Advertisement

Tree Genetics & Genomes

, 14:60 | Cite as

Identification of novel miRNAs and their target genes in Eucalyptus grandis

  • Zheng Lin
  • Qingfen Li
  • Qi Yin
  • Jinyan Wang
  • Baolong Zhang
  • Siming Gan
  • Ai-Min Wu
Short Communication
  • 46 Downloads
Part of the following topical collections:
  1. Gene Expression

Abstract

Despite Eucalyptus grandis being the most widely planted hardwood tree globally, along with the availability of a sequenced genome and easily accessible functional genetic tools, the quantities and roles of miRNA in its developmental processes remains largely unknown. In this study, we constructed small RNA libraries by high-throughput sequencing from Eucalyptus grandis samples, and 386 novel miRNAs were identified by miRDeep2. We found 179 novel miRNAs, 41 miRNA families, and 456 target genes in leaf samples, and 257 novel miRNAs, 61 miRNA families, and 483 target genes in stem samples. The function of the MIR396 family of miRNAs in Eucalyptus grandis was found to be mainly associated with the process of cell growth. By annotation analysis of miRNA targets, we found that some target genes, such as GRF, expansin-A15, and RPS2, had a close correlation in stem. Finally, the three randomly selected members of the MIR396 family were confirmed to express in Eucalyptus grandis by qRT-PCR, indicating that our reported miRNAs were existed. The identification of miRNAs and their target genes will lead to a greater understanding of the role of miRNAs in the physiology, growth, and development of Eucalyptus grandis trees.

Keywords

miRNA Target genes Eucalyptus grandis Function MIR396 

Notes

Acknowledgements

We thank Xianhai Zhao, Junbo He (South China Agricultural University) for critical discussion and suggestions. Chunjie Fan and Bingshan Zeng from the Research Institute of tropical forestry, Chinese Academy of Forestry, Guangzhou, presented the Eucalyptus plant.

Funding

This work was supported by the Open Fund of State Key Laboratory of Tree Genetics and Breeding (Beijing) (Grant Number TGB2015007), the National Key Research and Development Program of China (Grant Number 2016YFD0600105), and the National Natural Science Foundation of China (Grant Number 31670601, 31670670).

Supplementary material

11295_2018_1273_MOESM1_ESM.xls (280 kb)
ESM 1 (XLS 280 kb)
11295_2018_1273_MOESM2_ESM.xls (31 kb)
ESM 2 (XLS 31.4 kb)
11295_2018_1273_MOESM3_ESM.xls (19 kb)
ESM 3 (XLS 19.4 kb)
11295_2018_1273_MOESM4_ESM.xls (21 kb)
ESM 4 (XLS 20.7 kb)
11295_2018_1273_MOESM5_ESM.xls (11 kb)
ESM 5 (XLS 11.0 kb)
11295_2018_1273_MOESM6_ESM.xls (13 kb)
ESM 6 (XLS 13.0 kb)
11295_2018_1273_MOESM7_ESM.xls (16 kb)
ESM 7 (XLS 16.2 kb)
11295_2018_1273_MOESM8_ESM.xls (11 kb)
ESM 8 (XLS 11.3 kb)
11295_2018_1273_MOESM9_ESM.xls (10 kb)
ESM 9 (XLS 10.2 kb)
11295_2018_1273_MOESM10_ESM.xls (334 kb)
ESM 10 (XLS 334 kb)
11295_2018_1273_MOESM11_ESM.xls (282 kb)
ESM 11 (XLS 282 kb)
11295_2018_1273_MOESM12_ESM.xls (332 kb)
ESM 12 (XLS 332 kb)
11295_2018_1273_MOESM13_ESM.xls (328 kb)
ESM 13 (XLS 327 kb)
11295_2018_1273_Fig4_ESM.png (2.2 mb)
Fig. S1

Picture of a 5-month-old Eucalyptus grandis tree planted in a growth room at 25 °C and watered once every two days with tap water (a), the magnification of the leaf (b), and cross-section of the stem’s radius with phloroglucinol dye (c) were both shown (PNG 2.20 MB)

11295_2018_1273_MOESM14_ESM.tif (8.3 mb)
High resolution image (TIF 8.30 MB)
11295_2018_1273_Fig5_ESM.png (31 kb)
Fig. S2

The secondary structure of eu-MIR396e, a member in MIR396 family. The red color represents the mature sequence, the yellow color represents the cycle structure, and the blue color represents the star sequence. (PNG 31.4 KB)

