Transcriptional Cis-regulatory Modules Research Articles

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

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

Impaired glucocorticoid receptor function attenuates herpes simplex virus 1 production during explant-induced reactivation from latency in female mice.

A correlation exists between stress and increased episodes of human alpha-herpes virus 1 reactivation from latency. Stress increases corticosteroid levels; consequently, the glucocorticoid receptor (GR) is activated. Recent studies concluded that a GR agonist, but not an antagonist, accelerates productive infection and reactivation from latency. Furthermore, GR and certain stress-induced transcription factors cooperatively transactivate promoters that drive the expression of infected cell protein 0 (ICP0), ICP4, and VP16. This study revealed female mice expressing a GR containing a serine to alanine mutation at position 229 (GRS229A) shed significantly lower levels of infectious virus during explant-induced reactivation compared to male GRS229A or wild-type parental C57BL/6 mice. Furthermore, female GRS229A mice contained fewer VP16 + TG neurons compared to male GRS229A mice or wild-type mice during the early stages of explant-induced reactivation from latency. Collectively, these studies revealed that GR transcriptional activity has female-specific effects, whereas male mice can compensate for the loss of GR transcriptional activation.

REDfly: An Integrated Knowledgebase for Insect Regulatory Genomics.

Simple SummaryUnderstanding how genes are regulated is a vital area of current biological research and a crucial adjunct to ongoing efforts to sequence entire genomes. Knowing the DNA sequences responsible for gene regulation—transcriptional cis-regulatory modules (CRMs, e.g., “enhancers”) and transcription factor binding sites (TFBSs)—is important for many areas of research including interpretation and validation of data developed by large-scale genomics projects, providing training data for machine-learning CRM-discovery methods, genome annotation, modeling gene-regulatory networks, studying the evolution of gene regulation, and numerous aspects of the basic biology of transcriptional regulation. Knowledge of insect CRMs is also an important step in developing biotechnology methods for control of insect disease vectors and for eliminating pathogen transmission. The REDfly (Regulatory Element Database for Fly) database integrates all of the available insect cis-regulatory information from multiple sources to provide a comprehensive collection of known regulatory elements. In this paper, we describe REDfly’s basic contents and data model, emphasizing recently added features, and provide illustrated walk-throughs of some common search scenarios.We provide here an updated description of the REDfly (Regulatory Element Database for Fly) database of transcriptional regulatory elements, a unique resource that provides regulatory annotation for the genome of Drosophila and other insects. The genomic sequences regulating insect gene expression—transcriptional cis-regulatory modules (CRMs, e.g., “enhancers”) and transcription factor binding sites (TFBSs)—are not currently curated by any other major database resources. However, knowledge of such sequences is important, as CRMs play critical roles with respect to disease as well as normal development, phenotypic variation, and evolution. Characterized CRMs also provide useful tools for both basic and applied research, including developing methods for insect control. REDfly, which is the most detailed existing platform for metazoan regulatory-element annotation, includes over 40,000 experimentally verified CRMs and TFBSs along with their DNA sequences, their associated genes, and the expression patterns they direct. Here, we briefly describe REDfly’s contents and data model, with an emphasis on the new features implemented since 2020. We then provide an illustrated walk-through of several common REDfly search use cases.

Intrinsic control of muscle attachment sites matching.

Myogenesis is an evolutionarily conserved process. Little known, however, is how the morphology of each muscle is determined, such that movements relying upon contraction of many muscles are both precise and coordinated. Each Drosophila larval muscle is a single multinucleated fibre whose morphology reflects expression of distinctive identity Transcription Factors (iTFs). By deleting transcription cis-regulatory modules of one iTF, Collier, we generated viable muscle identity mutants, allowing live imaging and locomotion assays. We show that both selection of muscle attachment sites and muscle/muscle matching is intrinsic to muscle identity and requires transcriptional reprogramming of syncytial nuclei. Live-imaging shows that the staggered muscle pattern involves attraction to tendon cells and heterotypic muscle-muscle adhesion. Unbalance leads to formation of branched muscles, and this correlates with locomotor behavior deficit. Thus, engineering Drosophila muscle identity mutants allows to investigate, in vivo, physiological and mechanical properties of abnormal muscles.

