Computational discovery of regulatory elements in a continuous expression space.
Ontology highlight
ABSTRACT:
SUBMITTER: Lajoie M
PROVIDER: S-EPMC4053739 | biostudies-literature | 2012 Nov
REPOSITORIES: biostudies-literature
Publications
Computational discovery of regulatory elements in a continuous expression space.
Lajoie Mathieu M Gascuel Olivier O Lefort Vincent V Bréhélin Laurent L
Genome biology 20121127 11
Approaches for regulatory element discovery from gene expression data usually rely on clustering algorithms to partition the data into clusters of co-expressed genes. Gene regulatory sequences are then mined to find overrepresented motifs in each cluster. However, this ad hoc partition rarely fits the biological reality. We propose a novel method called RED2 that avoids data clustering by estimating motif densities locally around each gene. We show that RED2 detects numerous motifs not detected ...[more]
Similar Datasets
Project description:Phylogenetic footprinting is a method for the discovery of regulatory elements in a set of orthologous regulatory regions from multiple species. It does so by identifying the best conserved motifs in those orthologous regions. We describe a computer algorithm designed specifically for this purpose, making use of the phylogenetic relationships among the sequences under study to make more accurate predictions. The program is guaranteed to report all sets of motifs with the lowest parsimony scores, calculated with respect to the phylogenetic tree relating the input species. We report the results of this algorithm on several data sets of interest. A large number of known functional binding sites are identified by our method, but we also find several highly conserved motifs for which no function is yet known.
| S-EPMC186562 | biostudies-literature
Project description:The discovery of cancer driver mutations is a fundamental goal in cancer research. While many cancer driver mutations have been discovered in the protein-coding genome, research into potential cancer drivers in the non-coding regions showed limited success so far. Here, we present a novel comprehensive framework Dr.Nod for detection of non-coding cis-regulatory candidate driver mutations that are associated with dysregulated gene expression using tissue-matched enhancer-gene annotations. Applying the framework to data from over 1500 tumours across eight tissues revealed a 4.4-fold enrichment of candidate driver mutations in regulatory regions of known cancer driver genes. An overarching conclusion that emerges is that the non-coding driver mutations contribute to cancer by significantly altering transcription factor binding sites, leading to upregulation of tissue-matched oncogenes and down-regulation of tumour-suppressor genes. Interestingly, more than half of the detected cancer-promoting non-coding regulatory driver mutations are over 20 kb distant from the cancer-associated genes they regulate. Our results show the importance of tissue-matched enhancer-gene maps, functional impact of mutations, and complex background mutagenesis model for the prediction of non-coding regulatory drivers. In conclusion, our study demonstrates that non-coding mutations in enhancers play a previously underappreciated role in cancer and dysregulation of clinically relevant target genes.
| S-EPMC9976879 | biostudies-literature
Project description:BackgroundAlgorithms that locate evolutionarily conserved sequences have become powerful tools for finding functional DNA elements, including transcription factor binding sites; however, most methods do not take advantage of an explicit model for the constrained evolution of functional DNA sequences.ResultsWe developed a probabilistic framework that combines an HKY85 model, which assigns probabilities to different base substitutions between species, and weight matrix models of transcription factor binding sites, which describe the probabilities of observing particular nucleotides at specific positions in the binding site. The method incorporates the phylogenies of the species under consideration and takes into account the position specific variation of transcription factor binding sites. Using our framework we assessed the suitability of alignments of genomic sequences from commonly used species as substrates for comparative genomic approaches to regulatory motif finding. We then applied this technique to Saccharomyces cerevisiae and related species by examining all possible six base pair DNA sequences (hexamers) and identifying sequences that are conserved in a significant number of promoters. By combining similar conserved hexamers we reconstructed known cis-regulatory motifs and made predictions of previously unidentified motifs. We tested one prediction experimentally, finding it to be a regulatory element involved in the transcriptional response to glucose.ConclusionThe experimental validation of a regulatory element prediction missed by other large-scale motif finding studies demonstrates that our approach is a useful addition to the current suite of tools for finding regulatory motifs.
