Single-Cell Heterogeneity Analysis and CRISPR Screen Identify Key β-Cell-Specific Disease Genes.

ABSTRACT: Identification of human disease signature genes typically requires samples from many donors to achieve statistical significance. Here, we show that single-cell heterogeneity analysis may overcome this hurdle by significantly improving the test sensitivity. We analyzed the transcriptome of 39,905 single islets cells from 9 donors and observed distinct β cell heterogeneity trajectories associated with obesity or type 2 diabetes (T2D). We therefore developed RePACT, a sensitive single-cell analysis algorithm to identify both common and specific signature genes for obesity and T2D. We mapped both β-cell-specific genes and disease signature genes to the insulin regulatory network identified from a genome-wide CRISPR screen. Our integrative analysis discovered the previously unrecognized roles o

SUBMITTER: Fang Z 

PROVIDER: S-EPMC6573026 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature