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Anota2seq Analysis for Transcriptome-Wide Studies of mRNA Translation

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Estrogen Receptors

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2418))

Abstract

mRNA translation plays a critical role in determining proteome composition. In health, regulation of mRNA translation facilitates rapid gene expression responses to intra- and extracellular signals. Moreover, dysregulated mRNA translation is a common feature in disease states, including neurological disorders and cancer. Yet, most studies of gene expression focus on analysis of mRNA levels, leaving variations in translational efficiencies largely uncharacterized. Here, we outline procedures to identify mRNA-selective alterations in translational efficiencies on a transcriptome-wide scale using the anota2seq package. Anota2seq compares expression data originating from translated mRNA to data from matched total mRNA to identify changes in translated mRNA not paralleled by corresponding changes in total mRNA (interpreted as changes in translational efficiencies impacting protein levels), congruent changes in total and translated mRNA (interpreted as changes in transcription and/or mRNA stability), and changes in total mRNA not paralleled by corresponding alterations in translated mRNA (interpreted as translational buffering). To illustrate the functionality of the anota2seq analysis package, we demonstrate a detailed analysis using a polysome-profiling data set quantified by RNA sequencing, revealing that estrogen receptor α modulates gene expression via a type of translational buffering termed offsetting. Notably, this anota2seq analysis procedure is also applicable to ribosome-profiling (RiboSeq) data sets and can be adapted to a variety of other data types and experimental contexts. Finally, we provide guidance for extending anota2seq analysis to examine associations between untranslated regions and altered translational efficiencies as well as targeted cellular functions to gain insights into mechanisms and phenotypic consequences of altered mRNA translation. Thus, this step-by-step manual allows users to interrogate selective changes in mRNA translation on a transcriptome-wide scale using the Bioconductor package anota2seq.

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References

  1. Komili S, Silver PA (2008) Coupling and coordination in gene expression processes: a systems biology view. Nat Rev Genet 9:38–48

    Article  CAS  PubMed  Google Scholar 

  2. Tahmasebi S, Khoutorsky A, Mathews MB, Sonenberg N (2018) Translation deregulation in human disease. Nat Rev Mol Cell Biol 19(12):791–807

    Article  CAS  PubMed  Google Scholar 

  3. Andreev DE, O’Connor PB, Fahey C et al (2015) Translation of 5′ leaders is pervasive in genes resistant to eIF2 repression. Elife 4:e03971

    Article  PubMed  PubMed Central  Google Scholar 

  4. Guan B-J, van Hoef V, Jobava R et al (2017) A unique ISR program determines cellular responses to chronic stress. Mol Cell 68:885–900.e6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Jewer M, Lee L, Leibovitch M et al (2020) Translational control of breast cancer plasticity. Nat Commun 11:1–16

    Article  CAS  Google Scholar 

  6. Wouters BG, Koritzinsky M (2008) Hypoxia signalling through mTOR and the unfolded protein response in cancer. Nat Rev Cancer 8:851–864

    Article  CAS  PubMed  Google Scholar 

  7. Connolly E, Braunstein S, Formenti S, Schneider RJ (2006) Hypoxia inhibits protein synthesis through a 4E-BP1 and elongation factor 2 kinase pathway controlled by mTOR and uncoupled in breast cancer cells. Mol Cell Biol 26:3955–3965

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Hinnebusch AG, Ivanov IP, Sonenberg N (2016) Translational control by 5 ′ -untranslated regions of eukaryotic mRNAs. Science 352:1413–1416

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Schuster SL, Hsieh AC (2019) The untranslated regions of mRNAs in cancer. Trends Cancer 5:245–262

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Halbeisen RE, Gerber AP (2009) Stress-dependent coordination of transcriptome and Translatome in yeast. PLoS Biol 7:e1000105

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. Ingolia NT, Ghaemmaghami S, Newman JRSS, Weissman JS (2009) Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science 324:218–223

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Kiniry SJ, Michel AM, Baranov PV (2020) Computational methods for ribosome profiling data analysis. Wiley Interdiscip Rev RNA 11:e1577

    Article  CAS  PubMed  Google Scholar 

  13. Larsson O, Sonenberg N, Nadon R (2010) Identification of differential translation in genome wide studies. Proc Natl Acad Sci U S A 107:21487–21492

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Oertlin C, Lorent J, Murie C et al (2019) Generally applicable transcriptome-wide analysis of translation using anota2seq. Nucleic Acids Res 47:e70

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Kusnadi EP, Timpone C, Topisirovic I et al (2022) Regulation of gene expression via translational buffering. Biochim Biophys Acta, Mol Cell Res 1869:e119140

    Google Scholar 

  16. Lorent J, Kusnadi EP, Hoef V et al (2019) Translational offsetting as a mode of estrogen receptor α-dependent regulation of gene expression. EMBO J 38:e101323

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Hipolito VEB, Diaz JA, Tandoc KV et al (2019) Enhanced translation expands the endo-lysosome size and promotes antigen presentation during phagocyte activation. PLoS Biol 17:e3000535

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Chan K, Robert F, Oertlin C et al (2019) eIF4A supports an oncogenic translation program in pancreatic ductal adenocarcinoma. Nat Commun 10:1–16

    Article  CAS  Google Scholar 

  19. Gachet S, El-Chaar T, Avran D et al (2018) Deletion 6q drives T-cell leukemia progression by ribosome modulation. Cancer Discov 8:1615–1631

    Article  Google Scholar 

  20. Bartish M, Tong D, Pan Y et al (2020) MNK2 governs the macrophage antiinflammatory phenotype. Proc Natl Acad Sci U S A 117:27556–27565

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Schneider K, Nelson GM, Watson JL et al (2020) Protein stability buffers the cost of translation attenuation following eIF2α phosphorylation. Cell Rep 32:108154

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Kusnadi EP, Trigos AS, Cullinane C et al (2020) Reprogrammed mRNA translation drives resistance to therapeutic targeting of ribosome biogenesis. EMBO J 39:e105111

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Chaparro V, Leroux L-P, Masvidal L et al (2020) Translational profiling of macrophages infected with Leishmania donovani identifies mTOR- and eIF4A-sensitive immune-related transcripts. PLoS Pathog 16:e1008291

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Shah S, Molinaro G, Liu B et al (2020) FMRP control of ribosome translocation promotes chromatin modifications and alternative splicing of neuronal genes linked to autism. Cell Rep 30:4459–4472.e6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Eshraghi M, Karunadharma PP, Blin J et al (2021) Mutant huntingtin stalls ribosomes and represses protein synthesis in a cellular model of Huntington disease. Nat Commun 12:1461

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Hien A, Molinaro G, Liu B et al (2020) Ribosome profiling in mouse hippocampus: plasticity-induced regulation and bidirectional control by TSC2 and FMRP. Mol Autism 11:78

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. Sandri BJ, Masvidal L, Murie C et al (2019) Distinct cancer-promoting stromal gene expression depending on lung function. Am J Respir Crit Care Med 200:348–358

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Bearss JJ, Padi SK, Singh N et al (2021) EDC3 phosphorylation regulates growth and invasion through controlling P-body formation and dynamics. EMBO Rep 22:e50835

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Larsson O, Sonenberg N, Nadon R (2011) Anota: analysis of differential translation in genome-wide studies. Bioinformatics 27:1440–1441

    Article  CAS  PubMed  Google Scholar 

  30. Morita M, Siddiqui N, Katsumura S et al (2019) Hepatic posttranscriptional network comprised of CCR4–NOT deadenylase and FGF21 maintains systemic metabolic homeostasis. Proc Natl Acad Sci U S A 116:7973–7981

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Edgar R, Domrachev M, Lash AE (2002) Gene expression omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 30:207–210

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Barrett T, Wilhite SE, Ledoux P et al (2013) NCBI GEO: archive for functional genomics data sets - update. Nucleic Acids Res 41:D991–D995

