N.A. Ermolenko - Junior Research Scientist, Laboratory of Pharmacogenomics, Institute of Chemical Biology and Fun-damental Medicine Siberian Branch of the Russian Academy of Sciences (ICBFM SB RAS), Novosibirsk U.A. Boyarskykh - Ph.D. (Biol.), Junior Research Scientist, Laboratory of Pharmacogenomics, Institute of Chemical Biology and Fundamental Medicine Siberian Branch of the Russian Academy of Sciences (ICBFM SB RAS), Novosibirsk. E-mail: boyarskih.u@gmail.com A.A. Kechin - Post-graduate Student, Laboratory of Pharmacogenomics, Institute of Chemical Biology and Fundamental Medicine Siberian Branch of the Russian Academy of Sciences (ICBFM SB RAS), Novosibirsk State University. E-mail: a.a.kechin@gmail.com A.F. Lazarev - Dr.Sc. (Med.), Professor, Altai branch N.N. Blokhin Russian Cancer Research Center. E-mail: aoc@ab.ru V.D. Petrova - Ph.D. (Med.), Altai branch N.N. Blokhin Russian Cancer Research Center. E-mail: valent_04@mail.ru A.M. Mazitova  Student, Kazan Federal University. E-mail: sashamazitova@mail.ru N.E. Kushlinskii - Dr.Sc. (Med.), Professor, Head of the Clinical Biochemistry Laboratory, N.N. Blokhin Russian Cancer Research Center, Moscow. E-mail: biochimia@mtu-net.ru M.L. Philipenko - Ph.D. (Biol.), Head of the laboratory of pharmacogenomics, Institute of Chemical Biology and Funda-mental Medicine Siberian branch of the Russian Academy of Sciences, Novosibirsk. E-mail: mlfilipenko@gmail.co

The aim of this study was to evaluate the Illumina MiSeq massively parallel sequencing platform for routine clinical prac-tice. We implemented an amplicon-based method of the BRCA1 and BRCA2 genes resequencing to identify disease-causing mutations in hereditary breast cancer (HBC) patients. To analyze the results we designed our own workflow based on a combination of the freely available softwares. The study design included two parts. Firstly, we developed data analysis workflow by testing of a «training samples» (16 DNA samples with known BRCA1 and BRCA2 exons sequence). Secondly, the workflow was validated in a set of 80 samples from HBC patients. In order to determine variants, our workflow includes a set of filters: sequencing depth (>20%), variant allele frequency (>14%), FS (Phred-scased p-value using Fisher-s exact test to detect strand bias) and variant Quality (Q-score). As a result, 46 unique variants there were identified. Using the 1000 Genomes Project as a comparison group we determined nine nonsynonymous rare (allele frequency <0,001 in 1000 Genomes Project) mutations: (g. 41246297A→C, g. 41226488C→A, g. 41256236_41256237delGG, g. 32930673C→T, g. 32893369G→C, g. 32906593C→A, g. 32907129T→C, g. 32914151A→G, g. 32929242_32929243delAG; coordinates specified for GRCh37). We assume this variants may be disease-causing mutations in (HBC) patients g. 41246297A→C, g. 41226488C→A, g. 41256236_41256237delGG (gene BRCA1), g. 32930673C→T, g. 32893369G→C, g. 32906593C→A, g. 32907129T→C, g. 32914151A→G, g. 32929242_32929243delAG (gene BRCA2). The workflow developed in this study con-forms the sensitivity (98.6%) and specificity (94.4%) requirements for the clinical application and may be useful for genetic diagnosis of HBCS.

 

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