Prediction and assessment of splicing alterations: Implications for clinical testing

Amanda B. Spurdle, Fergus J. Couch, Frans B.L. Hogervorst, Paolo Radice, Olga M. Sinilnikova

Research output: Contribution to journalComment/debate

84 Scopus citations

Abstract

Sequence variants that may result in splicing alterations are a particular class of inherited variants for which consequences can be more readily assessed, using a combination of bioinformatic prediction methods and in vitro assays. There is also a general agreement that a variant would invariably be considered pathogenic on the basis of convincing evidence that it results in transcript(s) carrying a premature stop codon or an in-frame deletion disrupting known functional domain(s). This commentary discusses current practices used to assess the clinical significance of this class of variants, provides suggestions to improve assessment, and highlights the issues involved in routine assessment of potential splicing aberrations. We conclude that classification of sequence variants that may alter splicing is greatly enhanced by supporting in vitro analysis. Additional studies that assess large numbers of variants for induction of splicing aberrations and exon skipping are needed to define the contribution of splicing/exon skipping to cancer and disease. These studies will also provide the impetus for development of algorithms that better predict splicing patterns. To facilitate variant classification and development of more specific bioinformatic tools, we call for the deposition of all laboratory data from splicing analyses into national and international databases.

Original languageEnglish (US)
Pages (from-to)1304-1313
Number of pages10
JournalHuman mutation
Volume29
Issue number11
DOIs
StatePublished - Nov 1 2008

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Keywords

  • Bioinformatic prediction
  • Cancer
  • Oncology
  • Splicing
  • Unclassified variant

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

Cite this

Spurdle, A. B., Couch, F. J., Hogervorst, F. B. L., Radice, P., & Sinilnikova, O. M. (2008). Prediction and assessment of splicing alterations: Implications for clinical testing. Human mutation, 29(11), 1304-1313. https://doi.org/10.1002/humu.20901