    Article  CAS  PubMed  Google Scholar 

  33. Wang ZY, Leushkin E, Liechti A et al (2020) Transcriptome and translatome co-evolution in mammals. Nature 588:642–647

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Leppek K, Das R, Barna M (2018) Functional 5′ UTR mRNA structures in eukaryotic translation regulation and how to find them. Nat Rev Mol Cell Biol 19:158–174

    Article  CAS  PubMed  Google Scholar 

  35. Gebauer F, Schwarzl T, Valcárcel J, Hentze MW (2020) RNA-binding proteins in human genetic disease. Nat Rev Genet:1–14

    Google Scholar 

  36. Waldron JA, Tack DC, Ritchey LE et al (2019) MRNA structural elements immediately upstream of the start codon dictate dependence upon eIF4A helicase activity. Genome Biol 20:300

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Gandin V, Masvidal L, Hulea L et al (2016) nanoCAGE reveals 5′ UTR features that define specific modes of translation of functionally related MTOR-sensitive mRNAs. Genome Res 26:636–648

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Bava FA, Eliscovich C, Ferreira PG et al (2013) CPEB1 coordinates alternative 3′-UTR formation with translational regulation. Nature 495:121–125

    Article  CAS  PubMed  Google Scholar 

  39. Wolfe AL, Singh K, Zhong Y et al (2014) RNA G-quadruplexes cause eIF4A-dependent oncogene translation in cancer. Nature 513:65–70

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Wu Q, Wright M, Gogol MM et al (2020) Translation of small downstream ORFs enhances translation of canonical main open reading frames. EMBO J 39:e104763

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Bailey TL, Boden M, Buske FA et al (2009) MEME suite: tools for motif discovery and searching. Nucleic Acids Res 37:W202

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Fan D, Bitterman PB, Larsson O (2009) Regulatory element identification in subsets of transcripts: comparison and integration of current computational methods. RNA 15:1469–1482

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Timmons JA, Szkop KJ, Gallagher IJ (2015) Multiple sources of bias confound functional enrichment analysis of global -omics data. Genome Biol 16:186

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  44. Gaudet P, Dessimoz C (2017) Gene ontology: pitfalls, biases, and remedies. In: Methods in molecular biology. Humana Press Inc., Totowa, New Jersey, pp 189–205

    Google Scholar 

  45. Powers RK, Goodspeed A, Pielke-Lombardo H et al (2018) GSEA-InContext: identifying novel and common patterns in expression experiments. Bioinformatics 34:i555–i564

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Beissbarth T, Speed TP (2004) GOstat: find statistically overrepresented gene ontologies within a group of genes. Bioinformatics 20:1464–1465

    Article  CAS  PubMed  Google Scholar 

  47. Luo W, Friedman MS, Shedden K et al (2009) GAGE: generally applicable gene set enrichment for pathway analysis. BMC Bioinformatics 10:161

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. Wright GW, Simon RM (2003) A random variance model for detection of differential gene expression in small microarray experiments. Bioinformatics (Oxford, England) 19:2448–2455

    Article  CAS  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Oncology-Pathology, Science for Life Laboratory, Karolinska Institute, Stockholm, Sweden

    Christian Oertlin, Kathleen Watt, Johannes Ristau & Ola Larsson

Authors
  1. Christian Oertlin
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  2. Kathleen Watt
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  3. Johannes Ristau
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  4. Ola Larsson
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Corresponding author

Correspondence to Ola Larsson .

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Editors and Affiliations

  1. Sanford School of Medicine, University of South Dakota, Vermillion, SD, USA

    Kathleen M. Eyster

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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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Oertlin, C., Watt, K., Ristau, J., Larsson, O. (2022). Anota2seq Analysis for Transcriptome-Wide Studies of mRNA Translation. In: Eyster, K.M. (eds) Estrogen Receptors. Methods in Molecular Biology, vol 2418. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1920-9_15

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  • DOI: https://doi.org/10.1007/978-1-0716-1920-9_15

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1919-3

  • Online ISBN: 978-1-0716-1920-9

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