A Review of RNA Motifs, Identification Algorithms and their Function on Plants

Naderi, Davoud; Jami, Raheba; Rehman, Fazal UR

doi:10.22034/jpbb.2021.271442.1001

Document Type : Review Article

Authors

¹ Agricultural Biotechnology Research Institute, University of Zabol, Zabol, Iran

² Department of Horticulture, Faculty of Agriculture, Herat University, Herat, Afghanistan

³ Department of Plant Pathology, College of Agriculture, University of Sargodha, Punjab, Pakistan

https://doi.org/10.22034/jpbb.2021.271442.1001

Abstract

Recent Genomic research has significantly developed human knowledge on structural non-coding RNAs (ncRNAs) which folds into characteristic secondary structures and performs specific-structure dependent biological functions. Hence, RNA secondary structure prediction is among the most commonly evaluated issues in computational RNA biology. The aim of the present study is to introduce the key role of RNA motifs in biological processes. Such motifs are specifically effective in regulating gene expression, maintaining structure and strength of RNA molecule, splicing the early mRNA, and providing the most appropriate recognition site for protein binding. Doing research and analyzing RNA motifs requires using several methods and algorithms which can provide the structure and properties of these building blocks in organisms. Generally, the most successful computational methods used in organizing RNA include the QRNA, RNAz, and CMfinder algorithms, which correlate nucleotides and other features of RNA structure formation and maintenance. In plants, RNA Recognition Motif (RRM), an 80- amino acid protected motif, is one of the most abundant protein motifs in eukaryotes. This motif has various important roles like participating in growth processes and responding to stresses in plants, and accelerating different metabolic processes. In addition, further analysis of ORRM family members represented presence of ORRM2, ORRM3 and ORRM4 acting as RNA editing factors in mitochondria as well as ORRM6 which is a chloroplast RNA editing factor. Among the construction motifs, the Pseudoknot motif which contributes to several biological activities such as altering expression of pathogenic genes in some viruses and formation of telomerase and self-truncating introns is of great significance, since these are important breeding factors in biotechnology. Based on the results of the study, it can be proposed that further studies on bioinformatics analysis of plant motifs are required to be implemented to open new windows on controlling pathogens in plants.

Graphical Abstract

Keywords

References

1. Szakonyi D, Confraria A, Valerio C, Duque P, Staiger D. (2019). Plant RNA Biology. Frontiers in plant science, 10: 887. https://doi.org/10.3389/fpls.2019.00887

2. Yang X, Yang M, Deng H, Ding Y. (2018). New era of studying RNA secondary structure and its influence on gene regulation in plants. Frontiers in plant science, 9: 671. https://doi.org/10.3389/fpls.2018.00671

3. Pieczynski M, Kruszka K, Bielewicz D, Dolata J, Szczesniak M, Karlowski W, Jarmolowski A, Szweykowska-Kulinska Z. (2018). A role of U12 intron in proper pre-mRNA splicing of plant cap binding protein 20 genes. Frontiers in plant science, 9: 475. https://doi.org/10.3389/fpls.2018.00475

4. Zhang M, Perelson A S, Tung C-S. (2011). RNA structural motifs. eLS, 2011(August ): 1-10. https://doi.org/10.1002/9780470015902.a0003132.pub2

5. Chiang Y S, Gelfand T I, Kister A E, Gelfand I M. (2007). New classification of supersecondary structures of sandwich‐like proteins uncovers strict patterns of strand assemblage. Proteins: Structure, Function, and Bioinformatics, 68(4): 915-921. https://doi.org/10.1002/prot.21473

6. Raff M, Alberts B, Lewis J, Johnson A, Roberts K. (2002). Molecular biology of the cell 4th edition: National Center for Biotechnology InformationÕs Bookshelf.

