer–promoter interactions and how perturbations of such interactions affect transcription and subsequent physiological outcomes.

Multiplexed functional genomic assays to decipher the noncoding genome

Linkage disequilibrium and the incomplete regulatory annotation of the noncoding genome complicates the identification of functional noncoding genetic variants and their causal association with disease. Current computational methods for variant prioritization have limited predictive value, necessitating the application of highly parallelized experimental assays to efficiently identify functional noncoding variation. Here, we summarize two distinct approaches, massively parallel reporter assays and CRISPR-based pooled screens and describe their flexible implementation to characterize human noncoding genetic variation at unprecedented scale. Each approach provides unique advantages and limitations, highlighting the importance of multimodal methodological integration. These multiplexed assays of variant effects are undoubtedly poised to play a key role in the experimental characterization of noncoding genetic risk, informing our understanding of the underlying mechanisms of disease-associated loci and the development of more robust predictive classification algorithms.

Spatial and temporal control of expression with light-gated LOV-LexA

The ability to drive expression of exogenous genes in different tissues and cell types, under the control of specific enhancers, has been crucial for discovery in biology. While many enhancers drive expression broadly, several genetic tools were developed to obtain access to isolated cell types. Studies of spatially organized neuropiles in the central nervous system of fruit flies have raised the need for a system that targets subsets of cells within a single neuronal type, a feat currently dependent on stochastic flip-out methods. To access the same cells within a given expression pattern consistently across fruit flies, we developed the light-gated expression system LOV-LexA. We combined the bacterial LexA transcription factor with the plant-derived light, oxygen, or voltage photosensitive domain and a fluorescent protein. Exposure to blue light uncages a nuclear localizing signal in the C-terminal of the light, oxygen, or voltage domain and leads to the translocation of LOV-LexA to the nucleus, with the subsequent initiation of transcription. LOV-LexA enables spatial and temporal control of expression of transgenes under LexAop sequences in larval fat body and pupal and adult neurons with blue light. The LOV-LexA tool is ready to use with GAL4 and Split-GAL4 drivers in its current form and constitutes another layer of intersectional genetics that provides light-controlled genetic access to specific cells across flies.

Mushroom body input connections form independently of sensory activity in Drosophila melanogaster

Associative brain centers, such as the insect mushroom body, need to represent sensory information in an efficient manner. In Drosophila melanogaster, the Kenyon cells of the mushroom body integrate inputs from a random set of olfactory projection neurons, but some projection neurons-namely those activated by a few ethologically meaningful odors-connect to Kenyon cells more frequently than others. This biased and random connectivity pattern is conceivably advantageous, as it enables the mushroom body to represent a large number of odors as unique activity patterns while prioritizing the representation of a few specific odors. How this connectivity pattern is established remains largely unknown. Here, we test whether the mechanisms patterning the connections between Kenyon cells and projection neurons depend on sensory activity or whether they are hardwired. We mapped a large number of mushroom body input connections in partially anosmic flies-flies lacking the obligate odorant co-receptor Orco-and in wild-type flies. Statistical analyses of these datasets reveal that the random and biased connectivity pattern observed between Kenyon cells and projection neurons forms normally in the absence of most olfactory sensory activity. This finding supports the idea that even comparatively subtle, population-level patterns of neuronal connectivity can be encoded by fixed genetic programs and are likely to be the result of evolved prioritization of ecologically and ethologically salient stimuli.