RESUMEN
In the enteric nervous system (ENS), glia outnumber neurons by 4-fold and form an extensive network throughout the gastrointestinal tract. Growing evidence for the essential role of enteric glia in bowel function makes it imperative to understand better their molecular marker expression and how they relate to glia in the rest of the nervous system. We analyzed expression of markers of astrocytes and oligodendrocytes in the ENS and found, unexpectedly, that proteolipid protein 1 (PLP1) is specifically expressed by glia in adult mouse intestine. PLP1 and S100ß are the markers most widely expressed by enteric glia, while glial fibrillary acidic protein expression is more restricted. Marker expression in addition to cellular location and morphology distinguishes a specific subpopulation of intramuscular enteric glia, suggesting that a combinatorial code of molecular markers can be used to identify distinct subtypes. To assess the similarity between enteric and extraenteric glia, we performed RNA sequencing analysis on PLP1-expressing cells in the mouse intestine and compared their gene expression pattern to that of other types of glia. This analysis shows that enteric glia are transcriptionally unique and distinct from other cell types in the nervous system. Enteric glia express many genes characteristic of the myelinating glia, Schwann cells and oligodendrocytes, although there is no evidence of myelination in the murine ENS. GLIA 2015;63:2040-2057.
RESUMEN
We present a sensitive approach to predict genes expressed selectively in specific cell types, by searching publicly available expression data for genes with a similar expression profile to known cell-specific markers. Our method, CellMapper, strongly outperforms previous computational algorithms to predict cell type-specific expression, especially for rare and difficult-to-isolate cell types. Furthermore, CellMapper makes accurate predictions for human brain cell types that have never been isolated, and can be rapidly applied to diverse cell types from many tissues. We demonstrate a clinically relevant application to prioritize candidate genes in disease susceptibility loci identified by GWAS.