Identification of Protein Isoforms Using Reference Databases Built from Long and Short Read RNA-Sequencing

Alternative splicing can lead to
distinct protein isoforms. These
can have different functions in specific cells and tissues or in different
developmental stages. In this study, we explored whether transcripts
assembled from long read, nanopore-based, direct RNA-sequencing (RNA-seq)
could improve the identification of protein isoforms in human K562
cells. By comparing with Illumina-based short read RNA-seq, we showed
that a large proportion of Ensembl transcripts (5949/14,326) and genes
expressing alternatively spliced transcripts (486/2981) identified
with long direct reads were missed by short paired-end reads. By co-analyzing
proteomic and transcriptomic data, we also showed that some peptides
(826/35,976), proteins (262/3215), and protein isoforms arising from
distinct transcript variants (574/1212) identified with isoform-specific
peptides via custom long-read-based databases were missed in Illumina-derived
databases. Finally, we generated unequivocal peptide evidence for
a set of protein isoforms and showed that long read, direct RNA-seq
allows the discovery of novel protein isoforms not already in reference
databases or custom databases built from short read RNA-seq data.
Our analysis highlights the benefits of long read RNA-seq data in
the generation of reference databases to increase tandem mass spectrometry
(MS/MS) identification of protein isoforms.