Various sequencing based approaches are used to identify and characterize the activities of cis-regulatory elements in a genome-wide fashion. The activities of cis-regulatory elements such as enhancers, promoters, and repressors are determined by their sequence and secondary processes such as chromatin accessibility, DNA methylation, and bound histone markers. This study used machine learning models to evaluate the accuracy with which cis-regulatory elements identified by various commonly used sequencing techniques can be predicted by their underlying sequence alone to distinguish between cis-regulatory activity that is reflective of sequence content versus secondary processes. Models trained and evaluated on D. melanogaster sequences identified through DNase-seq and STARR-seq are significantly more accurate than models trained on sequences identified by H3K4me1, H3K4me3, and H3K27ac ChIP-seq, FAIRE-seq, and ATAC-seq. These results suggest that the activity detected by DNase-seq and STARR-seq can be largely explained by underlying DNA sequence, independent of secondary processes. Experimentally, a subset of DNase-seq and H3K4me1 ChIP-seq sequences were tested for enhancer activity using luciferase assays and compared with previous tests performed on STARR-seq sequences. The experimental data indicated that STARR-seq sequences are substantially enriched for enhancer-specific activity, while the DNase-seq and H3K4me1 ChIP-seq sequences are not. Taken together, these results indicate that the DNase-seq approach identifies a broad class of regulatory elements of which enhancers are a subset and the associated data are appropriate for training models for detecting regulatory activity from sequence alone, STARR-seq data are best for training enhancer-specific sequence models, and H3K4me1 ChIP-seq data are not well suited for training and evaluating sequence-based models for cis-regulatory element prediction (Nowling, 2023).

Bistable autoactivation has been proposed as a mechanism for cells to adopt binary fates during embryonic development. However, it is unclear whether the autoactivating modules found within developmental gene regulatory networks are bistable, unless their parameters are quantitatively determined. This study combined in vivo live imaging with mathematical modeling to dissect the binary cell fate dynamics of the fruit fly pair-rule gene fushi tarazu (ftz), which is regulated by two known enhancers: the early (non-autoregulating) element and the autoregulatory element. Live imaging of transcription and protein concentration in the blastoderm revealed that binary Ftz fates are achieved as Ftz expression rapidly transitions from being dictated by the early element to the autoregulatory element. Moreover, this study discovered that Ftz concentration alone is insufficient to activate the autoregulatory element, and that this element only becomes responsive to Ftz at a prescribed developmental time. Based on these observations, a dynamical systems model was developed, and its kinetic parameters were quantitated directly from experimental measurements. This model demonstrated that the ftz autoregulatory module is indeed bistable and that the early element transiently establishes the content of the binary cell fate decision to which the autoregulatory module then commits. Further in silico analysis revealed that the autoregulatory element locks the Ftz fate quickly, within 35 min of exposure to the transient signal of the early element. Overall, this work confirms the widely held hypothesis that autoregulation can establish developmental fates through bistability and, most importantly, provides a framework for the quantitative dissection of cellular decision-making (Zhao, 2023).

Using this approach, it was found that most mutations in enhancers led to changes in levels of reporter gene expression, but almost entirely within their native zones of expression, similar to previous studies using transgenic mutagenesis of the Shh enhancer in murine embryos, or the E3N enhancer and the wing spot¹⁹⁶ enhancer in fly embryos. Consistent with current results, known phenotypic evolution through nucleotide mutations of standing regulatory elements seems to appear either through changes in the levels or timings of expression within native zones or the loss of regulatory activities. For example, the evolution of pigmentation spots in fly wings occurred via a specific spatial increase in the melanic protein Yellow, which is uniformly expressed at low levels throughout the developing wings of fruit flies. Evolution of other traits such as thoracic ribs in vertebrates, limbs in snakes, pelvic structures in sticklebacks, and seed shattering in rice are all associated with loss of enhancer activity due to internal enhancer mutations. Additionally, mutations have been found to occur less often in functionally constrained regions of the genome, suggesting that mutation bias may reduce the occurrence of deleterious mutations in regulatory regions (Galupa, 2023).

Consistent with these results, phenotypic novelties underlain by enhancer-associated ectopic gains of expression are reportedly due to transposon mobilization, rearrangements in chromosome topology, or de novo evolution of enhancers from DNA sequences with unrelated or nonregulatory activities (Galupa, 2023).

Previous studies have explored the potential of random DNA sequences to lead to reporter gene expression, either as enhancers or promoters, especially in cell lines of prokaryotic or eukaryotic origin. These have shown that there is a short (or sometimes null) mutational distance between random sequences and active cis-regulatory elements, which may improve evolvability. This study tested random sequences in a developmental context and found that most showed enhancer activity across several types of tissues and developmental stages. These results are consistent with a study that tested enhancer activity of all 6-mers in developing zebrafish embryos and found a diverse range of expression for ~38% of the sequences at two developmental stages. We observed expression driven by random sequences even in the absence of motifs within their sequence for TFs with pioneering activity. Yet, when such motifs were included, nearly all sequences acted as 'strong' enhancers (leading to high levels of expression), consistent with the 'evolutionary barrier' to the formation of a novel enhancer being lower in regions that already contain motifs for DNA-binding factors, which can 'act cooperatively with newly emerging sites (Galupa, 2023).

It is interesting to note that, despite the high potential of random sequences to be expressed during development and across cell types, expression prior to gastrulation was never observed; this was not evaluated in the zebrafish study or in other studies. This may be due to the rapid rates of early fruit fly development, in which gene expression patterns are highly dynamic, and cell-fate specifications occur within minutes. As such, there may be extensive regulatory demands placed on transcriptional enhancers, reflected in the clusters of high-affinity binding sites common across early embryonic developmental enhancers as well as their extensive conservation in function and location (Galupa, 2023).

In the future, it will be interesting to explore how regulatory demands that change across development-such as nuclear differentiation, network cross-talk, and metabolic changes- are reflected in regulatory architectures and their evolvability. The observation that most random sequences led to expression suggests that the potential of any sequence within the genome to drive expression is enormous and thus 'an important playground for creating new regulatory variability and evolutionary innovation (Galupa, 2023).

This was further supported by the regulatory potential of the genomic sequences that were tested, containing Ubx/Hth motifs; indeed, the results from this work imply that enhancers would more likely evolve from sequences that contain or are biased toward specific motifs (e.g., GATA and Zelda). Perhaps the challenge from an evolutionary perspective has not been what allows expression, but what prevents expression; thus, mechanisms that repress 'spurious' expression might have evolved across genomes. This is in line with propositions that nucleosomal DNA in eukaryotes has evolved to repress transcription, along with transcriptional repressors and other mechanisms such as DNA methylation, as a response (at least partially) to 'the unbearable ease of expression' present in prokaryotes (Galupa, 2023).

The action of such repressive mechanisms could also explain why mutagenesis of developmental enhancers, which are subject to evolutionary selection, does not easily lead to expression outside their native patterns of expression. In sum, the findings of this study raise exciting questions about the evolution of enhancers and the emergence of novel patterns of expression that may underlie new phenotypes, suggesting an underappreciated role for de novo evolution of enhancers by happenstance. Genetic theories of morphological evolution will benefit from comparing controlled, multi-dimensional laboratory experiments with standing variation; such an integrative approach could provide the frameworks that will facilitate making of both transcriptional and evolutionary predictions (Galupa, 2023).

One limitation of this study lies on the numbers - this study has tested a significant number of enhancer variants, but it is still possible that ectopic expression would have been captured more frequently had a larger set of enhancer variants been tested. Also, in principle, a higher number of mutations per enhancer could have also enhanced the likelihood of ectopic expression. Previous work from this lab with the E3N enhancer reported that indeed the proportion of lines with ectopic expression increased with the number of mutations (Galupa, 2023).

However, this increase plateaued around 20%-30% for lines with ~3+ mutations per enhancer and in this study, the number of mutations in the enhancer variants for twiM^PE, rho^NEE, and tin^B ranges from 1 to 7 mutations, so it would be expected to have captured a number of lines with ectopic expression. Importantly, the assay captures millions of years of variation in a controlled setting decoupled from fitness costs. It is also possible that ectopic expression might be present in developmental stages that were not analyzed. Finally, would the results be different if a different promoter had been used? This was not tested formally, but based on published literature, it is believed that using a different promoter would not have major implications in the results observed. Testing a total of enhancer-promoter combinations in human cells, efficiency of enhancers has been shown to be approximately the same irrespective of the type of promoter used, and a recent combinatorial analysis of 1,000 human promoters and 1,000 human enhancers confirmed that most enhancers activate all promoters by similar amounts (Galupa, 2023).

These studies, in cell lines, could only address levels of expression, not spatial patterns-but very recently published results from the lab show that developmental promoters in fly embryos can drive a range of outputs but do not affect spatial aspects of expression, only levels (Galupa, 2023).

The cis-regulatory data that help in transcriptional regulation is arranged into modular pieces of a few hundred base pairs called CRMs (cis-regulatory modules) and numerous binding sites for multiple transcription factors are prominent characteristics of these cis-regulatory modules. The present study was designed to localize transcription factor binding site (TFBS) clusters on twelve Anterior-posterior (A-P) genes in Tribolium castaneum and compare them to their orthologous gene enhancers in Drosophila melanogaster. Out of the twelve A-P patterning genes, six were gap genes (Kruppel, Knirps, Tailless, Hunchback, Giant, and Caudal) and six were pair rule genes (Hairy, Runt, Even-skipped, Fushi-tarazu, Paired, and Odd-skipped). The genes along with 20 kb upstream and downstream regions were scanned for TFBS clusters using the Motif Cluster Alignment Search Tool (MCAST), a bioinformatics tool that looks for set of nucleotide sequences for statistically significant clusters of non-overlapping occurrence of a given set of motifs. The motifs used in the current study were Hunchback, Caudal, Giant, Kruppel, Knirps, and Even-skipped. The results of the MCAST analysis revealed the maximum number of TFBS for Hunchback, Knirps, Caudal, and Kruppel in both D. melanogaster and T. castaneum, while Bicoid TFBS clusters were found only in D. melanogaster. The size of all the predicted TFBS clusters was less than 1kb in both insect species. These sequences revealed more transversional sites (Tv) than transitional sites (Ti) and the average Ti/Tv ratio was 0.75 (Moudgil, 2023).

Topological operons might not be restricted to paralogous genes, and it remains to be seen whether they also interconnect unrelated genes encoding different components of common biological pathways, as seen for bacterial operons. It is anticipated that topological operons are likely to be a general feature of metazoan genomes, providing a strategy to integrate and coordinate the activities of distant regulatory genes engaged in complex cellular and developmental processes (Levo, 2022).

Unexpectedly, for AP-1 motifs, which were assessed in both species, the Drosophila- trained DeepSTARR model was able to predict the importance of AP-1 instances in human enhancers and in both species ETS-AP-1 pairs synergize only at short distances but not at longer ones. Ultimately, this demonstrates that although the specific rules vary between TF motif types and motif combinations, the types of rules as well as some specific rules apply more generally. Dissecting important types of rules in model cell lines together with the wealth of genomic data across many cell types (such as those from ENCODE) should unveil the gene- regulatory information in genomes and a general cis-regulatory code (de Almeida, 2022).

Neural progenitors produce diverse cells in a stereotyped birth order, but can specify each cell type for only a limited duration. In the Drosophila embryo, neuroblasts (neural progenitors) specify multiple, distinct neurons by sequentially expressing a series of temporal identity transcription factors with each division. Hunchback (Hb), the first of the series, specifies early-born neuronal identity. Neuroblast competence to generate early-born neurons is terminated when the hb gene relocates to the neuroblast nuclear lamina, rendering it refractory to activation in descendent neurons. Mechanisms and trans-acting factors underlying this process are poorly understood. This study identified Corto, an enhancer of Trithorax/Polycomb (ETP) protein, as a new regulator of neuroblast competence. The GAL4/UAS system was used to drive persistent misexpression of Hb in neuroblast 7-1 (NB7-1), a model lineage for which the early competence window has been well characterized, to examine the role of Corto in neuroblast competence. immuno-DNA Fluorescence in situ hybridization (DNA FISH) was used in whole embryos to track the position of the hb gene locus specifically in neuroblasts across developmental time, comparing corto mutants to control embryos. Finally, immunostaining was used in whole embryos to examine Corto's role in repression of Hb and a known target gene, Abdominal B (Abd-B). In corto mutants, the hb gene relocation to the neuroblast nuclear lamina was found to be delayed and the early competence window is extended. The delay in gene relocation occurs after hb transcription is already terminated in the neuroblast and is not due to prolonged transcriptional activity. Further, it was found that Corto genetically interacts with Posterior Sex Combs (Psc), a core subunit of polycomb group complex 1 (PRC1), to terminate early competence. Loss of Corto does not result in derepression of Hb or its Hox target, Abd-B, specifically in neuroblasts. These results show that in neuroblasts, Corto genetically interacts with PRC1 to regulate timing of nuclear architecture reorganization and support the model that distinct mechanisms of silencing are implemented in a step-wise fashion during development to regulate cell fate gene expression in neuronal progeny (Hafer, 2022).

In this study, TF binding was determined using two orthogonal methods: MNase-seq and dSMF. Mapping of TF binding by both these methods depends on the occupancy of a site, how tightly it is bound by a TF, and how effectively the TF protects underlying DNA—factors that are common to most genomic methods that map TF binding. Pairs of TFBSs separated by distances starting at 30 bp were studied because the methods used cannot resolve individual binding events at <30 bp. Future studies could determine if cooperativity between TFs is even stronger at distances shorter than 30 bp, with and without protein-protein interactions (Rao, 2021).

Several distinct activities and functions have been described for chromatin insulators, which separate genes along chromosomes into functional units. This paper describes a novel mechanism of functional separation whereby an insulator prevents gene repression. When the homie insulator is deleted from the end of a Drosophila even skipped (eve) locus, a flanking P-element promoter is activated in a partial eve pattern, causing expression driven by enhancers in the 3' region to be repressed. The mechanism involves transcriptional read-through from the flanking promoter. This conclusion is based on the following. Read-through driven by a heterologous enhancer is sufficient to repress, even when homie is in place. Furthermore, when the flanking promoter is turned around, repression is minimal. Transcriptional read-through that does not produce anti-sense RNA can still repress expression, ruling out RNAi as the mechanism in this case. Thus, transcriptional interference, caused by enhancer capture and read-through when the insulator is removed, represses eve promoter-driven expression. We also show that enhancer-promoter specificity and processivity of transcription can have decisive effects on the consequences of insulator removal. First, a core heat shock 70 promoter that is not activated well by eve enhancers did not cause read-through sufficient to repress the eve promoter. Second, these transcripts are less processive than those initiated at the P-promoter, measured by how far they extend through the eve locus, and so are less disruptive. These results highlight the importance of considering transcriptional read-through when assessing the effects of insulators on gene expression (Fujioka, 2021).

Chromatin architecture plays an important role in gene regulation. Recent advances in super-resolution microscopy have made it possible to measure chromatin 3D structure and transcription in thousands of single cells. However, leveraging these complex data sets with a computationally unbiased method has been challenging. This study presents a deep learning-based approach to better understand to what degree chromatin structure relates to transcriptional state of individual cells. Furthermore, methods were explored to "unpack the black box" to determine in an unbiased manner which structural features of chromatin regulation are most important for gene expression state. This approach was applied to an Optical Reconstruction of Chromatin Architecture dataset of the Bithorax gene cluster in Drosophila; it was shown to outperforms previous contact-focused methods in predicting expression state from 3D structure. The structural information is distributed across the domain, overlapping and extending beyond domains identified by prior genetic analyses. Individual enhancer-promoter interactions are a minor contributor to predictions of activity (Rajpurkar, 2021).

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 to earlier and later time-points. This "developmental hourglass" pattern has been observed in many phyla, yet the evolutionary constraints on gene expression, and underlying mechanisms of how this is regulated, remains elusive. Moreover, the role of positive selection on gene regulation in the more diverged earlier and later stages of embryogenesis remains unknown. Using DNase-seq to identify regulatory regions in two distant Drosophila species (D. melanogaster and D. virilis), this study 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, signatures of positive selection on developmental enhancers were detected 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 (Liu, 2021).

Single-cell technologies allow measuring chromatin accessibility and gene expression in each cell, but jointly utilizing both layers to map bona fide gene regulatory networks and enhancers remains challenging. This study generated independent single-cell RNA-seq and single-cell ATAC-seq atlases of the Drosophila eye-antennal disc and spatially integrate the data into a virtual latent space that mimics the organization of the 2D tissue using ScoMAP (Single-Cell Omics Mapping into spatial Axes using Pseudotime ordering). To validate spatially predicted enhancers, a large collection of enhancer-reporter lines and identify ~85% of enhancers in which chromatin accessibility and enhancer activity are coupled. Next, infer enhancer-to-gene relationships were inferred in the virtual space, finding that genes are mostly regulated by multiple, often redundant, enhancers. Exploiting cell type-specific enhancers, cell type-specific effects of bulk-derived chromatin accessibility QTLs were deconvoluted. Finally, Prospero was found to drive neuronal differentiation through the binding of a GGG motif. In summary, a comprehensive spatial characterization of gene regulation is provided in a 2D tissue (Bravo González-Blas, 2020).

Cellular identity is defined by Gene Regulatory Networks (GRNs), in which transcription factors bind to enhancers and promoters to regulate target gene expression, ultimately resulting in a cell type-specific transcriptome. Single-cell technologies provide new opportunities to study the mechanisms underlying cell identity. Particularly, single-cell transcriptomics allow measuring gene expression in each cell, while single-cell epigenomics, such as single-cell ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing), serves as a read-out of chromatin accessibility. Although these technologies and computational approaches are recently evolving to include spatial information, most approaches currently target single-cell transcriptomes. It remains a challenge how to exploit single-cell epigenomic data for resolving spatiotemporal enhancer activity and GRN dynamics, both experimentally and computationally (Bravo González-Blas, 2020).

In addition, while ATAC-seq is a powerful tool for predicting candidate enhancers, not all accessible regions correspond to functionally active enhancers. For example, accessible sites can correspond to ubiquitously accessible promoters or binding sites for insulator proteins; to repressed or inactive regions due to binding of repressive transcription factors; or to primed regions that are accessible across a tissue, but become only specifically activated in a subset of cell types. Importantly, single-cell ATAC-seq has not been fully exploited to explore these aspects yet. While most scATAC-seq studies have been carried out in mammalian systems, in which enhancer testing is not trivial, Cusanovich (2018) evaluated 31 cell type-specific enhancers predicted from scATAC-seq in the Drosophila embryo, finding that ~ 74% showed the expected activity patterns (Bravo González-Blas, 2020).

Another current challenge in the field of single-cell regulatory genomics is how to integrate epigenomic and transcriptomic information. Although some experimental approaches have been developed for profiling both the epigenome and the transcriptome of the same cell, currently either the quality of the measurements, or the throughput, is still significantly lower compared to each independent single-cell assay. For example, sci-CAR (Single-cell Combinatorial Indexing Chromatin Accessibility and mRNA) or SNARE-seq (Single-Nucleus Chromatin Accessibility and mRNA Expression sequencing) on human cells achieved a median of 1,000-4,000 UMIs (Unique Molecular Identifiers) and 1,500-3,000 fragments per cell, while the coverage with non-integrative methods, such as 10x, is around 20,000 UMIs and 10,000 fragments per cell for scRNA-seq and scATAC-seq, respectively. Methods that achieve high sensitivity, such as scCAT-seq (single-cell Chromatin Accessibility and Transcriptome sequencing), are based on microwell plates rather than droplet microfluidics, making their throughput limited (Bravo González-Blas, 2020).

Given the current limitations of combined omics methods, the computational integration of independent high-sensitivity assays provides a valuable alternative. For example, Seurat and Liger have been used to integrate independently sequenced single-cell transcriptomes and single-cell epigenomes. Nevertheless, these methods require the 'conversion' of the genomic region accessibility matrix into a gene-based matrix, and how to perform such a conversion is an unresolved issue. Some studies have used the accessibility around the Transcription Start Site (TSS) as proxy for gene expression (Bravo González-Blas, 2019); others aggregate the accessibility regions that are co-accessible (i.e., correlated) with the TSS of the gene in a certain space (Pliner et al., 2018). However, promoter accessibility is not always correlated with gene expression. Furthermore, enhancers can be located very far from their target genes-upstream or downstream, up to 1 Mbp in mammalian genomes, or up to 100-200 kb in Drosophila , often with intervening non-target genes in between-and relationships between enhancers and target genes are often not one-to-one (i.e., an enhancer can have multiple targets, and a gene can be regulated by more than one enhancer) (Shlyueva et al., 2014). Enhancer-promoter interactions can also be predicted using Hi-C approaches at the bulk level (Ghavi-Helm et al , 2019); however, these methods have limited sensitivity at single-cell resolution (Bravo González-Blas, 2020).

The Drosophila third-instar larval eye-antennal disc provides an ideal biological system for the spatial modeling of gene regulation at single-cell resolution. The eye-antennal disc comprises complex, dynamic, and spatially restricted cell populations in two dimensions. The antennal disc consists of four concentric rings (A1, A2, A3, and arista), each with a different transcriptome and different combinations of master regulators. For example, both Hth and Cut regulate the outer antennal rings (A1 and A2), with additional expression of Dll in A2, while Dll, Ss, and Dan/Danr are key for the development of the inner rings (A3 and arista), among others. On the other hand, a continuous cellular differentiation process from anterior to posterior occurs in the eye disc, in which progenitor cells differentiate into neuronal (i.e., photoreceptors) and non-neuronal (i.e., cone cells, bristle, and pigment cells) cell types. This differentiation wave is driven by the morphogenetic furrow (MF). Posterior to the MF, R8 photoreceptors are specified first, and then, they sequentially recruit R2/R5, R3/R4, and R7 photoreceptors and cone cells to form hexagonally packed units called ommatidia. In summary, the heterogeneity of cell types and differentiation trajectories results in diverse-static and dynamic-GRNs, which can be modeled with a combination of experimental and computational approaches (Bravo González-Blas, 2020).

This work first generated a scRNA-seq and a scATAC-seq atlas of the eye-antennal disc. Second, taking advantage of the fact that the disc proper is a 2D tissue, these single-cell profiles were spatially mapped on a latent space that mimics the eye-antennal disc, called the virtual eye-antennal disc. Next, by exploiting publicly available enhancer-reporter data, the relationship between enhancer accessibility and activity was assessed. Third, these virtual cells, for which both epigenomic and transcriptomic data are available, were used to derive links between enhancers and target genes using a new regression approach. Fourth, a panel of 50 bulk ATAC-seq profiles across inbred lines was used to predict cell type-specific caQTLs (chromatin accessibility QTLs). Finally, these findings were used to characterize the role of Prospero in the accessibility of photoreceptor enhancers. In summary, a comprehensive characterization is provided of gene regulation in the eye-antennal disc, using a strategy that is applicable to other tissues and organisms. These results can be explored as a resource on SCope and the UCSC Genome Browser (), and an R package, called ScoMAP (Single-Cell Omics Mapping into spatial Axes using Pseudotime ordering) is provided, to spatially integrate single-cell omics data and infer enhancer-to-gene relationships (Bravo González-Blas, 2020).

This work presents a semi-supervised approach to map omics data into a virtual template by extracting axial information via pseudotime ordering, available as an R package called ScoMAP. The main limitations of this approach are that (1) it can be currently only applied to 1D or 2D tissues, (2) it requires a priori information about at least one landmark between the real and the virtual cells and the direction of the axis, and (3) it assumes symmetry around the axes, meaning that other gradients may be lost as cells are spread randomly in each bin. Nevertheless, the spatial gene expression atlas resulting from the mapping of scRNA-seq accurately recapitulates known gene expression patterns and allows to generate virtual gene expression profiles for any gene, at a resolution comparable with novoSpaRc (Bravo González-Blas, 2020).

Whereas spatial inference has been reported based on scRNA-seq data, this work generates the first spatial map of a tissue from scATAC-seq data. This accessibility atlas effectively predicts enhancer-reporter activity for more than 700 enhancers from the Janelia FlyLight Project, with ~85% of enhancers showing matching accessibility and activity patterns. The remaining enhancers (~ 15%) are binding sites of the epithelial pioneer transcription factor Grainyhead, which primes these regions in all the epithelial cells without resulting in enhancer activity. Indeed, pioneer transcription factors are able to displace nucleosomes, resulting in an ATAC-seq signal; and despite that they are necessary, their binding is not sufficient for activity (Jacobs, 2018). Thus, enhancer accessibility can be achieved either by the binding of pioneer factors or through the cooperative binding of multiple TFs. These results highlight both the power of using scATAC-seq as a proxy of enhancer activity and the need for caution when dealing with pioneer factors (Bravo González-Blas, 2020).

The virtual map also acts as a latent space in which scATAC-seq and scRNA-seq data are available for each virtual cell. While experimental approaches for the simultaneous profiling of epigenome and transcriptome are emerging, these do not achieve the same throughout and sensitivity compared with the independent assays yet. Computationally, Granja (2019) has taken a similar approach, in which cells are mapped into the same latent space and for each single-cell transcriptome, the aggregate scATAC-seq profile of the closest neighbors is assigned. The resulting integrated profiles allow inferring relationships between enhancers and target genes. While Pliner (2018) has tackled this problem uniquely using scATAC-seq data, Granja (2019) used Pearson correlation between the chromatin accessibility and gene expression. This work extends this approach by also using random forest models to assess non-linear relationships. Of note, these approaches are not robust to pioneer sites, whose accessibility and activity are unpaired. For example, in the current approach a validated intronic enhancer of Atonal and Grainyhead in sca is missed, as the enhancer is ubiquitously accessible while only functional in the morphogenetic furrow, where the gene is expressed. Nevertheless, for the remaining 85% of the enhancers in which accessibility and activity are coupled, in this system, this study has been able to reconstruct novel and validated enhancer-to-target gene links (Bravo González-Blas, 2020).

The predicted links between enhancers and target genes support that (1) the probability of an enhancer regulating a gene decreases exponentially with the distance and the number of non-intervening genes in between, as also reported by others, and (2) genes are regulated by several-and in some cases, redundant-enhancers, with a median of 22 enhancers linked to each gene. Indeed, Cannavo (2016) reported in the Drosophila embryo that ~64% of the mesodermal loci have redundant (or shadow) enhancers, of which ~ 60% contain more than one pair of shadow enhancers. In agreement, this study finds that ~80% of the genes are regulated by shadow enhancers (6,937 out of 8,307 genes), out of which ~72% are regulated by at least three shadow enhancers (4,900 out of 6,937 genes). Transcription factors are more tightly regulated, being linked with a higher number of enhancers (with an average of 13 positive links per gene) and having almost twice the number of redundant enhancers compared with non-TFs genes. As abnormalities in the expression of transcription factor genes can have more severe phenotypes compared with final effector genes, having more-and redundant-enhancers may provide evolutionary robustness. In addition, the majority of shadow enhancers are partially redundant, meaning that they can be uniquely essential on other developmental stages or tissues, or under adverse environmental conditions (Bravo González-Blas, 2020).

Of note, almost ~50% of the inferred links are negatively correlated with their target genes. While polycomb-mediated repression has been shown to reduce region accessibility, other studies suggest that, although repressed enhancers are less accessible than active enhancers, they still show accessibility compared with the non-regulatory genome (Bozek, 2019). Such effect can be observed in the embryonic eve stripe 2 enhancer, which is active (and more accessible) in the second embryonic stripe, while repressed (and less accessible) in the rest. Meanwhile, in the eye-antennal disc, where it is not active nor repressed, there is no accessibility. Thus, accessible regions do not only correspond to primed or active enhancers, promoters, and insulators, but also to repressed enhancers (Bravo González-Blas, 2020).

Several works have focused on the inference of GRNs from single-cell data, mostly exploiting scRNA-seq to infer co-expression patterns between TFs and potential target genes. In an attempt to reduce the number of false-positive targets due to activating cascade effects, SCENIC, which additionally evaluates the enrichment of binding sites for the TF around the TSS of the putative target gene, was introduced. On the other hand, other studies have exploited single-cell ATAC-seq to find target enhancers with binding sites for specific TFs. For example, chromVAR aggregates regulatory regions based on motif enrichment and then evaluates these modules on single-cell ATAC-seq data, while cisTopic (Bravo Gonzalez-Blas, 2019) performs motif enrichment on sets of co-accessible enhancers inferred from scATAC-seq profiles (i.e., topics) to find common master regulators. However, none of these approaches incorporates knowledge about the TF nor target gene expression. This study has aimed to integrate all these layers-transcription factor binding sites, chromatin, and gene expression-to infer GRNs, by deriving co-expression modules between genes and transcription factors (from the scRNA-seq data) and pruning them based on the enrichment of the TF motif in the enhancers that regulate these genes (based on the enhancer-to-target gene links derived from the integration of scATAC and scRNA-seq data). Such networks de facto have enhancers, rather than genes, as nodes (i.e., TF-Enhancer-Gene networks) (Bravo González-Blas, 2020).

As bulk profiles may mask true biological signal (due to the proportions of the different cell types), single-cell data have been used to deconvolute cell type-specific signals from bulk RNA-seq data, permitting to exploit large cohorts with bulk omics data, complemented with only one single-cell reference atlas. This study has investigated the impact of genomic variation on cell type-specific enhancers. For example, the relevance was revealed of Atonal binding sites for opening Johnston's organ precursor-specific regions and the GGG motif, previously unlinked to any transcription factor, for opening photoreceptor regions. Interestingly, Atonal has been shown to be a key transcription factor for the specification of sensory neuronsand bHLH proteins have been proposed to act as pioneer transcription factors in certain contexts, such as the mammalian family member Ascl1 (Bravo González-Blas, 2020).

The importance of the GGG motif in neuronal enhancers was evident in most of the current analyses; however, its interpretation was a challenge because the binding TFs were unknown. While yeast one-hybrid (Y1H) experiments have been previously used to reverse-engineer which transcription factors can bind a motif of interest, lowly expressed TFs may be underrepresented in the cDNA library and interactions that occur in vivo may be missed (such as those dependent of post-transcriptional modifications). This study has used a novel in vivo approach, in which the changes that overexpression of potential TF candidates causes in chromatin accessibility at the bulk ATAC-seq level were evaluated. Although this strategy allows to characterize the effects of TF overexpression directly on the tissue of interest, it also has limitations, such as the limited throughput of in vivo genetic screens (one TF per experiment, compared to dozens of TFs that can be tested by Y1H or Perturb-ATAC in vitro). This requires making a stringent selection of potential candidates that can be further bounded by the existence of compatible tools, such as UAS-TF lines. In addition, the changes in chromatin may not be direct, but these effects can be partially ruled out using external data available, such as ChIP-seq (Bravo González-Blas, 2020).

This study found that the neuronal precursor transcription factor Prospero acts as the strongest binder of the GGG motif, followed by Nerfin-1 and l(3)neo38. In fact, overexpression of each of them, but especially Prospero, results in the opening of GGG regions; and all three transcription factors, especially Pros and Nerfin-1, can bind to the GGG motif. Based on the expression of these transcription factors, it is hypothesized that Nerfin-1-and l(3)neo38-are the early binders of the GGG motif, while Pros can bind to these regions in the late-born photoreceptors, where it is expressed. In fact, Pros and Nerfin-1 have been reported to share direct targets during CNS differentiation and have been found to be key regulators during the photoreceptor and retinal differentiation in other organisms, such as zebrafish, chicken, and mammals (Bravo González-Blas, 2020).

In summary, this study provides a comprehensive and user-friendly single-cell resource of the Drosophila's eye-antennal disc. It is envisioned that these computational strategies and enhancer resources will be of value not only to the Drosophila community, but also to the field of single-cell regulatory genomics in general (Bravo González-Blas, 2020).

Enhancers are essential drivers of cell states, yet the relationship between accessibility, regulatory activity, and in vivo lineage commitment during embryogenesis remains poorly understood. This study measured 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. This study demonstrates 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, a loss-of-function mutant was generated and an essential role for neuromuscular junction and brain development was uncovered (Reddington, 2020).

Chromatin accessibility profiling is a powerful method to map the regulatory genome-the full complement of regulatory elements engaged by transcription factors (TFs) and other regulatory proteins-in a specific cell type and biological context. Accessible regions are generally measured by the sensitivity of genomic regions to the nuclease DNaseI, e.g., 'DNase-seq', or insertion of the Tn5 transposase, e.g., 'ATAC-seq', following the displacement of canonical nucleosomes by TFs and other regulatory factors. when measured over cellular differentiation, these approaches can chart the dynamics of regulatory-element usage genome wide, infer the occupancy of DNA-binding factors en masse, and identify candidate TF drivers of cell-fate decisions (Reddington, 2020).

Although an excellent method to identify the location of regulatory elements, the precise relationship between chromatin accessibility, enhancer activity, and the timing of cell-fate decisions remains unclear. Chromatin accessibility is often equated with regulatory activity, but there are several reasons why this may not be the case. First, the precise molecular determinants of chromatin accessibility as measured by methods, such as DNase-seq and ATAC-seq, and the relative importance of different TF families, chromatin-remodeling complexes, and histone variants are not well understood. Second, chromatin accessibility per se provides no information about the identity of the bound proteins, whether they have activating or repressive activity, or the function of the regulatory region (enhancer, insulator, or origin of replication). Third, the activation of at least a subset of lineage-specific enhancers occurs via a multistep process during development, being bound in precursor cells ('priming'), but only becoming activated at subsequent developmental stages following an exchange or addition of TFs. Fourth, chromatin accessibility may reflect residual TF binding that remains in a recently diverged sister lineage. Directly connecting accessibility to enhancer activity more generally has been hampered by technical limitations-the activity of a large number of enhancers is rarely measured directly in vivo, but is rather inferred from secondary information, such as histone modifications, that are themselves imperfect correlates of enhancer activity. Therefore, it remains unclear if the timing of enhancer activity correlates with the timing of accessibility and if this relationship changes over development (Reddington, 2020).