11295_2018_1273_MOESM15_ESM.tif (1.1 mb)
High resolution image (TIF 1.13 MB)
11295_2018_1273_Fig6_ESM.png (76 kb)
Fig. S3

The miRNAs of leaf and stem. The green color represents the miRNAs number in stem, the purple color represents the miRNAs number in leaf, and the blue color represents the common miRNAs number in leaf and stem. (PNG 76.2 KB)

11295_2018_1273_MOESM16_ESM.tif (1.9 mb)
High resolution image (TIF 1.84 MB)
11295_2018_1273_Fig7_ESM.png (60 kb)
Fig. S4

The relative expression of MIR396 family members in different tissues. The horizontal axis represented different miRNA in the MIR396 family, the vertical axis was the relative expression of miRNA. The errror bars are standard deviations. (PNG 59.5 KB)

11295_2018_1273_MOESM17_ESM.tif (132 kb)
High resolution image (TIF 131 KB)
11295_2018_1273_Fig8_ESM.png (631 kb)
Fig. S5

The phylogenetic tree of the MIR396 family. The samples are from Arabidopsis thaliana (two members), Nicotiana tabacum (three members), Populus trichocarpa (seven members), and Eucalyptus grandis (11 members). (PNG 630 KB)

11295_2018_1273_MOESM18_ESM.tif (662 kb)
High resolution image (TIF 662 KB)
11295_2018_1273_Fig9_ESM.png (381 kb)
Fig. S6

The Biological Process of the target genes in all, conserved and non-conserved miRNAs in leaf(a) and stem(b). (PNG 381 KB)

11295_2018_1273_MOESM19_ESM.tif (1.8 mb)
High resolution image (TIF 1.79 MB)
11295_2018_1273_Fig10_ESM.png (235 kb)
Fig. S7

The Cellular Component of the target genes in all, conserved and non-conserved miRNAs in leaf(a) and stem(b). (PNG 235 KB)

11295_2018_1273_MOESM20_ESM.tif (1.1 mb)
High resolution image (TIF 1.14 MB)
11295_2018_1273_Fig11_ESM.png (272 kb)
Fig. S8

The Molecular Function of the target genes in all, conserved and non-conserved miRNAs in leaf(a) and stem(b). (PNG 272 KB)

11295_2018_1273_MOESM21_ESM.tif (1.2 mb)
High resolution image (TIF 1.24 MB)
11295_2018_1273_Fig12_ESM.png (113 kb)
Fig. S9

ᅟ(PNG 112 KB)

11295_2018_1273_MOESM22_ESM.tif (783 kb)
High resolution image (TIF 783 KB)
11295_2018_1273_Fig13_ESM.png (124 kb)
Fig. S10

ᅟ(PNG 124 KB)

11295_2018_1273_MOESM23_ESM.tif (779 kb)
High resolution image (TIF 779 KB)

