DOI: 10.6084/m9.figshare.30138907
title: Transcriptome data of the stem base of cuttings of Petunia axillaris and Petunia inflata

description: Transcriptome data from cuttings of <i>P. axillaris</i> and <i>P. inflata</i>Based on previous findings on the hormonal regulation during AR formation in <i>P. hybrida</i> Mitchell, a phytohormone targeted microarray was developed that covered those genes from <i>P. axillaris</i> and <i>P. inflata,</i> that putatively control homeostasis, signal transduction and downstream response of/to auxin, JA and SLs. To cover also the response of AR formation to ET, genes encoding ethylene response factors (ERFs), that may respond to ET and also other phytohormones such as JA (Heymann et al., 2018), were included as main gene family of the gene category “hormonal interaction” (short name “interaction”). To compile the gene list for the microarray, literature research was first carried out and genes/gene families involved in the pathways mentioned above were selected. Subsequently, the databases Petunia axillaris v1.6.2 CDS and Petunia inflata v1.0.1 CDS (solgenomics.net) were searched for respectively annotated genes. Furthermore, the NCBI database was searched for homologous genes in other Solanaceae species and the corresponding sequences (CDS or AAS) were blasted against the Petunia genomes. The results of the two blasts were compared and the gene list was adjusted accordingly. Later, based on the results of microarray, annotation of differentially expressed genes of the families <i>YUCCA, ILR/ILR-like</i>,<i> PIN/PIN-like</i>,<i> Aux/IAA</i>,<i> ARF, LBD, PINOID, </i>and <i>ERF</i> was updated using a new version of the <i>P. axillaris</i> genome 4.02 I, with the kind permission of Cris Kuhlemeier, University Bern, Switzerland (later published as Pax403 under https://www.ncbi.nlm.nih.gov/datasets/genome/GCA_026929995.1/).Based on the genome sequences of 1,265 genes of interest (605 from <i>P. axillaris</i>, 660 from <i>P. inflata</i>), an Array-to-Go Custom was designed by the company OakLabs GmbH (Henningsdorf, Germany). For this purpose, five to ten specific isothermal probes of 45-60 bp length were designed for each gene of interest. Additional 1000 probes from an earlier used microarray (Yang et al. 2019) were used for normalization. The probes were spotted on a microarray. Extracted RNA samples were labelled with a cy3 fluorescent dye and hybridized to the microarray, which was manufactured in collaboration with Agilent (Santa Clara, CA, USA). The best performing oligonucleotide probe(s) were selected for each gene based on the hybridization data and used for the subsequent data analysis. Quantil-normalized expression values of genes of interest were provided and then analysed as explained below.The microarray data was analysed using the CLC Genomic Workbench (Qiagen, Hilden, Germany). The normalized transcript levels determined at 0.5, 2, 24 and 72 hours post excision (hpe) (x) were related to the respective levels at 0 hpe (y), the time of excision, to calculate fold changes (FC). These fold changes were log-transformed to log2 FC (= log2 (x/y)). If the log2 FC were &gt;2 or &lt;−2 and p-values of expression values were &lt; 0.05 (t-test), the fold changes were taken as significant. Number of up- and downregulated genes (DEGs) of different categories were counted. Ratio of DEGs were calculated based on the total number of respective genes covered by the microarray