Article series: Applications of next-generation sequencing

Ribosome profiling: new views of translation, from single codons to genome scale

Journal name:
Nature Reviews Genetics
Year published:
Published online


Genome-wide analyses of gene expression have so far focused on the abundance of mRNA species as measured either by microarray or, more recently, by RNA sequencing. However, neither approach provides information on protein synthesis, which is the true end point of gene expression. Ribosome profiling is an emerging technique that uses deep sequencing to monitor in vivo translation. Studies using ribosome profiling have already provided new insights into the identity and the amount of proteins that are produced by cells, as well as detailed views into the mechanism of protein synthesis itself.

At a glance


  1. Ribosome footprint profiling.
    Figure 1: Ribosome footprint profiling.

    RNase digestion of polysomes that are carrying out translation in vivo yields ribosome-protected mRNA fragments, which are known as ribosome footprints. These footprints are recovered and converted into a DNA library through ligation of a linker followed by reverse transcription and circularization PCR. cDNA libraries are then analysed by deep sequencing. Figure is reproduced, with permission, from Ref. 65 © (2012) Macmillan Publishers Ltd. All rights reserved.

  2. Analysis of ribosome occupancy data.
    Figure 2: Analysis of ribosome occupancy data.

    a | The positions of ribosomes on many copies of an mRNA in a cell population are converted into nuclease-protected footprints that correspond to ribosome positions in vivo. Ribosome profiling data indicate the density of ribosomes at each position on the transcript; the thick line represents the protein-coding sequence and the thin lines represent the untranslated regions. b | The amount of protein synthesized corresponds to ribosome density across the protein-coding sequence of a transcript. Ribosome footprints indicate the total number of ribosomes that are engaged in synthesizing a protein, which is determined by the number of mRNAs in the cell and by the number of ribosomes that translate each transcript. Changes in either mRNA abundance (for example, having fewer mRNAs) or ribosome loading (for example, having fewer ribosomes per mRNA) will affect the number of ribosome footprints that are recovered from the gene.

  3. Alternative reading frames.
    Figure 3: Alternative reading frames.

    a | Alternative sites of translation initiation may be found in the 5′ transcript leader and may initiate translation of a short upstream open reading frame (uORF, shown in orange). These uORFs can overlap the start codon of the protein-coding gene, which leads to out-of-frame translation that extends into the coding sequence. Alternative reading frame translation can also begin within the protein-coding gene. An in-frame start codon within a gene can lead to a truncated protein, whereas an in-frame start codon upstream of a gene without an intervening stop codon can produce an extended protein product. The shaded regions represent the alternative mRNA sequences that are being translated. b | Alternative translation start sites may result either from non-canonical initiation, such as 'leaky scanning' past the first start codon, or from canonical initiation on alternative mRNA variants.

  4. Ribosomal pausing and co-translational processes.
    Figure 4: Ribosomal pausing and co-translational processes.

    a | Ribosomal stalling causes an accumulation of ribosome footprints at a specific position within a gene and thus a peak of ribosome footprint density. b | Footprints of ribosomes can be purified by pulldown assays through their association with co-translational protein biogenesis factors, such as folding chaperones, which indicate the time during translation and the position in the protein at which these factors act.

  5. Deconvolving transcription and translation.
    Figure 5: Deconvolving transcription and translation.

    Matched ribosome profiling and mRNA sequencing (RNA-seq) data distinguish between alternative modes of gene expression regulation. Transcriptional induction results in matched increases in mRNA abundance, as measured by RNA-seq, and protein synthesis, as measured by ribosome profiling. Translational induction manifests as an increase in ribosome profiling measurements without a corresponding change in mRNA abundance.


  1. Brown, P. O. & Botstein, D. Exploring the new world of the genome with DNA microarrays. Nature Genet. 21, 3337 (1999).
  2. Wang, Z., Gerstein, M. & Snyder, M. RNA-Seq: a revolutionary tool for transcriptomics. Nature Rev. Genet. 10, 5763 (2009).
  3. 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 324, 218223 (2009).
  4. Johannes, G., Carter, M. S., Eisen, M. B., Brown, P. O. & Sarnow, P. Identification of eukaryotic mRNAs that are translated at reduced cap binding complex eIF4F concentrations using a cDNA microarray. Proc. Natl Acad. Sci. USA 96, 1311813123 (1999).
  5. Arava, Y. et al. Genome-wide analysis of mRNA translation profiles in Saccharomyces cerevisiae. Proc. Natl Acad. Sci. USA 100, 38893894 (2003).
  6. Hendrickson, D. G. et al. Concordant regulation of translation and mRNA abundance for hundreds of targets of a human microRNA. PLoS Biol. 7, e1000238 (2009).
  7. Steitz, J. A. Polypeptide chain initiation: nucleotide sequences of the three ribosomal binding sites in bacteriophage R17 RNA. Nature 224, 957964 (1969).
  8. Wolin, S. L. & Walter, P. Ribosome pausing and stacking during translation of a eukaryotic mRNA. EMBO J. 7, 35593569 (1988).
  9. Kim, D. et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 14, R36 (2013).
  10. Anders, S. & Huber, W. Differential expression analysis for sequence count data. Genome Biol. 11, R106 (2010).
  11. Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139140 (2010).
  12. Olshen, A. B. et al. Assessing gene-level translational control from ribosome profiling. Bioinformatics 29, 29953002 (2013).
  13. Michel, A. M. et al. GWIPS-viz: development of a ribo-seq genome browser. Nucleic Acids Res. 42, D859D864 (2013).
  14. 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 147, 789802 (2011).
  15. Shah, P., Ding, Y., Niemczyk, M., Kudla, G. & Plotkin, J. B. Rate-limiting steps in yeast protein translation. Cell 153, 15891601 (2013).
  16. Arribere, J. A. & Gilbert, W. V. Roles for transcript leaders in translation and mRNA decay revealed by transcript leader sequencing. Genome Res. 23, 977987 (2013).
  17. Vogel, C. & Marcotte, E. M. Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nature Rev. Genet. 13, 227232 (2012).
  18. Michel, A. M. et al. Observation of dually decoded regions of the human genome using ribosome profiling data. Genome Res. 22, 22192229 (2012).
  19. Brar, G. A. et al. High-resolution view of the yeast meiotic program revealed by ribosome profiling. Science 335, 552557 (2012).
  20. Chew, G. L. et al. Ribosome profiling reveals resemblance between long non-coding RNAs and 5′ leaders of coding RNAs. Development 140, 28282834 (2013).
  21. Lee, S., Liu, B., Huang, S. X., Shen, B. & Qian, S. B. Global mapping of translation initiation sites in mammalian cells at single-nucleotide resolution. Proc. Natl Acad. Sci. USA 109, E2424E2432 (2012).
  22. Fritsch, C. et al. Genome-wide search for novel human uORFs and N-terminal protein extensions using ribosomal footprinting. Genome Res. 22, 22082218 (2012).
  23. Sonenberg, N. & Hinnebusch, A. G. Regulation of translation initiation in eukaryotes: mechanisms and biological targets. Cell 136, 731745 (2009).
  24. Starck, S. R. et al. Leucine-tRNA initiates at CUG start codons for protein synthesis and presentation by MHC class I. Science 336, 17191723 (2012).
  25. Menschaert, G. et al. Deep proteome coverage based on ribosome profiling aids mass spectrometry-based protein and peptide discovery and provides evidence of alternative translation products and near-cognate translation initiation events. Mol. Cell. Proteomics 12, 17801790 (2013).
  26. Fournier, C. T. et al. Amino termini of many yeast proteins map to downstream start codons. J. Proteome Res. 11, 57125719 (2012).
  27. Pelechano, V., Wei, W. & Steinmetz, L. M. Extensive transcriptional heterogeneity revealed by isoform profiling. Nature 497, 127131 (2013).
  28. Sonenberg, N. & Hinnebusch, A. G. New modes of translational control in development, behavior and disease. Mol. Cell 28, 721729 (2007).
  29. Stern-Ginossar, N. et al. Decoding human cytomegalovirus. Science 338, 10881093 (2012).
  30. Schwaid, A. G. et al. Chemoproteomic discovery of cysteine-containing human short open reading frames. J. Am. Chem. Soc. 135, 1675016753 (2013).
  31. Slavoff, S. A. et al. Peptidomic discovery of short open reading frame-encoded peptides in human cells. Nature Chem. Biol. 9, 5964 (2013).
  32. Kondo, T. et al. Small peptide regulators of actin-based cell morphogenesis encoded by a polycistronic mRNA. Nature Cell Biol. 9, 660665 (2007).
  33. Guttman, M., Russell, P., Ingolia, N. T., Weissman, J. S. & Lander, E. S. Ribosome profiling provides evidence that large noncoding RNAs do not encode proteins. Cell 154, 240251 (2013).
  34. Ulitsky, I. & Bartel, D. P. lincRNAs: genomics, evolution, and mechanisms. Cell 154, 2646 (2013).
  35. Drummond, D. A. & Wilke, C. O. The evolutionary consequences of erroneous protein synthesis. Nature Rev. Genet. 10, 715724 (2009).
  36. Carvunis, A. R. et al. Proto-genes and de novo gene birth. Nature 487, 370374 (2012).
  37. Calvo, S. E., Pagliarini, D. J. & Mootha, V. K. Upstream open reading frames cause widespread reduction of protein expression and are polymorphic among humans. Proc. Natl Acad. Sci. USA 106, 75077512 (2009).
  38. Plotkin, J. B. & Kudla, G. Synonymous but not the same: the causes and consequences of codon bias. Nature Rev. Genet. 12, 3242 (2011).
  39. Li, G. W., Oh, E. & Weissman, J. S. The anti- Shine–Dalgarno sequence drives translational pausing and codon choice in bacteria. Nature 484, 538541 (2012).
  40. Qian, W., Yang, J. R., Pearson, N. M., Maclean, C. & Zhang, J. Balanced codon usage optimizes eukaryotic translational efficiency. PLoS Genet. 8, e1002603 (2012).
  41. Stadler, M. & Fire, A. Wobble base-pairing slows in vivo translation elongation in metazoans. RNA 17, 20632073 (2011).
  42. Dana, A. & Tuller, T. Determinants of translation elongation speed and ribosomal profiling biases in mouse embryonic stem cells. PLoS Comput. Biol. 8, e1002755 (2012).
  43. Tuller, T. et al. An evolutionarily conserved mechanism for controlling the efficiency of protein translation. Cell 141, 344354 (2010).
  44. Woolstenhulme, C. J. et al. Nascent peptides that block protein synthesis in bacteria. Proc. Natl Acad. Sci. USA 110, E878E887 (2013).
  45. Charneski, C. A. & Hurst, L. D. Positively charged residues are the major determinants of ribosomal velocity. PLoS Biol. 11, e1001508 (2013).
  46. Ito, K. & Chiba, S. Arrest peptides: cis-acting modulators of translation. Annu. Rev. Biochem. 82, 171202 (2013).
  47. Pechmann, S., Willmund, F. & Frydman, J. The ribosome as a hub for protein quality control. Mol. Cell 49, 411421 (2013).
  48. Shalgi, R. et al. Widespread regulation of translation by elongation pausing in heat shock. Mol. Cell 49, 439452 (2013).
  49. Gerashchenko, M. V., Lobanov, A. V. & Gladyshev, V. N. Genome-wide ribosome profiling reveals complex translational regulation in response to oxidative stress. Proc. Natl Acad. Sci. USA 109, 1739417399 (2012).
