Integrated  Single-Molecule Long-Read Sequencing and Illumina sequencing reveals the resistance mechanism in response to barley yellow dwarf virus-GAV in Psathyrostachys huashanica

Abstract

Background: Even though Psathyrostachys huashanica has great potential and promising prospects for resistance gene mining and molecular genetic breeding and a significant germplasm resource value, there is not yet a reference genome available. To date, most of the studies of P. huashanica have focused on the creation of translocation lines and addition lines as well as the development of molecular markers. Therefore, there is a great lack of research at the transcriptional level.Results: The full-length transcriptome of P. huashanica was sequenced using PacBio isoform sequencing (Iso-Seq) of a pooled RNA sample derived from roots, stems, buds and leaves in equal amounts to explore potential full-length transcript isoforms. A total of 112,596 unique transcript isoforms were obtained, with a total length of 114,957,868 base pairs (bp). Illumina sequencing reads were used to correct and trim PacBio isoforms. In total, 103,875 unigenes were annotated with at least one functional database. In addition, a mass of DEGs involved in BYDV-GAV defence were identified; most of these resistance related genes showed gene ontology (GO), and KEGG enrichment analysis showed that these DEGs were mostly involved in the response to plant-pathogen interaction, plant hormone signal transduction and the MAPK signalling pathway. Then, twenty resistance-related upregulated genes, including MAPKs, CRPKs, CDPKs, PR proteins, WRKYs and disease resistance proteins were selected for RNA-seq data validation using quantitative real-time PCR, which showed consistencies between these two sets of data. Besides, the results also indicated that a series of defense-related genes were induced during BYDV-GAV infection at different stages.Conclusions: The full-length transcriptome dataset should contribute to improved P. huashanica stress resistance gene utilisation, and will serve as a reference database for the analysis of transcript expression in P. huashanica. In addition, we identified genes in our transcriptome dataset involved in the regulation of the BYDV-GAV infection response in P. huashanica.