Integrative in silico approaches to analyse microRNA-mediated responses in human diseases

IF 3.2 4区 医学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Meghna Agrawal, Ashutosh Mani
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引用次数: 0

Abstract

Advancements in sequencing technologies have facilitated omics level information generation for various diseases in human. High-throughput technologies have become a powerful tool to understand differential expression studies and transcriptional network analysis. An understanding of complex transcriptional networks in human diseases requires integration of datasets representing different RNA species including microRNA (miRNA) and messenger RNA (mRNA). This review emphasises on conceptual explanation of generalized workflow and methodologies to the miRNA mediated responses in human diseases by using different in silico analysis. Although, there have been many prior explorations in miRNA-mediated responses in human diseases, the advantages, limitations and overcoming the limitation through different statistical techniques have not yet been discussed. This review focuses on miRNAs as important gene regulators in human diseases, methodologies for miRNA-target gene prediction and data driven methods for enrichment and network analysis for miRnome–targetome interactions. Additionally, it proposes an integrative workflow to analyse structural components of networks obtained from high-throughput data. This review explains how to apply the existing methods to analyse miRNA-mediated responses in human diseases. It addresses unique characteristics of different analysis, its limitations and its statistical solutions influencing the choice of methods for the analysis through a workflow. Moreover, it provides an overview of promising common integrative approaches to comprehend miRNA-mediated gene regulatory events in biological processes in humans. The proposed methodologies and workflow shall help in the analysis of multi-source data to identify molecular signatures of various human diseases.

Abstract Image

分析人类疾病中 microRNA 介导的反应的整合性硅学方法
测序技术的进步促进了人类各种疾病的omics级信息生成。高通量技术已成为了解差异表达研究和转录网络分析的有力工具。要了解人类疾病中复杂的转录网络,需要整合代表不同 RNA 物种的数据集,包括微 RNA (miRNA) 和信使 RNA (mRNA)。这篇综述着重从概念上解释了通过使用不同的硅学分析来研究人类疾病中 miRNA 介导的反应的一般工作流程和方法。虽然此前已有许多关于 miRNA 介导的人类疾病反应的探索,但尚未讨论其优势、局限性以及通过不同统计技术克服局限性的问题。本综述重点讨论了作为人类疾病重要基因调控因子的 miRNA、miRNA-靶基因预测方法以及数据驱动的 miRnome-靶基因组相互作用富集和网络分析方法。此外,它还提出了一种综合工作流程,用于分析从高通量数据中获得的网络结构成分。本综述解释了如何应用现有方法分析 miRNA 介导的人类疾病反应。它探讨了不同分析方法的独特性、局限性以及影响通过工作流程选择分析方法的统计解决方案。此外,它还概述了有前景的常用综合方法,以理解人类生物过程中 miRNA 介导的基因调控事件。所提出的方法和工作流程将有助于分析多源数据,以确定各种人类疾病的分子特征。
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来源期刊
Journal of Gene Medicine
Journal of Gene Medicine 医学-生物工程与应用微生物
CiteScore
6.40
自引率
0.00%
发文量
80
审稿时长
6-12 weeks
期刊介绍: The aims and scope of The Journal of Gene Medicine include cutting-edge science of gene transfer and its applications in gene and cell therapy, genome editing with precision nucleases, epigenetic modifications of host genome by small molecules, siRNA, microRNA and other noncoding RNAs as therapeutic gene-modulating agents or targets, biomarkers for precision medicine, and gene-based prognostic/diagnostic studies. Key areas of interest are the design of novel synthetic and viral vectors, novel therapeutic nucleic acids such as mRNA, modified microRNAs and siRNAs, antagomirs, aptamers, antisense and exon-skipping agents, refined genome editing tools using nucleic acid /protein combinations, physically or biologically targeted delivery and gene modulation, ex vivo or in vivo pharmacological studies including animal models, and human clinical trials. Papers presenting research into the mechanisms underlying transfer and action of gene medicines, the application of the new technologies for stem cell modification or nucleic acid based vaccines, the identification of new genetic or epigenetic variations as biomarkers to direct precision medicine, and the preclinical/clinical development of gene/expression signatures indicative of diagnosis or predictive of prognosis are also encouraged.
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