Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Summary

Alternative splicing (AS) and alternative polyadenylation (APA) expand the diversity of transcript isoforms and their products. Here, we describe bioinformatic protocols to analyze bulk RNA-seq and 3' end sequencing assays to detect and visualize AS and APA varying across experimental conditions.

Abstract

As well as the typical analysis of RNA-Seq to measure differential gene expression (DGE) across experimental/biological conditions, RNA-seq data can also be utilized to explore other complex regulatory mechanisms at the exon level. Alternative splicing and polyadenylation play a crucial role in the functional diversity of a gene by generating different isoforms to regulate gene expression at the post-transcriptional level, and limiting analyses to the whole gene level can miss this important regulatory layer. Here, we demonstrate detailed step by step analyses for identification and visualization of differential exon and polyadenylation site usage across conditions, using Bioconductor and other packages and functions, including DEXSeq, diffSplice from the Limma package, and rMATS.

Introduction

RNA-seq has been widely used over the years typically for estimating differential gene expression and gene discovery¹. In addition, it can also be utilized to estimate varying exon level usage due to gene expressing different isoforms, hence contributing to a better understanding of gene regulation at the post-transcriptional level. The majority of eukaryotic genes generate different isoforms by alternative splicing (AS) to increase the diversity of mRNA expression. AS events can be divided into different patterns: skipping of complete exons (SE) where a ("cassette") exon is completely removed out of the transcript along with its flanki....

Protocol

1. Installation of tools and R packages used in the analysis

1. Conda is a popular and flexible package manager that allows convenient installation of packages with their dependencies across all platforms. Use 'Anaconda' (conda package manager) to install 'conda' which can be used to install the tools/packages required for the analysis.
2. Download 'Anaconda' according to the system requirements from https://www.anaconda.com/products/individual#Downloads and install it by following the prompts in graphical installer. Install all required packages using ‘conda’ by typin....

Results

After running the above step-by-step workflow, the AS and APA analysis outputs and representative results are in the form of tables and data plots, generated as follows.

AS:
The main output of the AS analysis (Supplementary Table 1 for diffSplice; Table 2 for DEXSeq) is a list of exons showing differential usage across conditions, and a list of genes showing significant overall splicing activity of one or more of its constituent exo.......

Discussion

In this study, we evaluated exon-based and event-based approaches to detect AS and APA in bulk RNA-Seq and 3' end sequencing data. The exon-based AS approaches produce both a list of differentially expressed exons and a gene-level ranking ordered by the statistical significance of overall gene-level differential splicing activity (Tables 1-2, 4-5). For the diffSplice package, differential usage is determined by fitting weighted linear models at an exon-level to estimate the differential log fold-chan.......

Materials

Name	Company	Catalog Number	Comments
Not relevent for computational study