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93 Publications visible to you, out of a total of 93
Responding to Stress: Diversity and Resilience of Grapevine in a Changing Climate Under the Perspective of Omics Research

Abstract (Expand)

hange, with its altered precipitation and extreme temperatures, significantly threatens global viticulture by affecting grapevine growth, yield, and fruit quality. Understanding the molecular underpinnings … of grapevine resilience is crucial for developing adaptive strategies. Our aim is to explore the application of multi-omics approaches (integrating genomics, transcriptomics, proteomics, metabolomics, and epigenetics) to investigate grapevine stress responses. Advances in these omics technologies have been pivotal in identifying key stress-response genes, metabolic pathways, and regulatory networks, particularly those contributing to grapevine tolerance to water deficiency, (such as drought and decreased precipitation), extreme temperatures, UV radiation, and salinity. Furthermore, the rich genetic reservoir within grapevines serves as a vital resource for enhancing stress tolerance. While adaptive strategies such as rootstock selection and precision irrigation are important, future research must prioritize integrated multi-omics studies, including those on regional climate adaptation and long-term breeding programs. Such efforts are essential to exploit genetic diversity and ensure the sustainability of viticulture in the evolving climate. In summary, this review demonstrates how utilizing the inherent genetic variability of grapevines and employing multi-omics approaches are critical for understanding and enhancing their resilience to the challenges posed by climate change.

Authors: Tomas Konecny, Armine Asatryan, Hans Binder

Date Published: 15th Aug 2025

Publication Type: Journal

Topology-aware pathway analysis of spatial transcriptomics

Abstract (Expand)

Spatial transcriptomics (ST) has transformed genomics by mapping gene expression onto intact tissue architecture, uncovering intricate cellular interactions that bulk and single-cell RNA sequencing … often overlook. Traditional ST workflows typically involve clustering spots, performing differential expression analyses, and annotating results via gene-set methods such as overrepresentation analysis (ORA) or gene set enrichment analysis (GSEA). More recent spatially-aware techniques extend these approaches by incorporating tissue organization into gene-set scoring. However, because they operate primarily at the level of individual genes, they may overlook the connectivity and topology of biological pathways, limiting their capacity to trace the propagation of signaling events within tissue regions. In this study, we address that gap by translating gene expression into pathway-level activity using the Pathway Signal Flow (PSF) algorithm. PSF integrates expression data with curated interaction networks to compute numeric activity scores for each branch of a biological pathway, producing a functionally annotated feature space that captures downstream signaling effects as branch-specific activity values. We applied PSF to two public 10x Genomics Visium datasets (human melanoma and mouse brain) and compared clustering based on PSF-derived pathway activities from 40 curated Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways and gene expression with standard Seurat Louvain clustering and spatially aware methods (Vesalius, spatialGE). We observed good correspondence between PSF-based and expression-based clustering when spatially aware clustering methods were used. This suggests that branch-level pathway activities can themselves drive clustering and pinpoint spatially deregulated processes. To assess cluster-specific functional annotation, we compared PSF results to conventional ORA (based on marker genes) and GSDensity (based on cluster-specific gene sets). PSF identified a broader set of significant pathways with substantial overlap with both ORA and GSDensity, providing increased sensitivity due to its branch-level resolution. We further demonstrated that PSF-derived activity values can be used to detect spatially deregulated pathway branches, yielding results comparable to those obtained with spatially aware gene set analysis approaches such as GSDensity and spatialGE. The availability of pathway topology and branch-specific information also enabled the identification of potential intercellular communication via ligand-receptor interactions between deregulated pathways in adjacent tumor regions. To support interactive exploration of results, we developed the PSF Spatial Browser, an R Shiny application for visualizing pathway activities, gene expression patterns, and deregulated pathway networks.

Authors: Siras Hakobyan, Maria Schmidt, H. Binder, A. Arakelyan

Date Published: 14th Aug 2025

Publication Type: Journal

The effects of space radiation on the transcriptome of heart right ventricle tissue

Abstract (Expand)

Deep space represents a challenging environment for human exploration and can be accompanied by harmful health-related risks. We aimed to assess the effect of simplified galactic cosmic ray simulated … (simGCRsim) and gamma (γ) ionizing radiation (IR) on transcriptome changes in right ventricular (RV) tissue after a single low dose (0.5 Gy, 500 MeV/nucleon) full body exposure in C57BL/6J male and female mice. In females, no differentially expressed genes (DEGs) and only 2 upregulated genes in males exposed to γ-IR were revealed. In contrast, exposure to simGCRsim-IR resulted in 4 DEGs in females and 371 DEGs in males, suggesting longer-lasting and sex-biased DEGs after simGCRsim-IR. Overrepresentation analysis of DEGs in simGCRsim-IR males revealed significant enrichment in pathways related to muscle contraction, hypertrophic cardiomyopathy, oxytocin release, the regulation of cytoskeleton, and genes associated with Alzheimer’s, Huntington’s, and Parkinson’s diseases. Our results suggested the RV transcriptome exhibits distinct responses after exposure based on both the IR and sex.

