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Planta Med 2019; 85(14/15): 1168-1176
DOI: 10.1055/a-0989-7302
Natural Product Chemistry and Analytical Studies
Original Papers
Georg Thieme Verlag KG Stuttgart · New York

Analysis of Panax ginseng miRNAs and Their Target Prediction Based on High-Throughput Sequencing

Yingfang Wang
1   School of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
2   Guangdong Engineering &Technology Research Center of Topical Precise Drug Delivery System, Guangzhou, Guangdong, China
,
Mengyuan Peng
1   School of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
,
Yanlin Chen
1   School of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
,
Wenjuan Wang
1   School of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
,
Zhihua He
1   School of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
,
Zemin Yang
3   School of Basic Courses, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
,
Zhiyun Lin
1   School of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
,
Mengjuan Gong
1   School of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
,
Yongqin Yin
1   School of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
,
Yu Zeng
1   School of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
› Author Affiliations
Further Information

Publication History

received 19 June 2019
revised 20 July 2019

accepted 03 August 2019

Publication Date:
21 August 2019 (online)

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Abstract

Panax ginseng has been widely and effectively used as medicine for thousands of years. However, only limited studies have been conducted to date on ginseng miRNAs. In the present study, we collected 3 ginseng samples from the Changbai Mountain in China. Small RNA libraries were constructed and sequenced on the Illumina HiSeq platform. Sequencing analyses identified 3798 miRNAs, including 298 known miRNAs and 3500 potentially novel miRNAs. The miR166, miR159, and miR396 families were among the most highly expressed miRNAs in all libraries. The results of miRNA expression analyses were validated by qRT-PCR. Target gene prediction through computational and pathway annotation analyses revealed that the primary pathways were related to plant development, including metabolic processes and single-organism processes. It has been reported that plant miRNAs might be one of the hidden bioactive ingredients in medicinal plants. Based on the combined use of RNAhybrid, Miranda, and TargetScan software, a total of 50,992 potential human genes were predicted as the putative targets of 2868 miRNAs. Interestingly, the enriched KEGG pathways were associated with some human diseases, especially cancer, immune system diseases, and neurological disorders, and this could support the clinical use of ginseng. However, the human targets of ginseng miRNAs should be confirmed by further experimental validation. Our results provided valuable insight into ginseng miRNAs and the putative roles of these miRNAs.

Key words

Panax ginseng - miRNAs - high-throughput sequencing - target gene - cross-kingdom regulation - Araliaceae

Supporting Information

    Statistics of clean data (Table 1S), categorization of clean tags (Table 2S), KEGG pathways for putative human targets (Table 3S), and distribution of the number of members in conserved miRNA families (Fig. 1S) are available as Supporting Information.

  • Supporting Information
 

  • References

  • 1 Zhao ZF, Wei HY, Guo YL, Gu W. [Potential distribution of Panax ginseng and its predicted responses to climate change]. Ying Yong Sheng Tai Xue Bao 2016; 27: 3607-3615
    PubMedSearch in Google Scholar
  • 2 Li MR, Shi FX, Zhou YX, Li YL, Wang XF, Zhang C, Wang XT, Liu B, Xiao HX, Li LF. Genetic and epigenetic diversities shed light on domestication of cultivated ginseng (Panax ginseng). Mol Plant 2015; 8: 1612-1622
    CrossrefPubMedSearch in Google Scholar
  • 3 Ru W, Wang D, Xu Y, He X, Sun YE, Qian L, Zhou X, Qin Y. Chemical constituents and bioactivities of Panax ginseng (C. A. Mey.). Drug Discov Ther 2015; 9: 23-32
    CrossrefPubMedSearch in Google Scholar
  • 4 Lee ST, Chu K, Sim JY, Heo JH, Kim M. Panax ginseng enhances cognitive performance in Alzheimer disease. Alz Dis Assoc Dis 2008; 22: 222-226
    CrossrefPubMedSearch in Google Scholar
  • 5 Riaz M, Rahman NU, Zia-Ul-Haq M, Jaffar HZE, Manea R. Ginseng: a dietary supplement as immune-modulator in various diseases. Trends In Food Sci Tech 2019; 83: 12-30
    CrossrefPubMedSearch in Google Scholar
  • 6 Wang J, Mei J, Ren G. Plant microRNAs: biogenesis, homeostasis, and degradation. Front Plant Sci 2019; 10: 360
    PubMedSearch in Google Scholar
  • 7 Xu J, Chu Y, Liao B, Xiao S, Yin Q, Bai R, Su H, Dong L, Li X, Qian J, Zhang J, Zhang Y, Zhang X, Wu M, Zhang J, Li G, Zhang L, Chang Z, Zhang Y, Jia Z, Liu Z, Afreh D, Nahurira R, Zhang L, Cheng R, Zhu Y, Zhu G, Rao W, Zhou C, Qiao L, Huang Z, Cheng YC, Chen S. Panax ginseng genome examination for ginsenoside biosynthesis. Gigascience 2017; 6: 1-15
    CrossrefPubMedSearch in Google Scholar
  • 8 Sirohi G, Khandelwal A, Kapoor M. High-throughput sequencing and differential expression analysis of miRNAs in response to Brassinosteroid treatment in Arabidopsis thaliana . Funct Integr Genomic 2019; 19: 597-615
    CrossrefPubMedSearch in Google Scholar
  • 9 Zheng Y, Chen K, Xu ZN, Liao PR, Zhang XT, Liu L, Wei KN, Liu DQ, Li YF, Sunkar R, Cui XM. Small RNA profiles from Panax notoginseng roots differing in sizes reveal correlation between miR156 abundances and root biomass levels. Sci Rep-Uk 2017; 7: 9418
    PubMedSearch in Google Scholar
  • 10 Lu C, Zhao SJ, Wang XS. Functional regulation of a UDP-glucosyltransferase gene (Pq3-O-UGT1) by RNA interference and overexpression in Panax quinquefolius . Plant Cell Tiss Org 2017; 129: 445-456
    CrossrefPubMedSearch in Google Scholar
  • 11 Khorolragchaa A, Kim YJ, Rahimi S, Sukweenadhi J, Jang MG, Yang DC. Grouping and characterization of putative glycosyltransferase genes from Panax ginseng Meyer. Gene 2014; 536: 186-192
    CrossrefPubMedSearch in Google Scholar
  • 12 Fan B, Dong WX, Chen TY, Chu JL, He BF. Switching glycosyltransferase UGT(BL)1 regioselectivity toward polydatin synthesis using a semi-rational design. Org Biomol Chem 2018; 16: 2464-2469
    CrossrefPubMedSearch in Google Scholar
  • 13 Pannu N, Bhatnagar A. Resveratrol: from enhanced biosynthesis and bioavailability to multitargeting chronic diseases. Biomed Pharmacother 2019; 109: 2237-2251
    CrossrefPubMedSearch in Google Scholar
  • 14 Liu T, Luo T, Guo X, Zou X, Zhou D, Afrin S, Li G, Zhang Y, Zhang R, Luo Z. PgMYB2, a MeJA-responsive transcription factor, positively regulates the dammarenediol synthase gene expression in Panax ginseng . Int J Mol Sci 2019; 20: E2219