References

  1. Allen E, Xie Z, Gustafson AM, Carrington JC (2005) microRNA-directed phasing during trans-acting siRNA biogenesis in plants. Cell 121:207–221CrossRefPubMedGoogle Scholar
  2. An C, Saha S, Jenkins JN, Scheffler BE, Wilkins TA, Stelly DM (2007) Transcriptome profiling, sequence characterization, and SNP-based chromosomal assignment of the EXPANSIN genes in cotton. Mol Gen Genomics 278:539–553CrossRefGoogle Scholar
  3. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25:25–29CrossRefPubMedPubMedCentralGoogle Scholar
  4. Barrera-Figueroa BE, Gao L, Diop NN, Wu Z, Ehlers JD, Roberts PA, Close TJ, Zhu JK, Liu R (2011) Identification and comparative analysis of drought-associated microRNAs in two cowpea genotypes. BMC Plant Biol 11:127CrossRefPubMedPubMedCentralGoogle Scholar
  5. Baucher M, Moussawi J, Vandeputte OM, Monteyne D, Mol A, Perez-Morga D, El JM (2013) A role for the miR396/GRF network in specification of organ type during flower development, as supported by ectopic expression of Populus trichocarpa miR396c in transgenic tobacco. Plant Biol (Stuttg) 15:892–898CrossRefGoogle Scholar
  6. Bent AF, Kunkel BN, Dahlbeck D, Brown KL, Schmidt R, Giraudat J, Leung J, Staskawicz BJ (1994) RPS2 of Arabidopsis thaliana: a leucine-rich repeat class of plant disease resistance genes. Science 265:1856–1860CrossRefPubMedGoogle Scholar
  7. de Oliveira LA, Breton MC, Bastolla FM, Camargo Sda S, Margis R, Frazzon J, Pasquali G (2012) Reference genes for the normalization of gene expression in eucalyptus species. Plant Cell Physiol 53:405–422CrossRefPubMedGoogle Scholar
  8. Dehury B, Panda D, Sahu J, Sahu M, Sarma K, Barooah M, Sen P, Modi M (2013) In silico identification and characterization of conserved miRNAs and their target genes in sweet potato (Ipomoea batatas L.) expressed sequence tags (ESTs). Plant Signal Behav 8:e26543CrossRefPubMedPubMedCentralGoogle Scholar
  9. Dezulian T, Palatnik JF, Huson D, Weigel D (2005) Conservation and divergence of microRNA families in plants. Genome Biol 6:P13CrossRefGoogle Scholar
  10. Ewing B, Green P (1998) Base-calling of automated sequencer traces using phred. II. Error probabilities. Genome Res 8:186–194CrossRefPubMedGoogle Scholar
  11. Fahlgren N, Howell MD, Kasschau KD, Chapman EJ, Sullivan CM, Cumbie JS, Givan SA, Law TF, Grant SR, Dangl JL, Carrington JC (2007) High-throughput sequencing of Arabidopsis microRNAs: evidence for frequent birth and death of MIRNA genes. PLoS One 2:e219CrossRefPubMedPubMedCentralGoogle Scholar
  12. Friedlander MR, Mackowiak SD, Li N, Chen W, Rajewsky N (2012) miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res 40:37–52CrossRefPubMedGoogle Scholar
  13. Griffiths-Jones S, Grocock RJ, van Dongen S, Bateman A, Enright AJ (2006) miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res 34:D140–D144CrossRefPubMedGoogle Scholar
  14. Ishida S, Takabayashi A, Ishikawa N, Hano Y, Endo T, Sato F (2008) A novel nuclear-encoded protein, NDH-Dependent Cyclic Electron Flow 5, is essential for the accumulation of chloroplast NAD(P)H dehydrogenase complexes. Plant Cell Physiol 50:383–393CrossRefGoogle Scholar
  15. Kanehisa M, Goto S, Kawashima S, Okuno Y, Hattori M (2004) The KEGG resource for deciphering the genome. Nucleic Acids Res 32:D277–D280CrossRefPubMedPubMedCentralGoogle Scholar
  16. Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10:R25CrossRefPubMedPubMedCentralGoogle Scholar
  17. Levy A, Szwerdszarf D, Abu-Abied M, Mordehaev I, Yaniv Y, Riov J, Arazi T, Sadot E (2014) Profiling microRNAs in Eucalyptus grandis reveals no mutual relationship between alterations in miR156 and miR172 expression and adventitious root induction during development. BMC Genomics 15:524CrossRefPubMedPubMedCentralGoogle Scholar
  18. Mao X, Cai T, Olyarchuk JG, Wei L (2005) Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics 21:3787–3793CrossRefPubMedGoogle Scholar
  19. Muñoz-Espinoza C, Di Genova A, Correa J, Silva R, Maass A, Gonzalez-Aguero M, Orellana A, Hinrichsen P (2016) Transcriptome profiling of grapevine seedless segregants during berry development reveals candidate genes associated with berry weight. BMC Plant Biol 16:104CrossRefPubMedPubMedCentralGoogle Scholar
