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A Ribo-Seq Method to Study Genome-Wide Translational Regulation in Plants

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Environmental Responses in Plants

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2494))

Abstract

Protein production from mRNA is one of the fundamental molecular processes in a cell. Accurate genome-wide information on the levels of translation and ribosome distribution on mRNA can be gathered by carrying out ribosome footprinting, aka Ribo-seq. Herein, we present a detailed protocol describing the construction of parallel Ribo-seq and RNA-seq libraries from Arabidopsis seedlings treated with the plant hormone auxin. The improved protocol for ribosome footprint library generation can be easily adapted to analyzing the effects on translation of genetic perturbations and various abiotic and biotic factors to shed the much-needed light on translational regulation in plants.

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References

  1. Ingolia NT, Ghaemmaghami S, Newman JR et al (2009) Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science 324(5924):218–223

    Article  CAS  Google Scholar 

  2. Ingolia NT, Lareau LF, Weissman JS (2011) Ribosome profiling of mouse embryonic stem cells reveals the complexity and dynamics of mammalian proteomes. Cell 147(4):789–802

    Article  CAS  Google Scholar 

  3. Brar GA, Yassour M, Friedman N et al (2012) High-resolution view of the yeast meiotic program revealed by ribosome profiling. Science 335:552–557

    Article  CAS  Google Scholar 

  4. Stern-Ginossar N, Weisburd B, Michalski A et al (2012) Decoding human cytomegalovirus. Science 338:1088–1093

    Article  CAS  Google Scholar 

  5. Hsu PY, Calviello L, Wu HYL et al (2016) Super-resolution ribosome profiling reveals unannotated translation events in Arabidopsis. Proc Natl Acad Sci 113:7126–7135

    Google Scholar 

  6. McGlincy NJ, Ingolia NT (2017) Transcriptome-wide measurement of translation by ribosome profiling. Methods 126:112–129

    Article  Google Scholar 

  7. Spealman P, Wang H, May G et al (2016) Exploring ribosome positioning on translating transcripts with ribosome profiling. In: Post-transcriptional gene regulation. Humana Press, New York, pp 71–97

    Chapter  Google Scholar 

  8. Chotewutmontri P, Stiffler N, Watkins KP et al (2018) Ribosome profiling in maize. In: Maize. Humana Press, New York, pp 165–183

    Chapter  Google Scholar 

  9. Gerashchenko MV, Gladyshev VN (2014) Translation inhibitors cause abnormalities in ribosome profiling experiments. Nuc Acids Res 42(17):e134–e134

    Article  Google Scholar 

  10. Gerashchenko MV, Gladyshev VN (2017) Ribonuclease selection for ribosome profiling. Nuc Acids Res 45(2):e6–e6

    Article  Google Scholar 

  11. Liu MJ, Wu SH, Wu JF et al (2013) Translational landscape of photomorphogenic Arabidopsis. Plant Cell 25:3699–3710

    Article  CAS  Google Scholar 

  12. Zoschke R, Watkins KP, Barkan A (2013) A rapid ribosome profiling method elucidates chloroplast ribosome behavior in vivo. Plant Cell 25:2265–2275

    Article  CAS  Google Scholar 

  13. Juntawong P, Hummel M, Bazin J et al (2015) Ribosome profiling: a tool for quantitative evaluation of dynamics in mRNA translation. In: Plant functional genomics. Humana Press, New York, pp 139–173

    Chapter  Google Scholar 

  14. Lei L, Shi J, Chen J et al (2015) Ribosome profiling reveals dynamic translational landscape in maize seedlings under drought stress. Plant J 84:1206–1218

    Article  CAS  Google Scholar 

  15. Merchante C, Brumos J, Yun J et al (2015) Gene-specific translation regulation mediated by the hormone-signaling molecule EIN2. Cell 163:684–697

    Article  CAS  Google Scholar 

  16. Bazin J, Baerenfaller K, Gosai SJ et al (2017) Global analysis of ribosome-associated noncoding RNAs unveils new modes of translational regulation. Proc Natl Acad Sci 114:10018–10027

    Article  Google Scholar 

  17. Liu TY, Huang HH, Wheeler D et al (2017) Time-resolved proteomics extends ribosome profiling-based measurements of protein synthesis dynamics. Cell Syst 4(6):636–644

    Article  CAS  Google Scholar 

  18. Shamimuzzaman M, Vodkin L (2018) Ribosome profiling reveals changes in translational status of soybean transcripts during immature cotyledon development. PLoS One 13(3):e0194596

    Article  Google Scholar 

  19. Zanetti ME, Chang F, Gong F et al (2005) Immunopurification of polyribosomal complexes of Arabidopsis for global analysis of gene expression. Plant Physiol 138(2):624–635

    Article  CAS  Google Scholar 

  20. Reynoso MA, Juntawong P, Lancia M et al (2015) Translating Ribosome Affinity Purification (TRAP) followed by RNA sequencing technology (TRAP-SEQ) for quantitative assessment of plant translatomes. In: Plant functional genomics. Humana Press, New York, pp 185–207

    Chapter  Google Scholar 

  21. Freeberg L, Kuersten S, Syed F (2013) Isolate and sequence ribosome-protected mRNA fragments using size-exclusion chromatography. Nat Methods 10(5):i–ii

    Article  CAS  Google Scholar 

  22. Vaidyanathan R, Kuersten S, Radek A et al (2013) Assessing mRNA translation: deep sequencing of ribosome footprints. J Biomol Tech 24:S60