7. Ray D, Kazan H, Cook K B, Weirauch M T, Najafabadi H S, Li X, Gueroussov S, Albu M, Zheng H, Yang A. (2013). A compendium of RNA-binding motifs for decoding gene regulation. Nature, 499(7457): 172-177. https://doi.org/10.1038/nature12311

8. Lambert N, Robertson A, Jangi M, McGeary S, Sharp P A, Burge C B. (2014). RNA Bind-n-Seq: quantitative assessment of the sequence and structural binding specificity of RNA binding proteins. Molecular cell, 54(5): 887-900. https://doi.org/10.1016/j.molcel.2014.04.016

9. Shi X, Germain A, Hanson M R, Bentolila S. (2016). RNA recognition motif-containing protein ORRM4 broadly affects mitochondrial RNA editing and impacts plant development and flowering. Plant Physiology, 170(1): 294-309. https://doi.org/10.1104/pp.15.01280

10. Daub J, Eberhardt R Y, Tate J G, Burge S W. (2015). Rfam: annotating families of non-coding RNA sequences: Springer. https://doi.org/10.1007/978-1-4939-2291-8_22

11. Liu N, Xiao Z-D, Yu C-H, Shao P, Liang Y-T, Guan D-G, Yang J-H, Chen C-L, Qu L-H, Zhou H. (2009). SnoRNAs from the filamentous fungus Neurospora crassa: structural, functional and evolutionary insights. BMC genomics, 10(1): 1-13. https://doi.org/10.1186/1471-2164-10-515

12. Rivas E, Eddy S R. (2001). Noncoding RNA gene detection using comparative sequence analysis. BMC bioinformatics, 2(1): 1-19. https://doi.org/10.1186/1471-2105-2-8

13. Washietl S, Hofacker I L, Stadler P F. (2005). Fast and reliable prediction of noncoding RNAs. Proceedings of the National Academy of Sciences, 102(7): 2454-2459. https://doi.org/10.1073/pnas.0409169102

14. Yao Z, Weinberg Z, Ruzzo W L. (2006). CMfinder—a covariance model based RNA motif finding algorithm. Bioinformatics, 22(4): 445-452. https://doi.org/10.1093/bioinformatics/btk008

15. Eddy S R, Durbin R. (1994). RNA sequence analysis using covariance models. Nucleic acids research, 22(11): 2079-2088. https://doi.org/10.1093/nar/22.11.2079

16. Li S, Breaker R R. (2017). Identification of 15 candidate structured noncoding RNA motifs in fungi by comparative genomics. BMC genomics, 18(1): 1-17. https://doi.org/10.1186/s12864-017-4171-y

17. Gruber A R, Findeiß S, Washietl S, Hofacker I L, Stadler P F. (2010). RNAz 2.0: improved noncoding RNA detection Biocomputing 2010 (pp. 69-79): World Scientific. https://doi.org/10.1142/9789814295291_0009

18. Pettersen E F, Goddard T D, Huang C C, Couch G S, Greenblatt D M, Meng E C, Ferrin T E. (2004). UCSF Chimera—a visualization system for exploratory research and analysis. Journal of computational chemistry, 25(13): 1605-1612. https://doi.org/10.1002/jcc.20084

19. Hou L, Xie J, Wu Y, Wang J, Duan A, Ao Y, Liu X, Yu X, Yan H, Perreault J. (2021). Identification of 11 candidate structured noncoding RNA motifs in humans by comparative genomics. BMC genomics, 22(1): 1-14. https://doi.org/10.1186/s12864-021-07474-9

20. Glisovic T, Bachorik J L, Yong J, Dreyfuss G. (2008). RNA-binding proteins and post-transcriptional gene regulation. FEBS letters, 582(14): 1977-1986. https://doi.org/10.1016/j.febslet.2008.03.004

21. Lorković Z J. (2009). Role of plant RNA-binding proteins in development, stress response and genome organization. Trends in plant science, 14(4): 229-236. https://doi.org/10.1016/j.tplants.2009.01.007

22. Shi X, Bentolila S, Hanson M R. (2016). Organelle RNA recognition motif-containing (ORRM) proteins are plastid and mitochondrial editing factors in Arabidopsis. Plant signaling & behavior, 11(5): 294-309. https://doi.org/10.1080/15592324.2016.1167299

