Figure 1

Illustration of the workflow to identify novel transcripts and peptides in developing mouse lens. Briefly, HISAT2, a splice aligner tool was used for the alignment of mouse lens RNA-Seq reads (FASTQ) to the mouse genome, followed by the transcripts annotation and expression quantification using the StringTie algorithm. In parallel, the RNA-Seq aligned data was further processed using JAFFA, and rMATS algorithms to detect fusion genes, and alternative splicing events, respectively, expressing in mouse lens. The novel transcripts (≥1.0TPM) were analyzed using a proteogenomics approach to identify novel peptides. The novel transcripts were translated into potential open reading frames (ORFs) to generate a reference database. The mouse lens proteome data (MS/MS spectra) was searched against this reference database to identify novel peptides. Finally, the novel peptides were validated through matching MS/MS spectra of synthetic peptides.