Putative Cis-regulatory Modules Research Articles

Integrative multi-omics increase resolution of the sea urchin posterior gut gene regulatory network at single cell level.

Drafting gene regulatory networks (GRNs) requires embryological knowledge pertaining to the cell type families, information on the regulatory genes, causal data from gene knockdown experiments and validations of the identified interactions by cis-regulatory analysis. We use multi-omics involving next-generation sequencing (-seq) to obtain the necessary information for drafting Strongylocentrotus purpuratus posterior gut GRN. Here we present an update to the GRN using i) a single cell RNA-seq derived cell atlas highlighting the 2 day post fertilization (dpf) sea urchin gastrula cell type families, as well as the genes expressed at single cell level, ii) a set of putative cis-regulatory modules and transcription factor (TF) binding sites obtained from chromatin accessibility ATAC-seq data, and iii) interactions directionality obtained from differential bulk RNA-seq following knockdown of the TF Sp-Pdx1, a key regulator of gut patterning in sea urchins. Combining these datasets, we draft the GRN for the hindgut Sp-Pdx1 positive cells in the 2 dpf gastrula embryo. Overall, our data suggests the complex connectivity of the posterior gut GRN and increases the resolution of gene regulatory cascades operating within it.

Genome-wide discovery of active regulatory elements and transcription factor footprints in Caenorhabditis elegans using DNase-seq.

Deep sequencing of size-selected DNase I–treated chromatin (DNase-seq) allows high-resolution measurement of chromatin accessibility to DNase I cleavage, permitting identification of de novo active cis-regulatory modules (CRMs) and individual transcription factor (TF) binding sites. We adapted DNase-seq to nuclei isolated from C. elegans embryos and L1 arrest larvae to generate high-resolution maps of TF binding. Over half of embryonic DNase I hypersensitive sites (DHSs) were annotated as noncoding, with 24% in intergenic, 12% in promoters, and 28% in introns, with similar statistics observed in L1 arrest larvae. Noncoding DHSs are highly conserved and enriched in marks of enhancer activity and transcription. We validated noncoding DHSs against known enhancers from myo-2, myo-3, hlh-1, elt-2, and lin-26/lir-1 and recapitulated 15 of 17 known enhancers. We then mined DNase-seq data to identify putative active CRMs and TF footprints. Using DNase-seq data improved predictions of tissue-specific expression compared with motifs alone. In a pilot functional test, 10 of 15 DHSs from pha-4, icl-1, and ceh-13 drove reporter gene expression in transgenic C. elegans. Overall, we provide experimental annotation of 26,644 putative CRMs in the embryo containing 55,890 TF footprints, as well as 15,841 putative CRMs in the L1 arrest larvae containing 32,685 TF footprints.

Characterization of a new Gsx2-cre line in the developing mouse telencephalon.

In this study, we generated a transgenic mouse line driving Cre and EGFP expression with two putative cis-regulatory modules (CRMs) (i.e., hs687 and hs678) upstream of the homeobox gene Gsx2 (formerly Gsh2), a critical gene for establishing lateral ganglionic eminence (LGE) identity. The combination of these two CRMs drives transgene expression within the endogenous Gsx2 expression domains along the anterior-posterior neuraxis. By crossing this transgenic line with the RosatdTomato (Ai14) reporter mouse line, we observed a unique recombination pattern in the lateral ventral telencephalon, namely the LGE and the dorsal half of the medial GE (MGE), but not in the septum. We found robust recombination in many cell types derived from these embryonic regions, including olfactory bulb and amygdala interneurons and striatal projection neurons from the LGE, as well as cortical interneurons from the MGE and caudal GE (CGE). In summary, this transgenic mouse line represents a new tool for genetic manipulation in the LGE/CGE and the dorsal half of MGE.

MyoD reprogramming requires Six1 and Six4 homeoproteins: genome-wide cis-regulatory module analysis.

