ReFeaFi: Genome-wide prediction of regulatory elements driving transcription initiation.
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ABSTRACT:
SUBMITTER: Umarov R
PROVIDER: S-EPMC8448322 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Self-transcribing active regulatory region sequencing (STARR-seq) is widely used to identify enhancers at the whole-genome level. However, whether STARR-seq works as efficiently in plants as in animal systems remains unclear. Here, we determined that the traditional STARR-seq method can be directly applied to rice (Oryza sativa) protoplasts to identify enhancers, though with limited efficiency. Intriguingly, we identified not only enhancers but also constitutive promoters with this technique. To increase the performance of STARR-seq in plants, we optimized two procedures. We coupled fluorescence activating cell sorting (FACS) with STARR-seq to alleviate the effect of background noise, and we minimized PCR cycles and retained duplicates during prediction, which significantly increased the positive rate for activating regulatory elements (AREs). Using this method, we determined that AREs are associated with AT-rich regions and are enriched for a motif that the AP2/ERF family can recognize. Based on GC content preferences, AREs are clustered into two groups corresponding to promoters and enhancers. Either AT- or GC-rich regions within AREs could boost transcription. Additionally, disruption of AREs resulted in abnormal expression of both proximal and distal genes, which suggests that STARR-seq-revealed elements function as enhancers in vivo. In summary, our work provides a promising method to identify AREs in plants.
| S-EPMC9674312 | biostudies-literature
Project description:The interactions between transcription factors (TFs) and cis-acting regulatory elements (CREs) provide crucial information on the regulation of gene expression. The determination of TF-binding sites and CREs experimentally is costly and time intensive. An in silico identification and annotation of TFs, and the prediction of CREs from rice are made possible by the availability of whole genome sequence and transcriptome data. In this study, we tested the applicability of two algorithms developed for other model systems for the identification of biologically significant CREs of co-expressed genes from rice. CREs were identified from the DNA sequences located upstream from the transcription start sites, untranslated regions (UTRs), and introns, and downstream from the translational stop codons of co-expressed genes. The biologically significance of each CRE was determined by correlating their absence and presence in each gene with that gene's expression profile using a meta-database constructed from 50 rice microarray data sets. The reliability of these methods in the predictions of CREs and their corresponding TFs was supported by previous wet lab experimental data and a literature review. New CREs corresponding to abiotic stresses, biotic stresses, specific tissues, and developmental stages were identified from rice, revealing new pieces of information for future experimental testing. The effectiveness of some-but not all-CREs was found to be affected by copy number, position, and orientation. The corresponding TFs that were most likely correlated with each CRE were also identified. These findings not only contribute to the prioritization of candidates for further analysis, the information also contributes to the understanding of the gene regulatory network.
| S-EPMC6918188 | biostudies-literature
Project description:A current goal of molecular biology is to identify transcriptional networks that regulate cell differentiation. However, identifying functional gene regulatory elements has been challenging in the context of developing tissues where material is limited and cell types are mixed. To identify regulatory sites during sex determination, we subjected Sertoli cells from mouse fetal testes to DNaseI-seq and ChIP-seq for H3K27ac. DNaseI-seq identified putative regulatory sites around genes enriched in Sertoli and pregranulosa cells; however, active enhancers marked by H3K27ac were enriched proximal to only Sertoli-enriched genes. Sequence analysis identified putative binding sites of known and novel transcription factors likely controlling Sertoli cell differentiation. As a validation of this approach, we identified a novel Sertoli cell enhancer upstream of Wt1, and used it to drive expression of a transgenic reporter in Sertoli cells. This work furthers our understanding of the complex genetic network that underlies sex determination and identifies regions that potentially harbor non-coding mutations underlying disorders of sexual development.
