Dataset - A complex network of additive and epistatic quantitative trait loci underlies natural variation of Arabidopsis thaliana quantitative disease resistance to Ralstonia solanacearum under heat stress
Roux, Fabrice (2020), Dataset - A complex network of additive and epistatic quantitative trait loci underlies natural variation of Arabidopsis thaliana quantitative disease resistance to Ralstonia solanacearum under heat stress, Dryad, Dataset, https://doi.org/10.5061/dryad.d2547d81c
Plant immunity is often negatively impacted by heat stress. However, the underlying molecular mechanisms remain poorly characterized. Based on a genome-wide association mapping approach, this study aims to identify in Arabidopsis thaliana the genetic bases of robust resistance mechanisms to the devastating pathogen Ralstonia solanacearum under heat stress. A local mapping population was phenotyped against the R. solanacearum GMI1000 strain at 27 and 30 °C. To obtain a precise description of the genetic architecture underlying natural variation of quantitative disease resistance (QDR), we applied a genome-wide local score analysis. Alongside an extensive genetic variation found in this local population at both temperatures, we observed a playful dynamics of quantitative trait loci along the infection stages. In addition, a complex genetic network of interacting loci could be detected at 30 °C. As a first step to investigate the underlying molecular mechanisms, the atypical meiotic cyclin SOLO DANCERS gene was validated by a reverse genetic approach as involved in QDR to R. solanacearum at 30 °C. In the context of climate change, the complex genetic architecture underlying QDR under heat stress in a local mapping population revealed candidate genes with diverse molecular functions.
How this dataset was collected and how it has been processed have been precisely described in the Material & Methods section of the article.
Agence Nationale de la Recherche, Award: DeCoD