Chromatin accessibility profiling has been applied extensively to human cell lines and primary tissues, providing a comprehensive picture of regulatory landscapes in definitive cell types and highlighting the extensive differences between them. In contrast, far less is known about how regulatory landscapes diverge during embryonic development. With few exceptions, much of what is known comes from whole embryos or dissected organs or tissues, which have limited sensitivity to detect enhancers that are active in small subsets of cells due to averaging over heterogeneous cell types (Reddington, 2020).

Single-cell methods can address some of these issues. The power of single-cell ATAC-seq was recently demonstrated by combinatorial indexing (sci-ATAC-seq) to dissect cell-type-specific signatures of open chromatin starting from whole embryos (Cusanovich, 2018). This 'shotgun' approach identified thousands of previously unidentified regulatory elements and was sufficient to annotate cell clusters and predict tissue-specific enhancer activity (Cusanovich, 2018). However, a limitation of single-cell genomics is that cell identities are assigned post hoc based on prior information, e.g., using marker genes. Having high-quality tissue- and time-resolved datasets are therefore an extremely useful resource for annotating single-cell data. In addition, given the current sparsity of single-cell epigenomics data, bulk data have greater statistical power to define cell-type and time-point-specific regulatory features de novo (Reddington, 2020).

To better characterize chromatin accessibility during the development of different embryonic cell lineages, a tissue- and time-resolved chromatin accessibility atlas was generated spanning the stages when all major cell types are specified during Drosophila embryogenesis, focusing on the mesoderm and neuronal lineages. This atlas was integrated with an extensive database of curated embryonic enhancers to systematically assess the relationship between enhancer accessibility and enhancer activity in vivo during cell-fate decisions. The high resolution of this tissue- and time-resolved data facilitated the discovery of thousands of previously unidentified tissue-specific regulatory elements. This study demonstrated the value of this resource to define cell identities in sci-ATAC-seq data (Cusanovich, 2018) and as a training set to identify sequence features that are predictive of tissue-specific regulatory-element usage. This allowed identification of many potential regulators in each lineage, one of which was characterize by genetic knockout, and an essential role was demonstrated in neuromuscular junction and brain development (Reddington, 2020).

In this study most l(3)neo38^CRISPR mutant embryos reached the pupal stage (74%), but then died as late (black) pupae; only 12% hatched from the pupal case compared with 90% of the control heterozygote animals. The small number of l(3)neo38^CRISPRadult flies that do hatch have severely reduced motility, are barely able to walk and unable to fly (with a 'wings-up' phenotype), and fail to reproduce, suggesting defects in the neuromuscular system (Reddington, 2020).

To further characterize these defects, third instar larval brains and neuromuscular junctions were examined via immunostaining. To assess the brain, advantage was taken of a GFP reporter (3xP3-GFP) driven by binding sites for the conserved neuronal transcription factor Pax6 present in the VasaCas9 line that was used for the CRISPR deletion. In wild type (heterozygous l(3)neo38^CRISPR/+) larval brains, GFP is highly expressed in the optic lobes (OL), with lower levels in the ventral nerve cord (VNC), similar to the Pax6 homolog, ey. Loss-of-function l(3)neo38^CRISPR brains show the reverse, with almost no GFP expression in the OL, and high expression in the VNC, especially in the posterior part (Reddington, 2020).

To examine the development of the neuromuscular junction (NMJ), homozygous loss-of-function third instar larvae were dissected and stained with anti-HRP (horseradish peroxidase, to mark neuronal membranes) and Brp (Bruchpilot, to mark synaptic active zones). This revealed neuromuscular junctions that are both smaller and less branched in l(3)neo38^CRISPR mutants. Quantifying the NMJ area at the ventral longitudinal muscles 6 and 7 in abdominal segments A3 and A4, using the HRP marker protein, revealed a significant reduction in the size of NMJs in homozygous loss-of-function mutants compared with wild-type larvae of the same age. Consistent with these neurological defects, l(3)neo38 occupies a subset of neuronal specific distal DHS, as seen using embryonic ChIP-seq data . The nearest genes of these l(3)neo38 ChIP peaks are enriched in functions related to postembryonic development and the regulation of neuron interactions and synapses (Reddington, 2020).

Drosophila is a long-standing model organism for the study of gene regulation, chromatin biology, cell-fate decisions, and general properties of embryonic development, with many fundamental biological processes being first discovered in this system. This study extended the Drosophila toolkit by generating an extensive resource of tissue-resolved chromatin accessibility during an in vivo time course of tissue development. By isolating highly pure populations of cell nuclei in a tight developmental time course, this atlas reveals the extensive dynamics that accompanies major developmental transitions in two important lineages: the nervous system and the mesoderm/muscle system. Importantly, this significantly extends knowledge beyond the previously available data collected from whole embryos and single cells from a smaller number of time points (Cusanovich, 2018). This resource can be easily searched and visualized (Reddington, 2020).

There are multiple approaches that can achieve cell-type-resolved chromatin accessibility information from developing embryos, such as the INTACT, BiTS, CaTaDA, and shotgun single-cell ATAC-seq. Each has its own strengths and weaknesses, making the choice of method dependent on technical issues. An advantage of this modified BiTS approach is that it can be applied to wild-type embryos of theoretically any species, although it is limited by the availability of high-quality antibodies against nuclear marker proteins of interest. Single-cell ATAC-seq is a very exciting alternative as it negates the need for transgenic animals or antibodies to isolate cell populations, and provides an unbiased view of cellular heterogeneity (Cusanovich, 2018). However, without prior enrichment, hundreds of thousands to potentially millions of cells are required to capture rare cell types. At present the resolution is to sparse in singe-cell epigenetic data (scATAC-seq or ChIP-seq) to provide accurate quantification, or de novo detection, of enhancers from rare cell subsets-highlighting the need for detailed studies of specific tissues/cell-types to provide deep, quantitative information on regulatory regions for targeted cell populations (Reddington, 2020).

This study demonstrates the utility of this tissue- and time-resolved atlas to uncover biological insights into regulatory element usage during embryonic development. Many promoters, even those of tissue specific genes, are open constitutively, including in tissues where the gene is not expressed. In contrast, the majority of distal sites are dynamic and tissue-specific. Thousands of these overlap characterized enhancers, and are accessible in the appropriate tissue matching the enhancers' activity-strongly suggesting that the bulk of distal elements (with high developmental variance) are new tissue-specific enhancers. Similar to promoters, this study also uncovered a subset of enhancers that are open in lineages where they are not active at early embryonic stages, and this gets progressively lower as embryogenesis proceeds. This indicates that active enhancers become closed in other lineages as cells begin to differentiate. Interestingly, the majority of these are bound by ubiquitous TFs, which suggests that they are not sufficient to activate the enhancer. Perhaps they boost the levels of the enhancers activity in the 'right' tissue, when co-bound by lineage specific TFs or act as place holders to keep these enhancers open until the embryonic stage when the lineage-specific factor is expressed (Reddington, 2020).

This study has taken advantage of the availability of the assembled genomic sequence of flies, mosquitos, ants and bees to explore the presence of ultraconserved sequence elements in these phylogenetic groups. Non-coding sequences found within and flanking Drosophila developmental genes were compared to homologous sequences in Ceratitis capitata and Musca domestica. Many of the conserved sequence blocks (CSBs) that constitute Drosophila cis-regulatory DNA, recognized by EvoPrinter alignment protocols, are also conserved in Ceratitis and Musca. Also conserved is the position but not necessarily the orientation of many of these ultraconserved CSBs (uCSBs) with respect to flanking genes. Using the mosquito EvoPrint algorithm, uCSBs shared among distantly related mosquito species were identified. Side by side comparison of bee and ant EvoPrints of selected developmental genes identify uCSBs shared between these two Hymenoptera, as well as less conserved CSBs in either one or the other taxon but not in both. Analysis of uCSBs in these dipterans and Hymenoptera will lead to a greater understanding of their evolutionary origin and function of their conserved non-coding sequences and aid in discovery of core elements of enhancers (Brody, 2020).

Phylogenetic footprinting of Drosophila genomic DNA has revealed that cis-regulatory enhancers can be distinguished from other essential gene regions based on their characteristic pattern of conserved sequences. Cross-species alignments have also identified conserved non-coding sequence elements associated with vertebrate developmental genes, and sequences that are conserved among ancient and modern vertebrates (e.g., the sea lamprey and mammals). Elements conserved between disparate taxa are considered to be 'ultraconserved elements'. Previous studies have identified ultra-conserved elements in dipterans, Drosophila species and sepsids and mosquitos. Comparison of consensus transcription factor binding sites in the spider Cupiennius salei and the beetle Tribolium castaneum have been shown to be functional in transgenic Drosophila (Brody, 2020).

This study describes sequence conservation of non-coding sequences within and flanking developmentally important genes in the medfly Ceratitis capitata, the house fly Musca domestica and Drosophila genomic sequences (see Genomic regions analyzed for presence of uCSBs). The house fly and Medfly have each diverged from Drosophila for ~100 and ~120 My respectively. This analysis reveals that, in many cases, CSBs that are highly conserved in Drosophila species, as detected using the Drosophila EvoPrinter algorithm, are also conserved in Ceratitis and Musca. Additionally, the linear order of these ultraconserved CSBs (uCSBs) with respect to flanking structural genes is also maintained. However, a subset of the uCSBs exhibits inverted orientation relative to the Drosophila sequence, suggesting that while enhancer location is conserved, their orientation relative to flanking genes is not (Brody, 2020).

For detection of conserved sequences in mosquitos, EvoPrinter algorithms were adapted to include 22 species of Anopheles plus Culex pipens and Aedes aegypti. Use of Anopheles species allows for the resolution of CSB clusters that resemble those of Drosophila. Comparison of Anopheles with Culex and Aedes, separated by ∼150 million years of evolutionary divergence, reveals uCSBs shared among these taxa. Although mosquitoes are considered to be Dipterans, uCSBs were identified conserved between mosquito species but these were generally not found in flies (Brody, 2020).

In addition, EvoPrinter tools were developed for sequence analysis of seven bee and thirteen ant species. Both ants and bees belong to the Hymenoptera order and have been separated by ~170 million years. Within the bees, Megachile and Dufourea are sufficiently removed from Apis and Bombus (~100 My) that only portions of CSBs are shared between species: these can be considered to be uCSBs. uCSBs are found that are shared between ant and bee species, and these are positionally conserved with respect to their associated structural genes. Finally, this study shows that ant specific and bee specific CSB clusters that are not shared between the two taxa are in fact interspersed between shared uCSBs (Brody, 2020).

A previous study of 19 consecutive in vivo tested Drosophila enhancers, contained within a 28.9 kb intragenic region located between the vvl and Prat2 genes, revealed that each CSB cluster functioned independently as a spatial/temporal cis-regulatory enhancer (Kundu, 2013). Submission of this enhancer field to the RefSeq Genome Database of Ceratitis capitata via BLASTn revealed 17 uCSBs; all 17 regions were colinear and located between the Ceratitis orthologs of Drosophila vvl and Prat2 genes. In each case the matches between Ceratitis and Drosophila corresponded to either a complete or a portion of a CSB identified by the Drosophila EvoPrinter as being highly conserved among Drosophila species (Kundu, 2013). Submission of the same Drosophila region to Musca domestica RefSeq Genome Database using BLASTn revealed 13 uCSBs that were colinearly arrayed within the Musca genome. Nine of these Ceratitis and Musca CSBs were present in both species and corresponded to CSBs contained in several of the enhancers identified in a previous study of the Drosophila enhancer field (Kundu, 2013). The conservation within one of these embryonic neuroblast enhancers, vvl-41, is shown in the following figure (Ultra-conserved sequences shared among a Drosophila ventral veins lacking enhancer and orthologous DNA within the Ceratitis capitata and Musca domestica genomes.). Each of the CSB elements in vvl-41 that are shared between Dm and Ceratitis are in the same orientation with respect to the vvl structural gene. Three-way alignments of each of the other eight uCSBs within the vvl enhancer field that are shared between Dm, Ceratitis and Musca are shown in a supplemental figure. The uCSB of vvl-49 in Ceratitis is in reverse orientation with respect to the vvl structural gene. Many of the uCSBs in Musca are in a different orientation on the contig than in Dm, indicating microinversions. One of the two uCSBs in Ceratitis goosecoid was in reverse orientation compared to Drosophila CSBs, while three of the four uCSBs in Musca goosecoid were in reverse orientation. One uCSB each in Ceratitis and Musca castor was in reverse orientation compared to Drosophila castor. 10 of the 15 uCSBs in the Musca wingless non-coding region were in the reverse orientation compared to the orientation in Drosophila, while all uCSBs in Ceratitis Dscam2 were in forward orientation compared to the orientation in Drosophila. It is concluded that, except for microinversions, the order and orientation is the same, with respect to flanking genes of highly conserved non-coding sequences in select developmental determinants of Drosophila, Ceratitis and Musca (Brody, 2020).

Many of the non-coding regions in dipteran genomes contain uCSBs, especially in and around developmental determinants, and many of these are likely to be cis-regulatory elements such as those found in the vvl enhancer field. Another example is the prevalence of uCSBs found in the non-coding sequences associated the Dm hth gene locus. A previous study identified an ultraconserved region in hth shared between Drosophila and Anopheles. This study has identified additional hth uCSBs shared among Dm, Ceratitis and Musca. A 55,100 bp upstream region of Dm hth terminating just after the start of the first exon. A total of 11 CSBs shared between the three species, 5 CSBs were shared between Dm and Ceratitis but not Musca, and 6 CSBs were shared between Dm and Musca, but not Ceratitis. Ceratitis exhibited 4 uCSBs and Musca exhibited 8 uCSBs that were in reversed orientation with respect to the Drosophila orthologous regions. Additional genes analyzed in this paper were also analyzed for association with uCSBs in Ceratitis and Musca, and these results are summarized in the table. In some cases, for example wingless in Ceratitis, the presence of uCSBs could not be verified because of the incomplete assembly of the genome, leaving coding sequences and uCSBs on different contigs. In another case, Dscam2 in Musca, no uCSBs were identified (Brody, 2020).

EvoPrint analysis of Drosophila hth sequences immediately upstream and including the first exon, revealed a conserved sequence cluster associated with the transcriptional start site. Two of the longer CSBs were conserved in both Ceratitis and Musca, one shorter CSB was conserved only in Musca, and a second shorter CSB was conserved only in Ceratitis. Each of the uCSBs was in the same orientation with respect to the hth structural gene (Brody, 2020).

EvoPrinting combinations of species using A. gambiae as a reference species and multiple species from the Neocellia and Myzomyia series and the Neomyzomyia provides a sufficient evolutionary distance from A. gambiae to resolve CSBs. Phylogenic analysis has revealed the Anopheles species diverged from ~48 My to ~30 My while Aedes and Culex diversified from the Anopheles lineage in the Jurassic era or even earlier (Brody, 2020).

This study sought to identify uCSBs in selected mosquito developmental genes by comparing Anopheles species with Aedes and Culex. Non-coding sequences associated with the mosquito homolog of the morphogen wingless were examined to discover associated conserved non-coding sequences. A CSB cluster slightly more than 27,000 bp upstream of the A. gambiae wingless coding exons is shown (EvoPrint analysis of the intragenic region adjacent to the Anopheles Wnt-4 and wingless genes identifies ultra-conserved sequences shared with the evolutionary distant Culex pipiens and Aedes aegypti genomes). CSB orientation in A. gambiae was reversed with respect to the ORF when compared to the orentations of both Culex and Aedes CSBs. It is noteworthy that this EvoPrint, carried out using multiple Anopheles, consists of a cluster of CSBs, resembling EvoPrints carried out using Drosophila species. This general pattern of CSB clusters separated by poorly conserved 'spacers' is prevalent among other developmental determinants in mosquitos. uCSBs, conserved in Culex and Aedes, coincide with CSBs revealed by EvoPrint analysis of Anopheles non-coding sequences. A supplemental figure illustrates an EvoPrinter scorecard for the non-coding wingless-associated CSB cluster described in the above figure. Scores for the first four species, all members of the gambiae complex, are similar to that of A. gambiae against itself, with subsequent scores reflecting increased divergence from A. gambiae. Culex and Aedes are distinguished from the other species by their belonging to a distinctive branch of the mosquito evolutionary tree, the Culicinae subfamily and their low scores against the A. gambiae input sequence. No uCSBs were detected associated with gbb or gsc, while uCSBs were readily detected associated with vvl, cas and hth. A single uCSB in Aedes cas and two uCSBs in Culex cas exhibited a reverse configuration compared to the uCSBs in Anopheles. One uCSB in Culex vvl and no uCSBs in Aedes vvl exhibited a reverse configuration compared to the uCSB in Anopheles. Finally, all uCSBs in Culex and Aedes hth were in forward orientation compared to Anopheles. None of the uCSBs shared between Drosophila, Ceratitis and Musca were conserved in mosquitos, with the exception of a single uCSB associated with a 3'UTR (CTTCGTTTTTGCAAGAGGCCCATATAGCTCGCCAA) that is fully conserved in the Dipteran species tested, A possible explanation for this lack of conservation is the observation that mosquitos are only distantly related to Diptera (Brody, 2020).

