Large-scale mapping of mammalian transcriptomes identifies conserved genes associated with different cell states.

ABSTRACT: Distinguishing cell states based only on gene expression data remains a challenging task. This is true even for analyses within a species. In cross-species comparisons, the results obtained by different groups have varied widely. Here, we integrate RNA-seq data from more than 40 cell and tissue types of four mammalian species to identify sets of associated genes as indicators for specific cell states in each species. We employ a statistical method, TROM, to identify both protein-coding and non-coding indicators. Next, we map the cell states within each species and also between species using these indicator genes. We recapitulate known phenotypic similarity between related cell and tissue types and reveal molecular basis for their similarity. We also report novel associations between severa

SUBMITTER: Yang Y 

PROVIDER: S-EPMC5389511 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature