Automated Author Profile

Reinhardt, Maren

Current S-Index

1.0

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.5

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

Identification and characterization of new structured RNA classes in plants

Alternative splicing is a very important mechanism to diversify an organism’s transcriptome with minimal increases in genome size. It can modify the function of the finished protein or affect its regulation, e.g. induce nonsense-mediated decay (NMD) to degrade the transcript. Mechanisms that affect alternative splicing are therefore of great interest. It has been shown that splicing can be affected by RNA secondary structures within pre-mRNAs. These structured regions of RNA (strucRNA) would affect their transcript in cis, but only a few such cases are known in plants. In this study, we interrogate plant genomes for cis-regulatory strucRNAs. By applying a comparative-genomics-based approach to 130 plant genomes, we identified 16 strucRNA candidates. Five candidates likely regulate in cis using alternative splicing and NMD. Other predictions might not regulate alternative splicing, including four putative small nucleolar RNAs (snoRNAs). Of our five cis-regulatory strucRNAs that are implicated in alternative splicing control, two are now experimentally validated in follow-up studies. These results stand in contrast to the few previously validated examples. Although we were able to predict some strucRNAs, all motifs had generally modest levels of covariation, which is a pattern of mutations that indicates a conserved secondary structure. With few mutations, comparative-genomics-based approaches to find strucRNAs are less effective. Other approaches of finding regulatory RNAs in plants might thus be needed, and more available genomic or transcriptomic data might improve the quality and quantity of promising candidates.

Authors

  • Sack, Maximilian ;
  • Reinhardt, Maren ;
  • Burgardt, Rica ;
  • Berg, Philipp ;
  • Bauer, Julia ;
  • Wachter, Andreas ;
  • Weinberg, Zasha
1 Citation0 Mentions85% FAIR0.5 Dataset Index
10.6084/m9.figshare.294415972025

Identification and characterization of new structured RNA classes in plants

Alternative splicing is a very important mechanism to diversify an organism’s transcriptome with minimal increases in genome size. It can modify the function of the finished protein or affect its regulation, e.g. induce nonsense-mediated decay (NMD) to degrade the transcript. Mechanisms that affect alternative splicing are therefore of great interest. It has been shown that splicing can be affected by RNA secondary structures within pre-mRNAs. These structured regions of RNA (strucRNA) would affect their transcript in cis, but only a few such cases are known in plants. In this study, we interrogate plant genomes for cis-regulatory strucRNAs. By applying a comparative-genomics-based approach to 130 plant genomes, we identified 16 strucRNA candidates. Five candidates likely regulate in cis using alternative splicing and NMD. Other predictions might not regulate alternative splicing, including four putative small nucleolar RNAs (snoRNAs). Of our five cis-regulatory strucRNAs that are implicated in alternative splicing control, two are now experimentally validated in follow-up studies. These results stand in contrast to the few previously validated examples. Although we were able to predict some strucRNAs, all motifs had generally modest levels of covariation, which is a pattern of mutations that indicates a conserved secondary structure. With few mutations, comparative-genomics-based approaches to find strucRNAs are less effective. Other approaches of finding regulatory RNAs in plants might thus be needed, and more available genomic or transcriptomic data might improve the quality and quantity of promising candidates.

Authors

  • Sack, Maximilian ;
  • Reinhardt, Maren ;
  • Burgardt, Rica ;
  • Berg, Philipp ;
  • Bauer, Julia ;
  • Wachter, Andreas ;
  • Weinberg, Zasha
1 Citation0 Mentions85% FAIR0.5 Dataset Index
10.6084/m9.figshare.29441597.v12025