Hane Lee1,2, Alden Y Huang3, Lee-Kai Wang3, Amanda J Yoon2, Genecee Renteria2, Ascia Eskin2, Rebecca H Signer2, Naghmeh Dorrani4, Shirley Nieves-Rodriguez2, Jijun Wan2, Emilie D Douine2, Jeremy D Woods4, Esteban C Dell'Angelica2, Brent L Fogel2,5, Martin G Martin4, Manish J Butte4,6, Neil H Parker7, Richard T Wang2, Perry B Shieh5, Derek A Wong4, Natalie Gallant8,9, Kathryn E Singh8,9, Y Jane Tavyev Asher4,10,11, Janet S Sinsheimer2,12,13, Deborah Krakow2,4,14,15, Sandra K Loo16, Patrick Allard17, Jeanette C Papp2, Christina G S Palmer2,16,17, Julian A Martinez-Agosto2,4,16, Stanley F Nelson18,19,20. 1. Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA. 2. Department of Human Genetics, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA. 3. Institute for Precision Health, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA. 4. Department of Pediatrics, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA. 5. Department of Neurology, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA. 6. Department of Microbiology, Immunology, and Molecular Genetics, University of California-Los Angeles, Los Angeles, CA, USA. 7. Department of Medicine, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA. 8. Department of Pediatrics, School of Medicine, University of California-Irvine, Irvine, CA, USA. 9. Miller Children's and Women's Hospital, Long Beach, CA, USA. 10. Department of Pediatrics, Cedars-Sinai Medical Center, Los Angeles, CA, USA. 11. Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA. 12. Department of Biomathematics, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA. 13. Department of Biostatistics, Fielding School of Public Health, University of California-Los Angeles, Los Angeles, CA, USA. 14. Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA. 15. Department of Orthopaedic Surgery, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA. 16. Department of Psychiatry & Biobehavioral Sciences, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA. 17. Institute for Society and Genetics, Life Sciences, University of California-Los Angeles, Los Angeles, CA, USA. 18. Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA. snelson@mednet.ucla.edu. 19. Department of Human Genetics, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA. snelson@mednet.ucla.edu. 20. Department of Pediatrics, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA. snelson@mednet.ucla.edu.
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.
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.
Authors: David R Murdock; Hongzheng Dai; Lindsay C Burrage; Jill A Rosenfeld; Shamika Ketkar; Michaela F Müller; Vicente A Yépez; Julien Gagneur; Pengfei Liu; Shan Chen; Mahim Jain; Gladys Zapata; Carlos A Bacino; Hsiao-Tuan Chao; Paolo Moretti; William J Craigen; Neil A Hanchard; Brendan Lee Journal: J Clin Invest Date: 2021-01-04 Impact factor: 14.808
Authors: Daniel Danis; Julius O B Jacobsen; Leigh C Carmody; Michael A Gargano; Julie A McMurry; Ayushi Hegde; Melissa A Haendel; Giorgio Valentini; Damian Smedley; Peter N Robinson Journal: Am J Hum Genet Date: 2021-07-21 Impact factor: 11.025
Authors: Mira Holliday; Emma S Singer; Samantha B Ross; Seakcheng Lim; Sean Lal; Jodie Ingles; Christopher Semsarian; Richard D Bagnall Journal: Circ Genom Precis Med Date: 2021-03-03
Authors: Emily K Mis; Annalisa G Sega; Rebecca H Signer; Tracy Cartwright; Weizhen Ji; Julian A Martinez-Agosto; Stanley F Nelson; Christina G S Palmer; Hane Lee; Thomas Mitzelfelt; Monica Konstantino; Lauren Jeffries; Mustafa K Khokha; Elysa Marco; Martin G Martin; Saquib A Lakhani Journal: Am J Med Genet A Date: 2021-01-13 Impact factor: 2.802
Authors: Maria Luisa Brandi; Sunita K Agarwal; Nancy D Perrier; Kate E Lines; Gerlof D Valk; Rajesh V Thakker Journal: Endocr Rev Date: 2021-03-15 Impact factor: 19.871