Resolving organoid brain region identities by mapping single-cell genomic data to reference atlases

Abstract

Self-organizing tissues resembling brain structures generated from human stem cells offer exciting possibilities to study human brain development, disease, and evolution. These 3D models are complex and can contain cells at various stages of differentiation from different brain regions. Single-cell genomic methods provide powerful approaches to explore cell composition, differentiation trajectories, and genetic perturbations in brain organoid systems. However, it remains a major challenge to understand the heterogeneity observed within and between individual organoids. Here, we develop a set of computational tools (VoxHunt) to assess brain organoid patterning, developmental state, and cell identity through comparisons to spatial and single-cell transcriptome reference datasets. We use VoxHunt to characterize and visualize cell compositions using single-cell and bulk genomic data from multiple organoid protocols modeling different brain structures. VoxHunt will be useful to assess organoid engineering protocols and to annotate cell fates that emerge in organoids during genetic and environmental perturbation experiments.