Revealing the History and Mystery of RNA-Seq

Abstract

Advances in RNA-sequencing technologies have led to the development of intriguing experimental setups, a massive accumulation of data, and high demand for tools to analyze it. To answer this demand, computational scientists have developed a myriad of data analysis pipelines, but it is less often considered what the most appropriate one is. The RNA-sequencing data analysis pipeline can be divided into three major parts: data pre-processing, followed by the main and downstream analyses. Here, we present an overview of the tools used in both the bulk RNA-seq and at the single-cell level, with a particular focus on alternative splicing and active RNA synthesis analysis. A crucial part of data pre-processing is quality control, which defines the necessity of the next steps; adapter removal, trimming, and filtering. After pre-processing, the data are finally analyzed using a variety of tools: differential gene expression, alternative splicing, and assessment of active synthesis, the latter requiring dedicated sample preparation. In brief, we describe the commonly used tools in the sample preparation and analysis of RNA-seq data.

Introns: the “dark matter” of the eukaryotic genome

“…Importantly, the advent of next-generation sequencing and computational analysis will invariably play a critical role in uncovering some of these mysteries. Throughout this article, we have described several of these methods, and here we point readers to other reviews ( Halperin et al, 2021 ; Lorenzi et al, 2021 ; Gondane and Itkonen, 2023 ).…”

E.PathDash, pathway activation analysis of publicly available pathogen gene expression data

“…The rise in transcriptomic data production began with the invention of the microarray in 1995 16 and has continued through the past three decades, with data accumulating ever more rapidly after the development of sequencing methodologies that utilize the computational and hardware advances of modern computing 17 . Public repositories such as the European Bioinformatics Institute's ArrayExpress 18 and the National Center for Biotechnology Information's Gene Expression Omnibus (GEO) 19 , have come online in concert with the rise of high-throughput sequencing data.…”

Transcriptional Landscapes of Herelleviridae Bacteriophages and Staphylococcus aureus during Phage Infection: An Overview

“…Various technologies have been developed to study and determine transcriptomes, which include DNA hybridization, DNA microarrays, complementary DNA Amplified Fragment Length Polymorphism (cDNA-AFLP), Expressed Sequence Tags (ESTs) sequencing, Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS), and RNA sequencing (RNA-seq) [ 18 ]. It is important to highlight that RNA-seq, utilizing next-generation sequencing platforms, is widely regarded as the optimal solution in modern bioanalysis, offering virtually limitless possibilities [ 19 ].…”