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一种识别个体功能单核苷酸多态性和同工型 microRNAs 的方法。

An Approach to Identify Individual Functional Single Nucleotide Polymorphisms and Isoform MicroRNAs.

机构信息

College of Computer and Control Engineering, Qiqihar University, No. 42, Wenhua Street, Qiqihar, Heilongjiang 161006, China.

College of Light Industry and Textile, Qiqihar University, No. 42, Wenhua Street, Qiqihar, Heilongjiang 161006, China.

出版信息

Biomed Res Int. 2019 Jul 30;2019:6193673. doi: 10.1155/2019/6193673. eCollection 2019.

Abstract

MicroRNAs (miRNAs) and single nucleotide polymorphisms (SNPs) play important roles in disease risk and development, especially cancer. Importantly, when SNPs are located in pre-miRNAs, they affect their splicing mechanism and change the function of miRNAs. To improve disease risk assessment, we propose an approach and developed a software tool, IsomiR_Find, to identify disease/phenotype-related SNPs and isomiRs in individuals. Our approach is based on the individual's samples, with SNP information extracted from the 1000 Genomes Project. SNPs were mapped to pre-miRNAs based on whole-genome coordinates and then SNP-pre-miRNA sequences were constructed. Moreover, we developed matpred2, a software tool to identify the four splicing sites of mature miRNAs. Using matpred2, we identified isomiRs and then verified them by searching within individual miRNA sequencing data. Our approach yielded biomarkers for biological experiments, mined functions of miRNAs and SNPs, improved disease risk assessment, and provided a way to achieve individualized precision medicine.

摘要

微小 RNA(miRNAs)和单核苷酸多态性(SNPs)在疾病风险和发展中起着重要作用,尤其是癌症。重要的是,当 SNPs 位于 pre-miRNAs 中时,它们会影响其剪接机制并改变 miRNAs 的功能。为了提高疾病风险评估,我们提出了一种方法,并开发了一个名为 IsomiR_Find 的软件工具,用于识别个体中的疾病/表型相关 SNPs 和 isomiRs。我们的方法基于个体样本,SNP 信息从 1000 基因组计划中提取。根据全基因组坐标将 SNPs 映射到 pre-miRNAs 上,然后构建 SNP-pre-miRNA 序列。此外,我们开发了 matpred2,这是一种用于识别成熟 miRNA 四个剪接位点的软件工具。使用 matpred2,我们识别了 isomiRs,然后通过在个体 miRNA 测序数据中进行搜索来验证它们。我们的方法为生物实验提供了生物标志物,挖掘了 miRNAs 和 SNPs 的功能,改进了疾病风险评估,并为实现个体化精准医学提供了一种方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41bb/6699389/85491cf38a81/BMRI2019-6193673.001.jpg

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