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. 2017 Jul 11;10(487):eaag2476.
doi: 10.1126/scisignal.aag2476.

Gene expression profiles of brain endothelial cells during embryonic development at bulk and single-cell levels

Affiliations

Gene expression profiles of brain endothelial cells during embryonic development at bulk and single-cell levels

Mike Hupe et al. Sci Signal. .

Abstract

The blood-brain barrier is a dynamic interface that separates the brain from the circulatory system, and it is formed by highly specialized endothelial cells. To explore the molecular mechanisms defining the unique nature of vascular development and differentiation in the brain, we generated high-resolution gene expression profiles of mouse embryonic brain endothelial cells using translating ribosome affinity purification and single-cell RNA sequencing. We compared the brain vascular translatome with the vascular translatomes of other organs and analyzed the vascular translatomes of the brain at different time points during embryonic development. Because canonical Wnt signaling is implicated in the formation of the blood-brain barrier, we also compared the brain endothelial translatome of wild-type mice with that of mice lacking the transcriptional cofactor β-catenin (Ctnnb1). Our analysis revealed extensive molecular changes during the embryonic development of the brain endothelium. We identified genes encoding brain endothelium-specific transcription factors (Foxf2, Foxl2, Foxq1, Lef1, Ppard, Zfp551, and Zic3) that are associated with maturation of the blood-brain barrier and act downstream of the Wnt-β-catenin signaling pathway. Profiling of individual brain endothelial cells revealed substantial heterogeneity in the population. Nevertheless, the high abundance of Foxf2, Foxq1, Ppard, or Zic3 transcripts correlated with the increased expression of genes encoding markers of brain endothelial cell differentiation. Expression of Foxf2 and Zic3 in human umbilical vein endothelial cells induced the production of blood-brain barrier differentiation markers. This comprehensive data set may help to improve the engineering of in vitro blood-brain barrier models.

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