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Interpretation, Stratification and Evidence for Sequence Variants Affecting mRNA Splicing in Complete Human Genome Sequences
KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
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2013 (English)In: Genomics, Proteomics and Bioinformatics, ISSN 1672-0229, Vol. 11, no 2, 77-85 p.Article in journal (Refereed) Published
Abstract [en]

Information theory-based methods have been shown to be sensitive and specific for predicting and quantifying the effects of non-coding mutations in Mendelian diseases. We present the Shannon pipeline software for genome-scale mutation analysis and provide evidence that the software predicts variants affecting mRNA splicing. Individual information contents (in bits) of reference and variant splice sites are compared and significant differences are annotated and prioritized. The software has been implemented for CLC-Bio Genomics platform. Annotation indicates the context of novel mutations as well as common and rare SNPs with splicing effects. Potential natural and cryptic mRNA splicing variants are identified, and null mutations are distinguished from leaky mutations. Mutations and rare SNPs were predicted in genomes of three cancer cell lines (U2OS, U251 and A431), which were supported by expression analyses. After filtering, tractable numbers of potentially deleterious variants are predicted by the software, suitable for further laboratory investigation. In these cell lines, novel functional variants comprised 6-17 inactivating mutations, 1-5 leaky mutations and 6-13 cryptic splicing mutations. Predicted effects were validated by RNA-seq analysis of the three aforementioned cancer cell lines, and expression microarray analysis of SNPs in HapMap cell lines.

Place, publisher, year, edition, pages
2013. Vol. 11, no 2, 77-85 p.
Keyword [en]
Genome interpretation, Information theory, MRNA splicing, Mutation, Next-generation sequencing, messenger RNA, article, cancer cell culture, computer program, controlled study, gene expression, gene mutation, gene sequence, genetic variability, genome, genome analysis, genomics, human, human cell, microarray analysis, RNA splicing, sequence analysis, single nucleotide polymorphism, Genome, Human, Humans, Point Mutation, Polymorphism, Single Nucleotide, RNA, Messenger, RNA, Neoplasm, Software
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URN: urn:nbn:se:kth:diva-134659DOI: 10.1016/j.gpb.2013.01.008PubMedID: 23499923ScopusID: 2-s2.0-84876809756OAI: diva2:678079

QC 20131211

Available from: 2013-12-11 Created: 2013-11-27 Last updated: 2013-12-11Bibliographically approved

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Costea, Paul IgorAkan, Pelin
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Gene TechnologyScience for Life Laboratory, SciLifeLab

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