Myogenic regulatory factors of the MyoD family have the ability to reprogram differentiated cells toward a myogenic fate. In this study, we demonstrate that Six1 or Six4 are required for the reprogramming by MyoD of mouse embryonic fibroblasts (MEFs). Using microarray experiments, we found 761 genes under the control of both Six and MyoD. Using MyoD ChIPseq data and a genome-wide search for Six1/4 MEF3 binding sites, we found significant co-localization of binding sites for MyoD and Six proteins on over a thousand mouse genomic DNA regions. The combination of both datasets yielded 82 genes which are synergistically activated by Six and MyoD, with 96 associated MyoD+MEF3 putative cis-regulatory modules (CRMs). Fourteen out of 19 of the CRMs that we tested demonstrated in Luciferase assays a synergistic action also observed for their cognate gene. We searched putative binding sites on these CRMs using available databases and de novo search of conserved motifs and demonstrated that the Six/MyoD synergistic activation takes place in a feedforward way. It involves the recruitment of these two families of transcription factors to their targets, together with partner transcription factors, encoded by genes that are themselves activated by Six and MyoD, including Mef2, Pbx-Meis and EBF.

The analysis of novel distal Cebpa enhancers and silencers using a transcriptional model reveals the complex regulatory logic of hematopoietic lineage specification

C/EBPα plays an instructive role in the macrophage-neutrophil cell-fate decision and its expression is necessary for neutrophil development. How Cebpa itself is regulated in the myeloid lineage is not known. We decoded the cis-regulatory logic of Cebpa, and two other myeloid transcription factors, Egr1 and Egr2, using a combined experimental-computational approach. With a reporter design capable of detecting both distal enhancers and silencers, we analyzed 46 putative cis-regulatory modules (CRMs) in cells representing myeloid progenitors, and derived early macrophages or neutrophils. In addition to novel enhancers, this analysis revealed a surprisingly large number of silencers. We determined the regulatory roles of 15 potential transcriptional regulators by testing 32,768 alternative sequence-based transcriptional models against CRM activity data. This comprehensive analysis allowed us to infer the cis-regulatory logic for most of the CRMs. Silencer-mediated repression of Cebpa was found to be effected mainly by TFs expressed in non-myeloid lineages, highlighting a previously unappreciated contribution of long-distance silencing to hematopoietic lineage resolution. The repression of Cebpa by multiple factors expressed in alternative lineages suggests that hematopoietic genes are organized into densely interconnected repressive networks instead of hierarchies of mutually repressive pairs of pivotal TFs. More generally, our results demonstrate that de novo cis-regulatory dissection is feasible on a large scale with the aid of transcriptional modeling.1Current address: Department of Biology, University of North Dakota, 10 Cornell Street, Stop 9019, Grand Forks, ND 58202-9019, USA.

De novo prediction of cis-regulatory elements and modules through integrative analysis of a large number of ChIP datasets.

BackgroundIn eukaryotes, transcriptional regulation is usually mediated by interactions of multiple transcription factors (TFs) with their respective specific cis-regulatory elements (CREs) in the so-called cis-regulatory modules (CRMs) in DNA. Although the knowledge of CREs and CRMs in a genome is crucial to elucidate gene regulatory networks and understand many important biological phenomena, little is known about the CREs and CRMs in most eukaryotic genomes due to the difficulty to characterize them by either computational or traditional experimental methods. However, the exponentially increasing number of TF binding location data produced by the recent wide adaptation of chromatin immunoprecipitation coupled with microarray hybridization (ChIP-chip) or high-throughput sequencing (ChIP-seq) technologies has provided an unprecedented opportunity to identify CRMs and CREs in genomes. Nonetheless, how to effectively mine these large volumes of ChIP data to identify CREs and CRMs at nucleotide resolution is a highly challenging task.ResultsWe have developed a novel graph-theoretic based algorithm DePCRM for genome-wide de novo predictions of CREs and CRMs using a large number of ChIP datasets. DePCRM predicts CREs and CRMs by identifying overrepresented combinatorial CRE motif patterns in multiple ChIP datasets in an effective way. When applied to 168 ChIP datasets of 56 TFs from D. melanogaster, DePCRM identified 184 and 746 overrepresented CRE motifs and their combinatorial patterns, respectively, and predicted a total of 115,932 CRMs in the genome. The predictions recover 77.9% of known CRMs in the datasets and 89.3% of known CRMs containing at least one predicted CRE. We found that the putative CRMs as well as CREs as a whole in a CRM are more conserved than randomly selected sequences.ConclusionOur results suggest that the CRMs predicted by DePCRM are highly likely to be functional. Our algorithm is the first of its kind for de novo genome-wide prediction of CREs and CRMs using larger number of transcription factor ChIP datasets. The algorithm and predictions will hopefully facilitate the elucidation of gene regulatory networks in eukaryotes. All the predicted CREs, CRMs, and their target genes are available at http://bioinfo.uncc.edu/mniu/pcrms/www/.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-1047) contains supplementary material, which is available to authorized users.

