AASsites

AASsites identifies single nucleotide polymorphisms (SNPs) that influence RNA splicing by analyzing splice-site proximal variants to detect alterations in splicing patterns that may affect gene expression.

Key Features:

• Splice Site Analysis: Targets SNPs located near splice sites to identify variants that may alter normal splicing patterns.
• Gene Prediction Integration: Employs multiple gene prediction programs and open reading frame (ORF) prediction tools to analyze and compare wild-type and variant sequences.
• Rule-Based Classification System: Utilizes a custom rule system to classify SNPs as "likely," "probable," or "unlikely" to affect splicing.
• Extensive Database Screening: Screened approximately 80,000 human genome SNPs near splice sites and identified around 1,200 SNPs likely or probably associated with splicing modifications.
• Validation Against Known Databases: Thirty-three identified SNPs were corroborated by the ssSNP Target database as known to cause modified splicing.

Scientific Applications:

• Disease Risk Assessment: Identifying functional SNPs associated with disease risk supports more precise genetic screening and diagnosis.
• Pharmacogenomics: Characterizing SNPs that alter splicing informs studies of drug metabolism and individual treatment responses.
• Gene Function Studies: Elucidating effects of splicing alterations contributes to understanding gene regulation and expression.

Methodology:

Integrates multiple gene prediction programs and ORF prediction tools to compare wild-type and variant sequences for splice-site analysis and applies a custom rule-based classifier to categorize SNPs as likely, probable, or unlikely to affect splicing.