deepBase

deepBase provides comprehensive annotation and discovery of small RNAs from next-generation sequencing (NGS) small RNA datasets to support transcriptomic analysis.

Key Features:

• Extensive dataset: Contains deep sequencing data from 185 small RNA libraries derived from diverse tissues and cell lines across seven model organisms: human, mouse, chicken, Ciona intestinalis, Drosophila melanogaster, Caenorhabditis elegans, and Arabidopsis thaliana.
• Comprehensive annotation: Analyzed approximately 14.6 million unique reads that perfectly map to over 284 million genomic loci, resulting in identification of approximately 380,000 ncRNA-associated small RNAs (nasRNAs), ~1.5 million promoter-associated small RNAs (pasRNAs), ~4.0 million exon-associated small RNAs (easRNAs), and ~6 million repeat-associated small RNAs (rasRNAs).
• Candidate prediction: Employed miRDeep to predict 2,038 miRNA candidates and snoSeeker to predict 1,889 snoRNA candidates.
• Cluster grouping: Organized mapped reads into approximately 1.2 million RNA clusters for comparative and detailed analyses.

Scientific Applications:

• Small RNA annotation: Enable comprehensive annotation of diverse small RNA classes across multiple species.
• Novel small RNA discovery: Identify novel small RNAs associated with genomic features such as promoters, exons, repeats, and ncRNA loci.
• ncRNA functional investigation: Support investigation of ncRNA roles in gene regulation and expression using mapped small RNA evidence.
• Comparative transcriptomics: Facilitate comparative studies of small RNA expression and distribution across organisms, tissues, and cell lines.

Methodology:

Mapped high-throughput NGS small RNA reads to genomic loci, organized mapped reads into RNA clusters, and applied miRDeep and snoSeeker for miRNA and snoRNA candidate prediction and annotation of nasRNAs, pasRNAs, easRNAs, and rasRNAs.