Barley (Hordeum vulgare) is a valuable commodity in the Australian agricultural sector. Barley production is threatened by Net-Blotch (NB) disease, caused by two phenotypically distinct forms of Pyrenophora teres. While both NB forms are economically damaging, incidences of Pyrenophora teres f. teres (Ptt) outbreaks with increased virulence have been reported across Australia. To better understand the molecular interactions and genes responsible for disease resistance/susceptibility, there is a need for improved genomic resources. One such resource is high-quality reference genome annotations, essential for interpreting the functional role of genomic features. However, annotations are not always comprehensively captured for non-model crop plants because of the genome size, ploidy, and repeat content, including transposable elements. Barley with an estimated genome size of 5.1 Gbp and containing more than 80% repetitive elements presents a challenge. While recent efforts by barley researchers globally have vastly improved available genomic resources, annotations are still limited to the tissue type and stress conditions selected for in these studies. Therefore, a reproducible method is needed to enrich annotation resources under NB pressure and capture full transcriptomic diversity.
This study generated Oxford Nanopore direct RNA sequencing data for barley infected with or without NB disease to capture full-length transcripts and transcriptional isoforms expressed under disease stress. The performance of various bioinformatic tools available for gene annotations were then benchmarked. The optimum tools were implemented in a Nextflow-based pipeline to streamline the processing of direct RNA data and enrich gene annotation resources. Improvement of the barley genome annotation using data generated in this study and workflow allowed for the detection of over 1000 novel transcripts, some of which were predicted to have biologically important functions, including defence response. This work shows the importance of curating comprehensive reference resources in plant pathology transcriptomic studies and outlines a reproducible method to support the continued improvement of these resources.