23. Hackett J B, Shi X, Kobylarz A T, Lucas M K, Wessendorf R L, Hines K M, Bentolila S, Hanson M R, Lu Y. (2017). An organelle RNA recognition motif protein is required for photosystem II subunit psbF transcript editing. Plant Physiology, 173(4): 2278-2293. https://doi.org/10.1104/pp.16.01623

24. Shi X, Castandet B, Germain A, Hanson M R, Bentolila S. (2017). ORRM5, an RNA recognition motif-containing protein, has a unique effect on mitochondrial RNA editing. Journal of experimental botany, 68(11): 2833-2847. https://doi.org/10.1093/jxb/erx139

25. Castandet B, Hotto A M, Strickler S R, Stern D B. (2016). ChloroSeq, an optimized chloroplast RNA-Seq bioinformatic pipeline, reveals remodeling of the organellar transcriptome under heat stress. G3: Genes, Genomes, Genetics, 6(9): 2817-2827. https://doi.org/10.1534/g3.116.030783

26. Takeda R, Zirbel C L, Leontis N B, Wang Y, Ding B. (2018). Allelic RNA motifs in regulating systemic trafficking of Potato spindle tuber viroid. Viruses, 10(4): 160. https://doi.org/10.3390/v10040160

27. Jiang D, Wang M, Li S. (2017). Functional analysis of a viroid RNA motif mediating cell-to-cell movement in Nicotiana benthamiana. Journal of General Virology, 98(1): 121-125. https://doi.org/10.1099/jgv.0.000630

28. Hu W-W, Gong H, Pua E C. (2005). The pivotal roles of the plant S-adenosylmethionine decarboxylase 5′ untranslated leader sequence in regulation of gene expression at the transcriptional and posttranscriptional levels. Plant Physiology, 138(1): 276-286. https://doi.org/10.1104/pp.104.056770

29. Vilela C, McCarthy J E. (2003). Regulation of fungal gene expression via short open reading frames in the mRNA 5′ untranslated region. Molecular microbiology, 49(4): 859-867. https://doi.org/10.1046/j.1365-2958.2003.03622.x

30. Fiore J L, Nesbitt D J. (2013). An RNA folding motif: GNRA tetraloop–receptor interactions. Quarterly reviews of biophysics, 46(3): 223-264. https://doi.org/10.1017/S0033583513000048

31. Chambers A L, Ormerod G, Durley S C, Sing T L, Brown G W, Kent N A, Downs J A. (2012). The INO80 chromatin remodeling complex prevents polyploidy and maintains normal chromatin structure at centromeres. Genes & development, 26(23): 2590-2603. https://doi.org/10.1101/gad.199976.112

32. Beck J, Ebel F. (2013). Characterization of the major Woronin body protein HexA of the human pathogenic mold Aspergillus fumigatus. International Journal of Medical Microbiology, 303(2): 90-97. https://doi.org/10.1016/j.ijmm.2012.11.005

33. Yuan P, Jedd G, Kumaran D, Swaminathan S, Shio H, Hewitt D, Chua N-H, Swaminathan K. (2003). A HEX-1 crystal lattice required for Woronin body function in Neurospora crassa. Nature Structural & Molecular Biology, 10(4): 264-270. https://doi.org/10.1038/nsb910

34. Molinaro M, Tinoco Jr I. (1995). Use of ultra stable UNCG tetraloop hairpins to fold RNA structures: thermodynamic and spectroscopic applications. Nucleic acids research, 23(15): 3056-3063. https://doi.org/10.1093/nar/23.15.3056

35. Weinberg Z, Wang J X, Bogue J, Yang J, Corbino K, Moy R H, Breaker R R. (2010). Comparative genomics reveals 104 candidate structured RNAs from bacteria, archaea, and their metagenomes. Genome biology, 11(3): 1-17. https://doi.org/10.1186/gb-2010-11-3-r31

36. Staple D W, Butcher S E. (2005). Pseudoknots: RNA structures with diverse functions. PLoS Biol, 3(6): e213. 10.1371/journal.pbio.0030213

