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A Systematic Way to Infer the Regulation Relations of miRNAs on Target Genes and Critical miRNAs in Cancers.

ABSTRACT: MicroRNAs (miRNAs) are a class of important non-coding RNAs, which play important roles in tumorigenesis and development by targeting oncogenes or tumor suppressor genes. One miRNA can regulate multiple genes, and one gene can be regulated by multiple miRNAs. To promote the clinical application of miRNAs, two fundamental questions should be answered: what's the regulatory mechanism of a miRNA to a gene, and which miRNAs are important for a specific type of cancer. In this study, we propose a miRNA influence capturing (miRNAInf) to decipher regulation relations of miRNAs on target genes and identify critical miRNAs in cancers in a systematic approach. With the pair-wise miRNA/gene expression profiles data, we consider the assigning problem of a miRNA on target genes and determine the regulatory mechanisms by computing the Pearson correlation coefficient between the expression changes of a miRNA and that of its target gene. Furthermore, we compute the relative local influence strength of a miRNA on its target gene. Finally, integrate the local influence strength and target gene's importance to determine the critical miRNAs involved in specific cancer. Results on breast, liver and prostate cancers show that positive regulations are as common as negative regulations. The top-ranked miRNAs show great potential as therapeutic targets driving cancer to a normal state, and they are demonstrated to be closely related to cancers based on biological functional analysis, drug sensitivity/resistance analysis and survival analysis. This study will be helpful for the discovery of critical miRNAs and development of miRNAs-based clinical therapeutics.

SUBMITTER: Xu P

PROVIDER: S-EPMC7136563 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A Systematic Way to Infer the Regulation Relations of miRNAs on Target Genes and Critical miRNAs in Cancers.

Xu Peng P Wu Qian Q Yu Jian J Rao Yongsheng Y Kou Zheng Z Fang Gang G Shi Xiaolong X Liu Wenbin W Han Henry H

Frontiers in genetics 20200331

MicroRNAs (miRNAs) are a class of important non-coding RNAs, which play important roles in tumorigenesis and development by targeting oncogenes or tumor suppressor genes. One miRNA can regulate multiple genes, and one gene can be regulated by multiple miRNAs. To promote the clinical application of miRNAs, two fundamental questions should be answered: what's the regulatory mechanism of a miRNA to a gene, and which miRNAs are important for a specific type of cancer. In this study, we propose a miR ...[more]

PMID: 32296462

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Project description:BACKGROUND:MiRNAs (microRNA) are 18-24?nt endogenous noncoding RNAs that regulate gene expression at the post-transcriptional level, including tissue-specific, developmental timing and evolutionary conservation gene expression. RESULTS:This study used high-throughput sequencing technology for the first time in Larix olgensis, predicted 78 miRNAs, including 12,229,003 reads sRNA, screened differentially expressed miRNAs. Predicting target genes was helpful for understanding the miRNA regulation function and obtained 333 corresponding target genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotation were analysed, mostly including nucleic acid binding, plant hormone signal transduction, pantothenate and CoA biosynthesis, and cellulose synthase. This study will lay the foundation for clarifying the complex miRNA-mediated regulatory network for growth and development. In view of this, spatio-temporal expression of miR396, miR950, miR164, miR166 and miR160 were analysed in Larix olgensis during the growth stages of not lignified, beginning of lignification, and completely lignified in different tissues (root, stem, and leaf) by quantitative real-time PCR (qRT-PCR). There were differences in the expression of miRNAs in roots, stems and leaves in the same growth period. At 60?days, miR160, miR166 and miR396-2 exhibited the highest expression in leaves. At 120?days, most miRNAs in roots and stems decreased significantly. At 180?days, miRNAs were abundantly expressed in roots and stems. Meanwhile, analysis of the expression of miRNAs in leaves revealed that miR396-2 was reduced as time went on, whereas other miRNAs increased initially and then decreased. On the other hand, in the stems, miR166-1 was increase, whereas other miRNAs, especially miR160, miR164, miR396 and miR950-1, first decreased and then increased. Similarly, in the roots, miR950-2 first decreased and then increased, whereas other miRNAs exhibited a trend of continuous increase. CONCLUSIONS:The present investigation included rapid isolation and identification of miRNAs in Larix olgensis through construction of a sRNA library using Solexa and predicted 78 novel miRNAs, which showed differential expression levels in different tissues and stages. These results provided a theoretical basis for further revealing the genetic regulation mechanism of miRNA in the growth and development of conifers and the verification of function in target genes.

Project description:BackgroundSmall non-coding RNAs (21 to 24 nucleotides) regulate a number of developmental processes in plants and animals by silencing genes using multiple mechanisms. Among these, the most conserved classes are microRNAs (miRNAs) and small interfering RNAs (siRNAs), both of which are produced by RNase III-like enzymes called Dicers. Many plant miRNAs play critical roles in nutrient homeostasis, developmental processes, abiotic stress and pathogen responses. Currently, only 70 miRNA have been identified in soybean.MethodsWe utilized Illumina's SBS sequencing technology to generate high-quality small RNA (sRNA) data from four soybean (Glycine max) tissues, including root, seed, flower, and nodules, to expand the collection of currently known soybean miRNAs. We developed a bioinformatics pipeline using in-house scripts and publicly available structure prediction tools to differentiate the authentic mature miRNA sequences from other sRNAs and short RNA fragments represented in the public sequencing data.ResultsThe combined sequencing and bioinformatics analyses identified 129 miRNAs based on hairpin secondary structure features in the predicted precursors. Out of these, 42 miRNAs matched known miRNAs in soybean or other species, while 87 novel miRNAs were identified. We also predicted the putative target genes of all identified miRNAs with computational methods and verified the predicted cleavage sites in vivo for a subset of these targets using the 5' RACE method. Finally, we also studied the relationship between the abundance of miRNA and that of the respective target genes by comparison to Solexa cDNA sequencing data.ConclusionOur study significantly increased the number of miRNAs known to be expressed in soybean. The bioinformatics analysis provided insight on regulation patterns between the miRNAs and their predicted target genes expression. We also deposited the data in a soybean genome browser based on the UCSC Genome Browser architecture. Using the browser, we annotated the soybean data with miRNA sequences from four tissues and cDNA sequencing data. Overlaying these two datasets in the browser allows researchers to analyze the miRNA expression levels relative to that of the associated target genes. The browser can be accessed at http://digbio.missouri.edu/soybean_mirna/.

Dataset Information

A Systematic Way to Infer the Regulation Relations of miRNAs on Target Genes and Critical miRNAs in Cancers.

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A Systematic Way to Infer the Regulation Relations of miRNAs on Target Genes and Critical miRNAs in Cancers.

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