Skip to main content
eScholarship
Open Access Publications from the University of California

Diagnostic utility of transcriptome sequencing for rare Mendelian diseases.

  • Author(s): Lee, Hane
  • Huang, Alden Y
  • Wang, Lee-Kai
  • Yoon, Amanda J
  • Renteria, Genecee
  • Eskin, Ascia
  • Signer, Rebecca H
  • Dorrani, Naghmeh
  • Nieves-Rodriguez, Shirley
  • Wan, Jijun
  • Douine, Emilie D
  • Woods, Jeremy D
  • Dell'Angelica, Esteban C
  • Fogel, Brent L
  • Martin, Martin G
  • Butte, Manish J
  • Parker, Neil H
  • Wang, Richard T
  • Shieh, Perry B
  • Wong, Derek A
  • Gallant, Natalie
  • Singh, Kathryn E
  • Tavyev Asher, Y Jane
  • Sinsheimer, Janet S
  • Krakow, Deborah
  • Loo, Sandra K
  • Allard, Patrick
  • Papp, Jeanette C
  • Undiagnosed Diseases Network
  • Palmer, Christina GS
  • Martinez-Agosto, Julian A
  • Nelson, Stanley F
  • et al.

Published Web Location

https://www.nature.com/articles/s41436-019-0672-1
No data is associated with this publication.
Abstract

Purpose

We investigated the value of transcriptome sequencing (RNAseq) in ascertaining the consequence of DNA variants on RNA transcripts to improve the diagnostic rate from exome or genome sequencing for undiagnosed Mendelian diseases spanning a wide spectrum of clinical indications.

Methods

From 234 subjects referred to the Undiagnosed Diseases Network, University of California-Los Angeles clinical site between July 2014 and August 2018, 113 were enrolled for high likelihood of having rare undiagnosed, suspected genetic conditions despite thorough prior clinical evaluation. Exome or genome sequencing and RNAseq were performed, and RNAseq data was integrated with genome sequencing data for DNA variant interpretation genome-wide.

Results

The molecular diagnostic rate by exome or genome sequencing was 31%. Integration of RNAseq with genome sequencing resulted in an additional seven cases with clear diagnosis of a known genetic disease. Thus, the overall molecular diagnostic rate was 38%, and 18% of all genetic diagnoses returned required RNAseq to determine variant causality.

Conclusion

In this rare disease cohort with a wide spectrum of undiagnosed, suspected genetic conditions, RNAseq analysis increased the molecular diagnostic rate above that possible with genome sequencing analysis alone even without availability of the most appropriate tissue type to assess.

Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.

Main Content

This item is under embargo until May 12, 2021.

You may have access to the publisher's version here:

https://www.nature.com/articles/s41436-019-0672-1Notify me by email when this item becomes available