TY - JOUR
T1 - ALL-tRNAseq enables robust tRNA profiling in tissue samples
AU - Scheepbouwer, Chantal
AU - Aparicio-Puerta, Ernesto
AU - Gomez-Martin, Cristina
AU - Verschueren, Heleen
AU - van Eijndhoven, Monique
AU - Wedekind, Laurine E.
AU - Giannoukakos, Stavros
AU - Hijmering, Nathalie
AU - Gasparotto, Lisa
AU - van der Galien, Hilde T.
AU - van Rijn, Roos S.
AU - Aronica, Eleonora
AU - Kibbelaar, Robby
AU - Heine, Vivi M.
AU - Wesseling, Pieter
AU - Noske, David P.
AU - Vandertop, W. Peter
AU - de Jong, Daphne
AU - Pegtel, D. Michiel
AU - Hackenberg, Michael
AU - Wurdinger, Tom
AU - Gerber, Alan
AU - Koppers-Lalic, Danijela
N1 - Funding Information: This work was supported by the Dutch Cancer Society (KWF 2016-10476 to D.K.-L.), the Cancer Center Amsterdam Foundation (CCA2017-2-16 to D.K.-L.), and “Stichting MRD Hodgkin Lymphoma” (to D.M.P.). C.S was supported by a Cancer Center Amsterdam Foundation grant (CCA2021-5-26 to A.G.). A.G. was supported by the Nederlandse Organisatie voor Wetenschap-pelijk Onderzoek (NWO) Talent Programme Vidi grant (VI.V-idi.193.107). S.G., M.H., D.K.-L., and T.W. received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement number 765492. We thank Disa Tehler for stimulating discussions, and we are grateful to Hakan Kalay for assistance with the purification of AlkB enzymes. We thank Bram van den Broek for his contribution to the graphical images. Publisher Copyright: © 2023 Scheepbouwer et al.
PY - 2023/3/1
Y1 - 2023/3/1
N2 - Transfer RNAs (tRNAs) are small adaptor RNAs essential for mRNA translation. Alterations in the cellular tRNA population can directly affect mRNA decoding rates and translational efficiency during cancer development and progression. To evaluate changes in the composition of the tRNA pool, multiple sequencing approaches have been developed to overcome reverse transcription blocks caused by the stable structures of these molecules and their numerous base modifications. However, it remains unclear whether current sequencing protocols faithfully capture tRNAs existing in cells or tissues. This is specifically challenging for clinical tissue samples that often present variable RNA qualities. For this reason, we developed ALL-tRNAseq, which combines the highly processive MarathonRT and RNA demethylation for the robust assessment of tRNA expression, together with a randomized adapter ligation strategy prior to reverse transcription to assess tRNA fragmentation levels in both cell lines and tissues. Incorporation of tRNA fragments not only informed on sample integrity but also significantly improved tRNA profiling of tissue samples. Our data showed that our profiling strategy effectively improves classification of oncogenic signatures in glioblastoma and diffuse large B-cell lymphoma tissues, particularly for samples presenting higher levels of RNA fragmentation, further highlighting the utility of ALL-tRNAseq for translational research.
AB - Transfer RNAs (tRNAs) are small adaptor RNAs essential for mRNA translation. Alterations in the cellular tRNA population can directly affect mRNA decoding rates and translational efficiency during cancer development and progression. To evaluate changes in the composition of the tRNA pool, multiple sequencing approaches have been developed to overcome reverse transcription blocks caused by the stable structures of these molecules and their numerous base modifications. However, it remains unclear whether current sequencing protocols faithfully capture tRNAs existing in cells or tissues. This is specifically challenging for clinical tissue samples that often present variable RNA qualities. For this reason, we developed ALL-tRNAseq, which combines the highly processive MarathonRT and RNA demethylation for the robust assessment of tRNA expression, together with a randomized adapter ligation strategy prior to reverse transcription to assess tRNA fragmentation levels in both cell lines and tissues. Incorporation of tRNA fragments not only informed on sample integrity but also significantly improved tRNA profiling of tissue samples. Our data showed that our profiling strategy effectively improves classification of oncogenic signatures in glioblastoma and diffuse large B-cell lymphoma tissues, particularly for samples presenting higher levels of RNA fragmentation, further highlighting the utility of ALL-tRNAseq for translational research.
KW - cancer
KW - high-throughput sequencing
KW - tissue samples
KW - transfer RNA
UR - http://www.scopus.com/inward/record.url?scp=85151574209&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85151574209&partnerID=8YFLogxK
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85151574209&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/36810209
U2 - https://doi.org/10.1101/gad.350233.122
DO - https://doi.org/10.1101/gad.350233.122
M3 - Article
C2 - 36810209
SN - 0890-9369
VL - 37
SP - 243
EP - 257
JO - Genes and Development
JF - Genes and Development
IS - 5-6
ER -