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Assigning Co-Regulated Human Genes and Regulatory Gene Clusters.

ABSTRACT: Elucidating the role of genetic variation in the regulation of gene expression is key to understanding the pathobiology of complex diseases which, in consequence, is crucial in devising targeted treatment options. Expression quantitative trait locus (eQTL) analysis correlates a genetic variant with the strength of gene expression, thus defining thousands of regulated genes in a multitude of human cell types and tissues. Some eQTL may not act independently of each other but instead may be regulated in a coordinated fashion by seemingly independent genetic variants. To address this issue, we combined the approaches of eQTL analysis and colocalization studies. Gene expression was determined in datasets comprising 49 tissues from the Genotype-Tissue Expression (GTEx) project. From about 33,000 regulated genes, over 14,000 were found to be co-regulated in pairs and were assembled across all tissues to almost 15,000 unique clusters containing up to nine regulated genes affected by the same eQTL signal. The distance of co-regulated eGenes was, on average, 112 kilobase pairs. Of 713 genes known to express clinical symptoms upon haploinsufficiency, 231 (32.4%) are part of at least one of the identified clusters. This calls for caution should treatment approaches aim at an upregulation of a haploinsufficient gene. In conclusion, we present an unbiased approach to identifying co-regulated genes in and across multiple tissues. Knowledge of such common effects is crucial to appreciate implications on biological pathways involved, specifically when a treatment option targets a co-regulated disease gene.

SUBMITTER: Strunz T

PROVIDER: S-EPMC8470523 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND: Aroclor 1254 is a well-known hepatotoxin and consists of a complex mixture of polychlorinated biphenyls (PCBs), some of which have the ability to activate the aryl hydrocarbon receptor (AhR) and other transcription factors (TFs). Altered transcription factor expression enables activation of promoters of many genes, thereby inducing a regulatory gene network. In the past, computational approaches were not applied to understand the combinatorial interplay of TFs acting in concert after treatment of human hepatocyte cultures with Aroclor 1254. We were particularly interested in interrogating promoters for transcription factor binding sites of regulated genes. RESULTS: Here, we present a framework for studying a gene regulatory network and the large-scale regulation of transcription on the level of chromatin structure. For that purpose, we employed cDNA and oligomicroarrays to investigate transcript signatures in human hepatocyte cultures treated with Aroclor 1254 and found 910 genes to be regulated, 52 of which code for TFs and 47 of which are involved in cell cycle and apoptosis. We identified regulatory elements proximal to AhR binding sites, and this included recognition sites for the transcription factors ETS, SP1, CREB, EGR, NF-kB, NKXH, and ZBP. Notably, ECAT and TBP binding sites were identified for Aroclor 1254-induced and E2F, MAZ, HOX, and WHZ for Aroclor 1254-repressed genes. We further examined the chromosomal distribution of regulated genes and observed a statistically significant high number of gene pairs within a distance of 200 kb. Genes regulated by Aroclor 1254, are much closer located to each other than genes distributed randomly all over the genome. 37 regulated gene pairs are even found to be directly neighbored. Within these directly neighbored gene pairs, not all genes were bona fide targets for AhR (primary effect). Upon further analyses many were targets for other transcription factors whose expression was regulated by Aroclor 1254 (secondary effect). CONCLUSION: We observed coordinate events in transcript regulation upon treatment of human hepatocytes with Aroclor 1254 and identified a regulatory gene network of different TFs acting in concert. We determined molecular rules for transcriptional regulation to explain, in part, the pleiotropic effect seen in animals and humans upon exposure to Aroclor 1254.

Project description:BackgroundThe evolutionarily ancient parasite, Trypanosoma brucei, is unusual in that the majority of its genes are regulated post-transcriptionally, leading to the suggestion that transcript abundance of most genes does not vary significantly between different life cycle stages despite the fact that the parasite undergoes substantial cellular remodelling and metabolic changes throughout its complex life cycle. To investigate this in the clinically relevant sub-species, Trypanosoma brucei gambiense, which is the causative agent of the fatal human disease African sleeping sickness, we have compared the transcriptome of two different life cycle stages, the potentially human-infective bloodstream forms with the non-human-infective procyclic stage using digital gene expression (DGE) analysis.ResultsOver eleven million unique tags were generated, producing expression data for 7360 genes, covering 81% of the genes in the genome. Compared to microarray analysis of the related T. b. brucei parasite, approximately 10 times more genes with a 2.5-fold change in expression levels were detected. The transcriptome analysis revealed the existence of several differentially expressed gene clusters within the genome, indicating that contiguous genes, presumably from the same polycistronic unit, are co-regulated either at the level of transcription or transcript stability.ConclusionsDGE analysis is extremely sensitive for detecting gene expression differences, revealing firstly that a far greater number of genes are stage-regulated than had previously been identified and secondly and more importantly, this analysis has revealed the existence of several differentially expressed clusters of genes present on what appears to be the same polycistronic units, a phenomenon which had not previously been observed in microarray studies. These differentially regulated clusters of genes are in addition to the previously identified RNA polymerase I polycistronic units of variant surface glycoproteins and procyclin expression sites, which encode the major surface proteins of the parasite. This raises a number of questions regarding the function and regulation of the gene clusters that clearly warrant further study.

Project description:BackgroundTranscription factors (TFs) co-ordinately regulate target genes that are dispersed throughout the genome. This co-ordinate regulation is achieved, in part, through the interaction of transcription factors with conserved cis-regulatory motifs that are in close proximity to the target genes. While much is known about the families of transcription factors that regulate gene expression in plants, there are few well characterised cis-regulatory motifs.In Arabidopsis, over-expression of the MYB transcription factor PAP1 (PRODUCTION OF ANTHOCYANIN PIGMENT 1) leads to transgenic plants with elevated anthocyanin levels due to the co-ordinated up-regulation of genes in the anthocyanin biosynthetic pathway. In addition to the anthocyanin biosynthetic genes, there are a number of un-associated genes that also change in expression level. This may be a direct or indirect consequence of the over-expression of PAP1.ResultsOligo array analysis of PAP1 over-expression Arabidopsis plants identified genes co-ordinately up-regulated in response to the elevated expression of this transcription factor. Transient assays on the promoter regions of 33 of these up-regulated genes identified eight promoter fragments that were transactivated by PAP1. Bioinformatic analysis on these promoters revealed a common cis-regulatory motif that we showed is required for PAP1 dependent transactivation.ConclusionCo-ordinated gene regulation by individual transcription factors is a complex collection of both direct and indirect effects. Transient transactivation assays provide a rapid method to identify direct target genes from indirect target genes. Bioinformatic analysis of the promoters of these direct target genes is able to locate motifs that are common to this sub-set of promoters, which is impossible to identify with the larger set of direct and indirect target genes. While this type of analysis does not prove a direct interaction between protein and DNA, it does provide a tool to characterise cis-regulatory sequences that are necessary for transcription activation in a complex list of co-ordinately regulated genes.

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Assigning Co-Regulated Human Genes and Regulatory Gene Clusters.

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