Interrogating Transcriptional Regulatory Sequences in Tol2-Mediated Xenopus Transgenics

Identifying gene regulatory elements and their target genes in vertebrates remains a significant challenge. It is now recognized that transcriptional regulatory sequences are critical in orchestrating dynamic controls of tissue-specific gene expression during vertebrate development and in adult tissues, and that these elements can be positioned at great distances in relation to the promoters of the genes they control. While significant progress has been made in mapping DNA binding regions by combining chromatin immunoprecipitation and next generation sequencing, functional validation remains a limiting step in improving our ability to correlate in silico predictions with biological function. We recently developed a computational method that synergistically combines genome-wide gene-expression profiling, vertebrate genome comparisons, and transcription factor binding-site analysis to predict tissue-specific enhancers in the human genome. We applied this method to 270 genes highly expressed in skeletal muscle and predicted 190 putative cis-regulatory modules. Furthermore, we optimized Tol2 transgenic constructs in Xenopus laevis to interrogate 20 of these elements for their ability to function as skeletal muscle-specific transcriptional enhancers during embryonic development. We found 45% of these elements expressed only in the fast muscle fibers that are oriented in highly organized chevrons in the Xenopus laevis tadpole. Transcription factor binding site analysis identified >2 Mef2/MyoD sites within ∼200 bp regions in 6 of the validated enhancers, and systematic mutagenesis of these sites revealed that they are critical for the enhancer function. The data described herein introduces a new reporter system suitable for interrogating tissue-specific cis-regulatory elements which allows monitoring of enhancer activity in real time, throughout early stages of embryonic development, in Xenopus.

Transcriptional and epigenetic signatures of zygotic genome activation during early drosophila embryogenesis

BackgroundIn all Metazoa, transcription is inactive during the first mitotic cycles after fertilisation. In Drosophila melanogaster, Zygotic Genome Activation (ZGA) occurs in two waves, starting respectively at mitotic cycles 8 (approximately 60 genes) and 14 (over a thousand genes). The regulatory mechanisms underlying these drastic transcriptional changes remain largely unknown.ResultsWe developed an original gene clustering method based on discretized transition profiles, and applied it to datasets from three landmark early embryonic transcriptome studies. We identified 417 genes significantly up-regulated during ZGA. De novo motif discovery returned nine motifs over-represented in their non-coding sequences (upstream, introns, UTR), three of which correspond to previously known transcription factors: Zelda, Tramtrack and Trithorax-like (Trl). The nine discovered motifs were combined to scan ZGA-associated regions and predict about 1300 putative cis-regulatory modules. The fact that Trl is known to act as chromatin remodelling factor suggests that epigenetic regulation might play an important role in zygotic genome activation. We thus systematically compared the locations of predicted CRMs with ChIP-seq profiles for various transcription factors, 38 epigenetic marks from ModENCODE, and DNAse1 accessibility profiles. This analysis highlighted a strong and specific enrichment of predicted ZGA-associated CRMs for Zelda, CBP, Trl binding sites, as well as for histone marks associated with active enhancers (H3K4me1) and for open chromatin regions.ConclusionBased on the results of our computational analyses, we suggest a temporal model explaining the onset of zygotic genome activation by the combined action of transcription factors and epigenetic signals. Although this study is mainly based on the analysis of publicly available transcriptome and ChiP-seq datasets, the resulting model suggests novel mechanisms that underly the coordinated activation of several hundreds genes at a precise time point during embryonic development.

