Genetic and phenotypic heterogeneity occurs in many diseases, including autism. The advent of single‐cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq) has enabled the unbiased analysis of molecular profiles of individual cells, highlighting a remarkable level of heterogeneity in cellular populations that can contribute to the phenotypic heterogeneity in disease. The extent to which cellular heterogeneity might play a role in autism pathology currently remains unclear.

Arnold Kriegstein aims to address the role of cellular heterogeneity in autism using snRNA-seq to analyze the transcriptomes of single neuronal and glial nuclei from snap‐frozen postmortem brain tissue. Kriegstein’s team will perform these snRNA‐seq analyses on brain samples from children and adolescents with autism, and compare the results to age- and sex‐matched controls. The group will focus on cell-type‐specific alterations in the association and limbic systems of the brain, regions where dysfunction has been connected to behavioral manifestations of autism. Large‐scale 3’‐tagged gene-expression analysis on the 10X Genomics platform will ensure analysis of rare neural populations, while medium‐scale full‐transcript deep RNA sequencing on the Fluidigm C1 platform will be used to study dysregulation of alternative splicing and long noncoding RNA expression. By performing unbiased clustering of cell types based on single‐cell transcriptional profiles and comparing gene expression and long intergenic noncoding RNA (lincRNA) expression in each cell type between autism and control groups, Kriegstein’s group expects to identify cell-type‐specific molecular changes across affected individuals. In order to link the affected cell type to the cytoarchitecture of cortical and subcortical areas, the team will validate the findings in cryosections using single‐molecule fluorescent in situ hybridization (smFISH) and immunohistochemical analysis.

The results of this project will provide insight into region- and cell-type‐specific molecular changes in autism at an unprecedented level of resolution. Such findings are expected to help explain variations in disease phenotypes and ultimately inform the development of highly targeted therapies.