POSTAR2: deciphering the post-transcriptional regulatory logics.
Ontology highlight
ABSTRACT:
SUBMITTER: Zhu Y
PROVIDER: S-EPMC6323971 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Although metabolic networks have been reconstructed on a genome scale, the corresponding reconstruction and integration of governing transcriptional regulatory networks has not been fully achieved. Here we reconstruct such an integrated network for amino acid metabolism in Escherichia coli. Analysis of ChIP-chip and gene expression data for the transcription factors ArgR, Lrp and TrpR showed that 19 out of 20 amino acid biosynthetic pathways are either directly or indirectly controlled by these regulators. Classifying the regulated genes into three functional categories of transport, biosynthesis and metabolism leads to the elucidation of regulatory motifs that constitute the integrated network's basic building blocks. The regulatory logic of these motifs was determined on the basis of relationships between transcription factor binding and changes in the amount of transcript in response to exogenous amino acids. Remarkably, the resulting logic shows how amino acids are differentiated as signaling and nutrient molecules, revealing the overarching regulatory principles of the amino acid stimulon.
| S-EPMC3777760 | biostudies-literature
Project description:In the fission yeast Schizosaccharomyces pombe, the transcriptional-regulatory network that governs flocculation remains poorly understood. Here, we systematically screened an array of transcription factor deletion and overexpression strains for flocculation and performed microarray expression profiling and ChIP-chip analysis to identify the flocculin target genes. We identified five transcription factors that displayed novel roles in the activation or inhibition of flocculation (Rfl1, Adn2, Adn3, Sre2, and Yox1), in addition to the previously-known Mbx2, Cbf11, and Cbf12 regulators. Overexpression of mbx2(+) and deletion of rfl1(+) resulted in strong flocculation and transcriptional upregulation of gsf2(+)/pfl1(+) and several other putative flocculin genes (pfl2(+)-pfl9(+)). Overexpression of the pfl(+) genes singly was sufficient to trigger flocculation, and enhanced flocculation was observed in several combinations of double pfl(+) overexpression. Among the pfl1(+) genes, only loss of gsf2(+) abrogated the flocculent phenotype of all the transcription factor mutants and prevented flocculation when cells were grown in inducing medium containing glycerol and ethanol as the carbon source, thereby indicating that Gsf2 is the dominant flocculin. In contrast, the mild flocculation of adn2(+) or adn3(+) overexpression was likely mediated by the transcriptional activation of cell wall-remodeling genes including gas2(+), psu1(+), and SPAC4H3.03c. We also discovered that Mbx2 and Cbf12 displayed transcriptional autoregulation, and Rfl1 repressed gsf2(+) expression in an inhibitory feed-forward loop involving mbx2(+). These results reveal that flocculation in S. pombe is regulated by a complex network of multiple transcription factors and target genes encoding flocculins and cell wall-remodeling enzymes. Moreover, comparisons between the flocculation transcriptional-regulatory networks of Saccharomyces cerevisiae and S. pombe indicate substantial rewiring of transcription factors and cis-regulatory sequences.
| S-EPMC3516552 | biostudies-literature
Project description:BackgroundGene Regulatory Networks (GRNs) have been previously studied by using Boolean/multi-state logics. While the gene expression values are usually scaled into the range [0, 1], these GRN inference methods apply a threshold to discretize the data, resulting in missing information. Most of studies apply fuzzy logics to infer the logical gene-gene interactions from continuous data. However, all these approaches require an a priori known network structure.ResultsHere, by introducing a new probabilistic logic for continuous data, we propose a novel logic-based approach (called the LogicNet) for the simultaneous reconstruction of the GRN structure and identification of the logics among the regulatory genes, from the continuous gene expression data. In contrast to the previous approaches, the LogicNet does not require an a priori known network structure to infer the logics. The proposed probabilistic logic is superior to the existing fuzzy logics and is more relevant to the biological contexts than the fuzzy logics. The performance of the LogicNet is superior to that of several Mutual Information-based and regression-based tools for reconstructing GRNs.ConclusionsThe LogicNet reconstructs GRNs and logic functions without requiring prior knowledge of the network structure. Moreover, in another application, the LogicNet can be applied for logic function detection from the known regulatory genes-target interactions. We also conclude that computational modeling of the logical interactions among the regulatory genes significantly improves the GRN reconstruction accuracy.
