Preview

Vavilov Journal of Genetics and Breeding

Advanced search

Ribosomal profiling as a tool for studying translation in plants: main results, problems and future prospects

https://doi.org/10.18699/VJ21.028

Abstract

The expression of eukaryotic genes can be regulated at several stages, including the translation of mRNA. It is known that the structure of mRNA can affect both the efficiency of interaction with the translation apparatus in general and the choice of translation initiation sites. To study the translated fraction of the transcriptome, experimental methods of analysis were developed, the most informative of which is ribosomal profiling (RP, Ribo-seq). Originally developed for use in yeast systems, this method has been adapted for research in translation mechanisms in many plant species. This technology includes the isolation of the polysomal fraction and high-performance sequencing of a pool of mRNA fragments associated with ribosomes. Comparing the results of transcript coverage with reads obtained using the ribosome profiling with the transcriptional efficiency of genes allows the translation efficiency to be evaluated for each transcript. The exact positions of ribosomes determined on mRNA sequences allow determining the translation of open reading frames and switching between the translation of several reading frames – a phenomenon in which two or more overlapping frames are read from one mRNA and different proteins are synthesized. The advantage of this method is that it provides quantitative estimates of ribosome coverage of mRNA and can detect relatively rare translation events. Using this technology, it was possible to identify and classify plant genes by the type of regulation of their expression at the transcription, translation, or both levels. Features of the mRNA structure that affect translation levels have been revealed: the formation of G2 quadruplexes and the presence of specific motifs in the 5’-UTR region, GC content, the presence of alternative translation starts, and the influence of uORFs on the translation of downstream mORFs. In this review, we briefly reviewed the RP methodology and the prospects for its application to study the structural and functional organization and regulation of plant gene expression.

About the Authors

D. A. Afonnikov
Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Novosibirsk State University
Russian Federation

Novosibirsk



O. I. Sinitsyna
Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Novosibirsk State University
Russian Federation

Novosibirsk



T. S. Golubeva
Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Novosibirsk State University
Russian Federation

Novosibirsk



N. A. Shmakov
Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Novosibirsk State University
Russian Federation

Novosibirsk



A. V. Kochetov
Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Novosibirsk State University
Russian Federation

Novosibirsk



References

1. Abeles F.B., Morgan P.W., Saltveit Jr. M.E. Ethylene in Plant Biology. San Diego, CA: Academic Press, 2012.

2. Alatorre-Cobos F., Cruz-Ramírez A., Hayden C.A., Pérez-Torres C.-A., Chauvin A.-L., Ibarra-Laclette E., Alva-Cortés E., Jorgensen R.A., Herrera-Estrella L. Translational regulation of Arabidopsis XIPOTL1 is modulated by phosphocholine levels via the phylogenetically conserved upstream open reading frame. J. Exp. Bot. 2012;63(14): 5203-5221. DOI 10.1093/jxb/ers180.

3. Andreev D.E., O’Connor P.B., Loughran G., Dmitriev S.E., Baranov P.V., Shatsky I.N. Insights into the mechanisms of eukaryotic translation gained with ribosome profiling. Nucleic Acids Res. 2017; 45(2):513-526. DOI 10.1093/nar/gkw1190.

4. Archer S.K., Shirokikh N.E., Beilharz T.H., Preiss T. Dynamics of ribosome scanning and recycling revealed by translation complex profiling. Nature. 2016;535(7613):570-574. DOI 10.1038/nature18647.

5. Baek Y.S., Goodrich L.V., Brown P.J., James B.T., Moose S.P., Lambert K.N., Riechers D.E. Transcriptome profiling and genome-wide association studies reveal GSTs and other defense genes involved in multiple signaling pathways induced by herbicides Safener in grain sorghum. Front. Plant Sci. 2019;10:192. DOI 10.3389/fpls.2019.00192.

6. Brar G.A., Weissman J.S. Ribosome profiling reveals the what, when, where and how of protein synthesis. Nat. Rev. Mol. Cell Biol. 2015; 16:651-664. DOI 10.1038/nrm4069.

7. Brar G.A., Yassour M., Friedman N., Regev A., Ingolia N.T., Weissman J.S. High-resolution view of the yeast meiotic program revealed by ribosome profiling. Science. 2012;335(6068):552-557. DOI 10.1126/science.1215110.

8. Calviello L., Mukherjee N., Wyler E., Zauber H., Hirsekorn A., Selbach M., Landthaler M., Obermayer B., Ohler U. Detecting actively translated open reading frames in ribosome profiling data. Nat. Methods. 2016;13:165-170. DOI 10.1038/nmeth.3688.

