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3 Publications visible to you, out of a total of 3
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

Unveiling Iso- and Aniso-Hydric Disparities in Grapevine-A Reanalysis by Transcriptome Portrayal Machine Learning.

Abstract (Expand)

Mechanisms underlying grapevine responses to water(-deficient) stress (WS) are crucial for viticulture amid escalating climate change challenges. Reanalysis of previous transcriptome data uncovered … disparities among isohydric and anisohydric grapevine cultivars in managing water scarcity. By using a self-organizing map (SOM) transcriptome portrayal, we elucidate specific gene expression trajectories, shedding light on the dynamic interplay of transcriptional programs as stress duration progresses. Functional annotation reveals key pathways involved in drought response, pinpointing potential targets for enhancing drought resilience in grapevine cultivation. Our results indicate distinct gene expression responses, with the isohydric cultivar favoring plant growth and possibly stilbenoid synthesis, while the anisohydric cultivar engages more in stress response and water management mechanisms. Notably, prolonged WS leads to converging stress responses in both cultivars, particularly through the activation of chaperones for stress mitigation. These findings underscore the importance of understanding cultivar-specific WS responses to develop sustainable viticultural strategies in the face of changing climate.

Authors: T. Konecny, A. Asatryan, M. Nikoghosyan, H. Binder

Date Published: 6th Sep 2024

Publication Type: Journal

Machine learned-based visualization of the diversity of grapevine genomes worldwide and in Armenia using SOMmelier

Abstract (Expand)

In the proposed study three major issues have been addressed: Firstly, the diversity of grapevine accessions worldwide and particularly in Armenia, a small country located in the largely volcanic … Armenian Highlands, is incredibly rich in cultivated and especially wild grapes; secondly, the information hidden in their (whole) genomes, e.g., about the domestication history of grapevine over the last 11,000 years and phenotypic traits such as cultivar utilization and a putative resistance against powdery mildew, and, thirdly machine learning methods to extract and to visualize this information in an easy to percept way. We shortly describe the Self Origanizing Maps (SOM) portrayal method called “SOMmelier” (as the vine-genome “waiter”) and illustrate its power by applying it to whole genome data of hundreds of grapevine accessions. We also give a short outlook on possible future directions of machine learning in grapevine transcriptomics and ampelogaphy.

Authors: Kristina Magaryan, Maria Nikogհosyan, Anush Baloyan, Hripsime Gasoyan, Emma Hovhannisyan, Levon Galstyan, Tomas Konecny, Arsen Arakelyan, Hans Binder

Date Published: 6th Dec 2023

Publication Type: Journal

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