Informatics Approaches To Elucidate RRNA Binding Protein Roles In Gene Transcription,Splicing And MicroRNA Circuits Regulation

As the Human Encode and cancer genome project is put forward, high-throughput sequencing data increase at an exponential pace, How to use informatics technology to handle and analysis these huge amounts of data becomes the focus of recent biological and medical research. Bioinformatics plays a more key role in integrating and mining these data to solve important biological questions and elucidate new biological rules. New strategies and pipelines are required in order to address major questions and to process new types of data generated by new technologies. My thesis focuses on the application of RNA bioinformatics to solve the problems originated from biological requirements, ranging from RNA binding protein rules in transcription, splicing, and stability control, microRNA target detection, prediction model design of splicing regulation and machine learning.1)Mammalian cell utilize a complex post-transcriptional regulation networks to generate diverse phenotypes Alternative splicing and mRNAs stability control are two critical such mechanisms. PTB polypyrimidine tract binding protein is extensively involved in those two regulation, but the posttranscriptional regulation networks and the mechanism are poorly understood. MicroRNA (miRNA) are a class of recently identified-22nt small non-coding RNA, which can control gene expression by targeting mRNA3'UTRs. Based on CLIP-seq method, We obtain comprehensive PTB genome-wide mapping data in vivo, observed that PTB in significantly enriched in3'UTR region, and regulating the expression of several key genes, through comparison and optimization the constraints of public miRNA software, I write a pipeline to combine the experimental results and computational prediction, in our analysis miRNA seeds from this region widely overlap with PTB binding clusters. Then My colleague has performed RNA-seq/MAPS transcriptome data for the PTB-expressed and-silenced Hela cells, we anticipate the global view of the involvement of this protein in regulating of the alternative splicing, polyadenylation, miRNA regulation pathways. To determine how such changes in Ago2and PTB binding might be related to altered gene expression, we took a strategy to analyze the interplay by segregating expressed genes into five groups based on mapped PTB and Ago2binding events in their3'UTRs, finally proved that PTB has a previously undocumented function in the regulation of microRNA functions suppressing or enhancing microRNA targeting by competitive binding on target mRNA or altering local RNA secondary structure.Next, for the part of miRNA involved in neural differentiation function study,We found there may exist a positive and negative feedback loop between miRNA, transcription factor and splicing factor(PTB). A key event during neuronal induction is the relief of PTB-mediated blockage of microRNA action on multiple components of the REST complex, thereby depressing a large array of neuronal genes, including miR-124and multiple neuronal-specific transcription factors, in non-neuronal cells. This converts a negative feedback loop to a positive one to elicit cellular reprogramming to the neuronal lineage. The findings will provide important clues for people to understand the complex gene regulatory paradigms as well as functional mechanism of miRNA and RBPs.2) Pausing of Pol II during early elongation as a widespread regulatory mechanism in higher eukaryotes. However Little is known about the mechanism of how splicing factor will involve in the transcription regulation such as promoter-proximal pausing, elongation, or pre-mature termination.my college developed a novel method combined with ChlP-seq/GRO-seq technology, not only provide a genome-wide view of Pol II distribution also measure the transcription rate globally in MEFs. We reasoned that a quantitative comparison of ChIP-seq and GRO-seq signals at promoters would reveal what fraction of the ChIP signal at promoters is represented by engaged and elongation-competent Pol II, found that the engaged Pol II fraction is different among various species. Meanwhile In order to fully utilize those data, we design the hidden markov HMM model to simulation of RNA polymerase PolII in genomic pausing and elongation state. These findings reveal unanticipated a new insight in transcription/splicing coupling, a function of promoter-proximal nascent RNA.3) U2AF65is an essential splicing factor, which recognizes3'splice site (3'ss). Biochemical experiments on model pre-mRNAs have established that during the assembly of spliceosomal E complex, sequence-specific binding of U2AF65to the polypyrimidine tract (Py-tract) immediate downstream of the BPS and direct contact of U2AF35with the AG dinucleotide, which together defines functional3'splice sites. The U2AF heterodimer has been well studied for its role in defining functional3' splice sites in pre-mRNA splicing, but multiple critical problems are still outstanding, including the functional impact of their cancer-associated mutations. Through genome-wide analysis of CLIP-seq U2AF-RNA interactions, we report that U2AF is significantly enriched in the polypyrimidine tract region, with the capacity to define-88%of functional3'splice sites in the human genome. All identified6mer motifs are abundant in the uracil residue(U)(top Z-score291.7), We also found that U2AF65sites are strongly associated with a number of alternative splicing events, the top two events being intron retention and exon skipping, sequentially. RNAseq was then performed using the U2AF65-expressed and U2AF65-silenced Hela cells to obtain both the expression and splicing profiles of these cells. After normalizing the transcriptome dataset against the ribosomal genes, we found that the vast majority of genes became down regulated in U2AF65-depleted cells, this may reflect the real states in living cell. We also used the exon inclusion value to deduce altered splicing events in an unbiased manner combined with70validated RT-PCR genes, RNAmap suggests that upstream intronic binding events interfere with the immediate downstream3'splice site associated with either the alternative or competing constitutive exon, thus resulting in inclusion or skipping of the alternative exon.Finally, Machine learning model and Bayesian network design shall shed light on the global roles of this well-known splicing factors in pre-mRNA processing and mRNA expression pathway.