Broadcast Date: June 8th, 2016
Time: 11:00 am ET, 8:00 am PT

The cost effectiveness of RNA-Seq is often compromised by uninformative reads that are present in high abundance—a frequent consequence of standard RNA-Seq library preparation methods. These high abundance transcripts may be representative of cytoplasmic and mitochondrial rRNAs, globin, chloroplasts, housekeeping genes, or any other transcript species that may not be relevant to a study. In this webinar, we will describe a novel method for targeted depletion of unwanted transcripts in RNA-Seq libraries. The proprietary Insert Dependent Adaptor Cleavage (InDA-C) technology employs customized probes to target specific transcript species for exclusion in the final RNA-Seq library. Unlike methods that use hybridization-mediated pull-down strategies to deplete unwanted RNA species prior to cDNA synthesis, the InDA-C method depletes targeted transcripts from RNA-Seq libraries, avoiding off-target mRNA cross-hybridization events that can potentially introduce bias.

Who Should Attend

  • Scientists performing RNA-Seq studies who want to improve the efficiency and cost-effectiveness of their sequencing and bioinformatics resources.
  • Researchers studying model organism transcriptomics.
  • Investigators studying host-pathogen relationships.
  • Clinicians using FFPE or whole blood samples for RNA-Seq analysis.

You Will Learn

  • How InDA-C technology effectively removes specific transcripts from RNA-Seq libraries without perturbing the original total RNA population thereby providing a more accurate representation of biology.
  • How InDA-C primers can be designed to target virtually any class of unwanted transcripts from any species with inputs as low as 10 picograms.
  • How the integration of InDA-C into the library construction workflow produces a strand-specific library requiring no additional steps thus improving time to results.
  • How InDA-C targeted depletion of uninformative transcripts results in more sequencing reads derived from desired transcripts and improves detection of lowly expressed genes.

Produced with support from:

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Maureen Peterson, Ph.D.
Research Scientist,
NuGEN Technologies

Ashesh Saraiya, Ph.D.
Product Manager,
NuGEN Technologies