TRlnc

TRlnc aggregates and annotates transcriptional regulatory regions of human long noncoding RNAs (lncRNAs) to support analysis of cell type–specific regulatory mechanisms.

Key Features:

• Comprehensive regulatory collection: Contains 8,683,028 typical enhancers/super-enhancers and 32,348,244 chromatin accessibility regions associated with 91,906 human lncRNAs.
• Source datasets: Regulatory regions identified from over 900 human H3K27ac ChIP-seq, ATAC-seq, and DNase-seq samples.
• Genetic variant annotations: Includes common SNPs, risk SNPs, linkage disequilibrium SNPs, and expression quantitative trait loci (eQTLs) mapped to regulatory regions.
• Epigenetic and TF annotations: Provides transcription factor annotations, methylation sites, and histone modification information within regulatory regions.
• 3D chromatin interactions: Annotates regulatory regions with 3D chromatin interaction data relevant to lncRNA regulation.
• Cell type specificity: Maintains cell type–specific associations between regulatory elements and lncRNAs.
• Integration of existing resources: Aggregates multiple public datasets and annotations to provide consolidated regulatory information for lncRNAs.

Scientific Applications:

• Transcriptional regulatory network analysis: Study cell type–specific regulatory networks involving lncRNAs and their associated enhancers or accessibility regions.
• Genetic association interpretation: Interpret the impact of common SNPs, risk SNPs, LD SNPs, and eQTLs located in lncRNA regulatory regions on disease-related signals.
• Epigenetic mechanism investigation: Examine methylation patterns and histone modifications at lncRNA regulatory elements to infer regulatory mechanisms.
• 3D genome studies: Analyze chromatin interaction data to link distal regulatory elements to lncRNA loci and infer spatial regulatory relationships.
• Enhancer function characterization: Differentiate typical enhancers and super-enhancers associated with lncRNAs to assess their potential regulatory roles.

Methodology:

Regulatory regions were identified from over 900 human H3K27ac ChIP-seq, ATAC-seq, and DNase-seq datasets and annotated with common and risk SNPs, eQTLs, linkage disequilibrium SNPs, transcription factor annotations, methylation sites, histone modifications, and 3D chromatin interactions.