    CrossrefPubMedSearch in Google Scholar
  • 15 Afrin S, Zhu J, Cao H, Huang J, Xiu H, Luo T, Luo Z. Molecular cloning and expression profile of an abiotic stress and hormone responsive MYB transcription factor gene from Panax ginseng . Acta Bioch Bioph Sin 2015; 47: 267-277
    CrossrefPubMedSearch in Google Scholar
  • 16 Jiang XQ, Zhang CQ, Lu PT, Jiang GM, Liu XW, Dai FW, Gao JP. RhNAC3, a stress- associated NAC transcription factor, has a role in dehydration tolerance through regulating osmotic stress-related genes in rose petals. Plant Biotechnol J 2014; 12: 38-48
    CrossrefPubMedSearch in Google Scholar
  • 17 Chen X, Lu SC, Wang YF, Zhang X, Lv B, Luo LQ, Xi DD, Shen JB, Ma H, Ming F. OsNAC2 encoding a NAC transcription factor that affects plant height through mediating the gibberellic acid pathway in rice. Plant J 2015; 82: 302-314
    CrossrefPubMedSearch in Google Scholar
  • 18 Xie WY, Weng A, Melzig MF. MicroRNAs as new bioactive components in medicinal plants. Planta Med 2016; 82: 1153-1162
    Thieme ConnectPubMedSearch in Google Scholar
  • 19 Zhang L, Hou DX, Chen X, Li DH, Zhu LY, Zhang YJ, Li J, Bian Z, Liang XY, Cai X, Yin Y, Wang C, Zhang TF, Zhu DH, Zhang DM, Xu J, Chen Q, Ba Y, Liu J, Wang Q, Chen JQ, Wang J, Wang M, Zhang QP, Zhang JF, Zen K, Zhang CY. Exogenous plant MIR168a specifically targets mammalian LDLRAP1: evidence of cross-kingdom regulation by microRNA (vol 22, pg 273, 2012). Cell Res 2012; 22: 273-274
    CrossrefPubMedSearch in Google Scholar
  • 20 Zhou Z, Li XH, Liu JX, Dong L, Chen Q, Liu JL, Kong HH, Zhang QY, Qi X, Hou DX, Zhang L, Zhang GQ, Liu YC, Zhang YJ, Li J, Wang J, Chen X, Wang H, Zhang JF, Chen HL, Zen K, Zhang CY. Honeysuckle-encoded atypical microRNA2911 directly targets influenza A viruses. Cell Res 2015; 25: 39-49
    CrossrefPubMedSearch in Google Scholar
  • 21 Chin AR, Fong MY, Somlo G, Wu J, Swiderski P, Wu XW, Wang SE. Cross-kingdom inhibition of breast cancer growth by plant miR159. Cell Res 2016; 26: 217-228
    CrossrefPubMedSearch in Google Scholar
  • 22 Shahid S, Kim G, Johnson NR, Wafula E, Wang F, Coruh C, Bernal-Galeano V, Phifer T, dePamphilis CW, Westwood JH, Axtell MJ. MicroRNAs from the parasitic plant Cuscuta campestris target host messenger RNAs. Nature 2018; 553: 82-85
    PubMedSearch in Google Scholar
  • 23 Zhu K, Liu M, Fu Z, Zhou Z, Kong Y, Liang H, Lin Z, Luo J, Zheng H, Wan P, Zhang J, Zen K, Chen J, Hu F, Zhang CY, Ren J, Chen X. Plant microRNAs in larval food regulate honeybee caste development. PLoS Genet 2017; 13: e1006946
    CrossrefPubMedSearch in Google Scholar
  • 24 Li W, Liang Y, Yang B, Sun H, Wu W. Downregulation of ARNT2 promotes tumor growth and predicts poor prognosis in human hepatocellular carcinoma. J Gastroen Hepatol 2015; 30: 1085-1093
    CrossrefPubMedSearch in Google Scholar
  • 25 Kimura Y, Kasamatsu A, Nakashima D, Yamatoji M, Minakawa Y, Koike K, Fushimi K, Higo M, Endo-Sakamoto Y, Shiiba M, Tanzawa H, Uzawa K. ARNT2 regulates tumoral growth in oral squamous cell carcinoma. J Cancer 2016; 7: 702-710
    CrossrefPubMedSearch in Google Scholar
  • 26 Khotskaya YB, Holla VR, Farago AF, Mills Shaw KR, Meric-Bernstam F, Hong DS. Targeting TRK family proteins in cancer. Pharmacol Therapeut 2017; 173: 58-66
    CrossrefPubMedSearch in Google Scholar
  • 27 Lange AM, Lo HW. Inhibiting TRK proteins in clinical cancer therapy. Cancers (Basel) 2018; 10: E105
    CrossrefPubMedSearch in Google Scholar
  • 28 Shukla U, Hatani T, Nakashima K, Ogi K, Sada K. Tyrosine phosphorylation of 3BP2 regulates B cell receptor-mediated activation of NFAT. J Biol Chem 2009; 284: 33719-33728
    CrossrefPubMedSearch in Google Scholar
  • 29 Mukai T, Gallant R, Ishida S, Yoshitaka T, Kittaka M, Nishida K, Fox DA, Morita Y, Ueki Y. SH3BP2 gain-of-function mutation exacerbates inflammation and bone loss in a murine collagen-induced arthritis model. PLoS One 2014; 9: e105518
    CrossrefPubMedSearch in Google Scholar
  • 30 Mukai T, Gallant R, Ishida S, Kittaka M, Yoshitaka T, Fox DA, Morita Y, Nishida K, Rottapel R, Ueki Y. Loss of SH3 domain-binding protein 2 function suppresses bone destruction in tumor necrosis factor-driven and collagen-induced arthritis in mice. Arthritis Rheumatol 2015; 67: 656-667
    PubMedSearch in Google Scholar
  • 31 Bristow CL, Babayeva MA, LaBrunda M, Mullen MP, Winston R. alpha(1)Proteinase inhibitor regulates CD4(+) lymphocyte levels and is rate limiting in HIV-1 disease. PLoS One 2012; 7: e31383
    CrossrefPubMedSearch in Google Scholar
  • 32 Tamehiro N, Nishida K, Sugita Y, Hayakawa K, Oda H, Nitta T, Nakano M, Nishioka A, Yanobu-Takanashi R, Goto M, Okamura T, Adachi R, Kondo K, Morita A, Suzuki H. Ras homolog gene family H (RhoH) deficiency induces psoriasis-like chronic dermatitis by promoting TH17 cell polarization. J Allergy Clin Immunol 2019; 143: 1878-1891
    CrossrefPubMedSearch in Google Scholar
  • 33 Bauquet AT, Jin H, Paterson AM, Mitsdoerffer M, Ho IC, Sharpe AH, Kuchroo VK. The costimulatory molecule ICOS regulates the expression of c-Maf and IL-21 in the development of follicular T helper cells and TH-17 cells. Nat Immunol 2009; 10: 167-175
    CrossrefPubMedSearch in Google Scholar
  • 34 Lal D, Reinthaler EM, Dejanovic B, May P, Thiele H, Lehesjoki AE, Schwarz G, Riesch E, Ikram MA, van Duijn CM, Uitterlinden AG, Hofman A, Steinbock H, Gruber-Sedlmayr U, Neophytou B, Zara F, Hahn A. Genetic Commission of the Italian League against Epilepsy, EuroEPINOMICS CoGIE Consortium, Gormley P, Becker F, Weber YG, Cilio MR, Kunz WS, Krause R, Zimprich F, Lemke JR, Nurnberg P, Sander T, Lerche H, Neubauer BA. Evaluation of presumably disease causing SCN1A variants in a cohort of common epilepsy syndromes. PLoS One 2016; 11: e0150426
    CrossrefPubMedSearch in Google Scholar
  • 35 Tundo GR, Sbardella D, Ciaccio C, Grasso G, Gioia M, Coletta A, Polticelli F, Di Pierro D, Milardi D, Van Endert P, Marini S, Coletta M. Multiple functions of insulin-degrading enzyme: a metabolic crosslight?. Crit Rev Biochem Mol 2017; 52: 554-582
    CrossrefPubMedSearch in Google Scholar
  • 36 Yan T, Yoo D, Berardini TZ, Mueller LA, Weems DC, Weng S, Cherry JM, Rhee SY. PatMatch: a program for finding patterns in peptide and nucleotide sequences. Nucleic Acids Res 2005; 33: W262-W266
    CrossrefPubMedSearch in Google Scholar
  • 37 Lewis BP, Shih IH, Jones-Rhoades MW, Bartel DP, Burge CB. Prediction of mammalian microRNA targets. Cell 2003; 115: 787-798
    CrossrefPubMedSearch in Google Scholar