Bees and ants are members of the Hymenoptera Order, representing the Apoidea (bee) and Vespoidea (ant) super-families. Current estimates suggest that the two families have evolved separately for over 100 million years. To identify conserved sequences either shared by bees and ants or unique to each family, EvoPrinter alignment tools were developed for seven bee and 13 ant species and searched for CSBs that flank developmental determinants. Three approaches were employed to identify/confirm conserved elements and their positioning within bee and ant orthologous DNAs. First, EvoPrinter analysis of bee and ant genes identified conserved sequences in either bees or ants and ultra-conserved sequence elements shared by both families. Second, BLASTn alignments of the orthologous DNAs identified/confirmed CSBs that were either bee or ant specific or shared by both. Third, side-by-side comparisons of ant and bee EvoPrints and BLASTn comparisons revealed similar positioning of orthologous CSBs relative to conserved exons (Brody, 2020).

To identify conserved sequences within bee species EvoPrints of the honey bee (Apis mellifera) genes were generated using other Apis and Bombus species. Using EvoPrints of the Dscam2 locus, clusters of conserved sequences were resolved. Dscam2 is implicated in axon guidance in Drosophila and in regulation of social immunity behavior in honeybees. The EvoPrint scorecard revealed a high score (close relationship) with the homologous region in the other two Apis species. The more distant Bombus species score lower by greater than 50%, and Habropoda represents a step down from the more closely related Bombus species. Megachile shows a significantly lower score reflecting its more distant relationship to Apis mellifera. The relaxed EvoPrint readout reveals two CSB clusters. Only one sequence cluster, the lower 3' cluster, is conserved in all six test species examined, while the 5' cluster is present in all species except Megachile. BLAST searches confirmed that the 3' cluster was absent from Megachile, a more distant species Dufourea novaeangliae, and all ant species in the RefSeq genome database. BLASTn alignments also revealed conservation of the 3' cluster in D. novaeangliae, the wasp species Polistes canadensis and two ant species, Vollenhavia emeryi and Dinoponera quadriceps (Brody, 2020).

EvoPrinter analysis of bee and ant genes that are orthologs of Drosophila neural development genes goosecoid (gsc) and castor (cas) revealed conserved non-coding DNA that is unique to either bees or ants or conserved in both. EvoPrints of the Hymenoptera orthologs identify non-coding conserved sequence clusters that contained core uCSBs shared by both ant and bee superfamilies, and these uCSBs are frequently flanked by family-specific conserved clusters. For example, analysis of the non-coding sequence upstream of the Wasmannia auropunctata (ant) cas first exon identifies both a conserved sequence cluster that contains ant and bee uCSBs and an ant specific conserved cluster that has no counterpart found in bees. It is likely that the ant specific cluster was deleted in bees, since BLASTn searches of Wasmannia against the European paper wasp Polistes dominula reveals conservation of a core sequence corresponding to this cluster. The combined evolutionary divergence in the gsc and cas EvoPrints, accomplished by use of multiple test species, reveals that many of the amino acid codon specificity positions are conserved while wobble positions in their ORFs are not. The lack of wobble conservation indicates that the combined divergence of the test species used to generate the prints afford near base pair resolution of essential DNA (Brody, 2020).

Cross-group/side-by-side bee and ant comparison of their conserved DNA was performed using bee specific and ant specific EvoPrints and by BLASTn alignments (see Side-by-side comparison of conserved sequences within the bee and ant glass bottom boat loci identify clusters of conserved and species-specific sequences.). This figure highlights the conservation observed among bee and ant exons and flanking sequence of the glass bottom boat (gbb, 60A) locus of Apis melliflera EvoPrinted with four bee test species and the Wasmannia auropunctata gbb locus EvoPrinted with three ant species. Position and orientation of these CSB clusters and uCSBs is conserved. Similarly, EvoPrinting a single exon and flanking regions of the Apis mellifera homothorax locus with four bee species and generating an ant specific EvoPrint of the orthologous ant sequence of the Ooceraea biroi homothorax locus with ten other ant species, reveals CSBs that are conserved in both Apis and Ooceraea, as well as sequences that are restricted to one of the two Hymenopteran families (Brody, 2020).

This study describes the use of EvoPrinter to detect the presence of ultraconserved non-coding sequences in flies, including Drosophila species, Ceratitis and Musca, in mosquitos and in Hymenoptera species. uCSBs of the three fly taxa have, for the most part, maintained their linear order suggesting a functional constraint on the order of regulatory sequences. For mosquitos, an older taxon than that of flies and the Hymenoptera, uCSBs are found to be shared between Anopheles, Culex and Aedes. Importantly, in Hymenoptera, uCSBs were found within clusters of conserved sequences shared between ants and bees. This conservation of core sequences in enhancers suggests that these morphologically divergent taxa share common regulatory networks. These approaches to detection of uCSBs in flies, mosquitos and ants and bees will lead to a greater understanding of their evolutionary origin and the function of their conserved non-coding sequences. Knowledge of clusters of CSBs and of uCSBs is an important tool for discovery of the core elements of enhancers and their sequence extent (Brody, 2020).

In most cases both nBLAST and the EvoPrinter algorithm had similar sensitivities and gave comparable results. However, it is recommended that the two techniques should be used in conjunction with one another to enhance CSB and uCSB detection. For example, by using both approaches, uCSBs were discovered that were identified by one tool but not both. The advantage of EvoPrinter is the presentation of an interspecies comparison as a single sequence, while the advantage of nBLAST is that it provides a sensitive detection of sequence homology in a one-on-one alignment. EMBOSSED Needle alignment gives an even more sensitive detection of shorter sequences and is of use once BLAT or EvoPrinter has been used to discover shared CSBs and/or CSB clusters (Brody, 2020).

These results suggest that most, if not all, silencers are also enhancers in a different cell type. CRM bifunctionality complicates the understanding of how gene regulation is specified in the genome and how it is read out in different cell types. The observation that the vast majority of complex trait- and disease-associated variants identified from genome-wide association studies (GWASs) map to noncoding sequences, most of which occur within DNase I hypersensitive sites, emphasizes the importance of understanding these elements. The characterization of bifunctional elements will help in elucidating how precise gene expression patterns are encoded in the genome and aid in the interpretation of cis-regulatory variation (Gisselbrecht, 2019).

This is the first study to investigate the molecular-genetic organization of polytene chromosome interbands located on both molecular and cytological maps of Drosophila genome. The majority of the studied interbands contained one gene with a single transcription initiation site; the remaining interbands contained one gene with several alternative promoters, two or more unidirectional genes, and "head-to-head" arranged genes. In addition, intricately arranged interbands containing three or more genes in both unidirectional and bidirectional orientation were found. Insulator proteins, ORC, P-insertions, DNase I hypersensitive sites, and other open chromatin structures were situated in the promoter region of the genes located in the interbands. This area is critical for the formation of the interband, an open chromatin region in which gene transcription and replication are combined (Zykova, 2019).

Drosophila bithorax complex (BX-C) is one of the best model systems for studying the role of boundaries (insulators) in gene regulation. Expression of three homeotic genes, Ubx, abd-A, and Abd-B, is orchestrated by nine parasegment-specific regulatory domains. These domains are flanked by boundary elements, which function to block crosstalk between adjacent domains, ensuring that they can act autonomously. Paradoxically, seven of the BX-C regulatory domains are separated from their gene target by at least one boundary, and must "jump over" the intervening boundaries. To understand the jumping mechanism, the Mcp boundary was replaced with Fab-7 and Fab-8. Mcp is located between the iab-4 and iab-5 domains, and defines the border between the set of regulatory domains controlling abd-A and Abd-B. When Mcp is replaced by Fab-7 or Fab-8, they direct the iab-4 domain (which regulates abd-A) to inappropriately activate Abd-B in abdominal segment A4. For the Fab-8 replacement, ectopic induction was only observed when it was inserted in the same orientation as the endogenous Fab-8 boundary. A similar orientation dependence for bypass activity was observed when Fab-7 was replaced by Fab-8. Thus, boundaries perform two opposite functions in the context of BX-C-they block crosstalk between neighboring regulatory domains, but at the same time actively facilitate long distance communication between the regulatory domains and their respective target genes (Postaka, 2018).

Boundaries flanking the Abd-B regulatory domains must block crosstalk between adjacent regulatory domains but at the same time allow more distal domains to jump over one or more intervening boundaries and activate Abd-B expression. While several models have been advanced to account for these two paradoxical activities, replacement experiments argued that both must be intrinsic properties of the Abd-B boundaries. Thus Fab-7 and Fab-8 have blocking and bypass activities in Fab-7 replacement experiments, while heterologous boundaries including multimerized dCTCF sites and Mcp from BX-C do not. One idea is that Fab-7 and Fab-8 are simply 'permissive' for bypass. They allow bypass to occur, while boundaries like multimerized dCTCF or Mcp are not permissive in the context of Fab-7. Another is that they actively facilitate bypass by directing the distal Abd-B regulatory domains to the Abd-B promoter. Potentially consistent with an 'active' mechanism that involves boundary pairing interactions, the bypass activity of Fab-8 and to a lesser extent Fab-7 is orientation dependent (Postaka, 2018).

In the studies reported it this study have tested these two models further. For this purpose the Mcp boundary was used for in situ replacement experiments. Mcp defines the border between the regulatory domains that control expression of abd-A and Abd-B. In this location, it is required to block crosstalk between the flanking domains iab-4 and iab-5, but it does not need to mediate bypass. In this respect, it differs from the boundaries that are located within the set of regulatory domains that control either abd-A or Abd-B, as these boundaries must have both activities. If bypass were simply passive, insertion of a 'permissive' Fab-7 or Fab-8 boundary in either orientation in place of Mcp would be no different from insertion of a generic 'non-permissive' boundary such as multimerized dCTCF sites. Assuming that Fab-7 and Fab-8 can block crosstalk out of context, they should fully substitute for Mcp. In contrast, if bypass in the normal context involves an active mechanism in which more distal regulatory domains are brought to the Abd-B promoter, then Fab-7 and Fab-8 replacements might also be able to bring iab-4 to the Abd-B promoter in a configuration that activates transcription. If they do so, then this process would be expected to show the same orientation dependence as is observed for bypass of the Abd-B regulatory domains in Fab-7 replacements (Postaka, 2018).

Consistent with the idea that a boundary located at the border between the domains that regulate abd-A and Abd-B need not have bypass activity, it was found that multimerized binding sites for the dCTCF protein fully substitute for Mcp. Like the multimerized dCTCF sites, Fab-7 and Fab-8 are also able to block crosstalk between iab-4 and iab-5. In the case of Fab-7, its' blocking activity is incomplete and there are small clones of cells in which the mini-y reporter is activated in A4. In contrast, the blocking activity of Fab-8 is comparable to the multimerized dCTCF sites and the mini-y reporter is off throughout A4. One plausible reason for this difference is that Mcp and the boundaries flanking Mcp (Fab-4 and Fab-6) utilize dCTCF as does Fab-8, while this architectural protein does not bind to Fab-7 (Postaka, 2018).

Importantly, in spite of their normal (or near normal) ability to block crosstalk, both boundaries still perturb Abd-B regulation. In the case of Fab-8, the misregulation of Abd-B is orientation dependent just like the bypass activity of this boundary when it is used to replace Fab-7. When inserted in the reverse orientation, Fab-8 behaves like multimerized dCTCF sites and it fully rescues the Mcp deletion. In contrast, when inserted in the forward orientation, Fab-8 induces the expression of Abd-B in A4 (PS9), and the misspecification of this parasegment. Unlike classical Mcp deletions or the Mcp^PRE replacement described in this study, expression of the Abd-B gene in PS9 is driven by iab-4, not iab-5. This conclusion is supported by two lines of evidence. First, the mini-y reporter inserted in iab-5 is off in PS9 cells indicating that iab-5 is silenced by PcG factors as it should be in this parasegment. Second, the ectopic expression of Abd-B is eliminated when the iab-4 regulatory domain is inactivated (Postaka, 2018).

These results, taken together with previous studies, support a model in which the chromatin loops formed by Fab-8 inserted at Mcp in the forward orientation brings the enhancers in the iab-4 regulatory domain in close proximity to the Abd-B promoter, leading to the activation of Abd-B in A4 (PS9). In contrast, when inserted in the opposite orientation, the topology of the chromatin loops formed by the ectopic Fab-8 boundary are not compatible with productive interactions between iab-4 and the Abd-B promoter. Moreover, it would appear that boundary bypass for the regulatory domains that control Abd-B expression is not a passive process in which the boundaries are simply permissive for interactions between the regulatory domains and the Abd-B promoter. Instead, it seems to be an active process in which the boundaries are responsible for bringing the regulatory domains into contact with the Abd-B gene. It also seems likely that bypass activity of Fab-8 (and also Fab-7) may have a predisposed preference, namely it is targeted for interactions with the Abd-B gene. This idea would fit with transgene bypass experiments, which showed that both Fab-7 and Fab-8 interacted with an insulator like element upstream of the Abd-B promoter, AB-I, while the Mcp boundary didn't (Postaka, 2018).

Similar conclusions can be drawn from the induction of Abd-B expression in A4 (PS9) when Fab-7 is inserted in place of Mcp. Like Fab-8, this boundary inappropriately targets the iab-4 regulatory domain to Abd-B. Unlike Fab-8, Abd-B is ectopically activated when Fab-7 is inserted in both the forward and reverse orientations. While the effects are milder in the reverse orientation, the lack of pronounced orientation dependence is consistent with experiments in which Fab-7 was inserted at its endogenous location in the reverse orientation. Unlike Fab-8 only very minor iab-6 bypass defects were observed. In addition to the activation of Abd-B in A4 (PS9) the Fab-7 Mcp replacements also alter the pattern of Abd-B regulation in more posterior segments. In the forward orientation, A4 and A5 are transformed towards an A6 identity, while A6 is also misspecified. Similar though somewhat less severe effects are observed in these segments when Fab-7 is inserted in the reverse orientation. At this point the mechanisms responsible for these novel phenotypic effects are uncertain. One possibility is that pairing interactions between the Fab-7 insert and the endogenous Fab-7 boundary disrupt the normal topological organization of the regulatory domains in a manner similar to that seen in boundary competition transgene assays. An alternative possibility is that Fab-7 targets iab-4 to the Abd-B promoter not only in A4 (PS9) but also in cells in A5 (PS10) and A6 (PS11). In this model, Abd-B would be regulated not only by the domain that normally specifies the identity of the parasegment (e.g., iab-5 in PS10), but also by interactions with iab-4. This dual regulation would increase the levels of Abd-B, giving the weak GOF phenotypes. Potentially consistent with this second model, inactivating iab-4 in the Mcp^F8 replacement not only rescues the A4 (PS9) GOF phenotypes but also suppresses the loss of anterior trichomes in the A6 tergite (Postaka, 2018).

The model whereby phase separation of coactivators compartmentalizes and concentrates the transcription apparatus at SEs and their regulated genes raises many questions. How does condensation contribute to regulation of transcriptional output? A study of RNA Pol II clusters, which may be phase-separated condensates, suggests a positive correlation between condensate lifetime and transcriptional output. What components drive formation and dissolution of transcriptional condensates? These studies indicate that BRD4 and MED1 likely participate, but the roles of DNA-binding TFs, RNA Pol II, and regulatory RNAs require further study. Why do some proteins, such as HP1a, contribute to phase-separated heterochromatin condensates and others contribute to euchromatic condensates? The rules that govern partitioning into specific types of condensates have begun to be studied and will need to be defined for proteins involved in transcriptional condensates. Does condensate misregulation contribute to pathological processes in disease, and will new insights into condensate behaviors present new opportunities for therapy? Mutations within IDRs and misregulation of phase separation have already been implicated in a number of neurodegenerative diseases. Tumor cells have exceptionally large SEs at driver oncogenes that are not found in their cell of origin, and some of these are exceptionally sensitive to drugs that target SE components. How is it possible to take advantage of phase separation principles established in physics and chemistry to more effectively improve understanding of this form of regulatory biology? Addressing these questions at the crossroads of physics, chemistry, and biology will require collaboration across these diverse sciences (Sabari, 2018).

