TREND-DB

TREND-DB catalogs alternative polyadenylation (APA) dynamics from TREND-seq datasets to map transcriptome 3' end diversification (TREND) and the effects of depleting over 170 proteins involved in transcriptional, co-transcriptional, posttranscriptional regulation and epigenetic processes.

Key Features:

• TREND-seq dataset integration: Incorporates TREND-seq datasets to quantify APA and transcriptome 3' end diversification (TREND).
• Catalog of protein depletion effects: Records APA changes upon depletion of over 170 proteins involved in transcriptional, co-transcriptional, posttranscriptional gene regulation, epigenetic modifications, and related processes.
• APA landscape visualization: Generates visual representations of APA and TREND dynamics across experimental conditions.
• Global APA network mapping: Constructs maps linking APA regulators to affected genes and vice versa to characterize APA interactions.
• Condition-specific functional enrichment: Performs functional enrichment analyses on APA-affected genes across RNAi conditions.
• UCSC Genome Browser integration: Provides customizable layers for the UCSC Genome Browser enabling examination of individual transcript isoforms with annotations for epigenetic modifications, miRNA binding sites, and RNA-binding proteins.

Scientific Applications:

• APA regulation studies: Characterizes how APA contributes to gene expression regulation and transcript isoform diversity in diverse biological programs.
• Disease mechanism investigation: Links perturbations in APA to potential disease mechanisms and to identification of diagnostic and therapeutic target candidates.
• Isoform-level regulatory analysis: Enables examination of epigenetic marks, miRNA binding sites, and RNA-binding protein associations at the transcript isoform level.

Methodology:

Analysis of TREND-seq datasets to quantify APA and TREND, cataloging APA changes upon depletion of >170 proteins (RNAi conditions), mapping global APA networks, performing condition-specific functional enrichment analyses, and exporting customizable annotation layers for the UCSC Genome Browser including epigenetic modifications, miRNA binding sites, and RNA-binding proteins.