Authors: Roksana Zakharyan, Siras Hakobyan, Agnieszka Brojakowska, Malik Bisserier, Shihong Zhang, Mary K. Khlgatian, Amit Kumar Rai, Suren Davitavyan, Ani Stepanyan, Tamara Sirunyan, Gisane Khachatryan, Susmita Sahoo, Venkata Naga Srikanth Garikipati, Arsen Arakelyan, David A. Goukassian

Date Published: 21st Jul 2025

Publication Type: Journal

Telomere Maintenance Pathways in Lower-Grade Gliomas: Insights from Genetic Subtypes and Telomere Length Dynamics

Abstract (Expand)

Telomere maintenance mechanisms (TMMs) play a critical role in cancer biology, particularly in lower-grade gliomas (LGGs), where telomere dynamics and pathway activity remain poorly understood. In this … study, we analyzed TCGA-LGG and CGGA datasets, focusing on telomere length variations, pathway activity, and survival data across IDH subtypes. Additional validation was performed using the GEO COPD and GBM datasets, ensuring consistency in data processing and batch effect correction. Our analysis revealed significant differences in TEL pathway activation between Short- and Long-TL groups, emphasizing the central role of TERT in telomere maintenance. In contrast, ALT pathway activation displayed subtype-specific patterns, with IDH-wt tumors exhibiting the highest ALT activity, primarily driven by the RAD51 branch. Validation using CGGA data confirmed these findings, demonstrating consistent TEL and ALT pathway behaviors across datasets. Additionally, genetic subtype analysis revealed substantial telomere length variability associated with ATRX and IDH mutation status. Notably, IDHwt-ATRX WT tumors exhibited the shortest telomere length and the highest ALT pathway activity. These findings highlight distinct telomere regulatory dynamics across genetic subtypes of LGG and provide new insights into potential therapeutic strategies targeting telomere maintenance pathways.

Authors: Meline Hakobyan, Hans Binder, Arsen Arakelyan

Date Published: 28th Apr 2025

Publication Type: Journal

Transcriptome alterations in long-term mining region residents: Insights into immune response and molecular pathways.

Abstract (Expand)

Pollution with metals and metalloids is a global problem that adversely affects human health and environment. Although several studies have reported gene expression changes in response to human exposures … to metals, there are a limited number of studies exploring the effect of long-term residence in mining areas. The evidence of increased levels of several essential and non-essential metals in soil, water, and plants in Kapan mining area (Armenia) has been previously demonstrated in several environmental studies. Our study investigated the impact of long-term residence in this mining area on the transcriptome state of human peripheral blood mononuclear cells and the possible association of transcriptome changes with the blood metallome. In total, 58 participants including 27 mining region residents (MRR) and 31 non-mining region residents (NMR) were selected for our study. Transcriptomic analysis of peripheral blood mononuclear cells was performed by mRNA sequencing. Differential expression analyses were conducted using generalized linear modeling, optimized for participant demographics, cell types, and sequencing technical factors, followed by pathway analysis. The study revealed that long-term residence in a mining area is correlated with alterations in the blood transcriptome, with responses varying by sex. The identified transcriptome changes were enriched for pathways related to immune response and RNA translation. These changes correlated with higher blood levels of a mixture of non-essential metals, including arsenic, antimony, nickel, thallium, and beryllium. Additionally, the study identified differences in the transcriptome response between male and female MRR. While females exhibited a stronger immune response, males show dysregulation in ion transport and epigenetic modifications. Our findings contribute to understanding the effects of long-term residence in mining regions and can aid in developing more effective risk assessment and mitigation approaches in target populations.

Authors: A. Stepanyan, A. Arakelyan, J. Schug

Date Published: 24th Mar 2025

Publication Type: Journal

Assigning Transcriptomic Subtypes to Chronic Lymphocytic Leukemia Samples Using Nanopore RNA-Sequencing and Self-Organizing Maps.

