In silico nano-dissection: defining cell type specificity at transcriptional level in human disease (glomeruli)

ABSTRACT: To identify genes with cell-lineage-specific expression not accessible by experimental micro-dissection, we developed a genome-scale iterative method, in-silico nano-dissection, which leverages high-throughput functional-genomics data from tissue homogenates using a machine-learning framework. This study applied nano-dissection to chronic kidney disease and identified transcripts specific to podocytes, key cells in the glomerular filter responsible for hereditary proteinuric syndromes and acquired CKD. In-silico prediction accuracy exceeded predictions derived from fluorescence-tagged-murine podocytes, identified genes recently implicated in hereditary glomerular disease and predicted genes significantly correlated with kidney function. The nano-dissection method is broadly applicable to define lineage specificity in many functional and disease contexts.

ORGANISM(S): Homo sapiens

PROVIDER: GSE47183 | GEO | 2013/08/06

SECONDARY ACCESSION(S): PRJNA205044

REPOSITORIES: GEO