ABSTRACT
Transfer RNAs are essential for translating genetic information into proteins. The human genome contains hundreds of predicted tRNA genes, many in multiple copies. How their expression is regulated to control tRNA repertoires is unknown. Here we combined quantitative tRNA profiling and chromatin immunoprecipitation with sequencing to measure tRNA expression following the differentiation of human induced pluripotent stem cells into neuronal and cardiac cells. We find that tRNA transcript levels vary substantially, whereas tRNA anticodon pools, which govern decoding rates, are more stable among cell types. Mechanistically, RNA polymerase III transcribes a wide range of tRNA genes in human induced pluripotent stem cells but on differentiation becomes constrained to a subset we define as housekeeping tRNAs. This shift is mediated by decreased mTORC1 signalling, which activates the RNA polymerase III repressor MAF1. Our data explain how tRNA anticodon pools are buffered to maintain decoding speed across cell types and reveal that mTORC1 drives selective tRNA expression during differentiation.
Subject(s)
Anticodon , Induced Pluripotent Stem Cells , Humans , RNA Polymerase III/genetics , RNA Polymerase III/metabolism , Induced Pluripotent Stem Cells/metabolism , RNA, Transfer/genetics , RNA, Transfer/metabolism , Mechanistic Target of Rapamycin Complex 1/genetics , Gene ExpressionABSTRACT
The genetic code of mammalian cells can be expanded to allow the incorporation of non-canonical amino acids (ncAAs) by suppressing in-frame amber stop codons (UAG) with an orthogonal pyrrolysyl-tRNA synthetase (PylRS)/tRNAPylCUA (PylT) pair. However, the feasibility of this approach is substantially hampered by unpredictable variations in incorporation efficiencies at different stop codon positions within target proteins. Here, we apply a proteomics-based approach to quantify ncAA incorporation rates at hundreds of endogenous amber stop codons in mammalian cells. With these data, we compute iPASS (Identification of Permissive Amber Sites for Suppression; available at www.bultmannlab.eu/tools/iPASS), a linear regression model to predict relative ncAA incorporation efficiencies depending on the surrounding sequence context. To verify iPASS, we develop a dual-fluorescence reporter for high-throughput flow-cytometry analysis that reproducibly yields context-specific ncAA incorporation efficiencies. We show that nucleotides up- and downstream of UAG synergistically influence ncAA incorporation efficiency independent of cell line and ncAA identity. Additionally, we demonstrate iPASS-guided optimization of ncAA incorporation rates by synonymous exchange of codons flanking the amber stop codon. This combination of in silico analysis followed by validation in living mammalian cells substantially simplifies identification as well as adaptation of sites within a target protein to confer high ncAA incorporation rates.
Subject(s)
Amino Acids/metabolism , Genetic Code , Animals , Cell Line , Codon , Codon, Terminator , Computer Simulation , Embryonic Stem Cells/metabolism , Flow Cytometry , Genes, Reporter , HEK293 Cells , Humans , Linear Models , Mice , Mutation , ProteomicsABSTRACT
Measurements of cellular tRNA abundance are hampered by pervasive blocks to cDNA synthesis at modified nucleosides and the extensive similarity among tRNA genes. We overcome these limitations with modification-induced misincorporation tRNA sequencing (mim-tRNAseq), which combines a workflow for full-length cDNA library construction from endogenously modified tRNA with a comprehensive and user-friendly computational analysis toolkit. Our method accurately captures tRNA abundance and modification status in yeast, fly, and human cells and is applicable to any organism with a known genome. We applied mim-tRNAseq to discover a dramatic heterogeneity of tRNA isodecoder pools among diverse human cell lines and a surprising interdependence of modifications at distinct sites within the same tRNA transcript.
