Objective

The necrotrophic fungal pathogen Pyrenophora tritici-repentis causes tan spot disease of wheat (Triticum aestivum). Tan spot is an economically significant leaf disease, which has a major impact on the wheat industry worldwide. Here, we present exploratory RNA sequence data sets with the following aims: (1) to investigate in planta gene expression of both the host and pathogen during wheat tan spot infection by P. tritici-repentis, (2) to investigate in vitro P. tritici-repentis gene expression during vegetative and sporulating growth stages, and (3) to provide RNA sequencing for bioinformatics support of gene predictions in P. tritici-repentis [1] and wheat.

Data description

In total, six RNA libraries were Illumina HiSeq sequenced to yield 24 and 25 million read pairs respectively for 3 and 4 days post-infection with P. tritici-repentis, 28 and 23 million read pairs respectively for 3 and 4 days post-inoculation of control wheat, and 23 and 26 million read pairs for 7-day old vegetative fungal mycelia and 9-day old sporulating mycelia respectively (Data file 1) (Table 1). The time points were chosen to maximise the appearance of early disease symptoms in planta and capture a latent growth and sporulating growth phase in vitro.

Table 1 Overview of data files/data sets

To determine host gene expression during P. tritici-repentis infection, datasets from infected and non-infected leaf samples were individually aligned to the Chinese Spring wheat genome (IWGS V1.0) [2]. Over half of the reads for each dataset mapped to the wheat genome (Data file 1). A total of 33,449 genes (24%) of the 137,056 high-confidence wheat reference genes were detected in both the control and infected groups (Data file 2).

For P. tritici-repentis expression during host infection, datasets from 3 and 4 days post-infection were also individually aligned to the P. tritici-repentis genome of isolate M4 [1]. Only 0.4–0.6% of the sample reads mapped to the genome (Data file 1). A total of 9101 and 9824 transcripts were detected at 3 and 4 days post-infection respectively (Data file 3).

To profile P. tritici-repentis genes expressed at different mycelia growth stages, the in vitro vegetative and sporulating datasets were individually aligned to the M4 genome [1] with approximately half of the reads in concordant alignment (Data file 1). A total of 10,933 M4 transcripts were expressed in vitro and of these 8548 transcripts were found expressed in both vegetative and sporulating mycelia (Data file 4).

Methodology

Plant and fungal material

The fully extended leaves of the 2-week-old susceptible wheat (Triticum aestivum) variety Machete were inoculated with the P. tritici-repentis race 1 M4 isolate or a mock control solution [3]. Infected and control leaves were collected at 3 and 4 days post-inoculation (DPI). In vitro M4 samples of vegetative mycelia and sporulating mycelia grown on V8PDA agar [3] were harvested at 7 days and 9 days respectively. All samples were snap frozen in liquid nitrogen immediately after harvest, and stored at − 80 °C prior to RNA extraction.

RNA extraction and sequencing

RNA was extracted using TRIzol Reagent (Thermo Fisher Scientific, USA), further purified using Zymo-Spin columns (Zymo Research, USA) as per the manufacturer’s guidelines prior to LiCl precipitation. RNA samples were pooled from 3 biological replicates. Isolated RNA was ribo-depleted and sequenced as un-stranded, 100 bp pair-end (PE) reads on an Illumina HiSeq2000 machine. A total of 30.6 Gb of raw sequence of 6 libraries was obtained. Further method details can be found in Supplementary file 1.

Sequence analysis

Reads were quality checked with FASTQC [4] and trimmed using TrimmomaticPE V0.32 [5]. The trimmed reads were aligned to the P. tritici-repentis M4 reference genome (NCBI GenBank accession NQIK00000000.1) [1] and wheat Chinese Spring genome IWGS V1.0 [2] using Bowtie2/TopHat2 version 2.0.9 [6, 7]. Expression analysis was conducted with the Cufflinks package guided by the reference genes for M4 and high confidence genes in wheat [8].

Limitations

The data sets generated were pooled from three biological RNA samples and therefore have no replicates for differential expression studies. The downloadable sequence data is stored raw and requires quality filtering before use.