Generic placeholder image

Current Bioinformatics

Editor-in-Chief

ISSN (Print): 1574-8936
ISSN (Online): 2212-392X

Research Article

Elucidating the Functional Role of Predicted miRNAs in Post- Transcriptional Gene Regulation Along with Symbiosis in Medicago truncatula

Author(s): Moumita Roy Chowdhury, Jolly Basak* and Ranjit Prasad Bahadur*

Volume 15 , Issue 2 , 2020

Page: [108 - 120] Pages: 13

DOI: 10.2174/1574893614666191003114202

Price: $65

Abstract

Background: microRNAs are small non-coding RNAs which inhibit translational and post-transcriptional processes whereas long non-coding RNAs are found to regulate both transcriptional and post-transcriptional gene expression. Medicago truncatula is a well-known model plant for studying legume biology and is also used as a forage crop. In spite of its importance in nitrogen fixation and soil fertility improvement, little information is available about Medicago non-coding RNAs that play important role in symbiosis.

Objective: In this study we have tried to understand the role of Medicago ncRNAs in symbiosis and regulation of transcription factors.

Methods: We have identified novel miRNAs by computational methods considering various parameters like length, MFEI, AU content, SSR signatures and tried to establish an interaction model with their targets obtained through psRNATarget server.

Results: 149 novel miRNAs are predicted along with their 770 target proteins. We have also shown that 51 of these novel miRNAs are targeting 282 lncRNAs.

Conclusion: In this study role of Medicago miRNAs in the regulation of various transcription factors are elucidated. Knowledge gained from this study will have a positive impact on the nitrogen fixing ability of this important model plant, which in turn will improve the soil fertility.

Keywords: Non-coding RNAs, Medicago truncatula, miRNAs, lncRNA, symbiosis, transcription regulation.

