elDORS: An elevated Database Of RNA Sequences

Authors

Dutta, N., Vicens, Q.

Abstract

Massive and integrated sequence databases have revolutionized computational protein structure prediction. RNA lags due to a lack of consolidated sequence resources. To bridge this gap, we developed elDORS_raw, which comprises up-to-date sequence information, including recent metagenomes and transcriptome sequence data. We optimized an 80% sequence-identity clustered version named elDORS for use with the RNAcmap3 split-strategy for multiple sequence alignment (MSA) and the widely used rMSA pipeline. Our benchmarking demonstrates that elDORS-augmented MSA pipelines match or exceed the alignment depth obtained with massive legacy databases across different queries, including blind CASP challenges, effectively eliminating sequence retrieval failures challenging orphan RNAs. To aid homology searches, predicting RNA properties, training new models, and other downstream tasks, elDORS is freely accessible.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 16 Jul 2026.

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