Filter and export

Publications

What is a Publication?
2 Publications visible to you, out of a total of 2
Wild grapes of Armenia: unexplored source of genetic diversity and disease resistance.

Abstract (Expand)

The present study is the first in-depth research evaluating the genetic diversity and potential resistance of Armenian wild grapes utilizing DNA-based markers to understand the genetic signature of … this unexplored germplasm. In the proposed research, five geographical regions with known viticultural history were explored. A total of 148 unique wild genotypes were collected and included in the study with 48 wild individuals previously collected as seed. A total of 24 nSSR markers were utilized to establish a fingerprint database to infer information on the population genetic diversity and structure. Three nSSR markers linked to the Ren1 locus were analyzed to identify potential resistance against powdery mildew. According to molecular fingerprinting data, the Armenian V. sylvestris gene pool conserves a high genetic diversity, displaying 292 different alleles with 12.167 allele per loci. The clustering analyses and diversity parameters supported eight genetic groups with 5.6% admixed proportion. The study of genetic polymorphism at the Ren1 locus revealed that 28 wild genotypes carried three R-alleles and 34 wild genotypes carried two R-alleles associated with PM resistance among analyzed 107 wild individuals. This gene pool richness represents an immense reservoir of under-explored genetic diversity and breeding potential. Therefore, continued survey and research efforts are crucial for the conservation, sustainable management, and utilization of Armenian wild grape resources in the face of emerging challenges in viticulture.

Authors: K. Margaryan, R. Topfer, B. Gasparyan, A. Arakelyan, O. Trapp, F. Rockel, E. Maul

Date Published: 25th Dec 2023

Publication Type: Journal

Machine learning extracts marks of thiamine's role in cold acclimation in the transcriptome of Vitis vinifera.

Abstract (Expand)

INTRODUCTION: The escalating challenge of climate change has underscored the critical need to understand cold defense mechanisms in cultivated grapevine Vitis vinifera. Temperature variations can affect … the growth and overall health of vine. METHODS: We used Self Organizing Maps machine learning method to analyze gene expression data from leaves of five Vitis vinifera cultivars each treated by four different temperature conditions. The algorithm generated sample-specific "portraits" of the normalized gene expression data, revealing distinct patterns related to the temperature conditions applied. RESULTS: Our analysis unveiled a connection with vitamin B1 (thiamine) biosynthesis, suggesting a link between temperature regulation and thiamine metabolism, in agreement with thiamine related stress response established in Arabidopsis before. Furthermore, we found that epigenetic mechanisms play a crucial role in regulating the expression of stress-responsive genes at low temperatures in grapevines. DISCUSSION: Application of Self Organizing Maps portrayal to vine transcriptomics identified modules of coregulated genes triggered under cold stress. Our machine learning approach provides a promising option for transcriptomics studies in plants.

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

Date Published: 21st Dec 2023

Publication Type: Journal

Powered by
 (v.1.15.0-main)
About ArmLifeBank | Funding and Programmes | Credits
Copyright © 2008 - 2024 The University of Manchester and HITS gGmbH