Next »
Graphical Abstract
[1]
Eddy SR. Non-coding RNA genes and the modern RNA world. Nat Rev Genet 2001; 2(12): 919-29.
[http://dx.doi.org/10.1038/35103511] [PMID: 11733745]
[2]
Lee RC, Feinbaum RL, Ambros V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 1993; 75(5): 843-54.
[http://dx.doi.org/10.1016/0092-8674(93)90529-Y] [PMID: 8252621]
[3]
Ambros V. microRNAs: tiny regulators with great potential. Cell 2001; 107(7): 823-6.
[http://dx.doi.org/10.1016/S0092-8674(01)00616-X] [PMID: 11779458]
[4]
Kong Y, Han JH. MicroRNA: biological and computational perspective. Genomics Proteomics Bioinformatics 2005; 3(2): 62-72.
[http://dx.doi.org/10.1016/S1672-0229(05)03011-1] [PMID: 16393143]
[5]
Kulkarni M, Ozgur S, Stoecklin G. On track with P-bodies. Biochem Soc Trans 2010; 38(Pt 1): 242-51.
[http://dx.doi.org/10.1042/BST0380242] [PMID: 20074068]
[6]
Khraiwesh B, Arif MA, Seumel GI, et al. Transcriptional control of gene expression by microRNAs. Cell 2010; 140(1): 111-22.
[http://dx.doi.org/10.1016/j.cell.2009.12.023] [PMID: 20085706]
[7]
Morozova N, Zinovyev A, Nonne N, Pritchard L-L, Gorban AN, Harel-Bellan A. Kinetic signatures of microRNA modes of action. RNA 2012; 18(9): 1635-55.
[http://dx.doi.org/10.1261/rna.032284.112] [PMID: 22850425]
[8]
Llave C, Xie Z, Kasschau KD, Carrington JC. Cleavage of Scarecrow-like mRNA targets directed by a class of Arabidopsis miRNA. Science 2002; 297(5589): 2053-6.
[http://dx.doi.org/10.1126/science.1076311] [PMID: 12242443]
[9]
Mathonnet G, Fabian MR, Svitkin YV, et al. MicroRNA inhibition of translation initiation in vitro by targeting the cap-binding complex eIF4F. Science 2007; 317(5845): 1764-7.
[http://dx.doi.org/10.1126/science.1146067] [PMID: 17656684]
[10]
Pillai RS, Bhattacharyya SN, Artus CG, et al. Inhibition of translational initiation by Let-7 MicroRNA in human cells. Science 2005; 309(5740): 1573-6.
[http://dx.doi.org/10.1126/science.1115079] [PMID: 16081698]
[11]
Nissan T, Parker R. Computational analysis of miRNA-mediated repression of translation: implications for models of translation initiation inhibition. RNA 2008; 14(8): 1480-91.
[http://dx.doi.org/10.1261/rna.1072808] [PMID: 18579870]
[12]
Olsen PH, Ambros V. The lin-4 regulatory RNA controls developmental timing in Caenorhabditis elegans by blocking LIN-14 protein synthesis after the initiation of translation. Dev Biol 1999; 216(2): 671-80.
[http://dx.doi.org/10.1006/dbio.1999.9523] [PMID: 10642801]
[13]
Petersen CP, Bordeleau ME, Pelletier J, Sharp PA. Short RNAs repress translation after initiation in mammalian cells. Mol Cell 2006; 21(4): 533-42.
[http://dx.doi.org/10.1016/j.molcel.2006.01.031] [PMID: 16483934]
[14]
Nottrott S, Simard MJ, Richter JD. Human let-7a miRNA blocks protein production on actively translating polyribosomes. Nat Struct Mol Biol 2006; 13(12): 1108-14.
[http://dx.doi.org/10.1038/nsmb1173] [PMID: 17128272]
[15]
Coller J, Parker R. Eukaryotic mRNA decapping. Annu Rev Biochem 2004; 73: 861-90.
[http://dx.doi.org/10.1146/annurev.biochem.73.011303.074032] [PMID: 15189161]
[16]
Jones-Rhoades MW, Bartel DP, Bartel B. MicroRNAS and their regulatory roles in plants. Annu Rev Plant Biol 2006; 57: 19-53.
[http://dx.doi.org/10.1146/annurev.arplant.57.032905.105218] [PMID: 16669754]
[17]
Lewis BP, Shih IH, Jones-Rhoades MW, Bartel DP, Burge CB. Prediction of mammalian microRNA targets. Cell 2003; 115(7): 787-98.
[http://dx.doi.org/10.1016/S0092-8674(03)01018-3] [PMID: 14697198]
[18]
Chen J, Zheng Y, Qin L, et al. Identification of miRNAs and their targets through high-throughput sequencing and degradome analysis in male and female Asparagus officinalis. BMC Plant Biol 2016; 16: 80.
[http://dx.doi.org/10.1186/s12870-016-0770-z] [PMID: 27068118]
[19]
Kang W, Friedländer MR. Computational prediction of miRNA genes from small RNA sequencing data. Front Bioeng Biotechnol 2015; 3: 7.
[http://dx.doi.org/10.3389/fbioe.2015.00007] [PMID: 25674563]
[20]
Brown JR, Sanseau P. A computational view of microRNAs and their targets. Drug Discov Today 2005; 10(8): 595-601.
[http://dx.doi.org/10.1016/S1359-6446(05)03399-4] [PMID: 15837603]
[21]
Zuker M. Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res 2003; 31(13): 3406-15.
[http://dx.doi.org/10.1093/nar/gkg595] [PMID: 12824337]
[22]
Ambros V, Bartel B, Bartel DP, et al. A uniform system for microRNA annotation. RNA 2003; 9(3): 277-9.
[http://dx.doi.org/10.1261/rna.2183803] [PMID: 12592000]
[23]
