Because iTP-seq uses custom transcript libraries and needs fewer reads per condition than Ribo-seq, you can test in parallel how multiple antibiotics, translation factors, engineered ribosomes, or other perturbations shape translation.
🔗 Read our paper here: rdcu.be/eZbiI
Using RNase R to generate ribosome-protected “inverse toeprints” and deep sequencing, iTP-seq reveals where ribosomes stall and what they’ve translated, with codon-level resolution and without needing a reference genome.
We’re thrilled to share our latest iTP-seq protocol for mapping bacterial translation landscapes in vitro — with a complete experimental workflow streamlined by Mélanie Gillard and an open source Python library for data analysis developed by Thibaud Renault.
