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A Novel Approach for the Identification of Pharmacogenetic Variants in MT-RNR1 through Next-Generation Sequencing Off-Target Data.

ABSTRACT: Specific genetic variants in the mitochondrially encoded 12S ribosomal RNA gene (MT-RNR1) cause aminoglycoside-induced irreversible hearing loss. Mitochondrial DNA is usually not included in targeted sequencing experiments; however, off-target data may deliver this information. Here, we extract MT-RNR1 genetic variation, including the most relevant ototoxicity variant m.1555A>G, using the off-target reads of 473 research samples, sequenced through a capture-based, custom-targeted panel and whole exome sequencing (WES), and of 1245 diagnostic samples with clinical WES. Sanger sequencing and fluorescence-based genotyping were used for genotype validation. There was a correlation between off-target reads and mitochondrial coverage (rcustomPanel = 0.39, p = 2 × 10-13 and rWES = 0.67, p = 7 × 10-21). The median read depth of MT-RNR1 m.1555 was similar to the average mitochondrial genome coverage, with saliva and blood samples giving comparable results. The genotypes from 415 samples, including three m.1555G carriers, were concordant with fluorescence-based genotyping data. In clinical WES, median MT-RNR1 coverage was 56×, with 90% of samples having ?20 reads at m.1555 position, and one m.1494T and three m.1555G carriers were identified with no evidence for heteroplasmy. Altogether, this study shows that obtaining MT-RNR1 genotypes through off-target reads is an efficient strategy that can impulse preemptive pharmacogenetic screening of this mitochondrial gene.

SUBMITTER: Lanillos J

PROVIDER: S-EPMC7408883 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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A Novel Approach for the Identification of Pharmacogenetic Variants in MT-RNR1 through Next-Generation Sequencing Off-Target Data.

Lanillos Javier J Santos María M Carcajona Marta M Roldan-Romero Juan María JM Martinez Angel M AM Calsina Bruna B Monteagudo María M Leandro-García Luis Javier LJ Montero-Conde Cristina C Cascón Alberto A Maietta Paolo P Alvarez Sara S Robledo Mercedes M Rodriguez-Antona Cristina C

Journal of clinical medicine 20200702 7

Specific genetic variants in the mitochondrially encoded 12S ribosomal RNA gene (MT-RNR1) cause aminoglycoside-induced irreversible hearing loss. Mitochondrial DNA is usually not included in targeted sequencing experiments; however, off-target data may deliver this information. Here, we extract MT-RNR1 genetic variation, including the most relevant ototoxicity variant m.1555A>G, using the off-target reads of 473 research samples, sequenced through a capture-based, custom-targeted p ...[more]

PMID: 32630724

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Project description:BACKGROUND: Excretory/secretory proteins (ESPs) play a major role in parasitic infection as they are present at the host-parasite interface and regulate host immune system. In case of parasitic helminths, transcriptomics has been used extensively to understand the molecular basis of parasitism and for developing novel therapeutic strategies against parasitic infections. However, none of transcriptomic studies have extensively covered ES protein prediction for identifying novel therapeutic targets, especially as parasites adopt non-classical secretion pathways. RESULTS: We developed a semi-automated computational approach for prediction and annotation of ES proteins using transcriptomic data from next generation sequencing platforms. For the prediction of non-classically secreted proteins, we have used an improved computational strategy, together with homology matching to a dataset of experimentally determined parasitic helminth ES proteins. We applied this protocol to analyse 454 short reads of parasitic nematode, Strongyloides ratti. From 296231 reads, we derived 28901 contigs, which were translated into 20877 proteins. Based on our improved ES protein prediction pipeline, we identified 2572 ES proteins, of which 407 (1.9%) proteins have classical N-terminal signal peptides, 923 (4.4%) were computationally identified as non-classically secreted while 1516 (7.26%) were identified by homology to experimentally identified parasitic helminth ES proteins. Out of 2572 ES proteins, 2310 (89.8%) ES proteins had homologues in the free-living nematode Caenorhabditis elegans and 2220 (86.3%) in parasitic nematodes. We could functionally annotate 1591 (61.8%) ES proteins with protein families and domains and establish pathway associations for 691 (26.8%) proteins. In addition, we have identified 19 representative ES proteins, which have no homologues in the host organism but homologous to lethal RNAi phenotypes in C. elegans, as potential therapeutic targets. CONCLUSION: We report a comprehensive approach using freely available computational tools for the secretome analysis of NGS data. This approach has been applied to S. ratti 454 transcriptomic data for in silico excretory/secretory proteins prediction and analysis, providing a foundation for developing new therapeutic solutions for parasitic infections.

Dataset Information

A Novel Approach for the Identification of Pharmacogenetic Variants in MT-RNR1 through Next-Generation Sequencing Off-Target Data.

Publications

A Novel Approach for the Identification of Pharmacogenetic Variants in <i>MT-RNR1</i> through Next-Generation Sequencing Off-Target Data.

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