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Plausible association between drought stress tolerance of barley (Hordeum vulgare L.) and programmed cell death via MC1 and TSN1 genes
Department of Agriculture and Natural Resources, Higher Education Center of Eghlid, Eghlid, Iran.
University of Skövde, School of Bioscience. University of Skövde, Systems Biology Research Environment. (Translationell bioinformatik, Translational Bioinformatics)ORCID iD: 0000-0003-1837-429X
Department of Crop Production and Plant Breeding, Shiraz University, Shiraz, Iran.
National Salinity Research Center, Agricultural Research, Education and Extension Organization, Yazd, Iran.
2020 (English)In: Physiologia Plantarum, ISSN 0031-9317, E-ISSN 1399-3054, Vol. 170, no 1, p. 46-59Article in journal (Refereed) Published
Abstract [en]

Studying the drought-responsive transcriptome is of high interest as it can serve as a blueprint for stress adaptation strategies. Despite extensive studies in this area, there are still many details to be uncovered, such as the importance of each gene involved in the stress response as well as the relationship between these genes and the physiochemical processes governing stress tolerance. This study was designed to address such important details and to gain insights into molecular responses of barley (Hordeum vulgare L.) to drought stress. To that, we combined RNA-seq data analysis with field and greenhouse drought experiments in a systems biology approach. RNA-sequence analysis identified a total of 665 differentially expressed genes (DEGs) belonging to diverse functional categories. A gene network was derived from the DEGs, which comprised of a total of 131 nodes and 257 edges. Gene network topology analysis highlighted two programmed cell death (PCD) modulating genes, MC1 (metacaspase 1) and TSN1 (Tudor-SN 1), as important (hub) genes in the predicted network. Based on the field trial, a drought-tolerant and a drought-susceptible barley genotype was identified from eight tested cultivars. Identified genotypes exhibited different physiochemical characteristics, including proline content, chlorophyll concentration, percentage of electrolyte leakage and malondialdehyde content as well as expression profiles of MC1 and TSN1 genes. Machine learning and correspondence analysis revealed a significant relationship between drought tolerance and measured characteristics in the context of PCD. Our study provides new insights which bridge barley drought tolerance to PCD through MC1 and TSN1 pathway.

Place, publisher, year, edition, pages
John Wiley & Sons, 2020. Vol. 170, no 1, p. 46-59
National Category
Genetics
Research subject
Bioinformatics
Identifiers
URN: urn:nbn:se:his:diva-18411DOI: 10.1111/ppl.13102ISI: 000526701900001PubMedID: 32246464Scopus ID: 2-s2.0-85083302349OAI: oai:DiVA.org:his-18411DiVA, id: diva2:1427652
Available from: 2020-04-30 Created: 2020-04-30 Last updated: 2022-05-10Bibliographically approved

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Lindlöf, Angelica

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