Distant cis-regulatory elements in human skeletal muscle differentiation

Identifying gene regulatory elements and their target genes in human cells remains a significant challenge. Despite increasing evidence of physical interactions between distant regulatory elements and gene promoters in mammalian cells, many studies consider only promoter-proximal regulatory regions. We identify putative cis-regulatory modules (CRMs) in human skeletal muscle differentiation by combining myogenic TF binding data before and after differentiation with histone modification data in myoblasts. CRMs that are distant (> 20 kb) from muscle gene promoters are common and are more likely than proximal promoter regions to show differentiation-specific changes in myogenic TF binding. We find that two of these distant CRMs, known to activate transcription in differentiating myoblasts, interact physically with gene promoters ( PDLIM3 and ACTA1) during differentiation. Our results highlight the importance of considering distal CRMs in investigations of mammalian gene regulation and support the hypothesis that distant CRM-promoter looping contacts are a general mechanism of gene regulation.

Alignment-free Sequence Comparison for Biologically Realistic Sequences of Moderate Length

The D(2) statistic, defined as the number of matches of words of some pre-specified length k, is a computationally fast alignment-free measure of biological sequence similarity. However there is some debate about its suitability for this purpose as the variability in D(2) may be dominated by the terms that reflect the noise in each of the single sequences only. We examine the extent of the problem and the effectiveness of overcoming it by using two mean-centred variants of this statistic, D(2)* and D(2c). We conclude that all three statistics are potentially useful measures of sequence similarity, for which reasonably accurate p-values can be estimated under a null hypothesis of sequences composed of identically and independently distributed letters. We show that D(2) and D(2)c, and to a somewhat lesser extent D(2)*, perform well in tests to classify moderate length query sequences as putative cis-regulatory modules.

Selective constraints in experimentally defined primate regulatory regions.

Changes in gene regulation may be important in evolution. However, the evolutionary properties of regulatory mutations are currently poorly understood. This is partly the result of an incomplete annotation of functional regulatory DNA in many species. For example, transcription factor binding sites (TFBSs), a major component of eukaryotic regulatory architecture, are typically short, degenerate, and therefore difficult to differentiate from randomly occurring, nonfunctional sequences. Furthermore, although sites such as TFBSs can be computationally predicted using evolutionary conservation as a criterion, estimates of the true level of selective constraint (defined as the fraction of strongly deleterious mutations occurring at a locus) in regulatory regions will, by definition, be upwardly biased in datasets that are a priori evolutionarily conserved. Here we investigate the fitness effects of regulatory mutations using two complementary datasets of human TFBSs that are likely to be relatively free of ascertainment bias with respect to evolutionary conservation but, importantly, are supported by experimental data. The first is a collection of almost >2,100 human TFBSs drawn from the literature in the TRANSFAC database, and the second is derived from several recent high-throughput chromatin immunoprecipitation coupled with genomic microarray (ChIP-chip) analyses. We also define a set of putative cis-regulatory modules (pCRMs) by spatially clustering multiple TFBSs that regulate the same gene. We find that a relatively high proportion (∼37%) of mutations at TFBSs are strongly deleterious, similar to that at a 2-fold degenerate protein-coding site. However, constraint is significantly reduced in human and chimpanzee pCRMS and ChIP-chip sequences, relative to macaques. We estimate that the fraction of regulatory mutations that have been driven to fixation by positive selection in humans is not significantly different from zero. We also find that the level of selective constraint in our TFBSs, pCRMs, and ChIP-chip sequences is negatively correlated with the expression breadth of the regulated gene, whereas the opposite relationship holds at that gene's nonsynonymous and synonymous sites. Finally, we find that the rate of protein evolution in a transcription factor appears to be positively correlated with the breadth of expression of the gene it regulates. Our study suggests that strongly deleterious regulatory mutations are considerably more likely (1.6-fold) to occur in tissue-specific than in housekeeping genes, implying that there is a fitness cost to increasing “complexity” of gene expression.

Studying the functional conservation of cis-regulatory modules and their transcriptional output

BackgroundCis-regulatory modules (CRMs) are distinct, genomic regions surrounding the target gene that can independently activate the promoter to drive transcription. The activation of a CRM is controlled by the binding of a certain combination of transcription factors (TFs). It would be of great benefit if the transcriptional output mediated by a specific CRM could be predicted. Of equal benefit would be identifying in silico a specific CRM as the driver of the expression in a specific tissue or situation. We extend a recently developed biochemical modeling approach to manage both prediction tasks. Given a set of TFs, their protein concentrations, and the positions and binding strengths of each of the TFs in a putative CRM, the model predicts the transcriptional output of the gene. Our approach predicts the location of the regulating CRM by using predicted TF binding sites in regions near the gene as input to the model and searching for the region that yields a predicted transcription rate most closely matching the known rate.ResultsHere we show the ability of the model on the example of one of the CRMs regulating the eve gene, MSE2. A model trained on the MSE2 in D. melanogaster was applied to the surrounding sequence of the eve gene in seven other Drosophila species. The model successfully predicts the correct MSE2 location and output in six out of eight Drosophila species we examine.ConclusionThe model is able to generalize from D. melanogaster to other Drosophila species and accurately predicts the location and transcriptional output of MSE2 in those species. However, we also show that the current model is not specific enough to function as a genome-wide CRM scanner, because it incorrectly predicts other genomic regions to be MSE2s.

