Research On Bidning Site Prediction And Regulatory Function Analysis Of Mirna And Transcription Factor

With the completion of the full length genome sequences determination of human and hundreds of other creatures, biologists are making plan of and carrying out the post genome project. The research focus is turned to working on the functions at molecular level from revealing creatures'genetic information. And understanding global transcriptional and post-transcriptional regulatory mechanisms is a fundamental goal of the post-genomic era.In recent years, as an important factor of the global transcriptional and post-transcriptional regulation, research of transcription factors and miRNA is becoming an important part in bioinformatics. In 2002 and 2003, miRNA was selected as "Ten news of science" by Science Press. More and more researchers of bioinformatics are focusing on the functions and regulatory mechanisms of transcription factors and miRNA. Conventional methods are confined to work on the regulatory functions of transcription factors and miRNA separately, which ignore their interaction on gene expression. Therefore gene expression is taken as a cut-in-point of researches on developing regulatory model of transcription factors and miRNA, predicting the binding sites and regulatory functions, and identifying the promoter region of miRNA. The major research contents of this thesis include the following four parts:(1)A binding sites predicting algorithm based on interactive regulating on gene expression of transcription factors and miRNA is proposed.Conventional computational methods using microarray data to investigate transcriptional regulation is analyzed and extended. With adequate consideration of the combinatorial regulation of transcription factors and miRNA on gene expression, a novel algorithm for identifying potential transcription factor and miRNA binding sites from microarray-derived gene expression data and genomic DNA sequences is proposed. The algorithm identifys potential transcription factor and miRNA binding sites by testing random subsets of all possible motifs of a fixed size in the 5'-regulatory region and 3'untranslated regions, and selecting those motifs that best fit a combinatorial model of gene expression levels. The predicted transcription factor and miRNA binding sites in mouse infetal alcohol syndrome has a biological significance, and the effectivity of the algorithm is validated.(2)Research on transcription factor and miRNA regulatory function analysis model based on binding sites information. Prediction of transcription factor binding sites and targets of miRNAs are always the hot research topics, and many mature databases and softwares have been developed. Identification of transcription factors and miRNAs binding sites based on relevant biologic knowledge is discussed. With the knowledge about reported transcription factors motif and the interaction of miRNA and its targets, the locating of the binding sites is interacted into relevant functional data. From the point of regulating the global gene expression patterns, the transcription factors and the miRNAs which cause the difference of gene expression are analyzed. With this method,5 transcription factors and 7 miRNAs which cause the growth of prostate carcinoma are predicted in the prostate carcinoma cell line. The correctness of the predicted results was verified by various biological knowledges.(3) A method using ChIP-seq derived data to identify promoter regions of miRNAs is presented.Identification of miRNA promoter regions is one of the difficulties of research on miRNA transcription regulation. Conventional methods predict miRNA promoter regions with features of genomes. With the advent of next generation sequencing, a an new data support for promoter regions prediction is provided by ChIP-Seq data, and a new way is thus opened up. Using ChIP-seq derived RNA Polâ…¡binding data, a model for identifying miRNA promoter regions is presented. A parameter learning algorithms is developed for parameter optimization with protein-coding genes' promoter regions data, and the promoter regions are prediction in the upstream regions of miRNAs. Through this method,72 miRNAs promoter regions were detected with RNA Polymeraseâ…¡ChIP-Seq data of breast cancer cells, and the genomes features of promoter regions are also analyzed.(4) Analysis and discussion on the regulatory function analyzing method of transcription factors and miRNAs based on multi-data fusion.With the advent of high-throughput data, analyzing the regulation mechanisms of gene transcription with multi-data fusion method becomes more and more important. Based on a concrete example, the regulatory functions of transcription factors and miRNAs are analyzed with experiments data of gene expression chip-seq, miRNA chip-seq, and ChIP-chip data. Method of multi-data fusion provides forceful support to systems biology and the development of gene regulatory networks.