👤 Ivan Vlasov

A variety of techniques for DNA sequencing, such as specific gene sequencing, whole genome sequencing, or exome sequencing, are currently used to detect single nucleotide variations (SNVs). Although RNA-seq can be used to identify SNVs, studies that employ this approach are uncommon, and those that do often rely on outdated mapping methods or methods that are more suitable for genomic and exomic alignment. In this work, our aim is to apply modern RNA-seq specific alignment method in order to identify SNV in a cohort of HCMP patients, and characterize those SNV to gain insight into possible mechanisms of HCMP pathogenesis. The algorithm of identification of SNV based on transcriptomic sequencing data has been developed and evaluated. The algorithm was evaluated and the optimal quality threshold was determined based on allelic discrimination for the rs397516037 mutation (MYBPC3 c.3697 C > T) among patients. A total of 42,809 SNVs with a quality of 75 or higher were identified in 48 transcriptomes of hypertrophic cardiomyopathy (HCMP) myocardial tissue. Verification of missense and nonsense variants in key HCMP genes using Sanger sequencing confirmed the accuracy of the pipeline results. To identify variants potentially associated with HCMP pathogenesis, a filtration process was conducted based on minor allele frequency, substitution prediction score and ClinVar outcome. 214 missense mutations and 6 nonsense mutations were selected. Together with nonsense mutations, 19 mutations meeting the strictest SIFT and PolypPhen criteria were identified as potential factors influencing HCMP pathogenesis. We have developed and validated a method for identifying SNVs based on transcriptomic data, which can be used to identify putative pathogenic variants. We identified mutations in key HCMP genes MYBPC3 and MYH7 in a cohort of patients. We also found potentially pathologic mutations in genes ANXA6 and FEM1 A and obtained data supporting the role of NEBL in myocardial diseases. This method would be useful in analyzing transcriptomic data available in the Gene Expression Omnibus, but should be used with caution as we have tested it on a specific disease. Show less

The same pathway, such as the mitogen-activated protein kinase (MAPK) pathway, can produce different cellular responses, depending on stimulus or cell type. We examined the phosphorylation dynamics of the MAPK kinase MEK and its targets extracellular signal-regulated kinase 1 and 2 (ERK1/2) in primary hepatocytes and the transformed keratinocyte cell line HaCaT A5 exposed to either hepatocyte growth factor or interleukin-6. By combining quantitative mass spectrometry with dynamic modeling, we elucidated network structures for the reversible threonine and tyrosine phosphorylation of ERK in both cell types. In addition to differences in the phosphorylation and dephosphorylation reactions, the HaCaT network model required two feedback mechanisms, which, as the experimental data suggested, involved the induction of the dual-specificity phosphatase DUSP6 and the scaffold paxillin. We assayed and modeled the accumulation of the double-phosphorylated and active form of ERK1/2, as well as the dynamics of the changes in the monophosphorylated forms of ERK1/2. Modeling the differences in the dynamics of the changes in the distributions of the phosphorylated forms of ERK1/2 suggested that different amounts of MEK activity triggered context-specific responses, with primary hepatocytes favoring the formation of double-phosphorylated ERK1/2 and HaCaT A5 cells that produce both the threonine-phosphorylated and the double-phosphorylated form. These differences in phosphorylation distributions explained the threshold, sensitivity, and saturation of the ERK response. We extended the findings of differential ERK phosphorylation profiles to five additional cultured cell systems and matched liver tumor and normal tissue, which revealed context-specific patterns of the various forms of phosphorylated ERK. Show less