Predictive analysis method of micro ribonucleic acid (miRNA) target genes of cattle

Abstract

The invention relates to a predictive analysis method of micro ribonucleic acid (miRNA) target genes of the cattle and is suitable for prediction of the miRNA target genes of the cattle. The predictive analysis method of the miRNA target genes of cattle comprises the following steps: (1) establishing a 3'-untranslated region (UTR) data base, (2) obtaining a sequence of the miRNA of the cattle for species without 3'-UTR sequences, (3) obtaining a protein sequence of the cattle, (4) deducting a sequence coding for amino acids in protein (CDS) from the miRNA by writing a practical extraction and reporting language (PERL) script in order to obtain 5'-UTRs and 5'-UTR sequences of the genes, wherein the 3'- UTR sequences are gathered together, and the 3'-UTR data base is established, (5) downloading relevant data for species with an open 3'-UTR, (6) carrying out target genes prediction respectively by a plurality of software, and referring to miRGator software with regard to some miRNA which does not correspond and (7) carrying out statistic analysis and counting the target genes which are obtained through prediction in order to determine a most possible target gene. Generally, in step (6), intersection of a plurality of software prediction results is adopted, namely an overlap part.

Description

technical field [0001] The invention belongs to the field of biotechnology, and relates to a bovine miRNA target gene predictive analysis method, which is suitable for bovine miRNA target gene predictive analysis. Background technique [0002] miRNA is a single-stranded endogenous non-coding small RNA with a length of 18-25 nucleotides. It mainly inhibits its translation by completely or incompletely pairing with the 3' untranslated region of the target gene, thereby participating in the regulation of life activities such as individual development, cell apoptosis, proliferation and differentiation. Under pathological conditions, miRNAs can affect the occurrence and development of tumors by regulating their target genes and the signaling pathways they participate in, and play a role similar to oncogenes or tumor suppressor genes. Experiments have shown that in many tumors, some types of miRNAs are highly expressed, and these highly expressed miRNAs are related to tumor invas...

AI Technical Summary

Problems solved by technology

Compared with miRNA gene prediction, the prediction of target genes is more difficult. Because the number of known miRNA target genes is very limited, it cannot provide sufficient basis for prediction, and the identification steps of the predicted candidate genes are relatively cumbersome. It is difficult to achieve high-throughput and large-scale. From the known interactions between miRNA and target genes, it is concluded that the 2-8 nucleotides at the 5′ end of small RNAs are almost invariably completely integrated with the UTR region at the 3′ end of the target mRNA. Complementary, this feature has also been used to study many algorithms for predicting miRNA target genes

[0004] However, most of the current miRNA prediction algorithms and software are based on the view that the binding sites of miRNA and target genes are located in the 3'-UTR of the gene. In fact, a series of articles published in late 2008 showed that the binding sites of miRNA and target genes dots may also be in gene coding regions

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