Singh, Ajeet and Zahra, Shafaque and Das, Durdam and Kumar, Shailesh (2022) PtRNAdb: a web resource of plant tRNA genes from a wide range of plant species. 3 BIOTECH, 12 (9): 185. ISSN 2190-572X, 2190-5738
Full text not available from this repository. (Request a copy)Abstract
tRNA, as well as their derived products such as short interspersed nuclear elements (SINEs), pseudogenes, and transfer RNA (tRNA)-derived fragments (tRFs), have now been shown to be vital for cellular life, functioning, and adaptation during different stress conditions in all diverse life forms. In this study, we have developed PtRNAdb (www.nipgr.ac.in/PtRNAdb), a plant-exclusive tRNA database containing 113,849 tRNA gene sequences from phylogenetically diverse plant species. We have analyzed a total of 106 nuclear, 89 plastidial, and 38 mitochondrial genomes of plants by the tRNAscan-SE software package, and after careful curation of the output data, we integrated the data and developed this database. The information about the tRNA gene sequences obtained was further enriched with a consensus sequence-based study of tRNA genes based on their isoacceptors and isodecoders. We have also built covariance models based on the isoacceptors and isodecoders of all the tRNA sequences using the infernal tool. The user can also perform BLAST not only against PtRNAdb entries but also against all the tRNA sequences stored in the PlantRNA database and annotated tRNA genes across the plant kingdom available at NCBI. This resource is believed to be of high utility for plant researchers as well as molecular biologists to carry out further exploration of the plant tRNAome on a wider spectrum, as well as for performing comparative and evolutionary studies related to tRNAs, and their derivatives across all domains of life.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | DATABASE; PREDICTION; ALIGNMENT; SEARCH; tRNA; Non-coding RNAs; PtRNAdb; Database; Data curation; Genomics |
| Subjects: | 500 Science > 570 Life sciences |
| Divisions: | Informatics and Data Science |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 08 Feb 2024 15:32 |
| Last Modified: | 08 Feb 2024 15:32 |
| URI: | https://pred.uni-regensburg.de/id/eprint/57754 |
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