Deep sequencing analysis of apple infecting viruses in Korea = 국내에서 발생하는 사과 바이러스의 Deep sequencing 분석

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Title
Deep sequencing analysis of apple infecting viruses in Korea = 국내에서 발생하는 사과 바이러스의 Deep sequencing 분석
Author(s)
I S Cho; D Igori; Seungmo Lim; G S Choi; J Hammond; H S Lim; Jae Sun Moon
Bibliographic Citation
Plant Pathology Journal, vol. 32, no. 5, pp. 441-451
Publication Year
2016
Abstract
Deep sequencing has generated 52 contigs derived from five viruses; Apple chlorotic leaf spot virus (ACLSV), Apple stem grooving virus (ASGV), Apple stem pitting virus (ASPV), Apple green crinkle associated virus (AGCaV), and Apricot latent virus (ApLV) were identified from eight apple samples showing small leaves and/or growth retardation. Nucleotide (nt) sequence identity of the assembled contigs was from 68% to 99% compared to the reference sequences of the five respective viral genomes. Sequences of ASPV and ASGV were the most abundantly represented by the 52 contigs assembled. The presence of the five viruses in the samples was confirmed by RT-PCR using specific primers based on the sequences of each assembled contig. All five viruses were detected in three of the samples, whereas all samples had mixed infections with at least two viruses. The most frequently detected virus was ASPV, followed by ASGV, ApLV, ACLSV, and AGCaV which were withal found in mixed infections in the tested samples. AGCaV was identified in assembled contigs ID 1012480 and 93549, which showed 82% and 78% nt sequence identity with ORF1 of AGCaV isolate Aurora-1. ApLV was identified in three assembled contigs, ID 65587, 1802365, and 116777, which showed 77%, 78%, and 76% nt sequence identity respectively with ORF1 of ApLV isolate LA2. Deep sequencing assay was shown to be a valuable and powerful tool for detection and identification of known and unknown virome in infected apple trees, here identifying ApLV and AGCaV in commercial orchards in Korea for the first time.
Keyword
Apple virusesDeep sequencingVirome
ISSN
I000-0113
Publisher
Korea Soc-Assoc-Inst
DOI
http://dx.doi.org/10.5423/PPJ.OA.04.2016.0104
Type
Article
Appears in Collections:
1. Journal Articles > Journal Articles
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