  50. Liu, B., Han, Y. & Qian, S. B. Cotranslational response to proteotoxic stress by elongation pausing of ribosomes. Mol. Cell 49, 453463 (2013).
  51. Oh, E. et al. Selective ribosome profiling reveals the cotranslational chaperone action of trigger factor in vivo. Cell 147, 12951308 (2011).
  52. Han, Y. et al. Monitoring cotranslational protein folding in mammalian cells at codon resolution. Proc. Natl Acad. Sci. USA 109, 1246712472 (2012).
  53. Spriggs, K. A., Bushell, M. & Willis, A. E. Translational regulation of gene expression during conditions of cell stress. Mol. Cell 40, 228237 (2010).
  54. Wang, D. O., Martin, K. C. & Zukin, R. S. Spatially restricting gene expression by local translation at synapses. Trends Neurosci. 33, 173182 (2010).
  55. Hotamisligil, G. S. Endoplasmic reticulum stress and the inflammatory basis of metabolic disease. Cell 140, 900917 (2010).
  56. Thoreen, C. C. et al. A unifying model for mTORC1-mediated regulation of mRNA translation. Nature 485, 109113 (2012).
  57. Hsieh, A. C. et al. The translational landscape of mTOR signalling steers cancer initiation and metastasis. Nature 485, 5561 (2012).
  58. Cho, J. et al. LIN28A is a suppressor of ER-associated translation in embryonic stem cells. Cell 151, 765777 (2012).
  59. Castello, A. et al. Insights into RNA biology from an atlas of mammalian mRNA-binding proteins. Cell 149, 13931406 (2012).
  60. Baltz, A. G. et al. The mRNA-bound proteome and its global occupancy profile on protein-coding transcripts. Mol. Cell 46, 674690 (2012).
  61. Guo, H., Ingolia, N. T., Weissman, J. S. & Bartel, D. P. Mammalian microRNAs predominantly act to decrease target mRNA levels. Nature 466, 835840 (2010).
  62. Bazzini, A. A., Lee, M. T. & Giraldez, A. J. Ribosome profiling shows that miR-430 reduces translation before causing mRNA decay in zebrafish. Science 336, 233237 (2012).
  63. Stadler, M., Artiles, K., Pak, J. & Fire, A. Contributions of mRNA abundance, ribosome loading, and post- or peri-translational effects to temporal repression of C. elegans heterochronic miRNA targets. Genome Res. 22, 24182426 (2012).
  64. Heiman, M. et al. A translational profiling approach for the molecular characterization of CNS cell types. Cell 135, 738748 (2008).
  65. Ingolia, N. T., Brar, G. A., Rouskin, S., McGeachy, A. M. & Weissman, J. S. The ribosome profiling strategy for monitoring translation in vivo by deep sequencing of ribosome-protected mRNA fragments. Nature Protoc. 7, 15341550 (2012).

Download references

Author information


  1. Department of Embryology, Carnegie Institution, 3520 San Martin Drive, Baltimore, Maryland 21218, USA. Present address: Department of Molecular and Cell Biology, University of California, Berkeley, Barker Hall 422, Berkeley, California 94720, USA.

    • Nicholas T. Ingolia

Competing interests statement

N.T.I. is Inventor on patent application covering ribosome profiling.

Corresponding author

Correspondence to:

Author details

  • Nicholas T. Ingolia

    Nicholas T. Ingolia recently joined the Molecular and Cell Biology department at the University of California, Berkeley, USA, as Assistant Professor. Previously, he was a staff member at the Department of Embryology, Carnegie Institution for Science, Baltimore, Maryland, USA. He received his Ph.D. from Harvard University, Cambridge, Massachusetts, USA, and went on to do postdoctoral work at the University of California, San Francisco, USA, where he developed ribosome profiling. His laboratory seeks to better understand the molecular basis and cellular roles of translational regulation. Nicholas T. Ingolia's homepage.

Additional data