RNA Sequencing


Enables transcriptome profiling, sophisticated gene expression analysis and discovery of new species of RNA.

The transcriptome is comprised of different populations of RNA molecules, including mRNA, rRNA, tRNA, and other non-coding RNA (such as microRNA, lncRNA). RNA sequencing (RNA-Seq) using next-generation sequencing (NGS) technology allows us to profile the entire transcriptome, including both the coding and the noncoding regions. It also aids in the identification of genes that are differentially expressed in distinct cell populations and provides information on their relative abundance. In addition, it allows us to determine the effects of genetic variant splicing events, identify novel transcripts, detect gene fusions, isoforms and other structural variants, and call single nucleotide variants (SNVs).  


Why RNA Sequencing?

  • Enables the evaluation of RNA expression levels, variant splicing events, single nucleotide polymorphisms (SNPs), and insertion deletion (indels) events throughout the transcriptome
  • Provides the flexibility to evaluate specific populations of RNA through different technologies (targeted RNA sequencing, enrichment of mRNA or depletion of rRNA)
  • Facilitates the detection of low-abundance transcripts and isoforms through targeted sequencing

Supported workflows for RNA sequencing applications

Selecting the optimal RNA-Seq workflow for your experiment is dependent on many factors, including sample quality, input amount and the transcripts of interest. RNA-Seq workflows that are currently supported can be grouped into three main categories: 

RNA transcript depletion

Unwanted rRNA and/or other transcripts (e.g. globin in blood samples) are enzymatically depleted prior to library construction

mRNA capture

Poly(A)-tailed mRNA are selected through bead-based capture prior to library construction 

Targeted sequencing

Total RNA input is used to construct a cDNA library followed by hybridization capture of targets of interest