9. Carja O., Xing T., Wallace E.W.J., Plotkin J.B., Shah P. Riboviz: analysis and visualization of ribosome profiling datasets. BMC Bioinformatics. 2017;18:461. DOI 10.1186/s12859-017-1873-8.

10. Chhangawala S., Rudy G., Mason C.E., Rosenfeld J.A. The impact of read length on quantification of differentially expressed genes and splice junction detection. Genome Biol. 2015;16:131. DOI 10.1186/s13059-015-0697-y.

11. Chung B.Y., Hardcastle T.J., Jones J.D., Irigoyen N., Firth A.E., Baulcombe D.C., Brierley I. The use of duplex-specific nuclease in ribosome profiling and a user-friendly software package for Ribo-seq data analysis. RNA. 2015;21:1731-1745. DOI 10.1261/rna.052548.115.

12. Efroni I., Birnbaum K.D. The potential of single-cell profiling in plants. Genome Biol. 2016;17(1):65. DOI 10.1186/s13059-016-0931-2.

13. Faridani O.R., Abdullayev I., Hagemann-Jensen M., Schell J.P., Lanner F., Sandberg R. Single-cell sequencing of the small-RNA transcriptome. Nat. Biotechnol. 2016;34:1264-1266. DOI 10.1038/nbt.3701.

14. Gawroński P., Jensen P.E., Karpiński S., Leister D., Scharff L.B. Pausing of chloroplast ribosomes is induced by multiple features and is linked to the assembly of photosynthetic complexes. Plant Physiol. 2018;176:2557-2569. DOI 10.1104/pp.17.01564.

15. Hanfrey C., Franceschetti M., Mayer M.J., Illingworth C., Michael A.J. Abrogation of upstream open reading frame-mediated translational control of a plant S-adenosylmethionine decarboxylase results in polyamine disruption and growth perturbations. J. Biol. Chem. 2002; 277(46):44131-44139. DOI 10.1074/jbc.M206161200.

16. Heiman M., Kulicke R., Fenster R.J., Greengard P., Heintz N. Cell type-specific mRNA purification by translating ribosome affinity purification (TRAP). Nat. Protoc. 2014;9(6):1282-1291. DOI 10.1038/nprot.2014.085.

17. Hornstein N., Torres D., Das Sharma S., Tang G., Canoll P., Sims P.A. Ligation-free ribosome profiling of cell type-specific translation in the brain. Genome Biol. 2016;17:149. DOI 10.1186/s13059-0161005-1.

18. Hsu P.Y., Calviello L., Wu H.-Y.L., Li F.-W., Rothfels C.J., Ohler U., Benfey P.N. Super-resolution ribosome profiling reveals unannotated translation events in Arabidopsis. Proc. Natl. Acad. Sci. USA. 2016;113(45):E7126-E7135. DOI 10.1073/pnas.1614788113.

19. Imai A., Hanzawa Y., Komura M., Yamamoto K.T., Komeda Y., Takahashi T. The dwarf phenotype of the Arabidopsis acl5 mutant is suppressed by a mutation in an upstream ORF of a bHLH gene. Development. 2006;133:3575-3585. DOI 10.1242/dev.02535.

20. Ingolia N.T., Ghaemmaghami S., Newman J.R., Weissman J.S. Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science. 2009;324(5924):218-223. DOI 10.1126/science.1168978.

21. Ingolia N.T., Lareau L.F., Weissman J.S. Ribosome profiling of mouse embryonic stem cells reveals the complexity and dynamics of mammalian proteomes. Cell. 2011;147:789-802. DOI 10.1016/j.cell.2011.10.002.

22. Jackson R., Standart N. The awesome power of ribosome profiling. RNA. 2015;21:652-654. DOI 10.1261/rna.049908.115.

23. Jan C.H., Williams C.C., Weissman J.S. Principles of ER cotranslational translocation revealed by proximity-specific ribosome profiling. Science. 2014;346(6210):1257521. DOI 10.1126/science.1257521.

24. Jiao Y., Meyerowitz E.M. Cell-type specific analysis of translating RNAs in developing flowers reveals new levels of control. Mol. Syst. Biol. 2010;6:419. DOI 10.1038/msb.2010.76.

25. Juntawong P., Girke T., Bazin J., Bailey-Serres J. Translational dynamics revealed by genome-wide profiling of ribosome footprints in Arabidopsis. Proc. Natl. Acad. Sci. USA. 2014;111(1):E203-E212. DOI 10.1073/pnas.1317811111.

26. Kahles A., Behr J., Rätsch G. MMR: a tool for read multi-mapper resolution. Bioinformatics. 2016;32(5):770-772. DOI 10.1093/bioinformatics/btv624.