Bidirectionality has been suggested to be the ground state of transcription (Jin, 2017), and enhancer transcription may reflect this, serving as a source of evolutionary novelty. The finding that some TF-binding sites may possess the ability to initiate transcription suggests that selection for enhancer activity could allow promoter activity to arise as a by-product. If the presence of low-level promoter activity either as a consequence of selection for enhancer activity or simply due to the relative nonspecificity of the transcriptional machinery is common in enhancer elements, then eRNA could be exploited by evolution for other purposes in transcriptional regulation, including coactivator activity (e.g., activation of CBP [Bose, 2017] or TF trapping at enhancers [Sigova, 2015]). Alternatively, transcribed enhancers may have evolved from promoters, where a promoter was duplicated and became separated from its target gene over evolutionary time. Gradually, the sequence features leading to strong promoter activity would become more degenerate, while the element may gain more TF-binding sites. Although there is currently no evidence of this, it would fit with the promoter and enhancer activity that was observed in this study and with the fact that some species do not have distal enhancers but rather regulate gene expression by TF binding very close to the promoter. Although very speculative, alternative promoters may represent an intermediate state (from an evolutionary perspective) between promoters and enhancers. A previous study proposed that developmental enhancers evolve from inducible-type promoters (Arenas-Mena 2017). Of the elements that were tested in this study, main gene promoters appear to have evolved to drive proximal orientation-dependent activation, possessing strong intrinsic promoter potential. At the other extreme, distal enhancers possess weak promoter potential but seem to have specialized toward a distal orientation-independent mode of action-a function achieved, presumably, through acquiring binding sites for a set of factors distinct from promoters. Distal enhancers themselves represent a heterogeneous population of elements with variable transcriptional properties. The coexistence of the two functions opens many questions: How can the same regulatory element facilitate enhancer and promoter function? Can one function be perturbed independently of the other? A preliminary answer to the latter is suggested in this study: Enhancer function was unaffected by changing orientation, while some promoter activity was lost, suggesting separate directional sequence determinants for these promoters' activity (Mikhaylichenko, 2018).

While developmental studies of Drosophila neural stem cell lineages have identified transcription factors (TFs) important to cell identity decisions, currently only an incomplete understanding exists of the cis-regulatory elements that control the dynamic expression of these TFs. Previous studies have identified multiple enhancers that regulate the POU-domain TF paralogs nubbin and pdm-2 genes. Evolutionary comparative analysis of these enhancers reveals that they each contain multiple conserved sequence blocks (CSBs) that span TF DNA-binding sites for known regulators of neuroblast (NB) gene expression in addition to novel sequences. This study functionally analyzes the conserved DNA sequence elements within a NB enhancer located within the nubbin gene and highlights a high level of complexity underlying enhancer structure. Mutational analysis has revealed CSBs that are important for enhancer activation and silencing in the developing CNS. Adjusting the number and relative positions of the TF binding sites within these CSBs alters enhancer function (Ross, 2018).

A previous enhancer-reporter transgene survey identified an enhancer (denoted as nub-46) that recapitulated nub expression during embryonic cephalic lobe and VNC NB lineage development (Ross, 2015). As an initial step to functionally characterize the nub-46 enhancer, its conserved sequence blocks were identified by comparative evolutionary analysis using 12 Drosophila species, including D. melanogaster, D. simulans, D. sechellia, D. yakuba, D. erecta, D. ananassae, D. persimilis, D. pseudoobscura, D. willistoni, D. virilis, D. mojavensis, and D. grimshawi. This analysis revealed that nub-46 is made up of 11 CSBs. While many of its conserved elements are novel, a CSB, denoted as 'C', containing two adjacent 9-mer sequences (TAAAAATTG and CATAAAAAA) corresponds to the DNA-binding site motifs for Cas (Ross, 2018).

The nub-46 enhancer-reporter transgene expression is dynamic during embryonic CNS development. Transient nub-46 activation is observed at the cellular blastoderm stage, followed by progressive NB reactivation during embryonic neurogenesis. At stage 9, nub-46 regulates transgene reporter expression in several NBs per ventral cord hemisegment, and enhancer activity is detected in a subset of cephalic lobe NBs. Later in CNS development enhancer/reporter expression is detected in additional cephalic lobe and ventral cord NB lineages. After embryonic stage 13, nub-46 cis-regulatory activity is downregulated in both the brain and ventral cord (Ross, 2018).

To delimit the boundaries of the nub-46 enhancer, both 5' and 3' deletions were generated of the full nub-46 enhancer CSB cluster and the in vivo cis-regulatory activity of these truncated fragments was examined via enhancer-reporter transgenes. This analysis revealed that the centrally located CSBs were sufficient for embryonic CNS expression. However, compared to the full-length enhancer, a reduced enhancer/reporter activity was observed for the core that contains elements 'C' through 'I'. These findings demonstrate that the core fragment consists of activator and repressor sequences required for its wild-type spatial and temporal regulatory dynamics (Ross, 2018).

Given that Cas is a negative regulator of pdm gene expression in embryonic NBs, it was predicted that the putative Cas DNA-binding motifs within nub-46 are required to deactivate enhancer activity. Expression of nub-46 enhancer activity partially overlaps endogenous Cas protein expression in stage 13 embryos. To determine whether the putative Cas binding-motifs function as Cas binding sites, the regulatory activity was examined of a nub-46 deletion that lacks a 40 bp conserved region containing the two Cas motifs. Deletion of the Cas DNA-binding sites triggers ectopic enhancer activity in the cephalic lobes during stage 13, suggesting that the 'C' CSB functions as a repressor element during cephalic lobe development. Interestingly, no significant ectopic enhancer activity was observed in the developing VNC. Therefore, removal of the nub-46 'C' CSB does not completely account for the repressive action of Cas on the nub-46 enhancer, especially in the VNC, and other direct or indirect effects of Cas action on the nub should be considered (Ross, 2018).

While the 'C' element may contain repressor DNA-binding sites, it remained unknown how the nub-46 enhancer is activated in the embryonic CNS. To address this question, the effects of internal deletions within the nub-46 enhancer were further examined. Each of the 10 remaining CSBs were individually removed. Enhancers with these individual deletions were tested in two independent transgenic lines. The wild type control enhancer activity was tested under the same conditions and at the same time as the deletion mutants. It was observed that nub-46 variants lacking either the 'B' (AGAACGCAAT) element or 'E' (CTACCTGAG) element displayed only a modest reduction in enhancer activity compared to the wild-type. Surprisingly, it wasfound that singular removal of other CSBs had only subtle effects on enhancer activity during embryonic NB lineage development, suggesting that these CSBs may be either required at later time points or are functionally redundant (Ross, 2018).

Given that other cis-regulatory enhancers contain a combination of repeat and unique sequence elements, it was hypothesized that nub-46 activation may result from a complex set of multiple inputs. Indeed, self-alignment of conserved sequences within nub-46 revealed that the enhancer is made up of 11 distinct repeat and palindromic elements. Upon closer inspection, seven of the 10 repeat elements were found to be located within the 'C' element, and that many of these repeats were also found in CSBs 'D,' 'H,' and 'I' of the enhancer core (Ross, 2018).

Next, whether the repeat elements within the core are required for enhancer activation was assessed. Loss of the 'C' element does not significantly affect onset of enhancer-reporter expression during embryonic VNC development. Among the six repeats identified within the 'C' element, nearly all are present in the 'D,' 'H,' and 'I' elements, and it was speculated that these may compensate for the loss of repeats in the nub-46 [C]^- mutant. To test this hypothesis, the core was truncated to exclude the 'C' element (denoted as the [C ^-] and then further removed all elements containing repeats ('D,' 'H,' and 'I' elements) from the core enhancer (referred to as [CDHI]^-. Surprisingly, removal of these CSBs had little or no effect on enhancer activity. One possible explanation for the lack of any significant effect of element 'C' (and other elements containing repeat sequences) on enhancer activation is that activator sequences are located within elements lacking repeats (elements 'E,' 'F,' and 'G'). To investigate whether the 'E' (CTACCTGAG), 'F' (GGGGTGTCAAATACCAGC), and 'G' (TACCGTA) elements are required for enhancer activation, all three elements were removed from the enhancer [CEFG]^- and it was observed that deletion of these resulted in complete loss of reporter activity, suggesting that 'E,' 'F,' and 'G', containing only unique sequences, are required to activate reporter expression. To determine whether a subset of these elements is necessary for enhancer function, the effect was tested of different combinations of internal deletions on cis-regulatory activity during embryonic neurogenesis. While removal of either the 'E,' 'F,' or 'G' elements had little or no effect on enhancer function, only the combined loss of 'E' and 'F' compromised core activity. Notably, however, increased enhancer activity was identified with loss of 'F' and 'G', whereas loss of all three non-repeat elements disrupted enhancer function. Individual deletion of non-repeat CSBs exhibited minor reduction in enhancer activity within brain lineages (Ross, 2018).

Given that all three elements lacking repeat sequences are essential for enhancer function, it was next asked whether enhancer function is modified by the multiplicity of these sequences. To explore this, core enhancers were synthesized that contain three copies of either element, substituting each into the positions of the other two non-repeat elements. Construct expression was also examined during multiple stages of CNS development. Whenthe 'F' and 'G' elements were replaced with 'E' elements, increasing the number of 'E' elements to three, higher enhancer activity was observed within subsets of NBs compared to the wild-type during stage 11. However, by stage 13, higher levels of enhancer activity were also observed throughout the CNS. Notably, ectopic expression was also observed within putative PNS lineages during stage 14. It should be noted that additional co-localization experiments using cell lineage markers would be needed to substantiate the ectopic expression. Increasing the number of 'F' elements also altered core enhancer activity, but the effect was limited to a subset of lateral VNC NBs and dorso-anterior cephalic lobe cells during early stage 12. These differences were not apparent at stage 13 and stage 14. Increasing the number of 'G' elements resulted in diminished expression at all three stages examined (Ross, 2018).

The principal findings of this study are the identification of a core sequence within the nub-46 NB enhancer that is sufficient to recapitulate the embryonic expression pattern of nubbin and that novel non-repeated conserved sequences are required for enhancer activity. This study has delimited the target of Cas repression to a CSB containing two adjacent 9-mer sequences corresponding to the TF DNA-binding motif for Cas in CSB 'C.' Nevertheless, the possibility still exists that Cas is not the only repressor of nub-46 during embryonic CNS development (Ross, 2018).

Also activator CSBs were identified that contain uniquely represented sequences within the enhancer, suggesting that the enhancer may be regulated by as yet uncharacterized TF activators that play a role in the temporal regulation of nubbin. These data suggests that multiple copies of either 'E' or 'F' can function as an activator within the enhancer core. While previous studies have suggested that clusters of repeat regulatory sequences are an important aspect of enhancer regulation, this study points to unique non-repeated motifs as targets of transcriptional activators. While these initial observations revealed altered expression outside the spatial/temporal boundaries of nub-46 activity, further experiments using cell-type specific markers are needed to confirm this ectopic expression (Ross, 2018).

The model described in this study for TF AD function may explain the function of a class of heretofore poorly understood fusion oncoproteins. Many malignancies bear fusion-protein translocations involving portions of TFs. These abnormal gene products often fuse a DNA or chromatin-binding domain to a wide array of partners, many of which are IDRs. For example, MLL may be fused to 80 different partner genes in AML, the EWS-FLI rearrangement in Ewing's sarcoma causes malignant transformation by recruitment of a disordered domain to oncogenes, and the disordered phase-separating protein FUS is found fused to a DBD in certain sarcomas. Phase separation provides a mechanism by which such gene products result in aberrant gene expression programs; by recruiting a disordered protein to the chromatin, diverse coactivators may form phase-separated condensates to drive oncogene expression. Understanding the interactions that compose these aberrant transcriptional condensates, their structures, and behaviors may open new therapeutic avenues (Boija, 2018).

Drosophila bithorax complex (BX-C) is one of the best model systems for studying the role of boundaries (insulators) in gene regulation. Expression of three homeotic genes, Ubx, abd-A, and Abd-B, is orchestrated by nine parasegment-specific regulatory domains. These domains are flanked by boundary elements, which function to block crosstalk between adjacent domains, ensuring that they can act autonomously. Paradoxically, seven of the BX-C regulatory domains are separated from their gene target by at least one boundary, and must "jump over" the intervening boundaries. To understand the jumping mechanism, the Mcp boundary was replaced with Fab-7 and Fab-8. Mcp is located between the iab-4 and iab-5 domains, and defines the border between the set of regulatory domains controlling abd-A and Abd-B. When Mcp is replaced by Fab-7 or Fab-8, they direct the iab-4 domain (which regulates abd-A) to inappropriately activate Abd-B in abdominal segment A4. For the Fab-8 replacement, ectopic induction was only observed when it was inserted in the same orientation as the endogenous Fab-8 boundary. A similar orientation dependence for bypass activity was observed when Fab-7 was replaced by Fab-8. Thus, boundaries perform two opposite functions in the context of BX-C-they block crosstalk between neighboring regulatory domains, but at the same time actively facilitate long distance communication between the regulatory domains and their respective target genes (Postaka, 2018).

Boundaries flanking the Abd-B regulatory domains must block crosstalk between adjacent regulatory domains but at the same time allow more distal domains to jump over one or more intervening boundaries and activate Abd-B expression. While several models have been advanced to account for these two paradoxical activities, replacement experiments argued that both must be intrinsic properties of the Abd-B boundaries. Thus Fab-7 and Fab-8 have blocking and bypass activities in Fab-7 replacement experiments, while heterologous boundaries including multimerized dCTCF sites and Mcp from BX-C do not. One idea is that Fab-7 and Fab-8 are simply 'permissive' for bypass. They allow bypass to occur, while boundaries like multimerized dCTCF or Mcp are not permissive in the context of Fab-7. Another is that they actively facilitate bypass by directing the distal Abd-B regulatory domains to the Abd-B promoter. Potentially consistent with an 'active' mechanism that involves boundary pairing interactions, the bypass activity of Fab-8 and to a lesser extent Fab-7 is orientation dependent (Postaka, 2018).

In the studies reported it this study have tested these two models further. For this purpose the Mcp boundary was used for in situ replacement experiments. Mcp defines the border between the regulatory domains that control expression of abd-A and Abd-B. In this location, it is required to block crosstalk between the flanking domains iab-4 and iab-5, but it does not need to mediate bypass. In this respect, it differs from the boundaries that are located within the set of regulatory domains that control either abd-A or Abd-B, as these boundaries must have both activities. If bypass were simply passive, insertion of a 'permissive' Fab-7 or Fab-8 boundary in either orientation in place of Mcp would be no different from insertion of a generic 'non-permissive' boundary such as multimerized dCTCF sites. Assuming that Fab-7 and Fab-8 can block crosstalk out of context, they should fully substitute for Mcp. In contrast, if bypass in the normal context involves an active mechanism in which more distal regulatory domains are brought to the Abd-B promoter, then Fab-7 and Fab-8 replacements might also be able to bring iab-4 to the Abd-B promoter in a configuration that activates transcription. If they do so, then this process would be expected to show the same orientation dependence as is observed for bypass of the Abd-B regulatory domains in Fab-7 replacements (Postaka, 2018).

Consistent with the idea that a boundary located at the border between the domains that regulate abd-A and Abd-B need not have bypass activity, it was found that multimerized binding sites for the dCTCF protein fully substitute for Mcp. Like the multimerized dCTCF sites, Fab-7 and Fab-8 are also able to block crosstalk between iab-4 and iab-5. In the case of Fab-7, its' blocking activity is incomplete and there are small clones of cells in which the mini-y reporter is activated in A4. In contrast, the blocking activity of Fab-8 is comparable to the multimerized dCTCF sites and the mini-y reporter is off throughout A4. One plausible reason for this difference is that Mcp and the boundaries flanking Mcp (Fab-4 and Fab-6) utilize dCTCF as does Fab-8, while this architectural protein does not bind to Fab-7 (Postaka, 2018).

Importantly, in spite of their normal (or near normal) ability to block crosstalk, both boundaries still perturb Abd-B regulation. In the case of Fab-8, the misregulation of Abd-B is orientation dependent just like the bypass activity of this boundary when it is used to replace Fab-7. When inserted in the reverse orientation, Fab-8 behaves like multimerized dCTCF sites and it fully rescues the Mcp deletion. In contrast, when inserted in the forward orientation, Fab-8 induces the expression of Abd-B in A4 (PS9), and the misspecification of this parasegment. Unlike classical Mcp deletions or the Mcp^PRE replacement described in this study, expression of the Abd-B gene in PS9 is driven by iab-4, not iab-5. This conclusion is supported by two lines of evidence. First, the mini-y reporter inserted in iab-5 is off in PS9 cells indicating that iab-5 is silenced by PcG factors as it should be in this parasegment. Second, the ectopic expression of Abd-B is eliminated when the iab-4 regulatory domain is inactivated (Postaka, 2018).

