Modeling the combined effect of RNA-binding proteins and micrornas in post-transcriptional regulation

Download

index.pdf

Date

2015

Author

HafezQorani, Saber

Metadata

Show full item record

Item Usage Stats

201
views

137
downloads

Post-transcriptional regulation (PTR) controls the gene expression between transcription and translation. Regulation at this level is carried out by the interactions of trans-acting RNA-binding proteins (RBPs) and microRNAs (miRNAs) with cis-regulatory elements in mRNA. Majority of previous work have focused on the effect of a single factor independent of other co-factors bound to the same mRNA. However, recent studies have shown that RBPs and miRNAs can act in cooperation or competition with each other. In this thesis, we mapped the binding sites of both RBPs and miRNAs on human 3’UTRs, and utilized this collection of binding sites to better understand PTR networks. We first focused on several RBPs and assessed how accessibility and conservation differ between experimentally supported sites and other sites that are only computationally predicted. We then investigated the competitive effects of other factors on HuR binding and the resulting transcript abundance change upon HuR depletion. Next, we characterized the potential interactions between the factors by finding those pairs of factors with co-occurrence of motifs higher than expected by chance. Our results show that PUM1 and PUM2 have potential cooperative interactions with miRNAs. Finally, we used logistic regression with features compiled from the counts of sites of factors and dinucleotide frequency to accurately predict the stability and steady-state abundance of mRNAs. Altogether, results of this thesis suggest that studies of PTR must consider the effect of both RBPs and miRNAs, and their interactions.

Subject Keywords

Mitochondria., MicroRNAs., Proteins., Gene expression., Transcription factors.

URI

http://etd.lib.metu.edu.tr/upload/12619149/index.pdf
https://hdl.handle.net/11511/25105

Collections

Graduate School of Informatics, Thesis

Suggestions

OpenMETU
Core

Mathematical Modeling and Approximation of Gene Expression Patterns Yılmaz, Fatih; Öktem, Hüseyin Avni (2004-09-03) This study concerns modeling, approximation and inference of gene regulatory dynamics on the basis of gene expression patterns. The dynamical behavior of gene expressions is represented by a system of ordinary differential equations. We introduce a gene-interaction matrix with some nonlinear entries, in particular, quadratic polynomials of the expression levels to keep the system solvable. The model parameters are determined by using optimization. Then, we provide the time-discrete approximation of our time...
Modeling the combined effect of RNA-binding proteins and microRNAs in post-transcriptional regulation HAFEZQORANİ, Saber; LAFZİ, Atefeh; de Bruin, Ruben G.; VAN ZONNEVELD, Anton Jan; van der Veer, Eric P.; Aydın Son, Yeşim; Kazan, Hilal (2016-05-19) Recent studies show that RNA-binding proteins (RBPs) and microRNAs (miRNAs) function in coordination with each other to control post-transcriptional regulation (PTR). Despite this, the majority of research to date has focused on the regulatory effect of individual RBPs or miRNAs. Here, we mapped both RBP and miRNA binding sites on human 3'UTRs and utilized this collection to better understand PTR. We show that the transcripts that lack competition for HuR binding are destabilized more after HuR depletion. W...
Phenotypical characterization of microRNA-106B overexpression in MCF10A breast cell line Saygılı, Cansaran; Erson Bensan, Ayşe Elif; Department of Biology (2013) MicroRNAs are small non-coding RNAs which regulate gene expression by binding to 3’UTR of their target mRNAs. Deregulated expression of microRNAs is detected in many pathologies including different types of cancers. miR-106b, is a member of miR-106b-25 cluster and overexpressed in many cancers including breast cancer. Based on miR-106b overexpression, we hypothesized that miR-106b may be an oncogene candidate. To explore miR-106b related phenotypes, we used an already miR-106b transfected model cell line sy...
Integer linear programming based solutions for construction of biological networks Eren Özsoy, Öykü; Can, Tolga; Department of Health Informatics (2014) Inference of gene regulatory or signaling networks from perturbation experiments and gene expression assays is one of the challenging problems in bioinformatics. Recently, the inference problem has been formulated as a reference network editing problem and it has been show that finding the minimum number of edit operations on a reference network in order to comply with perturbation experiments is an NP-complete problem. In this dissertation, we propose linear programming based solutions for reconstruction o...
Employing decomposable partially observable Markov decision processes to control gene regulatory networks Erdogdu, Utku; Polat, Faruk; Alhajj, Reda (2017-11-01) Objective: Formulate the induction and control of gene regulatory networks (GRNs) from gene expression data using Partially Observable Markov Decision Processes (POMDPs).

Citation Formats

S. HafezQorani, “Modeling the combined effect of RNA-binding proteins and micrornas in post-transcriptional regulation,” M.S. - Master of Science, Middle East Technical University, 2015.