27. Kang W.-H., Sim Y.M., Koo N., Nam J.-Y., Lee J., Kim N., Jang H., Kim Y.-M., Yeom S.-I. Transcriptome profiling of abiotic responses to heat, cold, salt, and osmotic stress of Capsicum annuum L. Sci. Data. 2020;7:1-7. DOI 10.1038/s41597-020-0352-7.

28. Kazan K., Gardiner D.M. Transcriptomics of cereal – Fusarium graminearum interactions: what we have learned so far. Mol. Plant Pathol. 2018;19(3):764-778. DOI 10.1111/mpp.12561.

29. Kuo T.C.Y., Hatakeyama M., Tameshige T., Shimizu K.K., Sese J. Homeolog expression quantification methods for allopolyploids. Brief. Bioinform. 2018;21(2):395-407. DOI 10.1093/bib/bby121.

30. Kurihara Y., Makita Y., Kawashima M., Fujita T., Iwasaki S., Matsui M. Transcripts from downstream alternative transcription start sites evade uORF-mediated inhibition of gene expression in Arabidopsis. Proc. Natl. Acad. Sci. USA. 2018;115(30):7831-7836. DOI 10.1073/pnas.1804971115.

31. Lanver D., Müller A.N., Happel P., Schweizer G., Haas F.B., Franitza M., Pellegrin C., Reissmann S., Altmüller J., Rensing S.A. The biotrophic development of Ustilago maydis studied by RNA-seq analysis. Plant Cell. 2018;30(2):300-323. DOI 10.1105/tpc.17.00764.

32. Lauria F., Tebaldi T., Bernabò P., Groen E.J.N., Gillingwater T.H., Viero G. riboWaltz: Optimization of ribosome P-site positioning in ribosome profiling data. PLoS Comput. Biol. 2018;14. e1006169e1006169.

33. Lei L., Shi J., Chen J., Zhang M., Sun S., Xie S., Li X., Zeng B., Peng L., Hauck A. Ribosome profiling reveals dynamic translational landscape in maize seedlings under drought stress. Plant J. 2015; 84(6):1206-1218. DOI 10.1111/tpj.13073.

34. Liu M.-J., Wu S.-H., Wu J.-F., Lin W.-D., Wu Y.-C., Tsai T.-Y., Tsai H.-L., Wu S.-H. Translational landscape of photomorphogenic Arabidopsis. Plant Cell. 2013;25(10):3699-3710. DOI 10.1105/tpc.113.114769.

35. Lukoszek R., Feist P., Ignatova Z. Insights into the adaptive response of Arabidopsis thaliana to prolonged thermal stress by ribosomal profiling and RNA-Seq. BMC Plant Biol. 2016;16:221. DOI 10.1186/s12870-016-0915-0.

36. Marioni J.C., Mason C.E., Mane S.M., Stephens M., Gilad Y. RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays. Genome Res. 2008;18:1509-1517. DOI 10.1101/gr.079558.108.

37. McGlincy N.J., Ingolia N.T. Transcriptome-wide measurement of translation by ribosome profiling. Methods. 2017;126:112-129. DOI 10.1016/j.ymeth.2017.05.028.

38. Merchante C., Brumos J., Yun J., Hu Q., Spencer K.R., Enríquez P., Binder B.M., Heber S., Stepanova A.N., Alonso J.M. Gene-specific translation regulation mediated by the hormone-signaling molecule EIN2. Cell. 2015;163(3):684-697. DOI 10.1016/j.cell.2015.09.036.

39. Michel A.M., Mullan J.P.A., Velayudhan V., O’Connor P.B.F., DonohueC.A., Baranov P.V. RiboGalaxy: A browser based platform for the alignment, analysis and visualization of ribosome profiling data. RNA Biol. 2016;13(3):316-319. DOI 10.1080/15476286.2016.1141862.

40. Mironova V., Xu J. A single-cell view of tissue regeneration in plants. Curr. Opin. Plant Biol. 2019;52:149-154. DOI 10.1016/j.pbi.2019.09.003.

41. Mortazavi A., Williams B.A., McCue K., Schaeffer L., Wold B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat. Methods. 2008;5:621-628. DOI 10.1038/nmeth.1226.

42. Mustroph A., Bailey-Serres J. The Arabidopsis translatome cell-specific mRNA atlas: Mining suberin and cutin lipid monomer biosynthesis genes as an example for data application. Plant Signal. Behav. 2010;5(3):320-324. DOI 10.4161/psb.5.3.11187.

43. Pfeifer M., Kugler K.G., Sandve S.R., Zhan B., Rudi H., Hvidsten T.R., Mayer K.F.X., Olsen O.-A. Genome interplay in the grain transcriptome of hexaploid bread wheat. Science. 2014;345(6194):1250091. DOI 10.1126/science.1250091.