| S-EPMC5312035 | biostudies-literature
Project description:BackgroundA complete understanding of the regulatory mechanisms of gene expression is the next important issue of genomics. Many bioinformaticians have developed methods and algorithms for predicting transcriptional regulatory mechanisms from sequence, gene expression, and binding data. However, most of these studies involved the use of yeast which has much simpler regulatory networks than human and has many genome wide binding data and gene expression data under diverse conditions. Studies of genome wide transcriptional networks of human genomes currently lag behind those of yeast.ResultsWe report herein a new method that combines gene expression data analysis with promoter analysis to infer transcriptional regulatory elements of human genes. The Z scores from the application of gene set analysis with gene sets of transcription factor binding sites (TFBSs) were successfully used to represent the activity of TFBSs in a given microarray data set. A significant correlation between the Z scores of gene sets of TFBSs and individual genes across multiple conditions permitted successful identification of many known human transcriptional regulatory elements of genes as well as the prediction of numerous putative TFBSs of many genes which will constitute a good starting point for further experiments. Using Z scores of gene sets of TFBSs produced better predictions than the use of mRNA levels of a transcription factor itself, suggesting that the Z scores of gene sets of TFBSs better represent diverse mechanisms for changing the activity of transcription factors in the cell. In addition, cis-regulatory modules, combinations of co-acting TFBSs, were readily identified by our analysis.ConclusionBy a strategic combination of gene set level analysis of gene expression data sets and promoter analysis, we were able to identify and predict many transcriptional regulatory elements of human genes. We conclude that this approach will aid in decoding some of the important transcriptional regulatory elements of human genes.
| S-EPMC1586028 | biostudies-literature
Project description: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.
| S-EPMC5741056 | biostudies-literature
Project description:DNA methylation in repetitive elements (RE) suppresses their mobility and maintains genomic stability, and decreases in it are frequently observed in tumor and/or surrogate tissues. Averaging methylation across RE in genome is widely used to quantify global methylation. However, methylation may vary in specific RE and play diverse roles in disease development, thus averaging methylation across RE may lose significant biological information. The ambiguous mapping of short reads by and high cost of current bisulfite sequencing platforms make them impractical for quantifying locus-specific RE methylation. Although microarray-based approaches (particularly Illumina's Infinium methylation arrays) provide cost-effective and robust genome-wide methylation quantification, the number of interrogated CpGs in RE remains limited. We report a random forest-based algorithm (and corresponding R package, REMP) that can accurately predict genome-wide locus-specific RE methylation based on Infinium array profiling data. We validated its prediction performance using alternative sequencing and microarray data. Testing its clinical utility with The Cancer Genome Atlas data demonstrated that our algorithm offers more comprehensively extended locus-specific RE methylation information that can be readily applied to large human studies in a cost-effective manner. Our work has the potential to improve our understanding of the role of global methylation in human diseases, especially cancer.
| S-EPMC5587781 | biostudies-literature
Project description:Analysis of the human genome sequence has identified approximately 25000-30000 protein-coding genes, but little is known about how most of these are regulated. Mapping DNase I hypersensitive (HS) sites has traditionally represented the gold-standard experimental method for identifying regulatory elements, but the labor-intensive nature of this technique has limited its application to only a small number of human genes. We have developed a protocol to generate a genome-wide library of gene regulatory sequences by cloning DNase HS sites. We generated a library of DNase HS sites from quiescent primary human CD4(+) T cells and analyzed approximately 5600 of the resulting clones. Compared to sequences from randomly generated in silico libraries, sequences from these clones were found to map more frequently to regions of the genome known to contain regulatory elements, such as regions upstream of genes, within CpG islands, and in sequences that align between mouse and human. These cloned sites also tend to map near genes that have detectable transcripts in CD4(+) T cells, demonstrating that transcriptionally active regions of the genome are being selected. Validation of putative regulatory elements was achieved by repeated recovery of the same sequence and real-time PCR. This cloning strategy, which can be scaled up and applied to any cell line or tissue, will be useful in identifying regulatory elements controlling global expression differences that delineate tissue types, stages of development, and disease susceptibility.