  20. Myburg AA, Grattapaglia D, Tuskan GA, Hellsten U, Hayes RD, Grimwood J, Jenkins J, Lindquist E, Tice H, Bauer D, Goodstein DM, Dubchak I, Poliakov A, Mizrachi E, Kullan AR, Hussey SG, Pinard D, van der Merwe K, Singh P, van Jaarsveld I, Silva-Junior OB, Togawa RC, Pappas MR, Faria DA, Sansaloni CP, Petroli CD, Yang X, Ranjan P, Tschaplinski TJ, Ye CY, Li T, Sterck L, Vanneste K, Murat F, Soler M, Clemente HS, Saidi N, Cassan-Wang H, Dunand C, Hefer CA, Bornberg-Bauer E, Kersting AR, Vining K, Amarasinghe V, Ranik M, Naithani S, Elser J, Boyd AE, Liston A, Spatafora JW, Dharmwardhana P, Raja R, Sullivan C, Romanel E, Alves-Ferreira M, Kulheim C, Foley W, Carocha V, Paiva J, Kudrna D, Brommonschenkel SH, Pasquali G, Byrne M, Rigault P, Tibbits J, Spokevicius A, Jones RC, Steane DA, Vaillancourt RE, Potts BM, Joubert F, Barry K, Pappas GJ, Strauss SH, Jaiswal P, Grima-Pettenati J, Salse J, Van de Peer Y, Rokhsar DS, Schmutz J (2014) The genome of Eucalyptus grandis. Nature 510:356–362CrossRefPubMedGoogle Scholar
  21. Pappas M, Reis A, Farinell L, Pasquali G, Jr PG, Grattapaglia D (2011) Interspecific discovery and expression profiling of Eucalyptus micro RNAs by deep sequencing. BMC Proc 5:1–2Google Scholar
  22. Pappas MDCR, Pappas GJ, Grattapaglia D (2015) Genome-wide discovery and validation of Eucalyptus small RNAs reveals variable patterns of conservation and diversity across species of Myrtaceae. BMC Genomics 16:1113CrossRefPubMedPubMedCentralGoogle Scholar
  23. Romualdi C, Bortoluzzi S, D'Alessi F, Danieli GA (2003) IDEG6: a web tool for detection of differentially expressed genes in multiple tag sampling experiments. Physiol Genomics 12:159–162CrossRefPubMedGoogle Scholar
  24. Wang T, Chen L, Zhao M, Tian Q, Zhang WH (2011) Identification of drought-responsive microRNAs in Medicago truncatula by genome-wide high-throughput sequencing. BMC Genomics 12:367CrossRefPubMedPubMedCentralGoogle Scholar
  25. Wind M, Reines D (2000) Transcription elongation factor SII. Bioessays 22:327–336CrossRefPubMedPubMedCentralGoogle Scholar
  26. Zhang N, Yang J, Wang Z, Wen Y, Wang J, He W, Liu B, Si H, Wang D (2014) Identification of novel and conserved microRNAs related to drought stress in potato by deep sequencing. PLoS One 9:e95489CrossRefPubMedPubMedCentralGoogle Scholar
  27. Zhang Z, Jiang L, Wang J, Gu P, Chen M (2015) MTide: an integrated tool for the identification of miRNA-target interaction in plants. Bioinformatics 31:290–291CrossRefPubMedGoogle Scholar
  28. Zhao B, Liang R, Ge L, Li W, Xiao H, Lin H, Ruan K, Jin Y (2007) Identification of drought-induced microRNAs in rice. Biochem Biophys Res Commun 354:585–590CrossRefPubMedGoogle Scholar
  29. Zhao CZ, Xia H, Frazier TP, Yao YY, Bi YP, Li AQ, Li MJ, Li CS, Zhang BH, Wang XJ (2010) Deep sequencing identifies novel and conserved microRNAs in peanuts (Arachis hypogaea L.). BMC Plant Biol 10:3CrossRefPubMedPubMedCentralGoogle Scholar
  30. Zhou L, Liu Y, Liu Z, Kong D, Duan M, Luo L (2010) Genome-wide identification and analysis of drought-responsive microRNAs in Oryza sativa. J Exp Bot 61:4157–4168CrossRefPubMedGoogle Scholar
  31. Zou Q, Mao Y, Hu L, Wu Y, Ji Z (2014) miRClassify: an advanced web server for miRNA family classification and annotation. Comput Biol Med 45:157–160CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Zheng Lin
    • 1
    • 2
  • Qingfen Li
    • 1
    • 2
  • Qi Yin
    • 1
    • 2
  • Jinyan Wang
    • 3
  • Baolong Zhang
    • 3
  • Siming Gan
    • 4
  • Ai-Min Wu
    • 1
    • 2
  1. 1.State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresourcesSouth China Agricultural UniversityGuangzhouChina
  2. 2.Guangdong Key Laboratory for Innovative Development and Utilization of Forest Plant Germplasm, College of Forestry and Landscape ArchitecturesSouth China Agricultural UniversityGuangzhouChina
  3. 3.Provincial Key Laboratory of AgrobiologyJiangsu Academy of Agricultural SciencesNanjingChina
  4. 4.Research Institute of Tropical ForestryChinese Academy of ForestryGuangzhouChina

Personalised recommendations