These results, taken together with previous studies, support a model in which the chromatin loops formed by Fab-8 inserted at Mcp in the forward orientation brings the enhancers in the iab-4 regulatory domain in close proximity to the Abd-B promoter, leading to the activation of Abd-B in A4 (PS9). In contrast, when inserted in the opposite orientation, the topology of the chromatin loops formed by the ectopic Fab-8 boundary are not compatible with productive interactions between iab-4 and the Abd-B promoter. Moreover, it would appear that boundary bypass for the regulatory domains that control Abd-B expression is not a passive process in which the boundaries are simply permissive for interactions between the regulatory domains and the Abd-B promoter. Instead, it seems to be an active process in which the boundaries are responsible for bringing the regulatory domains into contact with the Abd-B gene. It also seems likely that bypass activity of Fab-8 (and also Fab-7) may have a predisposed preference, namely it is targeted for interactions with the Abd-B gene. This idea would fit with transgene bypass experiments, which showed that both Fab-7 and Fab-8 interacted with an insulator like element upstream of the Abd-B promoter, AB-I, while the Mcp boundary didn't (Postaka, 2018).

Similar conclusions can be drawn from the induction of Abd-B expression in A4 (PS9) when Fab-7 is inserted in place of Mcp. Like Fab-8, this boundary inappropriately targets the iab-4 regulatory domain to Abd-B. Unlike Fab-8, Abd-B is ectopically activated when Fab-7 is inserted in both the forward and reverse orientations. While the effects are milder in the reverse orientation, the lack of pronounced orientation dependence is consistent with experiments in which Fab-7 was inserted at its endogenous location in the reverse orientation. Unlike Fab-8 only very minor iab-6 bypass defects were observed. In addition to the activation of Abd-B in A4 (PS9) the Fab-7 Mcp replacements also alter the pattern of Abd-B regulation in more posterior segments. In the forward orientation, A4 and A5 are transformed towards an A6 identity, while A6 is also misspecified. Similar though somewhat less severe effects are observed in these segments when Fab-7 is inserted in the reverse orientation. At this point the mechanisms responsible for these novel phenotypic effects are uncertain. One possibility is that pairing interactions between the Fab-7 insert and the endogenous Fab-7 boundary disrupt the normal topological organization of the regulatory domains in a manner similar to that seen in boundary competition transgene assays. An alternative possibility is that Fab-7 targets iab-4 to the Abd-B promoter not only in A4 (PS9) but also in cells in A5 (PS10) and A6 (PS11). In this model, Abd-B would be regulated not only by the domain that normally specifies the identity of the parasegment (e.g., iab-5 in PS10), but also by interactions with iab-4. This dual regulation would increase the levels of Abd-B, giving the weak GOF phenotypes. Potentially consistent with this second model, inactivating iab-4 in the Mcp^F8 replacement not only rescues the A4 (PS9) GOF phenotypes but also suppresses the loss of anterior trichomes in the A6 tergite (Postaka, 2018).

Genome-wide studies has identified two enhancer classes in Drosophila that interact with different core promoters: housekeeping enhancers (hkCP) and developmental enhancers (dCP). It is hypothesized that the two enhancer classes are occupied by distinct architectural proteins, affecting their enhancer-promoter contacts. It was determined that both enhancer classes are enriched for RNA Polymerase II, CBP, and architectural proteins but there are also distinctions. hkCP enhancers contain H3K4me3 and exclusively bind Cap-H2, Chromator, DREF and Z4, whereas dCP enhancers contain H3K4me1 and are more enriched for Rad21 and Fs(1)h-L. Additionally, the interactions of each enhancer class were mapped utilizing a Hi-C dataset with <1 kb resolution. Results suggest that hkCP enhancers are more likely to form multi-TSS interaction networks and be associated with topologically associating domain (TAD) borders, while dCP enhancers are more often bound to one or two TSSs and are enriched at chromatin loop anchors. The data support a model suggesting that the unique architectural protein occupancy within enhancers is one contributor to enhancer-promoter interaction specificity (Cubenas-Potts, 2017).

This study characterize the protein occupancy, chromatin interactions and architecture profiles for the two enhancer classes found in Drosophila. Each enhancer class has distinct H3K4 methylation states, is bound by both common and distinct architectural proteins, and is involved in distinct types of chromatin interactions. First, it was established that hkCP enhancers exclusively bind CAP-H2, Chromator, DREF and Z4, while dCP enhancers do not and are preferentially enriched for but not exclusively bound by Fs(1)h-L and Rad21. In addition, hkCP enhancers are more likely than dCP enhancers to associate with multiple TSSs, which promotes a higher transcriptional output. Finally, hkCP enhancers preferentially associate with topologically associating domain (TAD) borders, whereas dCP enhancers are enriched at chromatin loop anchors present inside TADs. Interestingly, enhancers activated by both core promoters exhibit more hkCP enhancer like characteristics, indicating that the both CP enhancers may represent an intermediate among the distinctive hkCP and dCP enhancers. Altogether, these results provide strong correlative evidence, supporting a model suggesting that architectural proteins are critical regulators of enhancer-promoter interaction specificity and that the interactions between enhancers and promoters significantly contribute to the generation of 3D chromatin architecture (Cubenas-Potts, 2017).

The importance of architectural proteins in regulating enhancer-promoter interactions in Drosophila is supported by the observation that the vast majority of architectural protein sites present in the genome correspond to enhancers and promoters. Historically, architectural proteins were identified as insulators, which were functionally demonstrated to block enhancer-promoter interactions. The insulator function of architectural proteins correlates with their enrichment at TAD borders. However, several lines of evidence, including ChIA-PET analysis of CTCF- and cohesin-mediated interactions in mammals, suggest that these architectural proteins help mediate long range contacts among regulatory sequences. In Drosophila this study observed that nearly all of the Group 1 and Group 2 architectural protein sites are associated with enhancers or promoters defined by STARR-seq, TSSs or CBP peaks, suggesting that architectural proteins help mediate enhancer-promoter interactions. Notably, Group 3 architectural proteins include the classic insulator proteins CTCF, CP190, Mod(mdg4) and SuHw, and at least 25% of their peaks cannot be explained by enhancers or promoters. It is interesting to speculate that the non-enhancer-promoter sites may be involved in more classical insulator functions or contributing to the chromatin architecture of inactive regions of the genome (Cubenas-Potts, 2017).

The conclusion that architectural proteins are critical regulators of the specificity between enhancers and promoters is supported by two main lines of evidence. First, the current results demonstrate a strong correlation between each enhancer class and distinct architectural protein subcomplexes. Functional evidence supporting this conclusion comes from mutational analyses of the DRE motif in the distinct enhancer classes, which likely recruits DREF and the other hkCP enhancer associated architectural proteins. Zabidi (2015) demonstrated that the tandem DRE motif alone was sufficient to enhance expression of the housekeeping core promoter and that mutation of DRE motifs within an hkCP enhancer reduced its promoter interactions in a luciferase assay. Furthermore, addition of a DRE motif to a dCP enhancer changed its promoter specificity. Because DREF and potentially BEAF-32 bind to the DRE motif, these results strongly support a model suggesting that the differential occupancy of Cap-H2, Chromator, DREF and Z4 in the two enhancer classes is a critical regulator of their specific interactions with the core promoter types. However, the data cannot discount the notion that unique transcription factor binding at proximal TSSs also contribute to the specificity of enhancer-promoter interactions. Although hkCP enhancer identity is most highly correlated with CAP-H2, Chromator, DREF and Z4 localization, these four architectural proteins are not found in isolation within hkCP enhancers. BEAF-32 and CP190 are also strongly enriched in hkCP enhancers, which are also associated with high occupancy APBSs and TAD borders. Thus, the full architectural protein complement at hkCP enhancers is far more complex than the four hkCP-specific architectural proteins. In addition, architectural proteins that are truly unique to dCP enhancers were not detected. Because dCP enhancers exhibit higher cell type specificity, it cannot be discounted that there are additional dCP enhancers present in the Drosophila genome that were not identified by STARR-seq and thus, excluded from this analysis. From these studies, it is unclear if the enrichment of Fs(1)h-L and Rad21, particularly because Fs(1)h-L and Rad21 are present in hkCP enhancers at lower levels, or the absence of BEAF-32, CAP-H2, Chromator, CP190, DREF and Z4 truly distinguishes the architectural protein complexes found at dCP enhancers. In the future, careful biochemical analyses will be required to gain a comprehensive understanding of the complete organization of architectural protein subcomplexes associated with each enhancer class (Cubenas-Potts, 2017).

hkCP enhancers are associated with multi-TSS chromatin interactions and TAD borders. The promoter-clustering by hkCP enhancers results in a dose-dependent increase in transcriptional output for the interacting genes. Thus, one likely molecular mechanism by which hkCP enhancers promote robust transcriptional activation is by increasing the local concentration of RNA Polymerase II and general transcription factors (GTFs) by bringing multiple TSSs into close proximity. It is interesting that the hkCP enhancers, which form promoter clusters, are associated with TAD borders. It is speculated that the hkCP enhancer interactions involve inter-TAD contacts within the A-type compartment, indicative of the formation of transcription factories (70). From this analysis, it is unclear if the hkCP enhancers alone are sufficient for the formation of the 3D interactions or the neighboring TSSs and their associated transcription factors are also contributing to these contacts. It is hypothesized that the genes recruited to the factories contain the housekeeping promoter motifs (DRE, Ohler 1, Ohler 6 and TCT) and that the hkCP enhancer residents Cap-H2, Chromator, DREF and Z4, are critical to the formation of these 3D contacts (Cubenas-Potts, 2017).

dCP enhancers are more likely to be present within TADs and are enriched on the subTAD-like chromatin loop anchors. dCP enhancers do not form promoter clusters, but are more likely to interact with individual TSSs. One possible explanation for this observation is that the genes interacting with dCP enhancers require the binding of sequence-specific transcription factors, and increasing the concentration of GTFs and RNA polymerase II is not an effective mechanism to promote transcriptional output. The chromatin loop association is consistent with dCP enhancers forming a strong contact with a single TSS. However, it is acknowledged that dCP enhancers are likely one of multiple molecular mechanisms contributing to chromatin loop formation. Surprisingly, the chromatin loops that were observed in Drosophila are distinct from the chromatin loops described in humans. A recent study reported approximately 10,000 chromatin loops in the genome of GM12878 lymphoblastoid cells, but this study detected only 458 chromatin loops in Drosophila utilizing a similar method. The reason why there are so few chromatin loops in Drosophila compared to humans is unclear. It is possible that chromatin loops represent a more precise level of architecture within TADs between specific enhancers and promoters in mammals, but because TADs are significantly smaller in flies (median size 32.5 kb compared to 880 kb in mice, the chromatin loops are not as prominent or easily detected in the Drosophila genome. Notably, it appears that the chromatin loops are generated by different architectural proteins in the two species. The chromatin loops in humans are anchored by convergent CTCF motifs, while the results presented in this study demonstrate that the chromatin loop anchors in Drosophila are depleted of CTCF. Because the chromatin loops in Drosophila show a strong enrichment for Fs(1)h-L, a Brd4 homolog, and the architectural proteins Rad21, Nup98, TFIIIC and Mod(mdg4), it is possible that a combination of transcription and architectural proteins is required for chromatin loop formation in flies, which may be different from mammals . Altogether, it is clear that dCP enhancers are involved in individual contacts with TSSs and are likely one mechanism by which chromatin loops form in Drosophila (Cubenas-Potts, 2017).

Surprisingly, only ~20% and ~12.5% of all hkCP enhancer and ~7.5% and ~8.5% of dCP enhancer interactions involve a TSS or enhancer on the opposite anchor, respectively. The biological significance of the enhancer to non-TSS association is unclear. One possible explanation is that current methods for identifying statistically significant interactions are not sufficiently robust and that many of the enhancer to non-TSS interactions are not representative of biologically significant contacts. However, it cannot be discounted that the non-TSS interactions mediated by enhancers are real and the biological significance of these contacts remains to be determined. Throughout this analysis, the patterns of TSS interactions were compared with each enhancer class instead of drawing conclusions about the absolute number of TSSs bound per enhancer, minimizing the impact of any non-specific interactions within the data. Additional molecular studies for the various type of enhancer interactions (enhancer to promoter, enhancer to non-TSS, etc.) will be required to evaluate the various biological contributions of each (Cubenas-Potts, 2017).

This study found that the functional differences between enhancers that activate housekeeping versus developmental genes are reflected in their chromatin and architectural protein composition, and in the type of interactions they mediate. hkCP enhancers are marked by H3K4me3, associate with TAD borders, and mediate large TSS-clustered interactions to promote robust transcription. This class of enhancers contain the architectural proteins CAP-H2, Chromator, DREF and Z4. In contrast, dCP enhancers are marked by H3K4me1, associate with chromatin loop anchors and are more commonly associated with single TSS-contacts. dCP enhancers are depleted of the hkCP-specific architectural proteins and show an enrichment for Fs(1)h-L and Rad21. The results support a model suggesting that the unique occupancy of architectural proteins in the distinct enhancer classes are key contributors to the types of interactions that enhancers can mediate genome-wide, ultimately affecting enhancer-promoter specificity and 3D chromatin organization. In the future, further characterization of the broadly defined housekeeping and developmental enhancers into smaller subclasses may yield additional levels of regulation and formation of unique architectural protein and transcription factor protein complexes as key mediators of long range chromatin contacts (Cubenas-Potts, 2017).

Developmental gene expression is tightly regulated through enhancer elements, which initiate dynamic spatio-temporal expression, and Polycomb response elements (PREs), which maintain stable gene silencing. These two cis-regulatory functions are thought to operate through distinct dedicated elements. By examining the occupancy of the Drosophila pleiohomeotic repressive complex (PhoRC) during embryogenesis, extensive co-occupancy was revealed at developmental enhancers. Using an established in vivo assay for PRE activity, it was demonstrated that a subset of characterized developmental enhancers can function as PREs, silencing transcription in a Polycomb-dependent manner. Conversely, some classic Drosophila PREs can function as developmental enhancers in vivo, activating spatio-temporal expression. This study therefore uncovers elements with dual function: activating transcription in some cells (enhancers) while stably maintaining transcriptional silencing in others (PREs). Given that enhancers initiate spatio-temporal gene expression, reuse of the same elements by the Polycomb group (PcG) system may help fine-tune gene expression and ensure the timely maintenance of cell identities (Erceg, 2017).

While enhancers initiate spatio-temporal transcriptional activity, PREs maintain a previously determined transcriptional state of their target genes, thus leading to transcriptional memory. PREs are generally thought to be dedicated solely to gene silencing and not to contain enhancer-like features to activate gene expression. This study presents evidence to the contrary, that both functions can be encoded in the same cis-regulatory element, depending on the cellular context. This is not a rare event -- almost 25% of PhoRC occupancy is at developmental enhancers. Of the 16 elements that this study tested experimentally (either enhancers for PRE activity or PREs for enhancer activity), nine have dual function, being sufficient to activate transcription in a specific spatio-temporal pattern and mediate PcG-dependent silencing in vivo (Erceg, 2017).

These dual elements have interesting implications for transcriptional regulation during embryonic development. First, at the level of PcG protein recruitment, this subset of enhancers is highly enriched in the Pho motif, which distinguishes them from other developmental enhancers. This suggests that the recruitment of Pho to PhoRC enhancers is direct via sequence-specific DNA binding, consistent with an instructive model of recruitment, although other factors are likely involved. PcG proteins and developmental TFs bind in close proximity to each other within the same element (a single DNase hypersensitive site), raising the possibility of direct interplay between the two. The results indicate that the activity of PhoRC-bound enhancers is dominated by tissue-specific TFs that activate transcription in some cells while being dominated by a functional PcG complex in other cells. Is this due to mutually exclusive occupancy of developmental TFs and PcG proteins in different tissues, or do they compete functionally at these elements? The dramatic derepression of enhancer activity in different cell types upon PcG protein removal suggests that other tissue-specific TFs must occupy these enhancers in the PcG silenced cell. This has interesting implications for enhancer activity, as it is well known that TFs bind to thousands of sites (tens of thousands in mammalian cells), but only a subset of associated target genes changes expression when the TF is removed. This has led to the general assumption that the majority of binding events is nonfunctional or neutral. These data suggest that at least a subset of this embryonic occupancy can be functional if not actively antagonized by the presence of PcGs (Erceg, 2017).

Second, enhancer-mediated polycomb recruitment has interesting implications for the mechanism of PcG-mediated silencing. The current models suggest that PcG proteins silence transcription mainly by silencing a gene's promoter, in keeping with PcG recruitment to CpG islands in vertebrates, or by coordinating a three-dimensional repressive topology, where the entire gene's locus is silenced. In either mode, a gene's promoter would not be permissive to enhancer activation. The data suggest that there may be a third mode of very local silencing at an individual enhancer, leaving the promoter and the rest of the gene's regulatory landscape open for activation by other enhancers, as was observed at the prat2 locus. This would allow for much more fine-tuning of silencing in individual tissues and stages. It also suggests that PcG proteins could play a more dynamic role, similar to a 'standard' transcriptional repressor at enhancers (Erceg, 2017).

