NDLI: PON-mt-tRNA: a multifactorial probability-based method for classification of mitochondrial tRNA variations

Content Provider	PubMed Central
Author	Abhishek, Niroula Vihinen, Mauno
Copyright Year	2016
Abstract	Transfer RNAs (tRNAs) are essential for encoding the transcribed genetic information from DNA into proteins. Variations in the human tRNAs are involved in diverse clinical phenotypes. Interestingly, all pathogenic variations in tRNAs are located in mitochondrial tRNAs (mt-tRNAs). Therefore, it is crucial to identify pathogenic variations in mt-tRNAs for disease diagnosis and proper treatment. We collected mt-tRNA variations using a classification based on evidence from several sources and used the data to develop a multifactorial probability-based prediction method, PON-mt-tRNA, for classification of mt-tRNA single nucleotide substitutions. We integrated a machine learning-based predictor and an evidence-based likelihood ratio for pathogenicity using evidence of segregation, biochemistry and histochemistry to predict the posterior probability of pathogenicity of variants. The accuracy and Matthews correlation coefficient (MCC) of PON-mt-tRNA are 1.00 and 0.99, respectively. In the absence of evidence from segregation, biochemistry and histochemistry, PON-mt-tRNA classifies variations based on the machine learning method with an accuracy and MCC of 0.69 and 0.39, respectively. We classified all possible single nucleotide substitutions in all human mt-tRNAs using PON-mt-tRNA. The variations in the loops are more often tolerated compared to the variations in stems. The anticodon loop contains comparatively more predicted pathogenic variations than the other loops. PON-mt-tRNA is available at http://structure.bmc.lu.se/PON-mt-tRNA/.
Related Links	http://dx.doi.org/10.1093/nar/gkw046
Ending Page	2027
Page Count	8
Starting Page	2020
File Format	PDF
ISSN	13624962
e-ISSN	13624962
Journal	Nucleic Acids Research
Issue Number	5
Volume Number	44
Language	English
Publisher	Oxford University Press
Publisher Date	2016-03-18
Access Restriction	Open
Rights Holder	Oxford University Press
Subject Keyword	Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Genetics

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