Literature DB >> 33538166

Relationship between Secondary Metabolism and miRNA for Important Flavor Compounds in Different Tissues of Tea Plant (Camellia sinensis) As Revealed by Genome-Wide miRNA Analysis.

Hui Li1,2, Qingqing Lin1,2, Meilin Yan1,2, Mingle Wang1,2, Pu Wang1,2, Hua Zhao1,2, Yu Wang1,2, Dejiang Ni1,2, Fei Guo1,2.   

Abstract

This study investigated the regulatory relationship between important flavor compounds and microRNA (miRNA) in nine different tissues of tea plant by analyzing the related metabolites, small RNAs (sRNAs), degradome, and coexpression network. A total of 272 differential expressed miRNAs (DEmiRNAs) were obtained, including 198 conserved miRNAs and 74 novel miRNAs. Meanwhile, the expression patterns of miR159-GAMYB, miR167-ARF, and miR396-GRF pairs were investigated by quantitative real-time polymerase chain reaction (qRT-PCR) and the target sites were verified by 5'RNA ligase-mediated RACE (5' RLM-RACE). Further coexpression analysis showed that the content of gallated catechins was significantly and negatively correlated with the expression of miR156, but positively correlated with the expression of miR166 and miR172. Additionally, the expression of miR169a, miR169l, and miR319h was shown to be positively correlated with the content of nongallated catechins and the experssion levels of ANRa, ANRb, and LARb. Moreover, important volatile compounds, such as linalool, geraniol, and 2-phenylethanol, were found to be highly positively correlated with the expression of miR171o, miRN71a, miRN71b, miRN71c, and miRN71d. Our data indicate that these miRNAs may play important roles in regulating the biosynthesis of flavor compounds in different tissues of tea plant.

Entities:  

Keywords:  flavor compounds; miRNA; secondary metabolism; tea plant; tissues

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Year:  2021        PMID: 33538166     DOI: 10.1021/acs.jafc.0c07440

Source DB:  PubMed          Journal:  J Agric Food Chem        ISSN: 0021-8561            Impact factor:   5.279


  3 in total

1.  MTAGCN: predicting miRNA-target associations in Camellia sinensis var. assamica through graph convolution neural network.

Authors:  Haisong Feng; Ying Xiang; Xiaosong Wang; Wei Xue; Zhenyu Yue
Journal:  BMC Bioinformatics       Date:  2022-07-11       Impact factor: 3.307

2.  Multifaceted analyses reveal carbohydrate metabolism mainly affecting the quality of postharvest bamboo shoots.

Authors:  Zhen Li; Xiurong Xu; Kebin Yang; Chenglei Zhu; Yan Liu; Zhimin Gao
Journal:  Front Plant Sci       Date:  2022-09-21       Impact factor: 6.627

3.  Characterization of microRNAs from neem (Azadirachta indica) and their tissue-specific expression study in leaves and stem.

Authors:  Sujay Paul; Paula Reyes-Pérez; Paola Isabel Angulo-Bejarano; Aashish Srivastava; Sathishkumar Ramalingam; Ashutosh Sharma
Journal:  3 Biotech       Date:  2021-05-19       Impact factor: 2.893

  3 in total

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