使用元分析统一RNA-seq数据:生物信息学框架及其在植物基因组学中的应用

IF 4.5 Q1 PLANT SCIENCES
Bahman Panahi , Rasmieh Hamid , Feba Jacob , Hossein Mohammadzadeh Jalaly
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引用次数: 0

摘要

RNA测序(RNA- seq)通过实现不同条件下基因表达的高分辨率分析,改变了植物基因组学。然而,由于实验设计、测序平台和数据处理工作流程的差异,整合来自不同研究的RNA-Seq数据具有挑战性,这限制了转录组数据集的可比性和适用性。这篇综述概述了当前的元分析方法,这些方法解决了这些挑战,并提高了RNA-Seq数据整合的一致性、准确性和可解释性。我们讨论了数据规范化技术、汇总结果的统计框架和减少研究间可变性的计算工具等方法。我们还强调了预处理策略,包括批效应校正和标准化基因注释管道,这有助于可靠的交叉研究比较。我们强调RNA-Seq meta分析在植物基因组学中的实际意义。荟萃分析提高了一致性差异表达基因(DEGs)的鉴定,增强了功能注释,揭示了植物物种间保守的调控机制。这些见解在精确育种、应激反应研究和性状改良项目中都有应用。对于实施元分析的研究人员,本综述概述了关键考虑因素、推荐做法和可用资源。最后,我们强调了标准化协议和促进多组学集成的必要性,以解锁更深入的见解。随着转录组学数据集的扩展,元分析将在促进我们对植物生物学的理解及其在农业中的应用方面发挥至关重要的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unifying RNA-seq data using meta-analysis: Bioinformatics frameworks and application for plant genomics
RNA sequencing (RNA-Seq) has transformed plant genomics by enabling high-resolution profiling of gene expression across various conditions. However, integrating RNA-Seq data from different studies is challenging due to variability in experimental designs, sequencing platforms, and data processing workflows, which limits the comparability and applicability of transcriptomic datasets. This review provides an overview of current meta-analysis approaches that address these challenges and enhance the consistency, accuracy, and interpretability of RNA-Seq data integration. We discuss methodologies such as data normalization techniques, statistical frameworks for aggregating results, and computational tools that reduce inter-study variability. We also highlight preprocessing strategies, including batch effect correction and standardized gene annotation pipelines, which facilitate reliable cross-study comparisons. We emphasize the practical significance of RNA-Seq meta-analysis in plant genomics. Meta-analysis improves the identification of consistent differentially expressed genes (DEGs), enhances functional annotation, and uncovers conserved regulatory mechanisms across plant species. These insights have applications in precision breeding, stress-response studies, and trait improvement programs. For researchers implementing meta-analysis, this review outlines key considerations, recommended practices, and available resources. We conclude by highlighting the need for standardized protocols and promoting multi-omics integration to unlock deeper insights. As transcriptomic datasets expand, meta-analysis will play a crucial role in advancing our understanding of plant biology and its application in agriculture.
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来源期刊
Current Plant Biology
Current Plant Biology Agricultural and Biological Sciences-Plant Science
CiteScore
10.90
自引率
1.90%
发文量
32
审稿时长
50 days
期刊介绍: Current Plant Biology aims to acknowledge and encourage interdisciplinary research in fundamental plant sciences with scope to address crop improvement, biodiversity, nutrition and human health. It publishes review articles, original research papers, method papers and short articles in plant research fields, such as systems biology, cell biology, genetics, epigenetics, mathematical modeling, signal transduction, plant-microbe interactions, synthetic biology, developmental biology, biochemistry, molecular biology, physiology, biotechnologies, bioinformatics and plant genomic resources.
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