    PubMed Central  Google Scholar 

  23. Lareau LF, Hite DH, Hogan GJ et al (2014) Distinct stages of the translation elongation cycle revealed by sequencing ribosome-protected mRNA fragments. elife 3:e01257

    Article  Google Scholar 

  24. Lodish H, Berk A, Zipursky SL et al (2000) The three roles of RNA in protein synthesis. In: Molecular cell biology, 4th edn. WH Freeman, New York

    Google Scholar 

  25. Kraus AJ, Brink BG, Siegel TN (2019) Efficient and specific oligo-based depletion of rRNA. Sci Rep 9:1–8

    Google Scholar 

  26. Jayaprakash AD, Jabado O, Brown BD et al (2011) Identification and remediation of biases in the activity of RNA ligases in small-RNA deep sequencing. Nucl Acids Res 39(21):e141–e141

    Article  CAS  Google Scholar 

  27. Sorefan K, Pais H, Hall AE et al (2012) Reducing ligation bias of small RNAs in libraries for next generation sequencing. Silence 3:1–11

    Article  Google Scholar 

  28. Alexander B, Campo CD, Ignatova Z (2016) Map** the non-standardized biases of ribosome profiling. Biol Chem 397:23–35

    Article  Google Scholar 

  29. Kage U, Powell JJ, Gardiner DM et al (2020) Ribosome profiling in plants: what is not lost in translation? J Experim Bot 71:5323–5332

    Article  CAS  Google Scholar 

  30. Robins DM, Schimke RT (1978) Differential effects of estrogen and progesterone on ovalbumin mRNA utilization. J Biol Chem 253(24):8925–8934

    Article  CAS  Google Scholar 

  31. Hafner M, Landgraf P, Ludwig J, Rice A, Ojo T, Lin C, Holoch D, Lim C, Tuschl T (2008) Identification of microRNAs and other small regulatory RNAs using cDNA library sequencing. Methods 44(1):3–12

    Article  CAS  Google Scholar 

  32. Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J 17(1):10–12

    Article  Google Scholar 

  33. Howe KL, Contreras-Moreira B, De Silva N et al (2020) Ensembl genomes 2020—enabling non-vertebrate genomic research. Nucleic Acids Res 48:D689–D695

    Article  CAS  Google Scholar 

  34. Langmead B, Salzberg SL (2012) Fast gapped-read alignment with Bowtie 2. Nat Methods 9(4):357

    Article  CAS  Google Scholar 

  35. Engström PG, Steijger T, Sipos B et al (2013) Systematic evaluation of spliced alignment programs for RNA-seq data. Nat Methods 10(12):1185–1191

    Article  Google Scholar 

  36. Thorvaldsdóttir H, Robinson JT, Mesirov JP (2013) Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Briefings Bioinform 14(2):178–192

    Article  Google Scholar 

  37. Perkins P, Mazzoni-Putman S, Stepanova A et al (2019) RiboStreamR: a web application for quality control, analysis, and visualization of Ribo-seq data. BMC Genomics 20(5):1–9

    CAS  Google Scholar 

  38. Nunez AN, Kavlick JM, Robertson J et al (2008) Application of circular ligase to provide template for rolling circle amplification of low amounts of fragmented DNA. In: Nineteenth international symposium on human identification. Promega Corporation, Madison, pp 1–7

    Google Scholar 

  39. MiSeq System User Guide. http://application.sb-roscoff.fr/download/fr2424/abims/corre/ngs/1_illumina/MiSeq%20System%20User%20Guide%20(15027617).pdf

  40. MiniSeq System Guide. https://support.illumina.com/content/dam/illumina-support/documents/documentation/system_documentation/miniseq/miniseq-system-guide-1000000002695-04.pdf

  41. NextSeq 500 System Guide. https://support.illumina.com/content/dam/illumina-support/documents/documentation/system_documentation/nextseq/nextseq-500-system-guide-15046563-06.pdf

  42. NovaSeq 6000 System Guide. https://support.illumina.com/content/dam/illumina-support/documents/documentation/system_documentation/novaseq/novaseq-6000-system-guide-1000000019358-14.pdf

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Acknowledgments

The research in the Alonso-Stepanova Laboratory is supported by the National Science Foundation grants 1650139, 1444561, and 1940829 to ANS and JMA and 1750006 to ANS. We are thankful to Dr. Mario Fenech for the critical reading of this manuscript.

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Authors and Affiliations

  1. Department of Plant and Microbial Biology, Program in Genetics, North Carolina State University, Raleigh, NC, USA

    Hao Chen, Jose M. Alonso & Anna N. Stepanova

Authors
  1. Hao Chen
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  2. Jose M. Alonso
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  3. Anna N. Stepanova
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Corresponding author

Correspondence to Anna N. Stepanova .

Editor information

Editors and Affiliations

  1. Plant Molecular Biology, Instituto Gulbenkian de Ciência, Oeiras, Portugal

    Paula Duque

  2. Plant Molecular Biology, Instituto Gulbenkian de Ciência, Oeiras, Portugal

    Dóra Szakonyi

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© 2022 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Chen, H., Alonso, J.M., Stepanova, A.N. (2022). A Ribo-Seq Method to Study Genome-Wide Translational Regulation in Plants. In: Duque, P., Szakonyi, D. (eds) Environmental Responses in Plants. Methods in Molecular Biology, vol 2494. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2297-1_6

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  • DOI: https://doi.org/10.1007/978-1-0716-2297-1_6

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2296-4

  • Online ISBN: 978-1-0716-2297-1

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