The Tissue Atlas, generated by the Human Protein Atlas project, focuses on integrated omics for spatial localization of all human proteins down to the single cell level1. Genome-wide mRNA expression data is used for categorization of all human genes based on expression level and tissue distribution, combined with standardized immunohistochemistry for studying the protein localization in the context of neighboring cells. Recent advances of the Tissue Atlas include in-depth characterization of cell type-specific expression patterns, with main emphasis on the testis-specific proteome.
In the 2019 update of the public database www.proteinatlas.org, mRNA expression data from three different sources is merged and normalized for comprehensive categorization of all human genes in 37 different organs and tissues. The analysis shows that testis has by far the highest number of tissue-specific genes, however, many of the corresponding proteins lack a known function. Recently, the in situ expression of >500 proteins was characterized in eight different testicular cell types, allowing us to identify six distinct clusters of expression at different stages of spermatogenesis2. The analysis included numerous proteins previously classified as missing proteins (MPs). In a continued effort, we focus on single cell evaluation and spatial localization of >3,000 additional proteins with a cell type-specific expression in testis. By using multiplex immunofluorescence, the overlap between proteins with well-known testis functions and previously uncharacterized proteins can be determined, highlighting important targets for testis specific research.
Knowledge of the architecture of every human cell aids in identification of proteins that may accelerate research in molecular medicine, and contributes to further knowledge of underlying disease mechanisms. The Human Protein Atlas constitutes a comprehensive knowledge resource for gaining biological insight on human proteins. The publicly available datasets and high-resolution images allow for in-depth analysis of cell type-specific expression patterns and further exploration of MPs.