Next-generation muscle-directed gene therapy by in silico vector design

There is an urgent need to develop the next-generation vectors for gene therapy of muscle disorders, given the relatively modest advances in clinical trials. These vectors should express substantially higher levels of the therapeutic transgene, enabling the use of lower and safer vector doses. In the current study, we identify potent muscle-specific transcriptional cis-regulatory modules (CRMs), containing clusters of transcription factor binding sites, using a genome-wide data-mining strategy. These novel muscle-specific CRMs result in a substantial increase in muscle-specific gene transcription (up to 400-fold) when delivered using adeno-associated viral vectors in mice. Significantly higher and sustained human micro-dystrophin and follistatin expression levels are attained than when conventional promoters are used. This results in robust phenotypic correction in dystrophic mice, without triggering apoptosis or evoking an immune response. This multidisciplinary approach has potentially broad implications for augmenting the efficacy and safety of muscle-directed gene therapy.

Redeployment of a conserved gene regulatory network during Aedes aegypti development

Changes in gene regulatory networks (GRNs) underlie the evolution of morphological novelty and developmental system drift. The fruitfly Drosophila melanogaster and the dengue and Zika vector mosquito Aedes aegypti have substantially similar nervous system morphology. Nevertheless, they show significant divergence in a set of genes co-expressed in the midline of the Drosophila central nervous system, including the master regulator single minded and downstream genes including short gastrulation, Star, and NetrinA. In contrast to Drosophila, we find that midline expression of these genes is either absent or severely diminished in A. aegypti. Instead, they are co-expressed in the lateral nervous system. This suggests that in A. aegypti this “midline GRN” has been redeployed to a new location while lost from its previous site of activity. In order to characterize the relevant GRNs, we employed the SCRMshaw method we previously developed to identify transcriptional cis-regulatory modules in both species. Analysis of these regulatory sequences in transgenic Drosophila suggests that the altered gene expression observed in A. aegypti is the result of trans-dependent redeployment of the GRN, potentially stemming from cis-mediated changes in the expression of sim and other as-yet unidentified regulators. Our results illustrate a novel “repeal, replace, and redeploy” mode of evolution in which a conserved GRN acquires a different function at a new site while its original function is co-opted by a different GRN. This represents a striking example of developmental system drift in which the dramatic shift in gene expression does not result in gross morphological changes, but in more subtle differences in development and function of the late embryonic nervous system.

Computationally designed liver-specific transcriptional modules and hyperactive factor IX improve hepatic gene therapy

AbstractThe development of the next-generation gene therapy vectors for hemophilia requires using lower and thus potentially safer vector doses and augmenting their therapeutic efficacy. We have identified hepatocyte-specific transcriptional cis-regulatory modules (CRMs) by using a computational strategy that increased factor IX (FIX) levels 11- to 15-fold. Vector efficacy could be enhanced by combining these hepatocyte-specific CRMs with a synthetic codon-optimized hyperfunctional FIX-R338LPadua transgene. This Padua mutation boosted FIX activity up to sevenfold, with no apparent increase in thrombotic risk. We then validated this combination approach using self-complementary adenoassociated virus serotype 9 (scAAV9) vectors in hemophilia B mice. This resulted in sustained supraphysiologic FIX activity (400%), correction of the bleeding diathesis at clinically relevant, low vector doses (5 × 1010 vector genomes [vg]/kg) that are considered safe in patients undergoing gene therapy. Moreover, immune tolerance could be induced that precluded induction of inhibitory antibodies to FIX upon immunization with recombinant FIX protein.

Improved accuracy of supervised CRM discovery with interpolated Markov models and cross-species comparison

Despite recent advances in experimental approaches for identifying transcriptional cis-regulatory modules (CRMs, ‘enhancers’), direct empirical discovery of CRMs for all genes in all cell types and environmental conditions is likely to remain an elusive goal. Effective methods for computational CRM discovery are thus a critically needed complement to empirical approaches. However, existing computational methods that search for clusters of putative binding sites are ineffective if the relevant TFs and/or their binding specificities are unknown. Here, we provide a significantly improved method for ‘motif-blind’ CRM discovery that does not depend on knowledge or accurate prediction of TF-binding motifs and is effective when limited knowledge of functional CRMs is available to ‘supervise’ the search. We propose a new statistical method, based on ‘Interpolated Markov Models’, for motif-blind, genome-wide CRM discovery. It captures the statistical profile of variable length words in known CRMs of a regulatory network and finds candidate CRMs that match this profile. The method also uses orthologs of the known CRMs from closely related genomes. We perform in silico evaluation of predicted CRMs by assessing whether their neighboring genes are enriched for the expected expression patterns. This assessment uses a novel statistical test that extends the widely used Hypergeometric test of gene set enrichment to account for variability in intergenic lengths. We find that the new CRM prediction method is superior to existing methods. Finally, we experimentally validate 12 new CRM predictions by examining their regulatory activity in vivo in Drosophila; 10 of the tested CRMs were found to be functional, while 6 of the top 7 predictions showed the expected activity patterns. We make our program available as downloadable source code, and as a plugin for a genome browser installed on our servers.

