Non-canonical proteoforms of the human fusiform gyrus in Alzheimers disease

Abstract

For a long time, the protein coding potential of our genome was underestimated. Only 2% of the genome was thought to be coding for the protein while the rest was called non-coding and junk. The two main sources of biasness which resulted in underestimation were prioritising conservation and length of the open reading frames (ORFs). But recent Ribo-seq studies and high throughput quantitative proteomics studies have shown that many ORFs previously annotated as non-coding are actually getting translated into proteins and these non-canonical proteins do have certain biological functions. These findings have added more parameter perspectives to look from about different diseases. This study aims to understand translation dynamics of these proteins encoded from non-canonical ORFs in neurological disorders affecting cognitive functions specifically targeting fusiform gyrus which is linked with face recognition and anime associations which are crucial symptoms in neurological disorders. This study uses transcriptomics and proteomics analysis to understand transcriptional and translational dynamics of ncORFs. A patient cohort from the Banner Sun Health Research Institute cohort is used, corresponding RNA-seq data and Quantitative MS/MS proteomics data published in different studies are used. A custom-made protein search database was created using transcriptomics tools like STAR, StringTie and Salmon to filter out expressed ncORFs within the non-coding region and not annotated as protein coding in either GENCODE or UniProt annotations. The custom ncORF-database was then later used in proteomics analysis as search space along with the canonical proteins. The entire comprehensive analysis has resulted in identification of 22,135 ncORF-encode proteins (ncPs) and out of which 67 are differentially expressed across different neurological conditions based on the | log2FC | >1 & p.adj < 0.05 criteria. The study highlights new molecular players which might be the missing links of known mechanisms.