Self-organizing human neuruloids allow disease modeling in the developing ectodermal compartment

Harnessing the self-organizing abilities of human embryonic stem cells to mimic normal and aberrant development is a pressing challenge. Generation of highly reproducible and standardized models would allow drug screening with unprecedented accuracy. Here we report single-cell RNA-seq data (10xGenomics) of human "neuruloids". Using micro-patterned technologies we recapitulate the self-organization of the complete human embryonic ectodermal compartment during neurulation containing: neural progenitors, neural crest, sensory placode and epidermis. Single-cell transcriptomics allowed the precise molecular characterization of each cell type in a faithful model of human neurulation. Additionally, isogenic neuruloids coupled to deep neural network analysis provide a unique opportunity to model human neuropathological disorders as demonstrated for Huntignton's disease. Overall design: Two single-cell RNAseq data sets of neuruloid day 7 (3ng/mL of BMP4) starting from hESCs (RUES2 and isogenic HTT 56CAG cell line).