Automated Author Profile

Dron, Jacqueline S.

Current S-Index

1.7

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.9

Average Dataset Index per dataset

Total Datasets

2

Total datasets for this author

Average FAIR Score

84.6%

Average FAIR Score per dataset

Total Citations

2

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Targeted sequencing reveals expanded genetic diversity of human transfer RNAs

Transfer RNAs are required to translate genetic information into proteins as well as regulate other cellular processes. Nucleotide changes in tRNAs can result in loss or gain of function that impact the composition and fidelity of the proteome. Despite links between tRNA variation and disease, the importance of cytoplasmic tRNA variation has been overlooked. Using a custom capture panel, we sequenced 605 human tRNA-encoding genes from 84 individuals. We developed a bioinformatic pipeline that allows more accurate tRNA read mapping and identifies multiple polymorphisms occurring within the same variant. Our analysis identified 522 unique tRNA-encoding sequences that differed from the reference genome from 84 individuals. Each individual had ~66 tRNA variants including nine variants found in less than 5% of our sample group. Variants were identified throughout the tRNA structure with 17% predicted to enhance function. Eighteen anticodon mutants were identified including potentially mistranslating tRNAs; e.g., a tRNASer that decodes Phe codons. Similar engineered tRNA variants were previously shown to inhibit cell growth, increase apoptosis and induce the unfolded protein response in mammalian cell cultures and chick embryos. Our analysis shows that human tRNA variation has been underestimated. We conclude that the large number of tRNA genes provides a buffer enabling the emergence of variants, some of which could contribute to disease.

Authors

  • Berg, Matthew D. ;
  • Giguere, Daniel J. ;
  • Dron, Jacqueline S. ;
  • Lant, Jeremy T. ;
  • Genereaux, Julie ;
  • Liao, Calwing ;
  • Wang, Jian ;
  • Robinson, John F. ;
  • Gloor, Gregory B. ;
  • Hegele, Robert A. ;
  • O’Donoghue, Patrick ;
  • Brandl, Christopher J.
1 Citation0 Mentions85% FAIR0.9 Dataset Index
10.6084/m9.figshare.95867872019

Targeted sequencing reveals expanded genetic diversity of human transfer RNAs

Transfer RNAs are required to translate genetic information into proteins as well as regulate other cellular processes. Nucleotide changes in tRNAs can result in loss or gain of function that impact the composition and fidelity of the proteome. Despite links between tRNA variation and disease, the importance of cytoplasmic tRNA variation has been overlooked. Using a custom capture panel, we sequenced 605 human tRNA-encoding genes from 84 individuals. We developed a bioinformatic pipeline that allows more accurate tRNA read mapping and identifies multiple polymorphisms occurring within the same variant. Our analysis identified 522 unique tRNA-encoding sequences that differed from the reference genome from 84 individuals. Each individual had ~66 tRNA variants including nine variants found in less than 5% of our sample group. Variants were identified throughout the tRNA structure with 17% predicted to enhance function. Eighteen anticodon mutants were identified including potentially mistranslating tRNAs; e.g., a tRNASer that decodes Phe codons. Similar engineered tRNA variants were previously shown to inhibit cell growth, increase apoptosis and induce the unfolded protein response in mammalian cell cultures and chick embryos. Our analysis shows that human tRNA variation has been underestimated. We conclude that the large number of tRNA genes provides a buffer enabling the emergence of variants, some of which could contribute to disease.

Authors

  • Berg, Matthew D. ;
  • Giguere, Daniel J. ;
  • Dron, Jacqueline S. ;
  • Lant, Jeremy T. ;
  • Genereaux, Julie ;
  • Liao, Calwing ;
  • Wang, Jian ;
  • Robinson, John F. ;
  • Gloor, Gregory B. ;
  • Hegele, Robert A. ;
  • O’Donoghue, Patrick ;
  • Brandl, Christopher J.
1 Citation0 Mentions85% FAIR0.9 Dataset Index
10.6084/m9.figshare.9586787.v12019