Dataset for genetic and transcriptome variation of ovary tomato response to heat stress

Résumé 0

Six tomato accessions with contrasted responses to high temeprature (HT) were selected and the ovary transcriptomes of plants grown under HT and control conditions were analyzed and differentially expressed genes identified. Plant Materials : For RNAseq study, six accessions were used, three tolerant to heat stress : Cervil (one of the parents of the MAGIC population), the F1 hybrid Cervil x Levovil (CerLev) and Nagcarlan, which is known as tolerant to heat stress (Xu et al 2017a), and three susceptible to heat stress, chosen among the MAGIC lines (MT102, MT54) and their parental lines (Levovil). Plants were grown in greenhouse in Avignon in 2018, in the same conditions as the core collection (control and HT conditions) described in Bineau et al (submitted). RNA extraction Ovaries were collected on flowers from the six accessions just before petals fully open (1-2 days after pollination) and immediately frozen in liquid nitrogen. Sampling was performed over three weeks, each week sample corresponding to a biological replicate. The three biological replicates per accession (corresponding to a minimum of 5 ovaries) were separately ground to get biological replicates. RNA was extracted using the Spectrum Plant Total RNA kit (Sigma‐Aldrich, Saint‐Quentin Fallavier, France) following the manufacturer's protocol and treated with On‐Column DNase I Digestion Set (Sigma‐Aldrich) to remove any remaining genomic DNA. RNA purity and integrity were assessed on a NanoDrop 1000 spectrophotometer (Thermo Fisher Scientific, Illkirch, France) and a Bioanalyser 2100 spectrophotometer (Agilent Technologies, Les Ulis, France), respectively. RNAseq Library construction and sequencing (100 bp pair end) were subcontracted to BGI. The minimal, maximal, and average amounts of raw sequencing data per sample were estimated to be 12.2 × 10⁹ bp, 13.6 × 10⁹ bp, and 12.56 × 10⁹ bp, respectively. Raw sequencing data quality was assessed using FASTQC v.0.11.8 software (Andrews, 2011) and aggregated with MULTIQC v.1.7 (Ewels et al., 2016). Sequences were trimmed using FASTP v.0.20.0 (Chen et al., 2018). On average, cleaning steps removed 4.06% of the data (min = 4.04%, max = 4.08%). Remaining data were aligned to the tomato reference genome (Heinz 1706, v.4.0) using STAR v.2.6.1b with two passes and providing the tomato gene model (annotation v4.1) to support the mapping process. Alignments were filtered to keep only concordantly mapped reads using Samtools v.1.9 (Li et al., 2009) and read counts per gene were generated for each library using HTSEQ v.0.11.2 (Anders et al., 2015). On average, 94.8% of read pairs were uniquely mapped per library (min = 91.5%, max = 96.2%) and 2.1% multi-mapped (min = 1.7%, max = 2.7%). The differential gene analysis was performed using the workspace DiCoExpres (Lambert et al, 2020). For further explanations, we refer to the manual of DiCoExpress. The Dataset contains the raw data and R script used and the main results provided by the analysis. For specific contrast for one accession, the scripts must be run again.