Zhang BH, Pan XP, Cox SB, Cobb GP, Anderson TA. Evidence that miRNAs are different from other RNAs. Cell Mol Life Sci 2006; 63(2): 246-54.
[http://dx.doi.org/10.1007/s00018-005-5467-7] [PMID: 16395542]
[24]
Ng Kwang Loong S, Mishra SK. Unique folding of precursor microRNAs: quantitative evidence and implications for de novo identification. RNA 2007; 13(2): 170-87.
[http://dx.doi.org/10.1261/rna.223807] [PMID: 17194722]
[25]
Nithin C, Patwa N, Thomas A, Bahadur RP, Basak J. Computational prediction of miRNAs and their targets in Phaseolus vulgaris using simple sequence repeat signatures. BMC Plant Biol 2015; 15: 140.
[http://dx.doi.org/10.1186/s12870-015-0516-3] [PMID: 26067253]
[26]
Joy N, Asha S, Mallika V, Soniya EV. De novo transcriptome sequencing reveals a considerable bias in the incidence of simple sequence repeats towards the downstream of ‘Pre-miRNAs’ of black pepper. PLoS One 2013; 8(3): e56694
[http://dx.doi.org/10.1371/journal.pone.0056694] [PMID: 23469176]
[27]
Chen M, Tan Z, Zeng G, Peng J. Comprehensive analysis of simple sequence repeats in pre-miRNAs. Mol Biol Evol 2010; 27(10): 2227-32.
[http://dx.doi.org/10.1093/molbev/msq100] [PMID: 20395311]
[28]
Joy N, Soniya EV. Identification of an miRNA candidate reflects the possible significance of transcribed microsatellites in the hairpin precursors of black pepper. Funct Integr Genomics 2012; 12(2): 387-95.
[http://dx.doi.org/10.1007/s10142-012-0267-2] [PMID: 22367484]
[29]
Nithin C, Thomas A, Basak J, Bahadur RP. Genome-wide identification of miRNAs and lncRNAs in Cajanus cajan. BMC Genomics 2017; 18(1): 878.
[http://dx.doi.org/10.1186/s12864-017-4232-2] [PMID: 29141604]
[30]
Ané JM, Zhu H, Frugoli J. Recent advances in Medicago truncatula genomics. Int J Plant Genomics 2008; 2008256597
[http://dx.doi.org/10.1155/2008/256597] [PMID: 18288239]
[31]
Young ND, Debellé F, Oldroyd GED, et al. The Medicago genome provides insight into the evolution of rhizobial symbioses. Nature 2011; 480(7378): 520-4.
[http://dx.doi.org/10.1038/nature10625] [PMID: 22089132]
[32]
Zhu Y, Sheaffer CC, Barnes DK. Forage yield and quality of six annual Medicago species in the North-Central USA. Agron J 1996; 88: 955-60.
[http://dx.doi.org/10.2134/agronj1996.00021962003600060019x]
[33]
Shrestha A, Hesterman OB, Squire JM, Fisk JW, Sheaffer CC. Annual medics and berseem clover as emergency forages. Agron J 1998; 90: 197-201.
[http://dx.doi.org/10.2134/agronj1998.00021962009000020013x]
[34]
Kozomara A, Griffiths-Jones S. miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res 2014; 42(Database issue): D68-73.
[http://dx.doi.org/10.1093/nar/gkt1181] [PMID: 24275495]
[35]
Spannagl M, Nussbaumer T, Bader KC, et al. PGSB PlantsDB: updates to the database framework for comparative plant genome research. Nucleic Acids Res 2016; 44(D1): D1141-7.
[http://dx.doi.org/10.1093/nar/gkv1130] [PMID: 26527721]
[36]
Paytuví Gallart A, Hermoso Pulido A, Anzar Martínez de Lagrán I, Sanseverino W, Aiese Cigliano R. GREENC: a Wiki-based database of plant lncRNAs. Nucleic Acids Res 2016; 44(D1): D1161-6.
[http://dx.doi.org/10.1093/nar/gkv1215] [PMID: 26578586]
[37]
Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990; 215(3): 403-10.
[http://dx.doi.org/10.1016/S0022-2836(05)80360-2] [PMID: 2231712]
[38]
Szcześniak MW, Deorowicz S, Gapski J, Kaczyński Ł, Makałowska I. miRNEST database: an integrative approach in microRNA search and annotation. Nucleic Acids Res 2012; 40: D198-204.
[http://dx.doi.org/10.1093/nar/gkr1159] [PMID: 22135287]
[39]
Mhuantong W, Wichadakul D. MicroPC (microPC): A comprehensive resource for predicting and comparing plant microRNAs. BMC Genomics 2009; 10: 366.
[http://dx.doi.org/10.1186/1471-2164-10-366] [PMID: 19660144]
[40]
Patanun O, Lertpanyasampatha M, Sojikul P, Viboonjun U, Narangajavana J. Computational identification of microRNAs and their targets in cassava (Manihot esculenta Crantz.). Mol Biotechnol 2013; 53(3): 257-69.
[http://dx.doi.org/10.1007/s12033-012-9521-z] [PMID: 22388699]
[41]
Katara P, Gautam B, Kuntal H, Sharma V. Prediction of miRNA targets, affected proteins and their homologs in Glycine max. Bioinformation 2010; 5(4): 162-5.
[http://dx.doi.org/10.6026/97320630005162] [PMID: 21364779]
[42]
Han Y, Luan F, Zhu H, et al. Computational identification of microRNAs and their targets in wheat (Triticum aestivum L.). Sci China C Life Sci 2009; 52(11): 1091-100.
[http://dx.doi.org/10.1007/s11427-009-0144-y] [PMID: 19937208]
