KAPAC

KAPAC infers regulatory sequence motifs that influence polyadenylation (poly(A)) site choice to analyze 3' end processing and 3' UTR length regulation from RNA sequencing data.

Key Features:

• Regulatory motif inference: Infers sequence motifs that affect poly(A) site selection and 3' end processing.
• Oligomeric motif analysis: Identifies oligomeric sequence motifs associated with changes in cleavage and polyadenylation patterns.
• RNA sequencing input: Operates on RNA sequencing datasets to detect motif–usage associations.
• Integration with PAQR: Functions as part of a framework alongside PAQR, which quantifies poly(A) site usage across conditions.
• Comparative conditions: Applied to RNA-seq data from normal and tumor tissues to reveal condition-specific motif effects.
• Regulator identification: Can highlight candidate regulators of poly(A) site choice, exemplified by PTBP1 in glioblastoma.

Scientific Applications:

• Regulation of poly(A) site selection: Elucidates sequence determinants that control polyadenylation site choice and 3' UTR length regulation.
• Cancer biology: Identifies motifs and regulators underlying altered cleavage and polyadenylation patterns in tumors, including analyses in glioblastoma implicating PTBP1.
• Comparative transcriptomics: Detects changes in 3' end processing between normal and disease states using RNA sequencing data.

Methodology:

Analyzes RNA sequencing data to identify oligomeric sequence motifs that affect poly(A) site choice; used together with PAQR to quantify poly(A) site usage across conditions and applied to RNA-seq datasets from normal and tumor tissues to uncover motifs linked to alterations in cleavage and polyadenylation patterns.