Proteomic data from leaves of twenty-four sunflower genotypes under water deficit

Thierry Balliau,Nicolas B Langlade,Michel Zivy,Mélisande Blein-Nicolas,Harold Duruflé,Nicolas Blanchet

doi:10.1051/ocl/2020074

Abstract

This article describes a proteomic data set produced from sunflower plants subjected to water deficit. Twenty-four sunflower genotypes were selected to represent genetic diversity within cultivated sunflower. They included both inbred lines and their hybrids. Water deficit was applied to plants in pots at the vegetative stage using the high-throughput phenotyping platform Heliaphen. We present here the identification of 3062 proteins and the quantification of 1211 of them in the leaves of the 24 genotypes grown under two watering conditions. These data allow the study of both the effects of genetic variations and watering conditions. They constitute a valuable resource for the community to study adaptation of crops to drought and the molecular basis of heterosis.

Highlights

Résumé – Données protéomiques produites à partir de vingt-quatre génotypes de tournesol soumis à un déficit hydrique
It is promising for agriculture adaptation to climate change as it can maintain yield better than most other crops in a wide range of environments, especially during drought stress (Debaeke and Bertrand, 2008; Debaeke et al, 2017)
Different ecophysiological traits were measured on these plants (Blanchet et al, 2018), making it possible to study the relationships between protein expression and plant traits as a function of water stress and heterozygosity. This dataset provides identification and quantification data for proteins of sunflower leaves from 142 plants distributed in 24 genotypes grown in water deficit (WD) or well watered (WW) conditions with 3 replicates

Summary

Data accessibility Related research article

Biology Proteomics Peptide and protein identification; protein quantification Mass spectrometry (LC-MS) mzXML open format for raw mass spectrometry data; opendocument format for protein identification (.ods file); R data file for protein quantification (.RData file) 24 genotypes of Helianthus annuus in two environmental conditions (irrigated or not) with 3 replicates Identification and quantification of sunflower leaf proteins The outdoor Heliaphen phenotyping platform at the Institut national de la recherche agronomique (INRA) station, Auzeville, France (43°31’41.8”N, 1°29’58.6”E) These data are publicly available in ProticDB with following DOI: https://doi.org/10.15454/TW59-P718 Badouin et al, 2017; Blanchet et al, 2018 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://www.thegpm.org/ X!TandemPipeline 3.4.3 “Elastine Durcie” Proteins: log (e-value) < À5 Proteins: minimum 2 peptides Peptides: e-value

Value of the data

Protein extraction

Findings

Bioinformatics annotation of proteins and quantification