[43]
Ye K, Chen Y, Hu X, Guo J. Computational identification of microRNAs and their targets in apple. Genes Genomics 2013; 35: 377-85.
[http://dx.doi.org/10.1007/s13258-013-0070-z]
[44]
Zhang B, Pan X, Anderson TA. Identification of 188 conserved maize microRNAs and their targets. FEBS Lett 2006; 580(15): 3753-62.
[http://dx.doi.org/10.1016/j.febslet.2006.05.063] [PMID: 16780841]
[45]
Bateman A, Martin MJ, O’Donovan C, et al. The UniProt Consortium. UniProt: the universal protein knowledgebase. Nucleic Acids Res 2017; 45(D1): D158-69.
[http://dx.doi.org/10.1093/nar/gkw1099] [PMID: 27899622]
[46]
Zhang B, Pan X, Cannon CH, Cobb GP, Anderson TA. Conservation and divergence of plant microRNA genes. Plant J 2006; 46(2): 243-59.
[http://dx.doi.org/10.1111/j.1365-313X.2006.02697.x] [PMID: 16623887]
[47]
Downie JA. The roles of extracellular proteins, polysaccharidesand signals in the interactions of rhizobia with legume roots. FEMS Microbiol 2010; 34(2): 150-70.
[http://dx.doi.org/10.1111/j.1365-313X.2006.02697.x]
[48]
Bazin J, Bustos-Sanmamed P, Hartmann C, Lelandais-Brière C, Crespi M. Complexity of miRNA-dependent regulation in root symbiosis. Philos Trans R Soc Lond B Biol Sci 2012; 367(1595): 1570-9.
[http://dx.doi.org/10.1098/rstb.2011.0228] [PMID: 22527400]
[49]
Chen X. A microRNA as a translational repressor of APETALA2 in Arabidopsis flower development. Science 2004; 303(5666): 2022-5.
[http://dx.doi.org/10.1126/science.1088060] [PMID: 12893888]
[50]
Zhang B, Pan X, Cobb GP, Anderson TA. Plant microRNA: a small regulatory molecule with big impact. Dev Biol 2006; 289(1): 3-16.
[http://dx.doi.org/10.1016/j.ydbio.2005.10.036] [PMID: 16325172]
[51]
Floyd SK, Bowman JL. Gene regulation: ancient microRNA target sequences in plants. Nature 2004; 428(6982): 485-6.
[http://dx.doi.org/10.1038/428485a] [PMID: 15057819]
[52]
Kim J, Jung JH, Reyes JL, et al. microRNA-directed cleavage of ATHB15 mRNA regulates vascular development in Arabidopsis inflorescence stems. Plant J 2005; 42(1): 84-94.
[http://dx.doi.org/10.1111/j.1365-313X.2005.02354.x] [PMID: 15773855]
[53]
Juarez MT, Kui JS, Thomas J, Heller BA, Timmermans MCP. microRNA-mediated repression of rolled leaf1 specifies maize leaf polarity. Nature 2004; 428(6978): 84-8.
[http://dx.doi.org/10.1038/nature02363] [PMID: 14999285]
[54]
Fei Y, Wang R, Li H, Liu S, Zhang H, Huang J. DPMIND: degradome-based plant miRNA-target interaction and network database. Bioinformatics 2018; 34(9): 1618-20.
[http://dx.doi.org/10.1093/bioinformatics/btx824] [PMID: 29280990]
[55]
Van de Velde W, Guerra JCP, De Keyser A, et al. Aging in legume symbiosis. A molecular view on nodule senescence in Medicago truncatula. Plant Physiol 2006; 141(2): 711-20.
[http://dx.doi.org/10.1104/pp.106.078691] [PMID: 16648219]
[56]
Long Y, Wang X, Youmans DT, Cech TR. How do lncRNAs regulate transcription? Sci Adv 2017; 3(9): eaao2110
[http://dx.doi.org/10.1126/sciadv.aao2110] [PMID: 28959731]
[57]
Ben Amor B, Wirth S, Merchan F, et al. Novel long non-protein coding RNAs involved in Arabidopsis differentiation and stress responses. Genome Res 2009; 19(1): 57-69.
[http://dx.doi.org/10.1101/gr.080275.108] [PMID: 18997003]
[58]
He Y. Noncoding rna-mediated chromatin silencing (RmCS) in plants. Mol Biol 2012; 2: 2e106.
[59]
Li Z-F, Zhang Y-C, Chen Y-Q. miRNAs and lncRNAs in reproductive development. Plant Sci 2015; 238: 46-52.
[http://dx.doi.org/10.1016/j.plantsci.2015.05.017] [PMID: 26259173]
[60]
Heo JB, Sung S. Vernalization-mediated epigenetic silencing by a long intronic noncoding RNA. Science 2011; 331(6013): 76-9.
[http://dx.doi.org/10.1126/science.1197349] [PMID: 21127216]
[61]
Swiezewski S, Liu F, Magusin A, Dean C. Cold-induced silencing by long antisense transcripts of an Arabidopsis Polycomb target. Nature 2009; 462(7274): 799-802.
[http://dx.doi.org/10.1038/nature08618] [PMID: 20010688]
[62]
Zhou H, Liu Q, Li J, et al. Photoperiod- and thermo-sensitive genic male sterility in rice are caused by a point mutation in a novel noncoding RNA that produces a small RNA. Cell Res 2012; 22(4): 649-60.
[http://dx.doi.org/10.1038/cr.2012.28] [PMID: 22349461]
[63]
Franco-Zorrilla JM, Valli A, Todesco M, et al. Target mimicry provides a new mechanism for regulation of microRNA activity. Nat Genet 2007; 39(8): 1033-7.
[http://dx.doi.org/10.1038/ng2079] [PMID: 17643101]

Rights & Permissions Print Export Cite as
© 2022 Bentham Science Publishers | Privacy Policy