Assessing similarity to primary tissue and cortical layer identity in induced pluripotent stem cell-derived cortical neurons through single-cell transcriptomics

Abstract

Induced pluripotent stem cell (iPSC)-derived cortical neurons potentially present a powerful new model to understand corticogenesis and neurological disease. Previous work has established that differentiation protocols can produce cortical neurons, but little has been done to characterize these at cellular resolution. In particular, it is unclear to what extent in vitro two-dimensional, relatively disordered culture conditions recapitulate the development of in vivo cortical layer identity. Single-cell multiplex reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) was used to interrogate the expression of genes previously implicated in cortical layer or phenotypic identity in individual cells. Totally, 93.6% of single cells derived from iPSCs expressed genes indicative of neuronal identity. High proportions of single neurons derived from iPSCs expressed glutamatergic receptors and synaptic genes. And, 68.4% of iPSC-derived neurons expressing at least one layer marker could be assigned to a laminar identity using canonical cortical layer marker genes. We compared single-cell RNA-seq of our iPSC-derived neurons to available single-cell RNA-seq data from human fetal and adult brain and found that iPSC-derived cortical neurons closely resembled primary fetal brain cells. Unexpectedly, a subpopulation of iPSC-derived neurons co-expressed canonical fetal deep and upper cortical layer markers. However, this appeared to be concordant with data from primary cells. Our results therefore provide reassurance that iPSC-derived cortical neurons are highly similar to primary cortical neurons at the level of single cells but suggest that current layer markers, although effective, may not be able to disambiguate cortical layer identity in all cells.

Cerebral cortical neuron diversity and development at single-cell resolution

“…A key use of scRNA-seq will be to validate in vitro models of human brain development and disease by comparing the cell types and developmental dynamics of these models to primary human tissues[51,56,57]. Cerebral organoids are fast becoming a popular model for early human brain development, but neither the variability across iPSC lines or individual organoids nor the correspondence of organoids to in vivo brain development is yet fully understood.…”

Batch effects and the effective design of single-cell gene expression studies

“…Using single-cell gene expression data, we can begin to effectively characterize and classify individual cell types and cell states, develop a better understanding of gene regulatory threshold effects in response to treatments or stress, and address a large number of outstanding questions that pertain to the regulation of noise and robustness of gene expression programs. Indeed, single cell gene expression data have already been used to study and provide unique insight into a wide range of research topics, including differentiation and tissue development345, the innate immune response67, and pharmacogenomics89.…”

Batch effects and the effective design of single-cell gene expression studies

“…Using single-cell gene expression data, we can begin to effectively characterize and classify individual cell types and cell states, develop a better understanding of gene regulatory threshold effects in response to treatments or stress, and address a large number of outstanding questions that pertain to the regulation of noise and robustness of gene expression programs. Indeed, single cell gene expression data have already been used to study and provide unique insight into a wide range of research topics, including differentiation and tissue development [3][4][5] , the innate immune response 6,7 , and pharmacogenomics 8,9 . Yet, there are a number of outstanding challenges that arose in parallel with the application of single cell technology 10 .…”