SROOGLE

SROOGLE analyzes four core splicing signals and splicing-regulatory sequences (SRSs) to score exon–intron junctions using nine algorithms, annotate 13 groups of putative SRSs, and assess the effects of point mutations on splicing.

Key Features:

• Integrated visualization: Presents splicing signal sequences and scoring data as cohesive graphical output for exon–intron structures.
• Core splicing signals analysis: Scores the four core splicing signals at exon/intron junctions using nine different algorithms to evaluate signal strength.
• Splicing-regulatory sequences (SRSs) annotation: Identifies and highlights sequences belonging to 13 distinct groups of putative SRSs derived from computational predictions and experimental data.
• Sequence input: Accepts exon sequences with flanking introns for analysis of junctions and regulatory elements.
• Point mutation simulation: Simulates point mutations at any position and evaluates their predicted impact on splicing.
• Additional metrics and statistics: Provides a range of additional metrics and statistical measures for each potential signal.

Scientific Applications:

• Gene expression and splicing regulation: Supports analysis of how splicing signals and SRSs influence exon recognition and gene expression regulation.
• RNA splicing mechanism studies: Provides quantitative data for investigating RNA splicing mechanisms and splice-site selection.
• Variant interpretation in genetic disorders: Facilitates assessment of the effects of point mutations on splicing in disorders linked to splicing defects.
• Alternative splicing research: Aids investigation into the molecular basis of alternative splicing and its implications for cellular function and disease.

Methodology:

Integrates multiple computational algorithms to score the four core splicing signals and identify SRSs, leverages experimental data and predictive models, and simulates point mutations to assess their effects on splicing.