Diagnostic utility of transcriptome sequencing for rare Mendelian diseases

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.

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References

  1. 1.

    Yang Y, Muzny DM, Xia F, et al. Molecular findings among patients referred for clinical whole-exome sequencing. JAMA. 2014;312:1870–1879.

  2. 2.

    Lee H, Deignan JL, Dorrani N, et al. Clinical exome sequencing for genetic identification of rare Mendelian disorders. JAMA. 2014;312:1880–1887.

  3. 3.

    Skinner D, Raspberry KA, King M. The nuanced negative: meanings of a negative diagnostic result in clinical exome sequencing. Sociol Health Illn. 2016;38:1303–1317.

  4. 4.

    Biesecker LG, Shianna KV, Mullikin JC. Exome sequencing: the expert view. Genome Biol. 2011;12:128.

  5. 5.

    Lionel AC, Costain G, Monfared N, et al. Improved diagnostic yield compared with targeted gene sequencing panels suggests a role for whole-genome sequencing as a first-tier genetic test. Genet Med. 2018;20:435–443.

  6. 6.

    Stavropoulos DJ, Merico D, Jobling R, et al. Whole genome sequencing expands diagnostic utility and improves clinical management in pediatric medicine. NPJ Genom Med. 2016;1:15012.

  7. 7.

    Belkadi A, Bolze A, Itan Y, et al. Whole-genome sequencing is more powerful than whole-exome sequencing for detecting exome variants. Proc Natl Acad Sci U S A. 2015;112:5473–5478.

  8. 8.

    Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009;10:57–63.

  9. 9.

    Pan Q, Shai O, Lee LJ, Frey BJ, Blencowe BJ. Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nat Genet. 2008;40:1413–1415.

  10. 10.

    Sultan M, Schulz MH, Richard H, et al. A global view of gene activity and alternative splicing by deep sequencing of the human transcriptome. Science. 2008;321:956–960.

  11. 11.

    Gonorazky HD, Naumenko S, Ramani AK, et al. Expanding the boundaries of RNA sequencing as a diagnostic tool for rare Mendelian disease. Am J Hum Genet. 2019;104:466–483.

  12. 12.

    Cummings BB, Marshall JL, Tukiainen T, et al. Improving genetic diagnosis in Mendelian disease with transcriptome sequencing. Sci Transl Med. 2017;9:386.

  13. 13.

    Kremer LS, Bader DM, Mertes C, et al. Genetic diagnosis of Mendelian disorders via RNA sequencing. Nat Commun. 2017;8:15824.

  14. 14.

    Splinter K, Adams DR, Bacino CA, et al. Effect of genetic diagnosis on patients with previously undiagnosed disease. N Engl J Med. 2018;379:2131–2139.

  15. 15.

    Splinter K, Hull SC, Holm IA, et al. Implementing the single institutional review board model: lessons from the Undiagnosed Diseases Network. Clin Transl Sci. 2018;11:28–31.

  16. 16.

    Thorvaldsdottir H, Robinson JT, Mesirov JP. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform. 2013;14:178–192.

  17. 17.

    Dobin A, Davis CA, Schlesinger F, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29:15–21.

  18. 18.

    Richards S, Aziz N, Bale S, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17:405–424.

  19. 19.

    GraphPad. QuickCalcs. https://www.graphpad.com/quickcalcs/confInterval2/. Accessed 29 March 2019.

  20. 20.

    Agamy O, Ben Zeev B, Lev D, et al. Mutations disrupting selenocysteine formation cause progressive cerebello-cerebral atrophy. Am J Hum Genet. 2010;87:538–544.

  21. 21.

    Hunt RC, Simhadri VL, Iandoli M, Sauna ZE, Kimchi-Sarfaty C. Exposing synonymous mutations. Trends Genet. 2014;30:308–321.

  22. 22.

    Stenson PD, Ball EV, Mort M, et al. Human Gene Mutation Database (HGMD): 2003 update. Hum Mutat. 2003;21:577–581.

  23. 23.

    Stenson PD, Mort M, Ball EV, Shaw K, Phillips A, Cooper DN. The Human Gene Mutation Database: building a comprehensive mutation repository for clinical and molecular genetics, diagnostic testing and personalized genomic medicine. Hum Genet. 2014;133:1–9.

  24. 24.

    Worman HJ, Bonne G. “Laminopathies”: a wide spectrum of human diseases. Exp Cell Res. 2007;313:2121–2133.

  25. 25.

    Benedetti S, Menditto I, Degano M, et al. Phenotypic clustering of lamin A/C mutations in neuromuscular patients. Neurology. 2007;69:1285–1292.

  26. 26.

    Abrams AJ, Fontanesi F, Tan NBL, et al. Insights into the genotype-phenotype correlation and molecular function of SLC25A46. Hum Mutat. 2018;39:1995–2007.

  27. 27.

    Wan J, Steffen J, Yourshaw M, et al. Loss of function of SLC25A46 causes lethal congenital pontocerebellar hypoplasia. Brain. 2016;139:2877–2890.

  28. 28.

    Clark MM, Stark Z, Farnaes L, et al. Meta-analysis of the diagnostic and clinical utility of genome and exome sequencing and chromosomal microarray in children with suspected genetic diseases. NPJ Genom Med. 2018;3:16.

  29. 29.

    Fresard L, Smail C, Ferraro NM, et al. Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts. Nat Med. 2019;25:911–919.

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Acknowledgements

Supported by awards from the National Institutes of Health (NIH) Common Fund, through the Office of Strategic Coordination and the Office of the NIH Director: U01HG007703 to the University of California–Los Angeles, U01HG007942 to Baylor College of Medicine, and U01HG007943 to HudsonAlpha Institute for Biotechnology. J.D.W. is supported by the UCLA Intercampus Medical Genetics Training Program, US Department of Health and Human Services (USHHS) Ruth L. Kirschstein Institutional National Research Service Award T32GM008243. This research and cores used are supported by NIH National Center for Advancing Translational Science (NCATS) UCLA Clinical and Translational Science Institute (CTSI) grant number UL1TR001881. B.L.F. is supported by NIH R01NS082094. S.N.-R. is supported by the NIH Training Grant in Genomic Analysis and Interpretation T32HG002536.

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Correspondence to Stanley F. Nelson MD.

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Lee, H., Huang, A.Y., Wang, L. et al. Diagnostic utility of transcriptome sequencing for rare Mendelian diseases. Genet Med (2019). https://doi.org/10.1038/s41436-019-0672-1

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Keywords

  • transcriptome sequencing
  • genome sequencing
  • exome sequencing
  • undiagnosed rare Mendelian diseases
  • molecular diagnosis

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