44. Ramírez-González R.H., Borrill P., Lang D., Harrington S.A., Brinton J., Venturini L., Davey M., Jacobs J., van Ex F., Pasha A., Khedikar Y., Robinson S.J., Cory A.T., Florio T., Concia L., Juery C., Schoonbeek H., Steuernagel B., Xiang D., Ridout C.J., Chalhoub B., Mayer K.F.X., Benhamed M., Latrasse D., Bendahmane A., International Wheat Genome Sequencing Consortium; Wulff B.B.H., Appels R., Tiwari V., Datla R., Choulet F., Pozniak C.J., Provart N.J., Sharpe A.G., Paux E., Spannagl M., Bräutigam A., Uauy C. The transcriptional landscape of polyploid wheat. Science. 2018;361(6403): eaar6089. DOI 10.1126/science.aar6089.

45. Rooijers K., Loayza-Puch F., Nijtmans L.G., Agami R. Ribosome profiling reveals features of normal and disease-associated mitochondrial translation. Nat. Commun. 2013;4:2886. DOI 10.1038/ncomms3886.

46. Saliba A.E., Westermann A.J., Gorski S.A., Vogel J. Single-cell RNAseq: advances and future challenges. Nucleic Acids Res. 2014; 42(14):8845-8860. DOI 10.1093/nar/gku555.

47. Schenk P.M., Kazan K., Wilson I., Anderson J.P., Richmond T., Somerville S.C., Manners J.M. Coordinated plant defense responses in Arabidopsis revealed by microarray analysis. Proc. Natl. Acad. Sci. USA. 2000;97(21):11655-11660. DOI 10.1073/pnas.97.21.11655.

48. Shamimuzzaman M., Vodkin L. Ribosome profiling reveals changes in translational status of soybean transcripts during immature cotyledon development. PLoS One. 2018;13(3):e0194596. DOI 10.1371/journal.pone.0194596.

49. Stern-Ginossar N., Weisburd B., Michalski A., Le V.T.K., Hein M.Y., Huang S.-X., Ma M., Shen B., Qian S.-B., Hengel H. Decoding human cytomegalovirus. Science. 2012;338(6110):1088-1093. DOI 10.1126/science.1227919.

50. Wang H., Wang Y., Xie Z. Computational resources for ribosome profiling: from database to Web server and software. Brief. Bioinform. 2017;20(1):144-155. DOI 10.1093/bib/bbx093.

51. Wang Z., Gerstein M., Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat. Rev. Genet. 2009;10:57-63. DOI 10.1038/nrg2484.

52. Willems P., Ndah E., Jonckheere V., Stael S., Sticker A., Martens L., van Breusegem F., Gevaert K., van Damme P. N-terminal proteomics assisted profiling of the unexplored translation initiation landscape in Arabidopsis thaliana. Mol. Cell. Proteomics. 2017;16(6):10641080. DOI 10.1074/mcp.M116.066662.

53. Wood T.E., Takebayashi N., Barker M.S., Mayrose I., Greenspoon P.B., Rieseberg L.H. The frequency of polyploid speciation in vascular plants. Proc. Natl. Acad. Sci. USA. 2009;106(33):13875-13879. DOI 10.1073/pnas.0811575106.

54. Wu H.-Y.L., Song G., Walley J.W., Hsu P.Y. The tomato translational landscape revealed by transcriptome assembly and ribosome profiling. Plant Physiol. 2019;181(1):367-380. DOI 10.1104/pp.19.00541.

55. Xu G., Greene G.H., Yoo H., Liu L., Marqués J., Motley J., Dong X. Global translational reprogramming is a fundamental layer of immune regulation in plants. Nature. 2017;545:487.

56. Yoo H., Greene G.H., Yuan M., Xu G., Burton D., Liu L., Marqués J., Dong X. Translational regulation of metabolic dynamics during effector-triggered immunity. Mol. Plant. 2019;13(1):88-98. DOI 10.1016/j.molp.2019.09.009.

57. Zoschke R., Watkins K.P., Barkan A. A rapid ribosome profiling method elucidates chloroplast ribosome behavior in vivo. Plant Cell. 2013;25(6):2265-2275. DOI 10.1105/tpc.113.111567.

58. Zumaquero A., Kanematsu S., Nakayashiki H., Matas A., MartínezFerri E., Barceló-Muñóz A., Pliego-Alfaro F., López-Herrera C., Cazorla F., Pliego C. Transcriptome analysis of the fungal pathogen Rosellinia necatrix during infection of a susceptible avocado rootstock identifies potential mechanisms of pathogenesis. BMC Genomics. 2019;20:1016. DOI 10.1186/s12864-019-6387-5.


Review

Views: 821


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2500-3259 (Online)