Issue |
OCL
Volume 27, 2020
|
|
---|---|---|
Article Number | 36 | |
Number of page(s) | 5 | |
Section | Agronomy | |
DOI | https://doi.org/10.1051/ocl/2020027 | |
Published online | 17 July 2020 |
Data paper
RNA expression dataset of 384 sunflower hybrids in field condition
Données d’expression d’ARN issues de 384 hybrides de tournesol cultivés en champ
1
LIPM, Université de Toulouse, INRAE, CNRS,
Castanet-Tolosan, France
2
MIAT, Université de Toulouse, INRAE,
Castanet-Tolosan, France
3
Innolea, Domaine de Sandreau, Mondonville,
31700
Blagnac, France
4
RAGT 2n,
BP 3336,
12033
Rodez, France
* Correspondence: nicolas.langlade@inrae.fr
Received:
11
March
2020
Accepted:
5
June
2020
This article describes how RNA expression data of 173 genes were produced on 384 sunflower hybrids grown in field conditions. Sunflower hybrids were selected to represent genetic diversity within cultivated sunflower. The RNA was extracted from mature leaves at one time seven days after anthesis. These data allow to differentiate the different genotype behaviours and constitute a valuable resource to the community to study the adaptation of crops to field conditions and the molecular basis of heterosis. It is available on data.inra.fr repository.
Résumé
Cet article décrit la production des niveaux d’expression de 173 gènes dans 384 hybrides de tournesol cultivés en conditions de champ. Les hybrides sont issus de parents choisis pour représenter la diversité génétique dans le tournesol cultivé. Les ARN ont été extraits à partir de feuilles matures environ sept jours après la floraison. Ces données permettent de différencier les comportements des différents génotypes et constituent une ressource importante pour les chercheurs intéressés dans l’adaptation des espèces cultivées aux conditions agronomiques et aux bases moléculaires de l’hétérosis. Elles sont disponibles sur le portail Data INRAE : data.inra.fr.
Key words: sunflower / genetics / gene expression / drought
Mots clés : tournesol / génétique / génomique / sécheresse
© C. Penouilh-Suzette et al., Hosted by EDP Sciences, 2020
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.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.