Large-scale analysis of transcriptional cis-regulatory modules reveals both common features and distinct subclasses

Analysis of 280 experimentally-verified cis-regulatory modules from Drosophila reveal features both common to all and unique to distinct subclasses of modules.

(Re)modeling the transcriptional enhancer

Transcriptional cis-regulatory modules have a fundamental role in regulating eukaryotic gene expression. A new study shows how computational modeling can test hypotheses about how regulatory elements function, with results that challenge conventional views of their organization.

REDfly: a Regulatory Element Database for Drosophila

Bioinformatics studies of transcriptional regulation in the metazoa are significantly hindered by the absence of readily available data on large numbers of transcriptional cis-regulatory modules (CRMs). Even the richly annotated Drosophila melanogaster genome lacks extensive CRM information. We therefore present here a database of Drosophila CRMs curated from the literature complete with both DNA sequence and a searchable description of the gene expression pattern regulated by each CRM. This resource should greatly facilitate the development of computational approaches to CRM discovery as well as bioinformatics analyses of regulatory sequence properties and evolution.

Clusters of regulatory signals for RNA polymerase II transcription associated with Alu family repeats and CpG islands in human promoters

Primate genomes contain a very large number of short interspersed GC-rich repeats of the Alu family, which are abundant in introns and intergenic spacers but also present in 5′ flanking regions of genes enriched in binding motifs (BMs) for transcription factors and frequently containing CpG islands. Here we studied whether CpG islands located in promoters of human genes overlap with Alu repeats and with clusters of BMs for the zinc-finger transcription factors Sp1, estrogen receptor α, and YY1. The presence of estrogen-response elements in Alu was shown earlier and here we confirm the presence in the consensus Alu sequence of the binding sites for Sp1 and YY1. Analyzing >5000 promoters from the two databases we found that Alu sequences are underrepresented in promoters compared to introns and that ∼4% of CpG islands located within the −1000 to +200 segments of human promoters overlap with Alu repeats. Although this fraction was found to be lower for proximal segments of promoters (−500 to +100), our results indicate that a significant number (>1000) of all human genes may be controlled by Alu-associated CpG islands. Analysis of clustering of potential BMs for the indicated transcription factors within some promoters also suggests that the Alu family contributed to the evolution of transcription cis-regulatory modules in the human genome. It is important that among Alu sequences overlapping with CpG islands in promoters a large fraction of members of the old Alu subfamilies is found, suggesting extensive retroposon-assisted regulatory genome evolution during the divergence of the primates.

SCORE: a computational approach to the identification of cis-regulatory modules and target genes in whole-genome sequence data. Site clustering over random expectation.

A large fraction of the information content of metazoan genomes resides in the transcriptional and posttranscriptional cis-regulatory elements that collectively provide the blueprint for using the protein-coding capacity of the DNA, thus guiding the development and physiology of the entire organism. As successive whole-genome sequencing projects--including those of mice and humans--are completed, we have full access to the regulatory genome of yet another species. But our ability to decipher the cis-regulatory code, and hence to link genes into regulatory networks on a global scale, is currently very limited. Here we describe SCORE (Site Clustering Over Random Expectation), a computational method for identifying transcriptional cis-regulatory modules based on the fact that they often contain, in statistically improbable concentrations, multiple binding sites for the same transcription factor. We have carried out a Drosophila genomewide inventory of predicted binding sites for the Notch-regulated transcription factor Suppressor of Hairless [Su(H)] and found that the fly genome contains highly nonrandom clusterings of Su(H) sites over a broad range of sequence intervals. We found that the most statistically significant clusters are very heavily enriched in both known and logical targets of Su(H) binding and regulation. The utility of the SCORE approach was validated by in vivo experiments showing that proper expression of the novel gene Him in adult muscle precursor cells depends both on Su(H) gene activity and sequences that include a previously unstudied cluster of four Su(H) sites, indicating that Him is a likely direct target of Su(H).