| S-EPMC1525002 | biostudies-literature
Project description:Regulatory elements play an important role in the variability of individual responses to drug treatment. This has been established through studies on three classes of elements that regulate RNA and protein abundance: promoters, enhancers and microRNAs. Each of these elements, and genetic variants within them, are being characterized at an exponential pace by next-generation sequencing (NGS) technologies. In this review, we outline examples of how each class of element affects drug response via regulation of drug targets, transporters and enzymes. We also discuss the impact of NGS technologies such as chromatin immunoprecipitation sequencing (ChIP-Seq) and RNA sequencing (RNA-Seq), and the ramifications of new techniques such as high-throughput chromosome capture (Hi-C), chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) and massively parallel reporter assays (MPRA). NGS approaches are generating data faster than they can be analyzed, and new methods will be required to prioritize laboratory results before they are ready for the clinic. However, there is no doubt that these approaches will bring about a systems-level understanding of the interplay between genetic variants and drug response. An understanding of the importance of regulatory variants in pharmacogenomics will facilitate the identification of responders versus non-responders, the prevention of adverse effects and the optimization of therapies for individual patients.
| S-EPMC3506911 | biostudies-literature
Project description:Over the last two decades, advances in experimental and computational technologies have greatly facilitated genomic research. Next-generation sequencing technologies have made de novo sequencing of large genomes affordable, and powerful computational approaches have enabled accurate annotations of genomic DNA sequences. Charting functional regions in genomes must account for not only the coding sequences, but also noncoding RNAs, repetitive elements, chromatin states, epigenetic modifications, and gene regulatory elements. A mix of comparative genomics, high-throughput biological experiments, and machine learning approaches has played a major role in this truly global effort. Here we describe some of these approaches and provide an account of our current understanding of the complex landscape of the human genome. We also present overviews of different publicly available, large-scale experimental data sets and computational tools, which we hope will prove beneficial for researchers working with large and complex genomes.
| S-EPMC5885252 | biostudies-literature
Project description:Cis-regulatory elements control gene expression in time and space and their disruption can lead to pathologies. Reporter assays allow the functional validation of enhancers and other regulatory elements, and transgenic mice provide a powerful tool to study gene regulation in vivo. However, these experiments are time-consuming and inefficient. Here, we increase the throughput of transgenic reporter assays by using a piggyBac transposon-based system, and use it to decode the regulatory landscape of atrial fibrillation, a prevalent cardiac arrhythmia. We systematically interrogated ten human atrial fibrillation associated loci, finding five new cardiac-specific enhancers. We also connected novel genes to atrial fibrillation through genome editing and three-dimensional chromatin structure analysis. Of note, we identified a bivalent regulatory element in the second intron of the CAV1 gene at the 7q31 locus, differentially acting upon four genes. Our approach also detected negative regulatory elements such as an ubiquitous silencer in the 16q22 locus that regulates ZFHX3 and can outcompete heart enhancers. Our study characterizes the function of new genetic elements that might be of relevance for the better understanding of gene regulation in cardiac arrhythmias. Thus, we have established a new framework for the efficient dissection of the genetic contribution to common human diseases.
2024-10-31 | GSE180396 | GEO
Project description:ATP-binding cassette (ABC) membrane transporters determine the disposition of many drugs, metabolites and endogenous compounds. Coding region variation in ABC transporters is the cause of many genetic disorders, but much less is known about the genetic basis and functional outcome of ABC transporter expression level variation. We used genotype and mRNA transcript level data from human lymphoblastoid cell lines to assess population and gender differences in ABC transporter expression, and to guide the discovery of genomic regions involved in transcriptional regulation. Nineteen of 49 ABC genes were differentially expressed between individuals of African, Asian and European descent, suggesting an important influence of race on expression level of ABC transporters. Twenty-four significant associations were found between transporter transcript levels and proximally located genetic variants. Several of the associations were experimentally validated in reporter assays. Through influencing ABC expression levels, these single-nucleotide polymorphisms may affect disease susceptibility and response to drugs.
