Insights for disease modeling from single cell transcriptomics of iPSC-derived neurons and astrocytes across differentiation time and co-culture

Trans-differentiation of human induced pluripotent stem cells into neurons (hiPSC-N) via Ngn2-induction has become an efficient system to quickly generate neurons for disease modeling and in vitro assay development, a significant step up from previously used neoplastic and other cell lines. Recent single-cell interrogation of Ngn2-induced neurons however, has revealed some similarities to unexpected neuronal lineages. Similarly, a straightforward method to generate hiPSC derived astrocytes (hiPSC-A) for the study of neuropsychiatric disorders has also been described. Here we examine the homogeneity and similarity of hiPSC-N and hiPSC-A to their in vivo counterparts, the impact of different lengths of time post Ngn2 induction on hiPSC-N (15 or 21 days) and of hiPSC-N / hiPSC-A co-culture. We explore how often genes differentially expressed between conditions relate to genetic risk for neuropsychiatric disease. Leveraging the wealth of existing public single-cell RNA-seq (scRNA-seq) data in Ngn2-induced neurons and in vivo data from the developing brain, we provide perspectives on the lineage origins and maturation of hiPSC-N and hiPSC-A. Both show heterogeneity and share similarity with multiple in vivo cell fates, and both cell types more precisely approximate their in vivo counterparts when co-cultured. hiPSC-A show more heterogeneity and similarities to other non-neural cell types, especially when cultured in isolation. Gene expression data from the hiPSC-N show excess of genes linked to schizophrenia (SZ) and autism spectrum disorders (ASD) as has been previously shown for neural stem cells and neurons. These overrepresentations of disease genes are strongest in our system at early times (day 15) in Ngn2-induction/maturation of neurons, which together with our observation of similarities with in vivo neurons earlier in development suggest they may be a better model for neurodevelopmental disorders. We have assembled this new scRNA-seq data along with the public data explored here as an integrated biologist-friendly web-resource for researchers seeking to understand this system more deeply: https://nemoanalytics.org/p?l=DasEtAl2022 .