| S-EPMC327130 | biostudies-other
Project description:Transcription initiation is orchestrated by dynamic molecular interactions, with kinetic steps difficult to detect. Utilizing a hybrid method, we aim to unravel essential kinetic steps of transcriptional regulation on the glnAp2 promoter, whose regulatory region includes two enhancers (sites I and II) and three low-affinity sequences (sites III-V), to which the transcriptional activator NtrC binds. By structure reconstruction, we analyze all possible organization architectures of the transcription apparatus (TA). The main regulatory mode involves two NtrC hexamers: one at enhancer II transiently associates with site V such that the other at enhancer I can rapidly approach and catalyze the σ54-RNA polymerase holoenzyme. We build a kinetic model characterizing essential steps of the TA operation; with the known kinetics of the holoenzyme interacting with DNA, this model enables the kinetics beyond technical detection to be determined by fitting the input-output function of the wild-type promoter. The model further quantitatively reproduces transcriptional activities of various mutated promoters. These results reveal different roles played by two enhancers and interpret why the low-affinity elements conditionally enhance or repress transcription. This work presents an integrated dynamic picture of regulated transcription initiation and suggests an evolutionarily conserved characteristic guaranteeing reliable transcriptional response to regulatory signals.
| S-EPMC5159524 | biostudies-literature
Project description:Inter-individual variation in gene regulatory elements is hypothesized to play a causative role in adverse drug reactions and reduced drug activity. However, relatively little is known about the location and function of drug-dependent elements. To uncover drug-associated elements in a genome-wide manner, we performed RNA-seq and ChIP-seq using antibodies against the pregnane X receptor (PXR) and three active regulatory marks (p300, H3K4me1, H3K27ac) on primary human hepatocytes treated with rifampin or vehicle control. Rifampin and PXR were chosen since they are part of the CYP3A4 pathway, which is known to account for the metabolism of more than 50% of all prescribed drugs. We selected 227 proximal promoters for genes with rifampin-dependent expression or nearby PXR/p300 occupancy sites and assayed their ability to induce luciferase in rifampin-treated HepG2 cells, finding only 10 (4.4%) that exhibited drug-dependent activity. As this result suggested a role for distal enhancer modules, we searched more broadly to identify 1,297 genomic regions bearing a conditional PXR occupancy as well as all three active regulatory marks. These regions are enriched near genes that function in the metabolism of xenobiotics, specifically members of the cytochrome P450 family. We performed enhancer assays in rifampin-treated HepG2 cells for 42 of these sequences as well as 7 sequences that overlap linkage-disequilibrium blocks defined by lead SNPs from pharmacogenomic GWAS studies, revealing 15/42 and 4/7 to be functional enhancers, respectively. A common African haplotype in one of these enhancers in the GSTA locus was found to exhibit potential rifampin hypersensitivity. Combined, our results further suggest that enhancers are the predominant targets of rifampin-induced PXR activation, provide a genome-wide catalog of PXR targets and serve as a model for the identification of drug-responsive regulatory elements.
| S-EPMC4183418 | biostudies-literature
Project description:Genome-wide transcription start site (TSS) profiles of the enterobacteria Escherichia coli and Klebsiella pneumoniae were experimentally determined through modified 5' RACE followed by deep sequencing of intact primary mRNA. This identified 3,746 and 3,143 TSSs for E. coli and K. pneumoniae, respectively. Experimentally determined TSSs were then used to define promoter regions and 5' UTRs upstream of coding genes. Comparative analysis of these regulatory elements revealed the use of multiple TSSs, identical sequence motifs of promoter and Shine-Dalgarno sequence, reflecting conserved gene expression apparatuses between the two species. In both species, over 70% of primary transcripts were expressed from operons having orthologous genes during exponential growth. However, expressed orthologous genes in E. coli and K. pneumoniae showed a strikingly different organization of upstream regulatory regions with only 20% identical promoters with TSSs in both species. Over 40% of promoters had TSSs identified in only one species, despite conserved promoter sequences existing in the other species. 662 conserved promoters having TSSs in both species resulted in the same number of comparable 5' UTR pairs, and that regulatory element was found to be the most variant region in sequence among promoter, 5' UTR, and ORF. In K. pneumoniae, 48 sRNAs were predicted and 36 of them were expressed during exponential growth. Among them, 34 orthologous sRNAs between two species were analyzed in depth, and the analysis showed that many sRNAs of K. pneumoniae, including pleiotropic sRNAs such as rprA, arcZ, and sgrS, may work in the same way as in E. coli. These results reveal a new dimension of comparative genomics such that a comparison of two genomes needs to be comprehensive over all levels of genome organization.
| S-EPMC3415461 | biostudies-literature