tRFTar

tRFTar predicts Argonaute (AGO)-mediated interactions between tRNA-derived fragments (tRFs) and target genes by computationally analyzing CLIP-seq datasets to map tRF-target gene interactions (TGIs).

Key Features:

• Systematic profiling: Systematically profiles potential AGO-mediated tRF-target gene interactions (TGIs).
• Extensive dataset analysis: Re-analyzes 146 CLIP-seq datasets and identifies 920,690 TGIs between 12,102 tRFs and 5,688 target genes.
• High signal-to-noise ratio: Predicted TGIs exhibit superior signal-to-noise ratio and show consistency with TGIs identified by orthogonal techniques.
• Enrichment and co-expression analysis: Reveals enrichment of 5'-tRFs and 3'-tRFs, overrepresentation of commonly expressed tRFs, targeting of conserved transcript regions, and co-expression between tRFs and their targets.
• Regulatory TGI filtering: Filters TGIs by consistent co-expression with target genes to define 25,281 putative regulatory tRF-target pairs.

Scientific Applications:

• Post-transcriptional regulation studies: Enables investigation of tRF-mediated post-transcriptional regulatory mechanisms via AGO-bound TGI maps.
• Functional genomics: Supports functional genomics analyses to link tRFs to gene regulatory outcomes.
• Transcriptome and RNA regulatory pathway analysis: Facilitates transcriptome-wide exploration of RNA-based regulatory pathways involving tRFs.

Methodology:

Computational re-analysis of 146 CLIP-seq datasets to identify AGO-bound tRFs and TGIs, assessment of signal-to-noise and consistency with orthogonal techniques, and filtering of TGIs based on consistent co-expression to define regulatory pairs.