RNA-Seq

RNA-Seq

RNA-Seq, or RNA sequencing, is a next-generation sequencing (NGS) application that analyzes the transcriptome. By sequencing RNA transcripts with high-throughput, RNA-seq provides a powerful approach in studying many aspects of gene expression. The technique has become a staple in molecular research, driving new insights in the biology of cancer and disease, therapeutics, and single-cell studies.

Depending on the nature of the study, the transcriptome may go beyond mere transcript mRNA to cover the entirety of a cell or tissue’s total RNA, including non-coding RNA and small RNA. RNA-Seq provides a comprehensive means to collect a variety of information regarding molecular gene expression. This includes quantitative data (from measuring differences in expression levels and alternative splicing) as well as qualitative data (from annotating expressed transcripts, exon/intron boundaries, transcription start sites and poly-A sites).

RNA-Seq procedures will vary depending on the intended experimental questions, but an RNA-Seq workflow typically proceeds through the following steps. Total RNA is first purified from cell and tissue samples through liquid-liquid partitioning or solid-phase extraction methods. The sample can then be enriched for target RNA by removing ribosomal RNA. Alternatively, mRNA or small RNA can be selected by hybridization or size selection. Purified RNA is reverse-transcribed to cDNA through RT-PCR. A sequencing platform-specific adapter sequence can be added through this step or ligated to the cDNA in a downstream step. Finally, the sequencing is carried out by a platform, such as Illumina, Ion Torrent, and PacBio. The University of Oregon’s RNA-seqlopedia provides a detailed overview of RNA-Seq.

RNA-Seq possesses exciting potential in disease research and clinical diagnostics. The diversity of different RNA types identified allows the possibility of using extracellular RNA as a non-invasive diagnostic indicator of disease (Byron 2016). In the context of cancer, transcriptional analyses of individual cells or thousands of samples provide new insights on the complexity and heterogeneity of tumors (Cieślik 2018). More recently, advances in single-cell RNA-Seq have greatly contributed to initiating work on the Human Cell Atlas, which seeks to systematically catalog and map cell types, lineages, and disease states.

The figure below outlines a general preparatory workflow for various RNA-seq applications.

Recommended Reading:

  • Prioritizing Sample Prep Helps Ensure Successful RNA-Seq

    Prioritizing Sample Prep Helps Ensure Successful RNA-Seq

    RNA-seq is used to understand the landscape of biologically expressed genes in different conditions and also to uncover non-coding RNAs such as microRNAs and long non-coding RNA. Studies have shown that differences in sample prep and enrichment can cause large variations in experimental outcomes.
  • Developments in Single-Cell RNA-Sequencing Technologies

    Developments in Single-Cell RNA-Sequencing Technologies

    Great interest in, and fast growth of, scRNA-seq technologies over the past several years has resulted in numerous scRNA-seq protocols. We explore how the current protocols can differ in cell isolation methods, barcoding, length of transcripts sequenced, and amplification methods.