| S-EPMC3325368 | biostudies-literature
Project description:Post-transcriptional gene regulation controls the amount of protein produced from an individual mRNA by altering rates of decay and translation. Many sequence elements that direct post-transcriptional regulation have been found; in mammals, most such elements are located within the 3' untranslated regions (3'UTRs). Comparative genomic studies demonstrate that mammalian 3'UTRs contain extensive conserved sequence tracts, yet only a small fraction corresponds to recognized elements, implying that many additional novel elements exist. Despite a variety of computational, molecular, and biochemical approaches, identifying functional 3'UTRs elements remains difficult.We created a high-throughput cell-based screen that enables identification of functional post-transcriptional 3'UTR regulatory elements. Our system exploits integrated single-copy reporters, which are expressed and processed as endogenous genes. We screened many thousands of short random sequences for their regulatory potential. Control sequences with known effects were captured effectively using our approach, establishing that our methodology was robust. We found hundreds of functional sequences, which we validated in traditional reporter assays, including verifying their regulatory impact in native sequence contexts. Although 3'UTRs are typically considered repressive, most of the functional elements were activating, including ones that were preferentially conserved. Additionally, we adapted our screening approach to examine the effect of elements on RNA abundance, revealing that most elements act by altering mRNA stability.We developed and used a high-throughput approach to discover hundreds of post-transcriptional cis-regulatory elements. These results imply that most human 3'UTRs contain many previously unrecognized cis-regulatory elements, many of which are activating, and that the post-transcriptional fate of an mRNA is largely due to the actions of many individual cis-regulatory elements within its 3'UTR.
| S-EPMC4778349 | biostudies-literature
Project description:MotivationThe accurate discovery and annotation of regulatory elements remains a challenging problem. The growing number of sequenced genomes creates new opportunities for comparative approaches to motif discovery. Putative binding sites are then considered to be functional if they are conserved in orthologous promoter sequences of multiple related species. Existing methods for comparative motif discovery usually rely on pregenerated multiple sequence alignments, which are difficult to obtain for more diverged species such as plants. As a consequence, misaligned regulatory elements often remain undetected.ResultsWe present a novel algorithm that supports both alignment-free and alignment-based motif discovery in the promoter sequences of related species. Putative motifs are exhaustively enumerated as words over the IUPAC alphabet and screened for conservation using the branch length score. Additionally, a confidence score is established in a genome-wide fashion. In order to take advantage of a cloud computing infrastructure, the MapReduce programming model is adopted. The method is applied to four monocotyledon plant species and it is shown that high-scoring motifs are significantly enriched for open chromatin regions in Oryza sativa and for transcription factor binding sites inferred through protein-binding microarrays in O.sativa and Zea mays. Furthermore, the method is shown to recover experimentally profiled ga2ox1-like KN1 binding sites in Z.mays.Availability and implementationBLSSpeller was written in Java. Source code and manual are available at http://bioinformatics.intec.ugent.be/blsspellerContactKlaas.Vandepoele@psb.vib-ugent.be or jan.fostier@intec.ugent.be.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC4653392 | biostudies-literature
Project description:We sought exonic transcriptional regulatory elements by shotgun cloning human cDNA fragments into luciferase reporter vectors and measuring the resulting expression levels in liver cells. We uncovered seven regulatory elements within coding regions and three within 3' untranslated regions (UTRs). Two of the putative regulatory elements were enhancers and eight were silencers. The regulatory elements were generally but not consistently evolutionarily conserved and also showed a trend toward decreased population diversity. Furthermore, the exonic regulatory elements were enriched in known transcription factor binding sites (TFBSs) and were associated with several histone modifications and transcriptionally relevant chromatin. Evidence was obtained for bidirectional cis-regulation of a coding region element within a tubulin gene, TUBA1B, by the transcription factors PPARA and RORA. We estimate that hundreds of exonic transcriptional regulatory elements exist, an unexpected finding that highlights a surprising multi-functionality of sequences in the human genome.
| S-EPMC3454335 | biostudies-literature