Third, this may have broader implications for cell fate decisions during rapid developmental transitions. When multipotent cells become specified into different lineages, a specific transcriptional program often needs to be activated in one cell while being repressed in other cells from the same progenitor population. Having active enhancers in the precursor cells remain accessible to directly recruit the PcG complexes would ensure that these enhancers become silenced in a timely manner. Conversely, having maternally deposited PcG proteins already bound to enhancers early in development may serve as placeholders to ensure that these dual elements remain open and available for TFs to activate at the appropriate development stage. Interestingly, in the majority of the tested cases, PcG proteins and developmental TFs use these dual elements to regulate the same target gene, the vast majority of which is key developmental regulators of cell identity (Erceg, 2017).

The identification of PREs in other species has remained a key challenge, with only a handful of PREs identified in mammals and plants to date. In mammals, the PcG system is recruited to inactive CpG islands, with few specific sequence features. Although there are mammalian homologs of the Drosophila Pho and dSfmbt proteins, Yin Yang 1 (YY1) and SFMBT, respectively, the conservation of PhoRC as a complex and its involvement in mammalian PcG silencing remain unclear. It is proposed that such dual enhancers/PREs will also exist in mammals, although, given this apparent lack of conservation of YY1 function, their mechanism of PcG recruitment may have diverged (Erceg, 2017).

There are other online resources of documented enhancers in the Drosophila genome, namely, FlyLight and Vienna Tiles. While these cis-regulatory libraries provide useful information, the coverage of the pdm locus in these databases is not complete. For example, FlyLight analysis did not detect 14 enhancers that flank the nub transcribed sequence. These include those located upstream to the nub long transcript (nub-12 and nub-13), its first intron (nub-28), second exon (nub-32a), second intron (nub-32b, nub-32c, nub-33, nub-36, nub-40b, nub-41, nub-42, nub-44, and nub-45a), and third intron (nub-49b). The FlyLight library also does not include seven pdm-2 enhancers: located in the upstream region (pdm2-21); within the second intron (pdm2-27 and pdm2-28) and lacks information regarding its downstream region (pdm2-45, pdm2-46, pdm2-47 and pdm2-48). Vienna Tiles also provides only partial coverage of the pdm locus, omitting the following 11 pdm locus enhancers: nub-58a, nub-58b, pdm2-13, pdm2-17, pdm2-21, pdm2-22, pdm2-23a, pdm2-31b, pdm2-32, pdm-33, and pdm2-48 . While the Vienna Tiles database provides information on embryonic and adult enhancers, it does not supply information on cis-regulatory activity during larval development. In addition, based on the current analysis, most of the reporter transgenes in these two libraries contain multiple enhancers. For example, he Vienna Tiles enhancer denoted as VT6436 enhancer is made up of two embryonic enhancers (nub-28 and nub-29) (Ross, 2015).

Analysis of the pdm locus enhancers identified four functionally related enhancers (nub-46, nub-49b, pdm2-34, and pdm2-37a) that activated expression during NB lineage development. The nub-46 and pdm2-34 enhancers are both located in the third intron of the nub and pdm-2 long transcript, respectively, whereas nub-49b and pdm2-37a are positioned immediately 5' to the transcriptional start site of their respective short isoform. While the nub-46 and pdm2-34 enhancers drove overlapping but nonidentical expression during embryonic and larval NB lineage development, nub-49b and pdm2-37a regulated similar expression patterns during postembryonic NB lineage development. Analysis of nub-46 and pdm2-34 revealed that these enhancers share multiple conserved DNA elements, albeit in largely unique configurations. Although these observations suggest these enhancers are related, additional studies are needed to further resolve subtle differences between their regulatory activities (Ross, 2015).

Comparative analysis of the nub and pdm-2 coding sequences revealed that their sequence relationship was mostly limited to the exons that encode their POU domains and homeodomains. In contrast, no evidence of collinearity was detected within their noncoding regions, suggesting that they have diverged at a faster rate than the coding sequences. Only one pdm ortholog was found in the mosquito, whereas the medfly and housefly carry both genes. Given this observation and accounting for the divergence of Drosophila from these distant Diptera, the pdm duplication event may have occurred in the Dipteran line between 100 and 260 million (Ross, 2015).

Given the presence of the pdm genes in the medfly and housefly genomes, it was asked whether some or all of the Drosophila CSCs could also be identified in these distant species. Submitting the D. melanogaster genomic sequences surrounding nub and pdm-2 to BLAST searches using the medfly and housefly genomes revealed sequences conserved in the three Dipteran species within several pdm locus CSCs (see Three-way alignment of ultraconserved sequences in conserved sequence clusters identified in Drosophila, housefly, and medfly) that were typically found within their longest conserved sequence blocks (CSBs). For example, a 48 bp sequence within the pdm2-26 CSC that is conserved in all drosophilids, in addition to the medfly and housefly (see The pdm2-26 enhancer contains ultraconserved sequences detected in multiple Diptera)(Ross, 2015).

These studies revealed that two-thirds of the CSCs function as cis-regulatory enhancers that regulate gene expression in a diverse array of spatiotemporal aspects, which taken together reflect pdm expression domains. These observations suggest that the pdm genes are dynamically regulated by multiple cis-regulatory modules, and that these enhancers are more amenable to evolutionary restructuring than their protein encoding exons. This is in agreement with recent reviews on the evolution of Dipteran enhancers highlighting the flexibility of enhancers to maintain their function after loss and/or gain of TF DNA binding sites. Also consistent with these observations, functionally related enhancers were found within the pdm locus that share conserved sequences, albeit in different arrangements and orientations (Ross, 2015).

From a mechanistic perspective, these observations suggest that enhancer behavior can be predicted based on the combination of the conserved elements shared among functionally related enhancers. Similar observations have been made by others. Hierarchical clustering analysis of shared conserved sequences revealed that pdm SOG enhancers may be grouped based on shared elements that are for the most part not present within other pdm locus CSCs. A similar analysis of adult median neurosecretory cell (mNSC) enhancers revealed that they grouped together, as evidenced by sharing of conserved sequence elements, which were largely absent in non-mNSC CSCs with the pdm locus. While further work is required to determine whether these shared elements are important for enhancer activity, these findings suggest a level of structural complexity in the presence and clustering of enhancers that requires further analysis. To construct a better representation of enhancer structure and thus cis-regulatory prediction, one would ideally prefer to use a larger training set of enhancers to improve the accuracy of prediction. These approaches will be addressed in future studies (Ross, 2015).

One of the principal findings of this study is the discovery of 77 enhancers that exhibit a remarkably diverse range of cis-regulatory activities during embryonic and postembryonic development. The biological significance of this enhancer diversity most likely reflects the diversity of the developmental programs in which these transcription factors participate. Functionally related enhancers that share multiple conserved DNA sequences were also identified, and these enhancers could be classified using hierarchical clustering techniques. In addition, this analysis has revealed that the collinearity between the pdm genes is predominantly confined to their POU domain and homeodomain exons, suggesting that their noncoding sequences are diverging at a faster rate than their coding sequences. These results should provide further insight into the regulatory logic that controls cis-regulatory function and thus gene regulation (Ross, 2015).

It was also considered whether either of the TBP-related factors, TRF1 and TRF2, are used instead of TBP at DPE-containing promoters. To this end, the effect of depleting TRF1 or TRF2 was examined upon the expression of DPE-containing versus TATA-containing endogenous genes. TRF1, which is largely involved in RNA polymerase III transcription in Drosophila, has little or no effect on transcription of DPE-containing or TATA-containing genes. TRF2 is important for both DPE-mediated and TATA-mediated transcription. The effect of TRF2 is similar to that of TAF4, which appears to contribute to both DPE-depentend and TATA-dependent transcription. Neither TRF1 nor TRF2 exhibit an opposite effect on DPE-mediated versus TATA-mediated transcription as do TBP, Mot1, and NC2. In addition, a genome-wide ChIP analysis of TRF2 did not reveal an association of TRF2 with DPE-containing genes. Thus, at the present time, there is no evidence suggesting a specific link between either TRF1 or TRF2 and DPE-mdidated or TATA-mediated transcription (Hsu, 2008).

In conclusion, the analysis of TBP, Mot1, and NC2 in the context of DPE-containing versus TATA-containing promoters has revealed a regulatory circuit that controls the balance between DPE-mediated versus TATA-mediated transcription. This circuit may be a key means by which DPE or TATA specificity of transcriptional enhancers is achieved. In the future, it will be interesting and important to build upon this core circuit to identify the connections and mechanisms by which biological networks use DPE and TATA specificity to increase the number of pathways by which signals can be transmitted (Hsu, 2008).

Cells often fine-tune gene expression at the level of transcription to generate the appropriate response to a given environmental or developmental stimulus. Both positive and negative influences on gene expression must be balanced to produce the correct level of mRNA synthesis. To this end, the cell uses several classes of regulatory coactivator complexes including two central players, TFIID and Mediator (MED), in potentiating activated transcription. Both of these complexes integrate activator signals and convey them to the basal apparatus. Interestingly, many promoters require both regulatory complexes, although at first glance they may seem to be redundant. RNA interference (RNAi) was used in Drosophila cells to selectively deplete subunits of the MED and TFIID complexes to dissect the contribution of each of these complexes in modulating activated transcription. The robust response of the metallothionein genes to heavy metal was used as a model for transcriptional activation by analyzing direct factor recruitment in both heterogeneous cell populations and at the single-cell level. Intriguingly, it was found that MED and TFIID interact functionally to modulate transcriptional response to metal. The metal response element-binding transcription factor-1 (MTF-1) recruits TFIID, which then binds promoter DNA, setting up a 'checkpoint complex' for the initiation of transcription that is subsequently activated upon recruitment of the MED complex. The appropriate expression level of the endogenous metallothionein genes is achieved only when the activities of these two coactivators are balanced. Surprisingly, it was found that the same activator (MTF-1) requires different coactivator subunits depending on the context of the core promoter. Finally, the stability of multi-subunit coactivator complexes can be compromised by loss of a single subunit, underscoring the potential for combinatorial control of transcription activation (Marr, 2006).

There are four known metallothionein genes in Drosophila: MtnA, MtnB, MtnC, and MtnD. Of these, the best characterized is the MtnA gene, which produces a transcript of ~600 bases in length, bearing one intron. All of the regulatory elements required for robust response to heavy metals, including copper, lie within 500 bp of the transcription start site. The gene is controlled by a single activator, metal response element-binding transcription factor 1 (MTF-1), which binds two adjacent metal response elements (MRE) 50 bp upstream of the TATA-box (Zhang, 2001). Quantitative PCR (qPCR) analysis of the endogenous gene in Drosophila S2 cells shows that the gene is highly induced (~250-fold) after a short exposure to copper. The total amount of stable MtnA mRNA approximates the level of the abundant transcript for the ribosomal subunit Rp49. Primer extension analysis confirms that transcriptional activation of the endogenous MtnA gene originates from a unique start site overlapping the core promoter. The transcript accumulates linearly for ~12 h, thus measurements in this time window likely reflect relative levels of transcription of the MtnA gene. Importantly, induction at the endogenous chromosomal locus is easily assayed in order to measure physiologically relevant transcriptional activation in the context of native chromatin. Taken together, these properties establish the endogenous MtnA gene as a useful model for studying transcriptional mechanisms governing an inducible gene (Marr, 2006).

Using chromatin immunoprecipitation (ChIP), it was found that the sequence-specific DNA-binding protein MTF-1 is specifically recruited to the MtnA promoter region in response to copper. Curiously, the ChIP of the promoter region was compared to a region 1 kb downstream, a significant amount of MTF-1 was found to be present on the promoter even in the absence of added copper. Under these conditions, little transcription is detected from this gene. As a preliminary experiment to investigate a potential functional interaction between TFIID and MED, it was first asked whether the two complexes are both recruited in a signal-dependent manner to the MtnA gene. Using ChIP, it was found that both TBP and the TAFs are efficiently recruited to the promoter region in response to copper. In addition, the MED17, MED24, MED26, and MED27 subunits of MED are all recruited to the promoter region in response to copper treatment. Consistent with the high level of induction, RNAPII occupancy at the MtnA promoter is also increased in response to heavy metal treatment. Thus, both core coactivator complexes and RNAPII are efficiently recruited to the promoter region upon induction and resultant binding of MTF-1 to the MREs (Marr, 2006).

Because the ChIP assay is limited to measuring response in a heterogeneous population of cells, a transgenic model system was extablished in Drosophila S2 cells in order to visualize the response at the single-cell level. Such an approach has proved useful in understanding transcription factor dynamics in vivo. By selecting for stably transfected MtnA firefly luciferase reporters, a concatenated transgenic locus was generated in a clonal line of S2 cells. The transgenic locus was assayed for dependence on copper using a luciferase assay. Importantly, transcription initiates a unique site that maps to the correct start site of the MtnA core promoter. With this substantial increase in gene number (~2000) at the integrated transgenic locus, it should now be possible to visualize direct recruitment of specific transcription factors to the MtnA promoter within a single cell (Marr, 2006).

As expected, in the absence of heavy metal, MTF-1 is predominantly cytoplasmic; however, in agreement with ChIP data, some MTF-1 can be detected at the transgenic cluster even in the absence of a metal stimulus. Thus, antibody labeling of MTF-1 provides a useful marker for the subnuclear location of the transgene cluster in both induced and uninduced cells. Notably, the locus is not undergoing transcription (as detected by RNA FISH) in the absence of heavy metal induction despite the presence of some MTF-1 at the transgene cluster. Upon copper induction, MTF-1 vacates the cytoplasm and accumulates selectively at the transgenic locus. Under these same conditions, TBP is also actively recruited to this cluster. Consistent with not only TBP but holo-TFIID complex recruitment, it was found that TAF2 also accumulates at the transgene. Likewise MED components recruited to the transgene were detected using antibodies against MED26. As expected, RNAPII is recruited to the cluster in a copper-dependent manner consistent with the transcriptional induction of the transgene under these conditions. In contrast, TBP-related factor 1 (TRF1), a subunit known to be a key component of the RNA polymerase III core promoter recognition complex, is not recruited to the transgene. This negative control helps rule out the possibility that the tandemly reiterated transgene is simply nonspecifically attracting transcription factors (Marr, 2006).

Having established by two independent methods that both TFIID and MED complexes are recruited to the MtnA promoter in an activator-dependent manner, their role in potentiating transcriptional activation of the endogenous MtnA gene was investigated. The efficient technique of RNAi in Drosophila S2 cells was used to knock down expression of TFIID and MED subunits. In addition, the activator MTF-1 was knocked down to ascertain the extent of the activator’s role in induction. After treatment with copper, total RNA was purified from dsRNA treated and untreated S2 cells and then they were assayed by two independent methods. First, a primer extension analysis was used on equivalent amounts of total RNA. This assay revealed that an accurate transcription is detected from one distinct core promoter start site. Next, qPCR normalized to the Rp49 mRNA was used, to confirm that there is little or no global disturbance of RNAPII transcription (Marr, 2006).

Not surprisingly, depletion of MTF-1 severely reduced transcriptional activation from the MtnA promoter, confirming the central role of this activator. RNAi directed against TBP also had a dramatic inhibitory effect. The MtnA promoter is <10% as active when TBP levels are severely depleted. Surprisingly, knockdown of multiple TAFs had little apparent effect on the ability of MTF-1 to activate MtnA. Indeed, depletion of the TAFs actually stimulated (1.5- to 2-fold) production of RNA. With the exception of TAF11, a reduction of individual TAFs resulted in a remarkably uniform response. The reason for this uniformity became apparent when the stability of the TFIID complex was examined in the RNAi-treated cells. The overall stability of the holo-TFIID complex appears to be coupled to the stability of certain individual TAFs. In the most dramatic example, RNAi-targeted reduction of TAF4 leads to the concomitant loss of TAF1, TAF5, TAF6, and TAF9, as well as a detectable reduction in TBP. Interestingly, TAF2 and TAF11 are largely unaffected by depletion of TAF4. Similar results are observed for the other TAFs as well. When the transcript levels of the TAFs were measure after RNAi treatment, it is clear that the loss of stability occurs at the protein level, since the transcript levels for nontargeted TAFs are unaffected. For example, when TAF4 is targeted, only the TAF4 transcript is depleted (Marr, 2006).

