There is an increasing demand for elucidating the biosynthetic pathway of medicinal plants, which are capable of producing several metabolites with great potentials for industrial drug production. Digitalis species are important medicinal plants for the production of cardenolide compounds. Advancement on culture techniques is strictly related to our understanding of the genomic background of species. There are a limited number of genomic studies on Digitalis species. The goal of this study is to contribute to the genomic data of Digitalis ferruginea subsp. schischkinii by presenting transcriptome annotation. Digitalis ferruginea subsp. schischkinii has a limited distribution in Turkey and Transcaucasia, and has a high level of lanatoside C, an important cardenolide. In the study, we sequenced the cDNA library prepared from RNA pools of D. ferruginea subsp. schischkinii tissues treated with various stress conditions. Comprehensive bioinformatics approaches were used for de novo assembly and functional annotation of D. ferruginea subsp. schischkinii transcriptome sequence data along with TF families predictions and phylogenetic analysis. In the study, 58,369 unigenes were predicted and unigenes were annotated by analyzing the sequence data in the non-redundant (NR) protein database, the non-redundant nucleotide (NT) database, Gene Orthology (GO), EuKaryotic Orthologous Groups (KOG), Kyoto Encyclopedia of Genes and Genomes (KEGG), SwissProt, and InterPro databases. This study is the first transcriptome data for D. ferruginea subsp. schischkinii.
Keywords: Bioinformatics; De novo assembly; Digitalis ferruginea subsp. schischkinii; Medicinal plant; Non-model organism; RNA-seq.