Identification of tissue-specific cis-regulatory modules based on interactions between transcription factors

BackgroundEvolutionary conservation has been used successfully to help identify cis-acting DNA regions that are important in regulating tissue-specific gene expression. Motivated by increasing evidence that some DNA regulatory regions are not evolutionary conserved, we have developed an approach for cis-regulatory region identification that does not rely upon evolutionary sequence conservation.ResultsThe conservation-independent approach is based on an empirical potential energy between interacting transcription factors (TFs). In this analysis, the potential energy is defined as a function of the number of TF interactions in a genomic region and the strength of the interactions. By identifying sets of interacting TFs, the analysis locates regions enriched with the binding sites of these interacting TFs. We applied this approach to 30 human tissues and identified 6232 putative cis-regulatory modules (CRMs) regulating 2130 tissue-specific genes. Interestingly, some genes appear to be regulated by different CRMs in different tissues. Known regulatory regions are highly enriched in our predicted CRMs. In addition, DNase I hypersensitive sites, which tend to be associated with active regulatory regions, significantly overlap with the predicted CRMs, but not with more conserved regions. We also find that conserved and non-conserved CRMs regulate distinct gene groups. Conserved CRMs control more essential genes and genes involved in fundamental cellular activities such as transcription. In contrast, non-conserved CRMs, in general, regulate more non-essential genes, such as genes related to neural activity.ConclusionThese results demonstrate that identifying relevant sets of binding motifs can help in the mapping of DNA regulatory regions, and suggest that non-conserved CRMs play an important role in gene regulation.

Combinatorial Analysis of Transcription Factor Partners Reveals Recruitment of c-MYC to Estrogen Receptor-α Responsive Promoters

In breast cancer and normal estrogen target tissues, estrogen receptor-alpha (ERalpha) signaling results in the establishment of spatiotemporal patterns of gene expression. Whereas primary target gene regulation by ERalpha involves recruitment of coregulatory proteins, coactivators, or corepressors, activation of these downstream promoters by receptor signaling may also involve partnership of ERalpha with other transcription factors. By using an integrated, genome-wide approach that involves ChIP-chip and computational modeling, we uncovered 13 ERalpha-responsive promoters containing both ERalpha and c-MYC binding elements located within close proximity (13-214 bp) to each other. Estrogen stimulation enhanced the c-MYC-ERalpha interaction and facilitated the association of ERalpha, c-MYC, and the coactivator TRRAP with these estrogen-responsive promoters, resulting in chromatin remodeling and increased transcription. These results suggest that ERalpha and c-MYC physically interact to stabilize the ERalpha-coactivator complex, thereby permitting other signal transduction pathways to fine-tune estrogen-mediated signaling networks.

A Discriminative Model for Identifying Spatial cis-Regulatory Modules

Transcriptional regulation is mediated by the coordinated binding of transcription factors to the upstream regions of genes. In higher eukaryotes, the binding sites of cooperating transcription factors are organized into short sequence units, called cis-regulatory modules. In this paper, we propose a method for identifying modules of transcription factor binding sites in a set of co-regulated genes, using only the raw sequence data as input. Our method is based on a novel probabilistic model that describes the mechanism of cis-regulation, including the binding sites of cooperating transcription factors, the organization of these binding sites into short sequence modules, and the regulation of a gene by its modules. We show that our method is successful in discovering planted modules in simulated data and known modules in yeast. More importantly, we applied our method to a large collection of human gene sets and found 83 significant cis-regulatory modules, which included 36 known motifs and many novel ones. Thus, our results provide one of the first comprehensive compendiums of putative cis-regulatory modules in human.