RNA Sequencing

Webinar: Discover More in Transcriptome Research with the Unprecedented Read Coverage, Sensitivity and Resolution of Targeted RNA Sequencing

Why RNA-Seq

The transcriptome is comprised of all RNA molecules, including mRNA, rRNA, tRNA, and other non-coding RNA transcribed in one cell or type/population of cells. Transcriptome analysis often aids in the identification of genes that are differentially expressed in distinct cell populations and the relative abundance at which they are expressed. Recently, long noncoding RNAs (lncRNAs) have been described that are a large and diverse class of transcribed RNA molecules, thought to play important regulatory functions, with a length of > 200 nucleotides.

Why Targeted RNA-Seq

Researchers have been able to perform whole-transcriptome sequencing (RNA-Seq) of cDNAs derived from RNA to evaluate expression levels, variant splicing events, SNPs, and InDels throughout the transcriptome. The standard whole-transcriptome RNA-Seq, however, may not provide the highest efficiency and cost-effectiveness to a researcher. No matter if you’re conducting  gene expression profiling or novel transcript discovery, enrichment by SeqCap is recommended. We created the SeqCap RNA enrichment system for exactly this purpose.

The benefits for the SeqCap RNA system include:

  • Decreased sequencing requirements, allowing the use of MiSeq for confident expression profiling — for example, for a panel of 250 genes, you may need 50x less sequencing compared to standard RNA-Seq to achieve the same accuracy and sensitivity
  • Eliminating the need for Poly A selection or rRNA depletion in your workflow — Instead, it selects directly for coding or noncoding regions, allowing for any design of your choosing
  • Increased flexibility — this system is suitable for a wide range of designs, from small panels up to whole transcriptome analysis, or other designs like lncRNA
  • Improved quantitation and detection efficiency for low abundance transcripts and isoforms —by focusing your sequencing reads on genes of interest and not on housekeeping genes