RESUMO
Türkiye is a major apple fruit producer in the crossroads of Europe and the Middle East. Several reports have described the presence of multiple viruses affecting apple production in Türkiye, including apple stem grooving virus (ASGV), apple stem pitting virus (ASPV), apple chlorotic leafspot virus (ACLSV), and apple mosaic virus (ApMV) (Kurçman 1977; Fidan 1994; Çaglayan et al. 2003). However, there are no reports of the presence of the recently discovered bunya-like viruses citrus concave gum-associated virus (CCGaV), and apple rubbery wood viruses 1 and 2 (ARWV1 and 2), as well as apple luteovirus 1 (ALV-1), and apple hammerhead viroid (AHVd) in Türkiye, all of which have been previously reported in other apple-producing countries (Wright et al. 2018; Liu et al. 2018; Zhang et al. 2014). Leaves from one Gala, two Granny Smith, and one Golden Delicious apple trees showing mild symptoms of curling, chlorosis, and yellowing were collected from four different orchards in the province of Hakkari, southeast Türkiye during June 2022 and sent to USDA APHIS Plant Germplasm Quarantine Program (under permit) for virus and viroid HTS-based diagnostics. Total RNA was isolated using the RNeasy Plant Mini Kit (Qiagen) following the manufacturer's guidelines to prepare RNAseq libraries using the TruSeq Stranded Total RNA Library Plant Kit (Illumina, Inc) as described in Malapi-Wight et al. (2021). Libraries were sequenced on the NextSeq500 sequencer (PE 2x75), and approximately 45 million reads were obtained per each sample on average. Bioinformatic analysis was performed as described in Costa et al. (2022) using Phytopipe, where unclassified pathogen-derived reads were de novo assembled and contigs were compared to the NCBI viral nucleotide and protein databases by BlastN and BlastX respectively using a 10-4 e-value cutoff. Nearly complete genome contigs were obtained for ACLSV (OR640150) and ASPV (OR640151) in all four samples and for ASGV (OR640152) in 3 of the 4 samples. The average BlastN identity to sequences in GenBank was 92.3% for ACLSV, ranging from 89-94 %. BlastN identity for ASPV was 86%, ranging from 81-92 % while the ASGV average BlastN identity was 98.2%. Nearly complete genomes with average genome coverage of 92.4% and 95.6% for RNA1 and RNA2 of CCGaV (OR640153 and OR640154), were found in two of the four samples with BlastN identity of 94.7% and 94.8% to GenBank sequences. Additionally, nearly complete genome of the large (L), medium (M), and small (S) segments for ARWV1 were found in two samples with average genome coverage of 99.9%, 99.4%, and 100% respectively and BlastN identity of 98.8%, 95.2%, and 98.4% (OR640155, OR640156, OR640157). ARWV2 contigs were also found in 1 sample where M and S segments had a coverage of 99.8% and BlastN identity of 95.4% (OR640158 and OR640159). The nearly complete genome of ALV-1 was also found in two of four samples with genome coverage of 94.1% and an average BlastN identity of 93.4% (OR640160). AHVd was found in one of the Granny Smith trees with 19,260 mapped reads to the reference GenBank MH049335.1 and identity of 98.3% (OR640149). The HTS findings of CCGaV, ARWV1, ARWV2, and ALV-1, from Türkiye were later confirmed by Sanger sequencing using custom-designed primers targeting the coat protein, the RNA-dependent RNA polymerase, or ~390bp for the AHVd genome (Supplementary Table 1). To further learn about the incidence of these agents, we tested 12 other apple samples from six different neighboring orchards and found them at 18.8% rate for CCGaV, 12.5% for both ARWV1 and ARWV2, 25% for ALV-1, and 37.5% for AHVd respectively. To our knowledge, this is the first report of the apple viruses CCGaV, ARWV1, ARWV2, and ALV-1, and the AHVd viroid in Türkiye. Further studies of the impact of these agents on orchard's health are necessary, including their prevalence in high apple production regions of Türkiye.
RESUMO
BACKGROUND: Detection of exotic plant pathogens and preventing their entry and establishment are critical for the protection of agricultural systems while securing the global trading of agricultural commodities. High-throughput sequencing (HTS) has been applied successfully for plant pathogen discovery, leading to its current application in routine pathogen detection. However, the analysis of massive amounts of HTS data has become one of the major challenges for the use of HTS more broadly as a rapid diagnostics tool. Several bioinformatics pipelines have been developed to handle HTS data with a focus on plant virus and viroid detection. However, there is a need for an integrative tool that can simultaneously detect a wider range of other plant pathogens in HTS data, such as bacteria (including phytoplasmas), fungi, and oomycetes, and this tool should also be capable of generating a comprehensive report on the phytosanitary status of the diagnosed specimen. RESULTS: We have developed an open-source bioinformatics pipeline called PhytoPipe (Phytosanitary Pipeline) to provide the plant pathology diagnostician community with a user-friendly tool that integrates analysis and visualization of HTS RNA-seq data. PhytoPipe includes quality control of reads, read classification, assembly-based annotation, and reference-based mapping. The final product of the analysis is a comprehensive report for easy interpretation of not only viruses and viroids but also bacteria (including phytoplasma), fungi, and oomycetes. PhytoPipe is implemented in Snakemake workflow with Python 3 and bash scripts in a Linux environment. The source code for PhytoPipe is freely available and distributed under a BSD-3 license. CONCLUSIONS: PhytoPipe provides an integrative bioinformatics pipeline that can be used for the analysis of HTS RNA-seq data. PhytoPipe is easily installed on a Linux or Mac system and can be conveniently used with a Docker image, which includes all dependent packages and software related to analyses. It is publicly available on GitHub at https://github.com/healthyPlant/PhytoPipe and on Docker Hub at https://hub.docker.com/r/healthyplant/phytopipe .
