Title
Correlation-based network analysis combined with machine learning techniques highlight the role of the GABA shunt in Brachypodium sylvaticum freezing tolerance
Date Issued
01 December 2020
Access level
open access
Resource Type
journal article
Author(s)
Sade N.
Liu L.
Rubio Wilhelmi M.d.M.
Brotman Y.
Luzarowska U.
Vogel J.P.
Blumwald E.
University of California
Publisher(s)
Nature Research
Abstract
Perennial grasses will account for approximately 16 billion gallons of renewable fuels by the year 2022, contributing significantly to carbon and nitrogen sequestration. However, perennial grasses productivity can be limited by severe freezing conditions in some geographical areas, although these risks could decrease with the advance of climate warming, the possibility of unpredictable early cold events cannot be discarded. We conducted a study on the model perennial grass Brachypodium sylvaticum to investigate the molecular mechanisms that contribute to cold and freezing adaption. The study was performed on two different B. sylvaticum accessions, Ain1 and Osl1, typical to warm and cold climates, respectively. Both accessions were grown under controlled conditions with subsequent cold acclimation followed by freezing stress. For each treatment a set of morphological parameters, transcription, metabolite, and lipid profiles were measured. State-of-the-art algorithms were employed to analyze cross-component relationships. Phenotypic analysis revealed higher adaption of Osl1 to freezing stress. Our analysis highlighted the differential regulation of the TCA cycle and the GABA shunt between Ain1 and Osl1. Osl1 adapted to freezing stress by repressing the GABA shunt activity, avoiding the detrimental reduction in fatty acid biosynthesis and the concomitant detrimental effects on membrane integrity.
Volume
10
Issue
1
Number
4489
Language
English
OCDE Knowledge area
Biotecnología agrícola, Biotecnología alimentaria
Scopus EID
2-s2.0-85081693406
PubMed ID
Source
Scientific Reports
ISSN of the container
20452322
Sponsor(s)
This work was supported by the US Department of Energy, Office of Science, Office of Biological and Environmental Research under Award Number DE-SC0008797 and by the Will W. Lester Endowment from the University of California.
Sources of information:
Directorio de Producción Científica
Scopus