| S-EPMC7372900 | biostudies-literature
Project description:Hemicellulose, the second most abundant plant biomass fraction after cellulose, is widely viewed as a potential substrate for the production of liquid fuels and other value-added materials. Degradation of hemicellulose by filamentous fungi requires production of many different enzymes, which are induced by biopolymers or its derivatives and regulated mainly at the transcriptional level through transcription factors (TFs). Neurospora crassa, a model filamentous fungus, expresses and secretes enzymes required for plant cell wall deconstruction. To better understand genes specifically associated with degradation of hemicellulose, we applied secretome and transcriptome analysis to N. crassa grown on beechwood xylan. We identified 34 secreted proteins and 353 genes with elevated transcription on xylan. The xylanolytic phenotype of strains with deletions in genes identified from the secretome and transcriptome analysis of the wild type was assessed, revealing functions for known and unknown proteins associated with hemicellulose degradation. By evaluating phenotypes of strains containing deletions of predicted TF genes in N. crassa, we identified a TF (XLR-1; xylan degradation regulator 1) essential for hemicellulose degradation that is an ortholog to XlnR/XYR1 in Aspergillus and Trichoderma species, respectively, a major transcriptional regulator of genes encoding both cellulases and hemicellulases. Deletion of xlr-1 in N. crassa abolished growth on xylan and xylose, but growth on cellulose and cellulolytic activity were only slightly affected. To determine the regulatory mechanisms for hemicellulose degradation, we explored the transcriptional regulon of XLR-1 under xylose, xylanolytic, and cellulolytic conditions. XLR-1 regulated only some predicted hemicellulase genes in N. crassa and was required for a full induction of several cellulase genes. Hemicellulase gene expression was induced by a combination of release from carbon catabolite repression (CCR) and induction. This systematic analysis illustrates the similarities and differences in regulation of hemicellulose degradation among filamentous fungi.
| S-EPMC3318299 | biostudies-literature
Project description:Modeling of transcriptional regulatory networks (TRNs) has been increasingly used to dissect the nature of gene regulation. Inference of regulatory relationships among transcription factors (TFs) and genes, especially among multiple TFs, is still challenging. In this study, we introduced an integrative method, LogicTRN, to decode TF-TF interactions that form TF logics in regulating target genes. By combining cis-regulatory logics and transcriptional kinetics into one single model framework, LogicTRN can naturally integrate dynamic gene expression data and TF-DNA-binding signals in order to identify the TF logics and to reconstruct the underlying TRNs. We evaluated the newly developed methodology using simulation, comparison and application studies, and the results not only show their consistence with existing knowledge, but also demonstrate its ability to accurately reconstruct TRNs in biological complex systems.
| S-EPMC5715098 | biostudies-literature
Project description:Mammalian Pumilio proteins, PUM1 and PUM2, are members of the PUF family of sequence-specific RNA-binding proteins. In this review, we explore their mechanisms, regulatory networks, biological functions, and relevance to diseases. Pumilio proteins bind an extensive network of mRNAs and repress protein expression by inhibiting translation and promoting mRNA decay. Opposingly, in certain contexts, they can activate protein expression. Pumilio proteins also regulate noncoding (nc)RNAs. The ncRNA, ncRNA activated by DNA damage (NORAD), can in turn modulate Pumilio activity. Genetic analysis provides new insights into Pumilio protein function. They are essential for growth and development. They control diverse processes, including stem cell fate, and neurological functions, such as behavior and memory formation. Novel findings show that their dysfunction contributes to neurodegeneration, epilepsy, movement disorders, intellectual disability, infertility, and cancer.
