snoDB

snoDB 2.0 is a specialized database dedicated to human small nucleolar RNAs (snoRNAs), providing comprehensive and up-to-date information in an interactive format. Developed at the Université de Sherbrooke, snoDB integrates data from multiple established databases with extensive manual curation from the literature.

Overview

The database was created to address the need for accurate, centralized information about human snoRNAs. snoDB removes redundancy by merging snoRNA entries from multiple sources based on genomic location, prioritizing data from Ensembl, RefSeq, snoRNA Atlas, snOPY, and literature-based annotations.

Key Features

Genomic and Sequence Data

• Genomic Locations: All coordinates based on GRCh38 human genome assembly
• Sequences: Complete snoRNA sequences with nucleotide-level detail
• Conservation: PhastCons conservation scores for 100 vertebrates from UCSC genome browser
• Host Genes: Comprehensive host gene information with Gene Ontology functional annotations
• snoRNA Copies: Classification based on RFAM families

snoRNA Structure and Function

• Motifs and Guide Regions: Box C, D, C’, D’ for C/D box snoRNAs; H and ACA boxes for H/ACA snoRNAs
• Predicted Elements: Custom algorithms for predicting boxes when not available in literature
• Target Identification: Both canonical (rRNA/snRNA) and non-canonical RNA targets

Interaction Data

• snoRNA-RNA Interactions:
  • Canonical interactions with rRNA and snRNA from multiple validated sources
  • Non-canonical interactions from RISE database
  • snoDB-predicted interactions for unannotated snoRNA copies
• snoRNA-Protein Interactions:
  • Data from ENCODE eCLIP experiments
  • 150 RNA binding proteins analyzed
  • Filtered for high-confidence interactions (p-value < 0.001)

Expression and Abundance

• Tissue Expression: TGIRT-Seq data from multiple normal tissues (brain, liver, testis, skeletal muscle, ovary, breast, prostate)
• Cancer Cell Lines: Expression in HCT116, MCF7, PC3, TOV112D, SKOV
• Reference Samples: Universal Human RNA (UHR) and Human Brain Reference (HBR)
• Host Gene Abundance: Parallel abundance measurements for host genes

rRNA Modifications

• Modification Sites: Comprehensive catalog of human rRNA modification positions
• Guide Mapping: Links between snoRNAs and their target modification sites
• Validation Status: Positions marked as validated or predicted
• Modification Levels: Quantitative data from RiboMethSeq, HydraPsiSeq, and mass spectrometry studies
• Multiple rRNA Versions: Support for snoRNABase, Ensembl, and RefSeq rRNA reference sequences

Data Sources

snoDB integrates data from:

• Databases: Ensembl, RefSeq, snoRNA Atlas, snOPY, RFAM, RISE
• Literature: Manually curated from publications
• Functional Data: Gene Ontology, ENCODE eCLIP
• Sequencing Data: TGIRT-Seq from GEO and SRA repositories
• Conservation: UCSC genome browser PhastCons scores
• Modifications: RiboMethSeq, HydraPsiSeq, SILNAS studies

Interactive Features

• Advanced Search: Filter and search across multiple snoRNA attributes
• Column Visibility: Customize table views
• Data Export: Download filtered datasets
• Abundance Viewer: Interactive visualization of expression patterns
• Sequence Search: Find snoRNAs by sequence similarity
• Statistics Dashboard: Overview of database contents with distribution charts

Associated Tools

snoRupdate

A C++ tool for integrating snoDB snoRNAs into genome annotations. Compatible with both Ensembl and RefSeq GTF files, enabling incorporation of up-to-date snoRNA annotations into RNA-Seq analysis pipelines.

Data Processing

• Unique Entries: Merged based on genomic overlap with prioritized source order
• Motif Prediction: Custom algorithms with Hamming distance-based degenerate sequence matching
• Structure Prediction: RNAfold (ViennaRNA) for H/ACA snoRNA hairpin regions
• Host Gene Assignment: Overlap analysis with manual curation to remove pseudogenes
• Interaction Filtering: Statistical thresholds and replicate consistency requirements

Version History

Current version: 2.0.0. The previous version remains accessible for legacy analyses.

Contact

• Database Inquiries: Danny Bergeron (danny.bergeron@usherbrooke.ca)
• Principal Investigator: Michelle Scott (Michelle.Scott@USherbrooke.ca)
• Institution: Université de Sherbrooke, Department of Biochemistry and Functional Genomics