eDAVE - Extension of GDC data analysis, visualization, and exploration tools.

Publicly available repositories such as Genomic Data Commons or Gene Expression Omnibus are a valuable research resource useful for hypothesis driven research as well as validation of the results of new experiments. Frequently however, the use of those opulent resources is challenging because advanced computational skills are required to mine deposited data. To address this challenge, we have developed eDAVE, a user-friendly, web and desktop interface enabling intuitive and robust analysis of almost 12 000 methylomes and transcriptomes from over 200 types of cells and tissues deposited in the Genomic Data Commons repository. The application is implemented in Python, supported for major browsers and available at: https://edave.pum.edu.pl/.

Identified in blood diet-related methylation changes stratify liver biopsies of NAFLD patients according to fibrosis grade.

BACKGROUND: High caloric diet and lack of physical activity are considered main causes of NAFLD, and a change in the diet is still the only effective treatment of this disease. However, molecular mechanism of the effectiveness of diet change in treatment of NAFLD is poorly understood. We aimed to assess the involvement of epigenetic mechanisms of gene expression regulation in treatment of NAFLD. Eighteen participants with medium- to high-grade steatosis were recruited and trained to follow the Mediterranean diet modified to include fibre supplements. At three timepoints (baseline, after 30 and 60 days), we evaluated adherence to the diet and measured a number of physiological parameters such as anthropometry, blood and stool biochemistry, liver steatosis and stiffness. We also collected whole blood samples for genome-wide methylation profiling and histone acetylation assessment. RESULTS: The diet change resulted in a decrease in liver steatosis along with statistically significant, but a minor change in BMI and weight of our study participants. The epigenetic profiling of blood cells identified significant genome-wide changes of methylation and acetylation with the former not involving regions directly regulating gene expression. Most importantly, we were able to show that identified blood methylation changes occur also in liver cells of NAFLD patients and the machine learning-based classifier that we build on those methylation changes was able to predict the stage of liver fibrosis with ROC AUC = 0.9834. CONCLUSION: Methylomes of blood cells from NAFLD patients display a number of changes that are most likely a consequence of unhealthy diet, and the diet change appears to reverse those epigenetic changes. Moreover, the methylation status at CpG sites undergoing diet-related methylation change in blood cells stratifies liver biopsies from NAFLD patients according to fibrosis grade.

Epigenetic activation of antiviral sensors and effectors of interferon response pathways during SARS-CoV-2 infection.

Recent studies have shown that methylation changes identified in blood cells of COVID-19 patients have a potential to be used as biomarkers of SARS-CoV-2 infection outcomes. However, different studies have reported different subsets of epigenetic lesions that stratify patients according to the severity of infection symptoms, and more importantly, the significance of those epigenetic changes in the pathology of the infection is still not clear. We used methylomics and transcriptomics data from the largest so far cohort of COVID-19 patients from four geographically distant populations, to identify casual interactions of blood cells' methylome in pathology of the COVID-19 disease. We identified a subset of methylation changes that is uniformly present in all COVID-19 patients regardless of symptoms. Those changes are not present in patients suffering from upper respiratory tract infections with symptoms similar to COVID-19. Most importantly, the identified epigenetic changes affect the expression of genes involved in interferon response pathways and the expression of those genes differs between patients admitted to intensive care units and only hospitalized. In conclusion, the DNA methylation changes involved in pathophysiology of SARS-CoV-2 infection, which are specific to COVID-19 patients, can not only be utilized as biomarkers in the disease management but also present a potential treatment target.

Methylation levels assessment with Methylation-Sensitive High-Resolution Melting (MS-HRM).

Testing for disease-related DNA methylation changes provides clinically relevant information in personalized patient care. Methylation-Sensitive High-Resolution Melting (MS-HRM) is a method used for measuring methylation changes and has already been used in diagnostic settings. This method utilizes one set of primers that initiate the amplification of both methylated and non-methylated templates. Therefore, the quantification of the methylation levels using MS-HRM is hampered by the PCR bias phenomenon. Some approaches have been proposed to calculate the methylation level of samples using the high-resolution melting (HRM) curves. However, limitations of the methylation calculation using MS-HRM have not been evaluated systematically and comprehensively. We used the Area Under the Curve (AUC), a derivative of the HRM curves, and least square approximation (LSA) to establish a procedure that allowed us to infer methylation levels in an MS-HRM experiment and assess the limitations of that procedure for the assays' specific methylation level measurement. The developed procedure allowed, with certain limitations, estimation of the methylation levels using HRM curves.

Long-Term Treatment with Bortezomib Induces Specific Methylation Changes in Differentiated Neuronal Cells.

Bortezomib (BTZ) is proteasome inhibitor, effectively used in the treatment of multiple myeloma, but frequently discontinued due to peripheral neuropathy, which develops in patients after consecutive treatment cycles. The molecular mechanisms affected by BTZ in neuronal cells, which result in neuropathy, remain unknown. However, BTZ is unlikely to lead to permanent morphological nerve damage, because neuropathy reverses after discontinuation of treatment, and nerve cells have very limited renewal capacity. We have previously shown that BTZ induces methylation changes in SH-SY5Y cells, which take part in the development of treatment resistance. Here, we hypothesized that BTZ affects the methylomes of mature neurons, and these changes are associated with BTZ neurotoxicity. Thus, we studied methylomes of neuronal cells, differentiated from the LUHMES cell line, after cycles of treatment with BTZ. Our results show that BTZ induces specific methylation changes in mature neurons, which are not present in SH-SY5Y cells after BTZ treatment. These changes appear to affect genes involved in morphogenesis, neurogenesis, and neurotransmission. Furthermore, identified methylation changes are significantly enriched within binding sites of transcription factors previously linked to neuron physiology, including EBF, PAX, DLX, LHX, and HNF family members. Altogether, our results indicate that methylation changes are likely to be involved in BTZ neurotoxicity.

How Machine Learning Methods Helped Find Putative Rye Wax Genes Among GBS Data.

The standard approach to genetic mapping was supplemented by machine learning (ML) to establish the location of the rye gene associated with epicuticular wax formation (glaucous phenotype). Over 180 plants of the biparental F2 population were genotyped with the DArTseq (sequencing-based diversity array technology). A maximum likelihood (MLH) algorithm (JoinMap 5.0) and three ML algorithms: logistic regression (LR), random forest and extreme gradient boosted trees (XGBoost), were used to select markers closely linked to the gene encoding wax layer. The allele conditioning the nonglaucous appearance of plants, derived from the cultivar Karlikovaja Zelenostebelnaja, was mapped at the chromosome 2R, which is the first report on this localization. The DNA sequence of DArT-Silico 3585843, closely linked to wax segregation detected by using ML methods, was indicated as one of the candidates controlling the studied trait. The putative gene encodes the ABCG11 transporter.