Abstract (Expand)

Background/Objectives: Massively parallel sequencing technologies have advanced chronic lymphocytic leukemia (CLL) diagnostics and precision oncology. Illumina platforms, while offering robust performance, … require substantial infrastructure investment and a large number of samples for cost-efficiency. Conversely, third-generation long-read nanopore sequencing from Oxford Nanopore Technologies (ONT) can significantly reduce sequencing costs, making it a valuable tool in resource-limited settings. However, nanopore sequencing faces challenges with lower accuracy and throughput than Illumina platforms, necessitating additional computational strategies. In this paper, we demonstrate that integrating publicly available short-read data with in-house generated ONT data, along with the application of machine learning approaches, enables the characterization of the CLL transcriptome landscape, the identification of clinically relevant molecular subtypes, and the assignment of these subtypes to nanopore-sequenced samples. Methods: Public Illumina RNA sequencing data for 608 CLL samples were obtained from the CLL-Map Portal. CLL transcriptome analysis, gene module identification, and transcriptomic subtype classification were performed using the oposSOM R package for high-dimensional data visualization with self-organizing maps. Eight CLL patients were recruited from the Hematology Center After Prof. R. Yeolyan (Yerevan, Armenia). Sequencing libraries were prepared from blood total RNA using the PCR-cDNA sequencing-barcoding kit (SQK-PCB109) following the manufacturer's protocol and sequenced on an R9.4.1 flow cell for 24-48 h. Raw reads were converted to TPM values. These data were projected into the SOMs space using the supervised SOMs portrayal (supSOM) approach to predict the SOMs portrait of new samples using support vector machine regression. Results: The CLL transcriptomic landscape reveals disruptions in gene modules (spots) associated with T cell cytotoxicity, B and T cell activation, inflammation, cell cycle, DNA repair, proliferation, and splicing. A specific gene module contained genes associated with poor prognosis in CLL. Accordingly, CLL samples were classified into T-cell cytotoxic, immune, proliferative, splicing, and three mixed types: proliferative-immune, proliferative-splicing, and proliferative-immune-splicing. These transcriptomic subtypes were associated with survival orthogonal to gender and mutation status. Using supervised machine learning approaches, transcriptomic subtypes were assigned to patient samples sequenced with nanopore sequencing. Conclusions: This study demonstrates that the CLL transcriptome landscape can be parsed into functional modules, revealing distinct molecular subtypes based on proliferative and immune activity, with important implications for prognosis and treatment that are orthogonal to other molecular classifications. Additionally, the integration of nanopore sequencing with public datasets and machine learning offers a cost-effective approach to molecular subtyping and prognostic prediction, facilitating more accessible and personalized CLL care.

Authors: A. Arakelyan, T. Sirunyan, G. Khachatryan, S. Hakobyan, A. Minasyan, M. Nikoghosyan, M. Hakobyan, A. Chavushyan, G. Martirosyan, Y. Hakobyan, H. Binder

Date Published: 13th Mar 2025

Publication Type: Journal

Long-lasting sex-specific alteration in left ventricular cardiac transcriptome following gamma and simGCRsim radiation

Abstract (Expand)

Space irradiation (IR) is an important health risk for deep-space missions. We reported heart failure with preserved ejection fraction like cardiac phenotype 660-days following exposure to a single-dose … of a simplified galactic cosmic ray simulation (simGCRsim) only in males with functional and structural impairment in left ventricular (LV) function. This sex-based dichotomy prompted us to investigate sex-specific changes in the LV transcriptome in three-month-old male and female mice exposed to 137Cs-γ- or simGCRsim-IR. Non-IR male and female (10 each) mice served as controls. LVs were collected at 440/660- and 440/550-days post-IR, male and female, respectively. RNA sequencing, differential gene expression, and functional annotation were performed on tissues from 5 mice/group. Sex and post-IR time points had the greatest influence on gene expression, surpassing the IR-type effects. SimGCRsim-IR showed more persistent transcriptome changes than γ-IR. We suggest that the single IR effects can persist up to 550-660 days, with overwhelmingly sex-biased responses at individual gene expression level.

Authors: Roksana Zakharyan, Siras Hakobyan, Agnieszka Brojakowska, Suren Davitavyan, Ani Stepanyan, Tamara Sirunyan, Gisane Khachatryan, Mary K. Khlgatian, Malik Bisserier, Shihong Zhang, Susmita Sahoo, Lahouaria Hadri, Venkata Naga Srikanth Garikipati, Arsen Arakelyan, David A. Goukassian

Date Published: 18th Feb 2025

Publication Type: Journal

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