Kinetic modeling reveals additional regulation at co-transcriptional level by post-transcriptional sRNA regulators.
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ABSTRACT:
SUBMITTER: Reyer MA
PROVIDER: S-EPMC8634553 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Coagulation factor XI (FXI) has become increasingly interesting for its role in pathogenesis of thrombosis. While elevated plasma levels of FXI have been associated with venous thromboembolism and ischemic stroke, its deficiency is associated with mild bleeding. We aimed to determine novel genetic and post-transcriptional plasma FXI regulators.We performed a genome-wide association study (GWAS) for plasma FXI levels, using novel data imputed to the 1000 Genomes reference panel. Individual GWAS analyses, including a total of 16,169 European individuals from the ARIC, GHS, MARTHA and PROCARDIS studies, were meta-analysed and further replicated in 2,045 individuals from the F5L family, GAIT2 and MEGA studies. Additional association with activated partial thromboplastin time (aPTT) was tested for the top SNPs. In addition, a study on the effect of miRNA on FXI regulation was performed using in silico prediction tools and in vitro luciferase assays.Three loci showed robust, replicating association with circulating FXI levels: KNG1 (rs710446, P-value?=?2.07?×?10-302), F11 (rs4253417, P-value ?=?2.86?×?10-193), and a novel association in GCKR (rs780094, P-value ?=?3.56 ×10-09), here for the first time implicated in FXI regulation. The two first SNPs (rs710446 and rs4253417) also associated with aPTT. Conditional and haplotype analyses demonstrated a complex association signal, with additional novel SNPs modulating plasma FXI levels in both the F11 and KNG1 loci. Finally, eight miRNAs were predicted to bind F11 mRNA. Over-expression of either miR-145 or miR-181 significantly reduced the luciferase activity in cells transfected with a plasmid containing FXI-3'UTR.These results should open the door to new therapeutic targets for thrombosis prevention.
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Project description:BackgroundTranscriptional regulation is a fundamental process in biological systems, where transcription factors (TFs) have been revealed to play crucial roles. In recent years, in addition to TFs, an increasing number of non-coding RNAs (ncRNAs) have been shown to mediate post-transcriptional processes and regulate many critical pathways in both prokaryotes and eukaryotes. On the other hand, with more and more high-throughput biological data becoming available, it is possible and imperative to quantitatively study gene regulation in a systematic and detailed manner.ResultsMost existing studies for inferring transcriptional regulatory interactions and the activity of TFs ignore the possible post-transcriptional effects of ncRNAs. In this work, we propose a novel framework to infer the activity of regulators including both TFs and ncRNAs by exploring the expression profiles of target genes and (post)transcriptional regulatory relationships. We model the integrated regulatory system by a set of biochemical reactions which lead to a log-bilinear problem. The inference process is achieved by an iterative algorithm, in which two linear programming models are efficiently solved. In contrast to available related studies, the effects of ncRNAs on transcription process are considered in this work, and thus more reasonable and accurate reconstruction can be expected. In addition, the approach is suitable for large-scale problems from the viewpoint of computation. Experiments on two synthesized data sets and a model system of Escherichia coli (E. coli) carbon source transition from glucose to acetate illustrate the effectiveness of our model and algorithm.ConclusionOur results show that incorporating the post-transcriptional regulation of ncRNAs into system model can mine the hidden effects from the regulation activity of TFs in transcription processes and thus can uncover the biological mechanisms in gene regulation in a more accurate manner. The software for the algorithm in this paper is available upon request.
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