Computation-assisted targeted proteomics of alternative splicing protein isoforms in the human heart.

ABSTRACT: Alternative splicing is prevalent in the heart and implicated in many cardiovascular diseases, but not every alternative transcript is translated and detecting non-canonical isoforms at the protein level remains challenging. Here we show the use of a computation-assisted targeted proteomics workflow to detect protein alternative isoforms in the human heart. We build on a recent strategy to integrate deep RNA-seq and large-scale mass spectrometry data to identify candidate translated isoform peptides. A machine learning approach is then applied to predict their fragmentation patterns and design protein isoform-specific parallel reaction monitoring detection (PRM) assays. As proof-of-principle, we built PRM assays for 29 non-canonical isoform peptides and detected 22 peptides in a human heart lysate. The predictions-aided PRM assays closely mirrored synthetic peptide standards for non-canonical sequences. This approach may be useful for validating non-canonical protein identification and discovering functionally relevant isoforms in the heart.

SUBMITTER: Han Y 

PROVIDER: S-EPMC8722536 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature