Dual Transcriptome of Post-Germinating Mutant Lines of Arabidopsis thaliana Infected by Alternaria brassicicola

Mailen Ortega-Cuadros, Laurine Chir, Sophie Aligon, Nubia Velasquez, Tatiana Arias, Jerome Verdier and Philippe Grappin ()
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Mailen Ortega-Cuadros: Institut Agro Rennes-Angers, University Angers, INRAE, IRHS, SFR 4207 QuaSaV, F-49000 Angers, France
Laurine Chir: Institut Agro Rennes-Angers, University Angers, INRAE, IRHS, SFR 4207 QuaSaV, F-49000 Angers, France
Sophie Aligon: Institut Agro Rennes-Angers, University Angers, INRAE, IRHS, SFR 4207 QuaSaV, F-49000 Angers, France
Nubia Velasquez: Institut Agro Rennes-Angers, University Angers, INRAE, IRHS, SFR 4207 QuaSaV, F-49000 Angers, France
Tatiana Arias: Fundación Orquídeas para la Paz, Sabaneta 055450, Colombia
Jerome Verdier: Institut Agro Rennes-Angers, University Angers, INRAE, IRHS, SFR 4207 QuaSaV, F-49000 Angers, France
Philippe Grappin: Institut Agro Rennes-Angers, University Angers, INRAE, IRHS, SFR 4207 QuaSaV, F-49000 Angers, France

Data, 2024, vol. 9, issue 11, 1-11

Abstract: Alternaria brassicicola is a seed-borne pathogen that causes black spot disease in Brassica crops, yet the seed defense mechanisms against this fungus remain poorly understood. Building upon recent reports that highlighted the involvement of indole pathways in seeds infected by Alternaria , this study provides transcriptomic resources to further elucidate the role of these metabolic pathways during the interaction between seeds and fungal pathogens. Using RNA sequencing, we examined the gene expression of glucosinolate-deficient mutant lines ( cyp79B2 / cyp79B3 and qko ) and a camalexin-deficient line ( pad3 ), generating a dataset from 14 samples. These samples were inoculated with Alternaria or water, and collected at 3, 6, and 10 days after sowing to extract total RNA. Sequencing was performed using DNBseq™ technology, followed by bioinformatics analyses with tools such as FastQC (version 0.11.9), multiQC (version 1.13), Venny (version 2.0), Salmon software (version 0.14.1), and R packages DESeq2 (version 1.36.0), ClusterProfiler (version 4.12.6) and ggplot2 (version 3.4.0). By providing this valuable dataset, we aim to contribute to a deeper understanding of seed defense mechanisms against Alternaria , leveraging RNA-seq for various analyses, including differential gene expression and co-expression correlation. This work serves as a foundation for a more comprehensive grasp of the interactions during seed infection and highlights potential targets for enhancing crop protection and management.

Keywords: glucosinolates; camalexin; necrotrophic fungi; RNA-seq; germinating seeds; plant–pathogen interaction (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2024
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