Effectiveness of integrated interpretation of exome and corresponding transcriptome data for detecting splicing variants of genes associated with autosomal recessive disorders

Mamiko Yamada, Hisato Suzuki, Yuichi Shiraishi, Kenjiro Kosaki

Research output: Contribution to journalArticle

Abstract

Purpose: Part of the weakness of exome analysis lies in the inability to detect aberrant splicing. An evaluation of the post-splicing mRNA sequence concurrently with genomic variants could improve the diagnostic rate. We aimed to investigate publicly available exome sequencing data and its matching transcriptomics data of phenotypically normal individuals to identify alternatively spliced variants from known genes associated with autosomal recessive disorders under the premise that some of the subjects could be carriers of such disorders. Methods: Aberrant splicing events and their triggering genomic variants were detected with the aid of Bayesian network method “SAVNet” which was originally developed for cancer genomics. Results: Forty aberrant splicing events including exon skipping, the creation of a new splice site, and the use of a cryptic splice site in response to the disruption of the authentic site were detected in 1916 genes among 31 of the 179 subjects from the 1000 Genomes Project. The predicted effects on proteins were either frameshift mutations (30) or large in-frame insertions or deletions (10). Five missense mutations and 2 silent mutations were reinterpreted as triggering major changes in transcript sequences. The detection rate of provisionally truncating pathogenic variants increased by 19%, compared with a conventional exome analysis. Conclusion: The coupling interpretation of exome and transcriptome data enhances the performance of conventional exome analyses through the proper interpretation of intronic variants that are outside of the GT/AG splicing consensus sequences and also allows the reinterpretation of “missense” or “silent” substitutions that can indeed have drastic effects on splicing.

Original languageEnglish
Article number100531
JournalMolecular Genetics and Metabolism Reports
Volume21
DOIs
Publication statusPublished - 2019 Dec

Fingerprint

Exome
Transcriptome
Genes
RNA Splice Sites
Frameshift Mutation
Bayes Theorem
Consensus Sequence
Missense Mutation
Genomics
Exons
Genome
Messenger RNA
Neoplasms
Proteins

Keywords

  • Alternative splicing
  • Exome
  • Mutation detection
  • Transcriptome

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics
  • Endocrinology

Cite this

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title = "Effectiveness of integrated interpretation of exome and corresponding transcriptome data for detecting splicing variants of genes associated with autosomal recessive disorders",
abstract = "Purpose: Part of the weakness of exome analysis lies in the inability to detect aberrant splicing. An evaluation of the post-splicing mRNA sequence concurrently with genomic variants could improve the diagnostic rate. We aimed to investigate publicly available exome sequencing data and its matching transcriptomics data of phenotypically normal individuals to identify alternatively spliced variants from known genes associated with autosomal recessive disorders under the premise that some of the subjects could be carriers of such disorders. Methods: Aberrant splicing events and their triggering genomic variants were detected with the aid of Bayesian network method “SAVNet” which was originally developed for cancer genomics. Results: Forty aberrant splicing events including exon skipping, the creation of a new splice site, and the use of a cryptic splice site in response to the disruption of the authentic site were detected in 1916 genes among 31 of the 179 subjects from the 1000 Genomes Project. The predicted effects on proteins were either frameshift mutations (30) or large in-frame insertions or deletions (10). Five missense mutations and 2 silent mutations were reinterpreted as triggering major changes in transcript sequences. The detection rate of provisionally truncating pathogenic variants increased by 19{\%}, compared with a conventional exome analysis. Conclusion: The coupling interpretation of exome and transcriptome data enhances the performance of conventional exome analyses through the proper interpretation of intronic variants that are outside of the GT/AG splicing consensus sequences and also allows the reinterpretation of “missense” or “silent” substitutions that can indeed have drastic effects on splicing.",
keywords = "Alternative splicing, Exome, Mutation detection, Transcriptome",
author = "Mamiko Yamada and Hisato Suzuki and Yuichi Shiraishi and Kenjiro Kosaki",
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language = "English",
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T1 - Effectiveness of integrated interpretation of exome and corresponding transcriptome data for detecting splicing variants of genes associated with autosomal recessive disorders

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AU - Suzuki, Hisato

AU - Shiraishi, Yuichi

AU - Kosaki, Kenjiro

PY - 2019/12

Y1 - 2019/12

N2 - Purpose: Part of the weakness of exome analysis lies in the inability to detect aberrant splicing. An evaluation of the post-splicing mRNA sequence concurrently with genomic variants could improve the diagnostic rate. We aimed to investigate publicly available exome sequencing data and its matching transcriptomics data of phenotypically normal individuals to identify alternatively spliced variants from known genes associated with autosomal recessive disorders under the premise that some of the subjects could be carriers of such disorders. Methods: Aberrant splicing events and their triggering genomic variants were detected with the aid of Bayesian network method “SAVNet” which was originally developed for cancer genomics. Results: Forty aberrant splicing events including exon skipping, the creation of a new splice site, and the use of a cryptic splice site in response to the disruption of the authentic site were detected in 1916 genes among 31 of the 179 subjects from the 1000 Genomes Project. The predicted effects on proteins were either frameshift mutations (30) or large in-frame insertions or deletions (10). Five missense mutations and 2 silent mutations were reinterpreted as triggering major changes in transcript sequences. The detection rate of provisionally truncating pathogenic variants increased by 19%, compared with a conventional exome analysis. Conclusion: The coupling interpretation of exome and transcriptome data enhances the performance of conventional exome analyses through the proper interpretation of intronic variants that are outside of the GT/AG splicing consensus sequences and also allows the reinterpretation of “missense” or “silent” substitutions that can indeed have drastic effects on splicing.

AB - Purpose: Part of the weakness of exome analysis lies in the inability to detect aberrant splicing. An evaluation of the post-splicing mRNA sequence concurrently with genomic variants could improve the diagnostic rate. We aimed to investigate publicly available exome sequencing data and its matching transcriptomics data of phenotypically normal individuals to identify alternatively spliced variants from known genes associated with autosomal recessive disorders under the premise that some of the subjects could be carriers of such disorders. Methods: Aberrant splicing events and their triggering genomic variants were detected with the aid of Bayesian network method “SAVNet” which was originally developed for cancer genomics. Results: Forty aberrant splicing events including exon skipping, the creation of a new splice site, and the use of a cryptic splice site in response to the disruption of the authentic site were detected in 1916 genes among 31 of the 179 subjects from the 1000 Genomes Project. The predicted effects on proteins were either frameshift mutations (30) or large in-frame insertions or deletions (10). Five missense mutations and 2 silent mutations were reinterpreted as triggering major changes in transcript sequences. The detection rate of provisionally truncating pathogenic variants increased by 19%, compared with a conventional exome analysis. Conclusion: The coupling interpretation of exome and transcriptome data enhances the performance of conventional exome analyses through the proper interpretation of intronic variants that are outside of the GT/AG splicing consensus sequences and also allows the reinterpretation of “missense” or “silent” substitutions that can indeed have drastic effects on splicing.

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