In contrast to the TAFs, RNAi reduction of MED subunits gave striking but variable effects on the ability of MTF-1 to activate transcription from the MtnA promoter. Unlike TFIID, the response is far from uniform. For example, dsRNA directed against MED23 has little effect on induction of MtnA, while loss of MED17, the Drosophila SRB4 homolog, has a strong inhibitory effect. The lack of a uniform response in the MED RNAi led to a further investigation of the potential differential response upon depletion of MED subunits at related promoters activated by MTF-1. As discussed above, Drosophila has four metallothionein genes that respond to heavy metals. Three of these—MtnA, MtnB, and MtnD—are active in S2 cells. All three of these genes are specifically activated by the same factor, MTF-1. All three Mtn genes were examined in a single experiment using qPCR. First, it was confirmed that all three promoters, MtnA, MtnB, and MtnD, require MTF-1 for induction. Remarkably, distinct differential requirements were found for MED subunits depending on the promoter. For example, loss of MED13, a subunit of the larger MED complex (ARC-L) thought to play a repressive role in transcription, is not essential for MtnA induction. In contrast, MED13 was found to be important for both MtnB and MtnD activation by MTF-1. In contrast, the opposite specificity was seen with the MED26 subunit, a component of the smaller MED complex (CRSP), thought to play predominantly a coactivator role in transcription. Interestingly, MED26 is required for full induction of the MtnA promoter but is dispensable for MTF-1 activation of the MtnB and MtnD promoters. Thus, these experiments reveal a remarkable example of differential dependence on cofactor composition even though all three promoters tested use the same activator. Apparently, the precise role of individual MED subunits depends on the promoter context and structure, despite the absence of any evidence of direct binding of DNA by the MED complex (Marr, 2006).

To help rule out nonspecific effects on transcription such as a change in the concentration of free RNA polymerase, representative targets from TFIID and MED were tested in a transient transfection assay where the effect to a second promoter can be normalized. In these experiments, TAF4 and MED17 were chosed as representative targets, since TAF4 compromises much of the TFIID complex and MED 17 is likely a component of the core MED complex. The transient transfection data are largely consistent with the data generated at the endogenous locus and at the transgene (Marr, 2006).

The data presented above suggest that activation of the MtnA gene requires specific MED subunits, and at the same time the TAFs appear to be playing a potential negative regulatory role. Because it is clear that the TAFs are specifically recruited in S2 cells to the MtnA promoter in a copper-dependent manner by MTF-1, whether TFIID recruitment can occur in the absence of the MED complex was examined. To achieve this, RNAi directed against MED17 was used, which results in an almost complete loss of MED activity. Surprisingly, TFIID is still efficiently recruited to the MtnA gene. ChIP experiments confirmed that TBP and TAF2 are still actively (and likely directly) recruited to the endogenous MtnA gene by MTF-1 even when the gene is transcriptionally inactive as measured by qPCR analysis. The MtnA luciferase transgene system was used to investigate this relationship at the single-cell level. Without any RNAi, TBP, TAF2, and RNAPII were all recruited to the transgene. In agreement with the ChIP data above, even in the absence of MED activity, after MED17 depletion, TBP and TAF2 are nevertheless efficiently recruited to the transgene. In contrast, no RNAPII can be detected at the transgene consistent with the loss of transcription activation. Apparently, TFIID is recruited to the promoter, but the promoter is not active in supporting transcription. Importantly, recruitment of this 'inactive TFIID' is dependent on the activator MTF-1. In the absence of MTF-1, no TFIID or RNAPII is recruited to the transgene (Marr, 2006).

This perplexing result of recruiting an apparently 'inactive' TFIID prompted an examination of what happens when both TAFs and MEDs were depleted. Remarkably when both the TAFs and MED complex are depleted and 'removed' from the MtnA promoter, MTF-1-dependent activation of transcription is restored to ~95% the level of untreated cells, which is well above the inhibited level observed when the MEDs alone are depleted. In humans and Drosophila, TAFs can be subunits of other complexes such as TFTC and STAGA, so it is possible that the functional interaction analyzed is not TFIID-specific. To test this, specific subunits of these other complexes were targeted to determine if they would have a similar ability to rescue the MED knockdown. Unlike the TFIID subunits, RNAi against dAda2b, dGCN5, dSPT3, and dTRA1 was unable to rescue the loss of the MED subunits. These findings taken together suggest that most likely the functional relationship revealed by these experiments with the MtnA promoter, indeed, involve some regulatory transaction between TFIID and MED (Marr, 2006).

The requirement for coactivator complexes mediating transcriptional responses to activators has been well documented. However, by using an inducible Drosophila gene as a model system, a previously unknown functional interaction has been uncovered between two coactivator complexes, TFIID and MED. In the absence of TAFs, the cell responds inappropriately to a metal stimulus. The cell synthesizes 50%–200% more mRNA from the MtnA gene than it does in the presence of the TAFs. The data suggest that at this gene, TFIID is recruited in an inactive state, a state that impedes initiation of transcription. It is believed that this sets up a checkpoint early in the initiation process to meter the RNA synthesis. The MED complex must be recruited to get past this checkpoint. It is postulated that the MED complex likely modifies TFIID, converting it to an active state. This could be accomplished either through one of the known enzymatic activities of MED, phosphorylating (cdk8) or ubiquitylating (MED8) TFIID subunits, or through some, as yet undetected, chaperone-like function that remodels TFIID into an active conformation. Not surprisingly then, in the absence of MED subunits the cell cannot mount an appropriate response to environmental signals. In fact, depletions of many of the MED subunits lead to <20% of the normal amount of mRNA. Unlike the uniform response to depletion of TAFs, the response to depletion of MEDs is much less uniform. One possibility is that the MED complex is more functionally and structurally diverse than TFIID. Indeed, alternative subcomplexes of MED have been purified biochemically, whereas no such subcomplexes of TFIID have been reported (Marr, 2006).

By analysis of three different Mtn genes, all of which are dependent on the same single activator, it was found, surprisingly, that there is a differential requirement of specific MED subunits at the three Mtn promoters. This is taken as evidence that, depending on the precise arrangement of cis elements and promoter context, the same activator can require different mediator subunits or modules to transmit its signals to the basal apparatus (Marr, 2006).

Interestingly, the kinase module of the MED complex, previously linked with repression functions, is required for efficient activation at two of the promoters. This result, combined with the finding that at the MtnA promoter the TAFs have a repressive regulatory influence on transcription initiation, underscores the difficulty in assigning black and white functions to the coactivator complexes. It is likely that both TFIID and MED interpret multiple inputs from cellular signals and act either positively or negatively depending on the signals received as well as the specific promoter context. As such, the complexes may better be viewed as coregulators since they can play either a positive or negative role in the process of modulating gene expression. For example, only when both TFIID and MED are intact do Drosophila S2 cells produce the appropriate amounts of MtnA mRNA. In contrast, when either coactivator complex is disrupted, aberrant levels of transcription are seen. However, when both coactivator complexes are depleted, a significant level of metal inducible activation is actually restored. Presumably, in this 'stripped down' system, some portion of the remaining TBP pool can mediate transcription. Curiously, in the absence of TAFs but with a full complement of MEDs, there is also an aberrant level of transcription consistent with the notion that there is some finely tuned codependence between the TBP/TAF complex and the MED complex at this promoter (Marr, 2006).

The results also reinforce the notion that the activator is the primary determinant of the transcriptional response. The MTF-1 depletion experiments were the most detrimental to mRNA induction. In the absence of MTF-1, there is no detectable activation of the Mtn genes. In contrast, there is some residual transcription of MtnA even when either the MEDs or TBP are largely depleted from the Drosophila cells. This remaining activity could be due to incomplete depletion, or it could indicate alternative mechanisms of activation that are activator-dependent but can partially bypass the requirement for the coregulator complexes (Marr, 2006).

In the course of testing the requirement for TAFs in activated transcription, the codependent stability of the TFIID complex was discovered. Particularly striking is the finding that TAF4 depletion destabilizes most of the other TAFs and, to some extent, even TBP. Therefore, the TAF depletion experiments most likely reflect a loss of holo-TFIID rather than just the loss of individual subunits. It is worth noting that metazoan organisms contain multiple variants of TAF4: TAF4b in vertebrates and No-hitter in Drosophila. Both of these have been implicated in tissue-specific gene expression. It is conceivable that substitution of this keystone TAF can provide a mechanism to change the entire coregulator profile of TFIID (Marr, 2006).

One intriguing question this work raises is: Why would an activator recruit an inactive TFIID complex to the promoter? There are several previously described cases in which TFIID occupancy at a promoter does not strictly correlate with transcriptional activity. However, in most of these cases the genes being examined were either in a repressed or an unstimulated state. In contrast, the current studies were designed to specifically measure the role of coactivator complexes such as TFIID and MED in the context of an active gene MtnA upon metal stimulation. The ability to deplete MED activity under these conditions revealed the unexpected finding that although TFIID is dynamically recruited to the MtnA promoter, TFIID is mainly held in an 'inactive' state until the second cofactor complex, MED, is recruited. Perhaps this recruitment of an 'inactive' TFIID is a more common phenomenon that can only be detected in special circumstances and may represent a previously unappreciated control mechanism in transcription activation. If the activator first recruits TFIID, then subsequently recruits MED, and there is a requirement for additional factors to potentiate the secondary recruitment of coregulator assemblies, then this provides a potential checkpoint for fine-tuning the control of gene expression. Alternatively, since the cell invests a significant amount of energy in making a high level of transcript, requirement of continued stimulation (i.e., activator bound at the promoter) for mRNA production would provide the most economical use of resources (Marr, 2006).

The presence of general transcription factors and other coactivators at the Drosophila hsp70 gene promoter in vivo has been examined by polytene chromosome immunofluorescence and chromatin immunoprecipitation at endogenous heat-shock loci or at a hsp70 promoter-containing transgene. These studies indicate that the hsp70 promoter is already occupied by TATA-binding protein (TBP) and several TBP-associated factors (TAFs), TFIIB, TFIIF (RAP30), TFIIH (XPB), TBP-free/TAF-containg complex (GCN5 and TRRAP), and the Mediator complex subunit 13 before heat shock. After heat shock, there is a significant recruitment of the heat-shock transcription factor, RNA polymerase II, XPD, GCN5, TRRAP, or Mediator complex 13 to the hsp70 promoter. Surprisingly, upon heat shock, there is a marked diminution in the occupancy of TBP, six different TAFs, TFIIB, and TFIIF, whereas there is no change in the occupancy of these factors at ecdysone-induced loci under the same conditions. Hence, these findings reveal a distinct mechanism of transcriptional induction at the hsp70 promoters, and further indicate that the apparent promoter occupancy of the general transcriptional factors does not necessarily reflect the transcriptional state of a gene (Lebedeva, 2005; full text of article).

An inverse correlation was observed between factor occupancy and transcriptional activation. In the absence of heat shock, it was found that TBP, TAFs, TFIIB, TFIIF, TFIIH, TFTC, and Mediator are present at the hsp70 promoter region. These results are similar to previous observations in which the basal factors have been found to be present at transcriptionally inactive promoters. Surprisingly, however, the apparent occupancy of TBP, several TAFs, TFIIB, and TFIIF significantly decreases upon transcriptional activation. These results could be due to some of the following scenarios: (1) upon activation, the undetected factors are present but adopt a conformation that renders them refractory to polytene chromosome staining and to ChIP analysis; (2) the factors that are not detected are indeed absent and do not participate in the ongoing transcription of the genes; or (3) the factors are present only transiently at the actively transcribed promoter and thus exhibit lower average occupancy upon polytene chromosome staining and ChIP analysis (Lebedeva, 2005).

The first scenario requires that TBP, several TAFs, TFIIB, and TFIIF simultaneously become essentially invisible to polytene immunostaining as well as to ChIP analysis upon transcriptional activation of hsp70 and other heat-shock genes. The observed effects are not a consequence of the heat shock treatment, because these factors are observed at ecdysone-responsive genes that have been subjected to heat shock. Moreover, for several factors (TBP, TAF1, and TAF10), the immunostaining was repeated with two different polyclonal antibodies that were raised against different epitopes, and identical results were obtained after heat-shock treatment. Furthermore, histone H3 K14 acetylation was detected at the hsp70 promoter after heat shock. Thus, the conditions allow the access of antibodies to proteins that are in close proximity to hsp70 promoter DNA. Thus, given that these experiments involve the use of many highly specific polyclonal antibodies and that the effect is observed with multiple polypeptides and is not a consequence of the heat-shock treatment, the first model appears to be unlikely (Lebedeva, 2005).

In the second scenario, TBP, several TAFs, TFIIB, and TFIIF do not participate in the ongoing transcription of heat-shock genes after heat induction. For instance, the factors required for transcription reinitiation may be a subset of those that participate in the first round of transcription. In fact, biochemical studies in yeast have shown that some, but not all, GTFs remain at the promoter after initiation and form a platform for the assembly of subsequent reinitiation complexes. This subset of factors includes TBP, TAF5, TFIIA, TFIIH, TFIIE, and Mediator, but not TFIIB or TFIIF. In accord with those results, this stydy found that TFIIH (XPB subunit) and Mediator (MED13), but not TFIIB or TFIIF remain at the hsp70 promoter after heat induction. In contrast, the apparent occupancy of TFIID (TBP, TAF1, and several other TAFs) is significantly reduced upon heat shock. Thus, for the second scenario to be correct, TBP and several TAFs must be dispensable for transcription reinitiation from heat-induced hsp70 promoters (Lebedeva, 2005).

In the third scenario, the average occupancy of the basal transcription factors at the hsp70 promoters is higher in the inactive gene than in the transcriptionally induced gene. This situation could occur if the basal transcription factors are in a static complex at the inactive hsp70 promoter and in a rapid cycling state of preinitiation-complex assembly and disassembly at the transcriptionally active hsp70 promoter. More specifically, in vivo data in the context of the third scenario suggest that TBP, several TAFs, TFIIB, and TFIIF make a transition from a static state to a rapidly cycling state upon heat-shock induction (Lebedeva, 2005).

It should be considered that the latter two scenarios might appear to be inconsistent with in vivo KMnO₄ footprinting data, which suggest that TFIID binds to the Drosophila hsp70 promoters both before and after heat shock. In this regard, it should be noted that ChIP (as well as immunofluorescence) and footprinting experiments yield distinct types of information. ChIP provides data regarding the occupancy of a particular factor at a specific DNA sequence but does not indicate how the factor interacts with DNA or if the factor is biochemically active. Moreover, in some instances, specific DNA-bound factors may not be detectable by ChIP (although, as discussed above, it is unlikely that multiple subunits of a protein complex, such as TFIID, would be invisible in a ChIP assay with multiple polyclonal antibodies). In vivo footprinting, however, shows that a factor is bound to a specific DNA sequence but does not indicate exactly what factor is bound to that sequence. Therefore, the models and data are not necessarily contradictory. For example, it is possible that the factor that is responsible for the TATA footprint in the induced gene is not TBP or TFIID but rather another protein, such as a TBP-related factor, or a TFTC/STAGA-type complex. Alternatively, an induced hsp70 promoter might not contain the complete TFIID complex but rather only a subcomplex or TBP alone that is in a ChIP-invisible state, possibly hidden under other proteins, such as the polymerase. At the present time, however, the resolution of these issues will require the development of more sophisticated assays for the analysis of the functions of transcription factors in vivo (Lebedeva, 2005).

Thus, a model for the activation of hsp70 genes is as follows. First, the inactive gene contains many GTFs (such as TFIIB, TFIID, TFIIF, and TFIIH) as well as the downstream paused RNA Pol II. Upon heat induction, HSF binds to the promoter and recruits coactivators, such as Mediator and SAGA complexes, and these factors promote the release of the paused polymerase and the assembly of a new transcription preinitiation complex. After initiation, the transcription complex might partially disassemble, at which point factors such as TFIIB and TFIID (or many TFIID subunits) dissociate from the template DNA. (TFIIF may remain associated with the elongating polymerase and thus depart the promoter region.) Then, in subsequent rounds of initiation (i.e., reinitiation), the reassociation of TFIIB and TFIID with the template may be fleeting with a low residence time at the promoter (the third scenario described above). Alternatively, TFIIB and TFIID may be dispensable for reinitiation (the second scenario described above). TFIIH, in contrast, is needed to unwind the template DNA for every new round of transcription; thus, the average occupancy of TFIIH at the promoter increases along with the polymerase in proportion to the number of transcription reinitiation events. Thus, upon heat induction, an increase would be observed in HSF, Mediator, SAGA/TFTC, TFIIH, and RNA Pol II as well as a decrease in TFIIB, TFIID (or many TFIID subunits), and TFIIF at the promoter (Lebedeva, 2005).

The specific mechanism of transcriptional activation by HSF at heat shock genes is likely to be one of multiple mechanisms of regulation that are used in vivo. For example, in contrast to what is seen at the hsp70 promoters, the apparent occupancy of TBP, TFIIB, and several TAFs at ecdysone-responsive promoters does not decrease upon transcriptional induction, even if the cells are also subjected to heat shock (Lebedeva, 2005).

In conclusion, these results with the hsp70 promoters provide an example of a transcriptional mechanism wherein the apparent occupancy of TBP, several TAFs, TFIIB, and TFIIF decreases upon gene activation. Therefore, the extent of the apparent occupancy of these factors at a given promoter does not necessarily reflect the transcriptional activity of that promoter. The discovery and analysis of distinct transcriptional mechanisms is a key step toward the ultimate goal of understanding all of many strategies that are used by the cell to control gene activity (Lebedeva, 2005).

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