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Using RNA-Sequencing Data to Examine Tissue-Specific Garlic Microbiomes.
Jo, Yeonhwa; Back, Chang-Gi; Kim, Kook-Hyung; Chu, Hyosub; Lee, Jeong Hun; Moh, Sang Hyun; Cho, Won Kyong.
Afiliación
  • Jo Y; Research Institute of Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea.
  • Back CG; Horticultural and Herbal Crop Environment Division, National Institute of Horticultural and Herbal Science, RDA, Wanju 55365, Korea.
  • Kim KH; Research Institute of Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea.
  • Chu H; R&D Division, BERTIS Inc., Seongnam-si 13605, Korea.
  • Lee JH; Plant Cell Research Institute of BIO-FD&C Co., Ltd., Incheon 21990, Korea.
  • Moh SH; Plant Cell Research Institute of BIO-FD&C Co., Ltd., Incheon 21990, Korea.
  • Cho WK; Research Institute of Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea.
Int J Mol Sci ; 22(13)2021 Jun 24.
Article en En | MEDLINE | ID: mdl-34202675
Garlic (Allium sativum) is a perennial bulbous plant. Due to its clonal propagation, various diseases threaten the yield and quality of garlic. In this study, we conducted in silico analysis to identify microorganisms, bacteria, fungi, and viruses in six different tissues using garlic RNA-sequencing data. The number of identified microbial species was the highest in inflorescences, followed by flowers and bulb cloves. With the Kraken2 tool, 57% of identified microbial reads were assigned to bacteria and 41% were assigned to viruses. Fungi only made up 1% of microbial reads. At the species level, Streptomyces lividans was the most dominant bacteria while Fusarium pseudograminearum was the most abundant fungi. Several allexiviruses were identified. Of them, the most abundant virus was garlic virus C followed by shallot virus X. We obtained a total of 14 viral genome sequences for four allexiviruses. As we expected, the microbial community varied depending on the tissue types, although there was a dominant microorganism in each tissue. In addition, we found that Kraken2 was a very powerful and efficient tool for the bacteria using RNA-sequencing data with some limitations for virome study.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Metagenoma / Metagenómica / Microbiota / Ajo Idioma: En Revista: Int J Mol Sci Año: 2021 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Metagenoma / Metagenómica / Microbiota / Ajo Idioma: En Revista: Int J Mol Sci Año: 2021 Tipo del documento: Article