Microscopy and transcriptomic datasets for investigating the drought-stress response and recovery in young and early senescent-old leaves from Brassica napus .

Abstract

The present dataset combines transcriptomic and microscopic analyses to investigate the responses of winter oilseed rape (WOSR, Brassica napus L., cultivar Aviso) to soil drought, with a focus on differences between young and early-senescent old leaves. For microscopy, 36 scans of 1 to 5 leaf cross-sections were acquired from paraffin-embedded leaf disc samples using a scanner with a 40x lens (Pannoramic Confocal, 3DHistech), capturing a large field of view (8-mm-long observed leaf tissue). The raw scanned cross-sections and analyzed images are available under doi.org/10.57745/RK5PM3 in the Recherche Data Gouvrepository. These high-quality scans enable the differentiation of mesophyll cells and tissues. Software analysis yielded a dataset with 54 selected cross-sectional areas, 291 delimited surfaces of palisade, spongy, and vessel tissues, and 11,136 individually delimited cells from the palisade and spongy layers. For transcriptomics, an Illumina Novaseq sequencer was used to generate 390 Gb of mRNA paired-end reads. The raw reads were filtered, mapped, and assigned to genes from the Brassica napus reference genome Darmor-bzh v10, which were subsequently used to identify differentially expressed genes (DEGs) and to perform gene ontology enrichment analysis. The raw reads are accessible under accession PRJNA939927 at the NCBI Sequence Read Archive (SRA). This high-quality dataset provides insights into the molecular mechanisms underlying oilseed rape's response to soil drought and may aid in the development of drought-tolerant cultivars. A total of 17,975 DEGs were identified between well-watered and severe drought conditions across the contrasted leaf developmental stages.

Plant phenotyping relevance

葉の断面画像を取得・解析し、組織面積や個別細胞などの植物形態形質を構造化した再利用可能なデータセットを提供しており、画像ベースの表現型取得が実質的な構成要素である。

Code and data availability

The article deposits its own plant-phenotyping assets publicly: raw and analyzed leaf cross-section microscopy scans (Recherche Data Gouv, doi:10.57745/RK5PM3) and the transcriptomic dataset (Recherche Data Gouv doi:10.57745/7HQSM3, mirrored at NCBI SRA under PRJNA939927). The analysis pipelines cited (nf-core/rnaseq,