De novo transcriptome of Phakopsora pachyrhizi by Illumina short-read sequencing

<i>Phakopsora pachyrhizi</i> is an obligate biotrophic fungal pathogen of soybean that causes Asian soybean rust (ASR), a devastating disease that can cause yield losses of 80% or greater. <i>P. pachyrhizi</i> secretes an arsenal of effector proteins to manipulate host immunity and promote disease. Current knowledge of the <i>P. pachyrhizi </i>genome is limited and only a small number of the total <i>P. pachyrhizi </i>effectors have been identified. We therefore sequenced the transcriptome of <i>P. pachyrhizi</i> during infection to identify <i>P. pachyrhizi </i>Candidate Secreted Effector Proteins (CSEPs). Total RNA was extracted from <i>P. pachyrhizi</i>-infected soybean leaf tissue collected at 3, 7, 10, and 14 days after inoculation (dai). Strand-specific cDNA libraries were prepared from ribosomal depleted RNA using NEBNext Ultra II RNA library prep kit according to the manufacturer's instructions. Paired-end short-read Illumina sequencing was performed on dual-indexed cDNA libraries using HiSeq3000 (150bp from each end; https://www.illumina.com/) and MiSeq (300bp from each end; https://www.illumina.com/). The raw reads obtained from Illumina short-read sequencing were quality assessed using FastQC v.0.11.2. Paired-end read trimming was conducted by Trimmomatic 0.36 using sliding window 4:15 and excluding read below a minimal length of 36. Trimmed paired-end RNA-Seq reads from 3, 7, 10, and 14 dai were mapped against the soybean genome v2.1 (https://plants.ensembl.org/Glycine_max) using STAR 2.5.3a aligner to remove soybean reads. The non-soybean short-reads were <i>de novo</i> assembled using Trinity v2.6.6. BLASTN (Basic Local Alignment Search Tool) search was performed on non-soybean transcripts using Blastplus v2.6.0 (NCBI: National Center for Biotechnology Information) to remove any plant transcripts with a query coverage greater than 80% and identity greater than 95%. The final <i>de novo </i>transcriptome containing non-plant, non-soybean transcripts for each time point was used for prediction of candidate effectors.<br><b>Citation:</b>M.G.Elmore, S.Banerjee, K.F.Pedley, A.Ruck, S.A.Whitham. <i>De novo</i> transcriptome of <i>Phakopsora</i> <i>pachyrhizi</i> uncovers putative effector repertoire during infection. Physiological and Molecular Plant Pathology.,<br>110 (2020),101464, 10.1016/j.pmpp.2020.101464