Cell type-specific analysis by single-cell profiling identifies a stable mammalian tRNA-mRNA interface and increased translation efficiency in neurons

Genome Res. 2022 Jan;32(1):97-110. doi: 10.1101/gr.275944.121. Epub 2021 Dec 2.

Abstract

The correlation between codon and anticodon pools influences the efficiency of translation, but whether differences exist in these pools across individual cells is unknown. We determined that codon usage and amino acid demand are highly stable across different cell types using available mouse and human single-cell RNA-sequencing atlases. After showing the robustness of ATAC-sequencing measurements for the analysis of tRNA gene usage, we quantified anticodon usage and amino acid supply in both mouse and human single-cell ATAC-seq atlases. We found that tRNA gene usage is overall coordinated across cell types, except in neurons, which clustered separately from other cell types. Integration of these data sets revealed a strong and statistically significant correlation between amino acid supply and demand across almost all cell types. Neurons have an enhanced translation efficiency over other cell types, driven by an increased supply of tRNAAla (AGC) anticodons. This results in faster decoding of the Ala-GCC codon, as determined by cell type-specific ribosome profiling, suggesting that the reduction of tRNAAla (AGC) anticodon pools may be implicated in neurological pathologies. This study, the first such examination of codon usage, anticodon usage, and translation efficiency resolved at the cell-type level with single-cell information, identifies a conserved landscape of translation elongation across mammalian cellular diversity and evolution.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Anticodon* / genetics
  • Codon
  • Mice
  • Neurons / metabolism
  • Protein Biosynthesis
  • RNA, Messenger / genetics
  • RNA, Transfer* / genetics
  • RNA, Transfer* / metabolism

Substances

  • Anticodon
  • Codon
  • RNA, Messenger
  • RNA, Transfer