Development Of New MiRNA Prediction And Real-time PCR Quantification Method And Comparative Transcriptomics Research Of Porcine Skeletal Muscle Tissue During Development

MicroRNAs(miRNAs) are recognized as one of the most important families of non-coding RNAs that serve as important sequence-specific post-transcriptional regulators of gene expression.MiRNAs(microRNAs) play critical roles in many important biological processes in mammals.Cloning and functional identification of miRNAs is an important aspect for understanding the mechanisms of gene regulation. Hundreds of miRNAs have been cloned in several species and few of their functions have bee identified by cell culture of in vivo experiments.However,there are still many miRNAs that remain to be cloned due to the miRNA cloning method limitations and the lack of either sequence features or robust algorithms to efficiently identify them. Moreover,for most of the currently cloned miRNAs,their function are still unknown. Recently,many new methods such as Solexa/Illuminaand 454 Life Sciences/Roche deep sequencing technology,miRNA microarray and precision miRNA quantification method have been widely used in miRNA studies and gain a lot of sucess.In this study we developed new approachs and software for miRNA analysis.Using the bioinformatical tools we developed and microarray hybridization technology,we investigated the expression of miRNA and mRNA in porcine tissues and possible miRNA and mRNA interactions involved in muscle development.We also developed a new miRNA Real-time based miRNA quantification method.The main results are as follows:An improved approach and software implementation for genome-wide fast microRNA precursor scansIn this study,we have development a new approach of in silicon miRNA precursor (pre-miRNA) prediction implemented in a software package called MiRFinder.We firstly evaluated features valuable for pre-miRNA prediction,such as the local secondary structure differences of the stem region of miRNA and non-miRNA hairpins.We have also established correlations between different types of mutations and the secondary structures of pre-miRNAs.Utilizing these features and combining some improvements of the current pre-miRNA prediction methods,we implemented a computational learning method SVM(support vector machine) to build a high throughput and good performance computational pre-miRNA prediction tool called MiRFinder.The tool was designed for genome-wise,pair-wise sequences from two related species.The method built into the tool consisted of two major steps:1) genome wide search for hairpin candidates and 2) exclusion of the non-robust structures based on analysis of 18 parameters by the SVM method.Results from applying the tool for chicken/human and D.melanogaster/D. pseudoobscura pair-wise genome alignments showed that the tool can be used for genome wide pre-miRNA predictions.The miRFinder can be a good alternative to current miRNA discovery software.This tool is available at http://www.bioinformatics.org/mirfinder/.Development of software for rapid mieroRNA library mining from the secondary generation deep sequencing dataBased on analyzing currently available deep sequencing miRNA libraries we presented an improved strategy of miRNA discovering.This strategy commingles multiple microRNA libraries and made use of SVM(support vector machine) classifier to distinguish between real and pseudo miRNAs.Dozens of evaluated features of pre-miRNA structure have bee used to filter out the non-robust hairpins.Several new features also have been introduced to remove the lower quality sequence reads,referred as background noise.A software package called MiR-â…¡has been developed to implement this strategy.An actual application in Caenorhabditis elegans and Mouse deep sequencing miRNA libraries demonstrated its top-tier performance.The MiR-â…¡is distributed under the GNU General Public License and has been tested on the GNU/Linux and Microsoft/Windows operating system.It is free available by request(Dr.Shu-hong Zhao).Rapid and accurate microRNA quantification using padlock probe capturing and real-time PCR amplificationRapid and accurate microRNA quantification is a basic requirement in miRNA research.In this study,we developed a two-step miRNA quantification approach based on padlock probe capturing followed by real-time PCR amplification.The sensitivity of this assay is good enough for quantifying miRNA expression from nanomoles of total RNA with variation coefficient less than 1%.The specificity of the method is enough to discriminate between miRNAs and its precursors as well as among closely related miRNA family members.The method is ideally suitable for rapid and accurate quantification of miRNA expression.Discovery of porcine microRNAs and profiling from skeletal muscle tissues during developmentIn this study,we identified hundreds of porcine miRNA candidates through in silico prediction and analyzed their expression in developing skeletal muscle using microarray. Microarray screening using RNA samples prepared from a 33-day whole embryo and an extra embryo membrane validated 296 of the predicted candidates.Comparative expression profiling across samples of longissimus muscle collected from 33-day and 65-day post-gestation fetuses,as well as adult pigs,identified 140 differentially expressed miRNAs amongst the age groups investigated.The differentially expressed miRNAs showed seven distinctive types of expression patterns,suggesting possible involvement in certain biological processes.Five of the differentially expressed miRNAs were validated using real-time PCR.In silico analysis of the miRNA-mRNA interaction sites suggested that the potential mRNA targets of the differentially expressed miRNAs may play important roles in muscle growth and development.