Dataset Information

Genomic structural variations for cardiovascular and metabolic comorbidity.

ABSTRACT: The objective of this study was to identify genes targeted by both copy number and copy-neutral changes in the right coronary arteries in the area of advanced atherosclerotic plaques and intact internal mammary arteries derived from the same individuals with comorbid coronary artery disease and metabolic syndrome. The artery samples from 10 patients were screened for genomic imbalances using array comparative genomic hybridization. Ninety high-confidence, identical copy number variations (CNVs) were detected. We also identified eight copy-neutral changes (cn-LOHs)?>?1.5?Mb in paired arterial samples in 4 of 10 individuals. The frequencies of the two gains located in the 10q24.31 (ERLIN1) and 12q24.11 (UNG, ACACB) genomic regions were evaluated in 33 paired arteries and blood samples. Two patients contained the gain in 10q24.31 (ERLIN1) and one patient contained the gain in 12q24.11 (UNG, ACACB) that affected only the blood DNA. An additional two patients harboured these CNVs in both the arteries and blood. In conclusion, we discovered and confirmed a gain of the 10q24.31 (ERLIN1) and 12q24.11 (UNG, ACACB) genomic regions in patients with coronary artery disease and metabolic comorbidity. Analysis of DNA extracted from blood indicated a possible somatic origin for these CNVs.

SUBMITTER: Nazarenko MS

PROVIDER: S-EPMC5264603 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Genomic structural variations for cardiovascular and metabolic comorbidity.

Nazarenko Maria S MS Sleptcov Aleksei A AA Lebedev Igor N IN Skryabin Nikolay A NA Markov Anton V AV Golubenko Maria V MV Koroleva Iuliia A IA Kazancev Anton N AN Barbarash Olga L OL Puzyrev Valery P VP

Scientific reports 20170125

The objective of this study was to identify genes targeted by both copy number and copy-neutral changes in the right coronary arteries in the area of advanced atherosclerotic plaques and intact internal mammary arteries derived from the same individuals with comorbid coronary artery disease and metabolic syndrome. The artery samples from 10 patients were screened for genomic imbalances using array comparative genomic hybridization. Ninety high-confidence, identical copy number variations (CNVs) ...[more]

PMID: 28120895

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Project description:BackgroundRecent studies have demonstrated the genetic significance of insertions, deletions, and other more complex structural variants (SVs) in the human population. With the development of the next-generation sequencing technologies, high-throughput surveys of SVs on the whole-genome level have become possible. Here we present split-read identification, calibrated (SRiC), a sequence-based method for SV detection.ResultsWe start by mapping each read to the reference genome in standard fashion using gapped alignment. Then to identify SVs, we score each of the many initial mappings with an assessment strategy designed to take into account both sequencing and alignment errors (e.g. scoring more highly events gapped in the center of a read). All current SV calling methods have multilevel biases in their identifications due to both experimental and computational limitations (e.g. calling more deletions than insertions). A key aspect of our approach is that we calibrate all our calls against synthetic data sets generated from simulations of high-throughput sequencing (with realistic error models). This allows us to calculate sensitivity and the positive predictive value under different parameter-value scenarios and for different classes of events (e.g. long deletions vs. short insertions). We run our calculations on representative data from the 1000 Genomes Project. Coupling the observed numbers of events on chromosome 1 with the calibrations gleaned from the simulations (for different length events) allows us to construct a relatively unbiased estimate for the total number of SVs in the human genome across a wide range of length scales. We estimate in particular that an individual genome contains ~670,000 indels/SVs.ConclusionsCompared with the existing read-depth and read-pair approaches for SV identification, our method can pinpoint the exact breakpoints of SV events, reveal the actual sequence content of insertions, and cover the whole size spectrum for deletions. Moreover, with the advent of the third-generation sequencing technologies that produce longer reads, we expect our method to be even more useful.

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Dataset Information

Genomic structural variations for cardiovascular and metabolic comorbidity.

Publications

Genomic structural variations for cardiovascular and metabolic comorbidity.

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