| S-EPMC6251728 | biostudies-literature
Project description:Most cancer alterations occur in the noncoding portion of the human genome, where regulatory regions control gene expression. The discovery of noncoding mutations altering the cells' regulatory programs has been limited to few examples with high recurrence or high functional impact. Here, we show that transcription factor binding sites (TFBSs) have similar mutation loads to those in protein-coding exons. By combining cancer somatic mutations in TFBSs and expression data for protein-coding and miRNA genes, we evaluate the combined effects of transcriptional and post-transcriptional alterations on the regulatory programs in cancers. The analysis of seven TCGA cohorts culminates with the identification of protein-coding and miRNA genes linked to mutations at TFBSs that are associated with a cascading trans-effect deregulation on the cells' regulatory programs. Our analyses of cis-regulatory mutations associated with miRNAs recurrently predict 12 mature miRNAs (derived from 7 precursors) associated with the deregulation of their target gene networks. The predictions are enriched for cancer-associated protein-coding and miRNA genes and highlight cis-regulatory mutations associated with the dysregulation of key pathways associated with carcinogenesis. By combining transcriptional and post-transcriptional regulation of gene expression, our method predicts cis-regulatory mutations related to the dysregulation of key gene regulatory networks in cancer patients.
| S-EPMC9757053 | biostudies-literature
Project description:Systems biology seeks a genomic-level interpretation of transcriptional regulatory information represented by patterns of protein-binding sites. Obtaining this information without direct experimentation is challenging; minor alterations in binding sites can have profound effects on gene expression, and underlie important aspects of disease and evolution. Quantitative modeling offers an alternative path to develop a global understanding of the transcriptional regulatory code. Recent studies have focused on endogenous regulatory sequences; however, distinct enhancers differ in many features, making it difficult to generalize to other cis-regulatory elements. We applied a systematic approach to simpler elements and present here the first quantitative analysis of short-range transcriptional repressors, which have central functions in metazoan development. Our fractional occupancy-based modeling uncovered unexpected features of these proteins' activity that allow accurate predictions of regulation by the Giant, Knirps, Krüppel, and Snail repressors, including modeling of an endogenous enhancer. This study provides essential elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms.
| S-EPMC2824527 | biostudies-literature
Project description:MicroRNAs (miRNAs) regulate diverse biological processes by repressing mRNAs, but their modest effects on direct targets, together with their participation in larger regulatory networks, make it challenging to delineate miRNA-mediated effects. Here, we describe an approach to characterizing miRNA-regulatory networks by systematically profiling transcriptional, post-transcriptional and epigenetic activity in a pair of isogenic murine fibroblast cell lines with and without Dicer expression. By RNA sequencing (RNA-seq) and CLIP (crosslinking followed by immunoprecipitation) sequencing (CLIP-seq), we found that most of the changes induced by global miRNA loss occur at the level of transcription. We then introduced a network modeling approach that integrated these data with epigenetic data to identify specific miRNA-regulated transcription factors that explain the impact of miRNA perturbation on gene expression. In total, we demonstrate that combining multiple genome-wide datasets spanning diverse regulatory modes enables accurate delineation of the downstream miRNA-regulated transcriptional network and establishes a model for studying similar networks in other systems.
| S-EPMC4831719 | biostudies-literature
Project description:RNA-binding proteins (RBPs) control and coordinate each stage in the life cycle of RNAs. Although in vivo binding sites of RBPs can now be determined genome-wide, most studies typically focused on individual RBPs. Here, we examined a large compendium of 114 high-quality transcriptome-wide in vivo RBP-RNA cross-linking interaction datasets generated by the same protocol in the same cell line and representing 64 distinct RBPs. Comparative analysis of categories of target RNA binding preference, sequence preference, and transcript region specificity was performed, and identified potential posttranscriptional regulatory modules, i.e. specific combinations of RBPs that bind to specific sets of RNAs and targeted regions. These regulatory modules represented functionally related proteins and exhibited distinct differences in RNA metabolism, expression variance, as well as subcellular localization. This integrative investigation of experimental RBP-RNA interaction evidence and RBP regulatory function in a human cell line will be a valuable resource for understanding the complexity of post-transcriptional regulation.
| S-EPMC6344852 | biostudies-other