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高影响力基因发现:基于基因共表达网络的单链特异性mRNA文库构建及差异调控分析

High Impact Gene Discovery: Simple Strand-Specific mRNA Library Construction and Differential Regulatory Analysis Based on Gene Co-Expression Network.

作者信息

Ichihashi Yasunori, Fukushima Atsushi, Shibata Arisa, Shirasu Ken

机构信息

RIKEN Center for Sustainable Resource Science, Yokohama, Kanagawa, Japan.

JST, PRESTO, Kawaguchi, Saitama, Japan.

出版信息

Methods Mol Biol. 2018;1830:163-189. doi: 10.1007/978-1-4939-8657-6_11.

DOI:10.1007/978-1-4939-8657-6_11
PMID:30043371
Abstract

Plant transcription factors have potential to behave as hubs in gene regulatory networks through altering the expression of many downstream genes, and identification of such hub transcription factors strongly enhances our understating of biological processes. Transcriptome analysis has become a staple of gene expression analyses. In addition to current advances in Next Generation Sequencing (NGS) technology, various methods for mRNA library construction and downstream data analyses have been enthusiastically developed. Here, we describe Breath Adapter Directional sequencing (BrAD-seq), a simple strand-specific mRNA library preparation for the Illumina platform, allowing easy scaling of transcriptome experiments with low reagent and labor costs. This protocol includes our recent modifications and the detailed practical procedure for BrAD-seq. Because extracting biological meanings from large-scale transcriptome data presents a significant challenge, we also describe a new analytical method that goes beyond differential expression. Differential regulatory analysis (DRA) is based on a gene co-expression network to address which regulatory factor or factors have the ability to predict the abundance of differentially expressed genes between two groups or conditions. This protocol provides a ready-to-use informatics pipeline from raw sequence data to DRA for plant transcriptome datasets.

摘要

植物转录因子有可能通过改变许多下游基因的表达而成为基因调控网络中的枢纽,鉴定此类枢纽转录因子能极大地增进我们对生物过程的理解。转录组分析已成为基因表达分析的主要手段。除了新一代测序(NGS)技术的当前进展外,人们还积极开发了各种用于mRNA文库构建和下游数据分析的方法。在此,我们描述了呼吸适配器定向测序(BrAD-seq),这是一种用于Illumina平台的简单链特异性mRNA文库制备方法,可实现转录组实验的轻松扩展,且试剂和劳动力成本较低。本方案包括我们最近的改进以及BrAD-seq的详细实际操作流程。由于从大规模转录组数据中提取生物学意义是一项重大挑战,我们还描述了一种超越差异表达的新分析方法。差异调控分析(DRA)基于基因共表达网络,以确定哪些调控因子能够预测两组或两种条件之间差异表达基因的丰度。本方案为植物转录组数据集提供了一个从原始序列数据到DRA的即用型信息学流程。

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