37. Takeda R, Petrov A I, Leontis N B, Ding B. (2011). A three-dimensional RNA motif in Potato spindle tuber viroid mediates trafficking from palisade mesophyll to spongy mesophyll in Nicotiana benthamiana. The Plant Cell, 23(1): 258-272. PMID: 21258006; PMCID: PMC3051236; https://doi.org/10.1105/tpc.110.081414

38. Adams P L, Stahley M R, Kosek A B, Wang J, Strobel S A. (2004). Crystal structure of a self-splicing group I intron with both exons. Nature, 430(6995): 45-50. https://doi.org/10.1038/nature02642

39. Ke A, Zhou K, Ding F, Cate J H, Doudna J A. (2004). A conformational switch controls hepatitis delta virus ribozyme catalysis. Nature, 429(6988): 201-205. https://doi.org/10.1038/nature02522

40. Jaeger J, Restle T, Steitz T A. (1998). The structure of HIV‐1 reverse transcriptase complexed with an RNA pseudoknot inhibitor. The EMBO journal, 17(15): 4535-4542. https://doi.org/10.1093/emboj/17.15.4535

41. Tung C-S. (1997). A computational approach to modeling nucleic acid hairpin structures. Biophysical journal, 72(2): 876-885. https://doi.org/10.1016/S0006-3495(97)78722-8

42. Wolters J. (1992). The nature of preferred hairpin structures in 16S-like rRNA variable regions. Nucleic acids research, 20(8): 1843-1850. https://doi.org/10.1093/nar/20.8.1843

43. Shu Z, Bevilacqua P C. (1999). Isolation and characterization of thermodynamically stable and unstable RNA hairpins from a triloop combinatorial library. Biochemistry, 38(46): 15369-15379. https://doi.org/10.1021/bi991774z

44. Diener J L, Moore P B. (1998). Solution structure of a substrate for the archaeal pre-tRNA splicing endonucleases: the bulge-helix-bulge motif. Molecular cell, 1(6): 883-894. https://doi.org/10.1016/S1097-2765(00)80087-8

45. Yoshinari S, Itoh T, Hallam S J, DeLong E F, Yokobori S-i, Yamagishi A, Oshima T, Kita K, Watanabe Y-i. (2006). Archaeal pre-mRNA splicing: a connection to hetero-oligomeric splicing endonuclease. Biochemical and Biophysical Research Communications, 346(3): 1024-1032. https://doi.org/10.1016/j.bbrc.2006.06.011

46. Ulyanov N B, Mujeeb A, Du Z, Tonelli M, Parslow T G, James T L. (2006). NMR structure of the full-length linear dimer of stem-loop-1 RNA in the HIV-1 dimer initiation site. Journal of biological chemistry, 281(23): 16168-16177. https://doi.org/10.1074/jbc.M601711200

47. Clever J L, Parslow T G. (1997). Mutant human immunodeficiency virus type 1 genomes with defects in RNA dimerization or encapsidation. Journal of virology, 71(5): 3407-3414. PMCID: PMC191485; PMID: 9094610

48. Cate J H, Gooding A R, Podell E, Zhou K, Golden B L, Kundrot C E, Cech T R, Doudna J A. (1996). Crystal structure of a group I ribozyme domain: principles of RNA packing. Science, 273(5282): 1678-1685. https://doi.org/10.1126/science.273.5282.1678

49. Tamura M, Holbrook S R. (2002). Sequence and structural conservation in RNA ribose zippers. Journal of molecular biology, 320(3): 455-474. https://doi.org/10.1016/S0022-2836(02)00515-6

Journal of Agricultural Sciences and Engineering

A Review of RNA Motifs, Identification Algorithms and their Function on Plants

References

References

Volume 3, Issue 1
January 2021
Pages 28-40

A Review of RNA Motifs, Identification Algorithms and their Function on Plants

References

References

Volume 3, Issue 1January 2021Pages 28-40

Volume 3, Issue 1
January 2021
Pages 28-40