Research Interactions Of Plant Long Non-coding RNA Based On Structure

Long non-coding RNA is the important large non-coding RNA molecules which have specificity regulatory function in biology, and it is consisted more than 200 nucleotides, encoding protein ability without ORF structure, they can play an important regulation role of a variety of levels on the chromosome in modification, epigenetic, transcriptional and post-transcriptional. With the wide application of high-throughput sequencing technology, more and more lncRNAs interact with mi RNA molecules as an endogenous mi RNAs target mimics(e TMs) to be revealed, inhibiting mi RNAs functions, to regulate protein expression levels of genes, which involved in the regulation process of complex diseases. However, studies related to the regulatory mechanisms of plant lncRNAs compared to humans and animals, much less.In order to explore the mechanism of interactions between lncRNAs and RNAs in plants, we used bioinformatics research methods, combined with the structural characteristics of RNAs, focusing on the plant species have received whole-genome sequence data to research the regulatory mechanism. For lack of references about the plant interactions researches between lncRNAs with RNAs, difficulties in this study include: how to choose the right lncRNAs and mi RNAs interaction research tools and databases; how to flite and evaluate targets of lncRNA with mi RNA; how to integrate two types of relational data of plant lncRNAs: mi RNAs and mi RNAs: m RNAs to a regulatory networks; and how to evaluate the network interactions. The comprehensive with the biological theory of RNAs sequences produced interactions by the way of complementary bases pairing, based on this theory we designed for the entire experiment analysis process, including: analysis for structural characters of known plant lncRNAs, through the structural features of lncRNAs, analyzed the possible relationship between structure and function, and to set the threshold screening plant lncRNAs primary data; plant lncRNAs and mi RNAs interactions prediction based on thermodynamic and structural characteristics, and screening plants lncRNAs as endogenous mi RNAs target mimics; plant mi RNA-m RNA targets predicted based on plant mi RNAs and m RNAs binding structural features and mi RNAs seeding area near perfect matching principle, and screening targets data interaction with lncRNAs; establish lncRNA: mi RNA: m RNA primary biological regulatory networks, using network analysis tools(Cytoscape) integrate two types of interactions data; analysis GO functions of network modules and predict plant lncRNAs regulatory functions. Further explains the interactions between plant lncRNAs and RNAs through research model of this paper design the lncRNA and RNA interaction, for in-depth study of plant lncRNAs relevant regulatory functions provides an effective reference method. With the deepening of the field of plant lncRNAs research, regulation mechanism between non-coding RNAs and genes more specifically, it is possible to provide a theoretical guidance for the crop breeding, increase production, drought and cold resistance and so on.