Generation of ENSEMBL-based proteogenomics databases boosts the identification of non-canonical peptides.

Abstract

SummaryWe have implemented the pypgatk package and the pgdb workflow to create proteogenomics databases based on ENSEMBL resources. The tools allow the generation of protein sequences from novel protein-coding transcripts by performing a three-frame translation of pseudogenes, lncRNAs, and other non-canonical transcripts, such as those produced by alternative splicing events. It also includes exonic out-of-frame translation from otherwise canonical protein-coding mRNAs. Moreover, the tool enables the generation of variant protein sequences from multiple sources of genomic variants including COSMIC, cBioportal, gnomAD, and mutations detected from sequencing of patient samples. pypgatk and pgdb provide multiple functionalities for database handling, notably optimized target/decoy generation by the algorithm DecoyPyrat. Finally, we perform a reanalysis of four public datasets in PRIDE by generating cell-type specific databases for 65 cell lines using the pypgatk and pgdb workflow, revealing a wealth of non-canonical or cryptic peptides amounting to more than 10% of the total number of peptides identified (43,501 out of 402,512). AvailabilityThe software is freely available. pypgatk: (https://github.com/bigbio/py-pgatk/), and pgdb: (https://github.com/nf-core/pgdb) ContactYasset Perez-Riverol (yperez@ebi.ac.uk), Rui Branca (rui.mamede-branca@ki.se) Supplementary informationSupplementary data are available online.