We used single cell genomic approaches to map DNA copy number variation (CNV) in neurons obtained from human induced pluripotent stem cell (hiPSC) lines and post-mortem human brains. We identified aneuploid neurons as well as numerous subchromosomal CNVs in euploid neurons. Neurotypic hiPSC-derived neurons had larger CNVs than fibroblasts, and several large deletions were found in hiPSC-derived neurons but not in matched neural progenitor cells. Single cell sequencing of endogenous human frontal cortex neurons revealed that 13%-41% of neurons have at least one megabase-scale de novo CNV, that deletions are twice as common as duplications, and that a subset of neurons have highly aberrant genomes marked by multiple alterations. Our results show that mosaic copy number variation is abundant in human neurons.

A basic assumption about the normal nervous system is that its neurons possess identical genomes. Here we present direct evidence for genomic variability, manifested as chromosomal aneuploidy, among developing and mature neurons. Analysis of mouse embryonic cerebral cortical neuroblasts in situ detected lagging chromosomes during mitosis, suggesting the normal generation of aneuploidy in these somatic cells. Spectral karyotype analysis identified Ϸ33% of neuroblasts as aneuploid. Most cells lacked one chromosome, whereas others showed hyperploidy, monosomy, and͞or trisomy. The prevalence of aneuploidy was reduced by culturing cortical explants in medium containing fibroblast growth factor 2. Interphase fluorescence in situ hybridization on embryonic cortical cells supported the rate of aneuploidy observed by spectral karyotyping and detected aneuploidy in adult neurons. Our results demonstrate that genomes of developing and adult neurons can be different at the level of whole chromosomes.

Single-cell sequencing methods have emerged as powerful tools for identification of heterogeneous cell types within defined brain regions. Application of single-cell techniques to study the transcriptome of activated neurons can offer insight into molecular dynamics associated with differential neuronal responses to a given experience. Through evaluation of common whole-cell and single-nuclei RNA-sequencing (snRNA-seq) methods, here we show that snRNA-seq faithfully recapitulates transcriptional patterns associated with experience-driven induction of activity, including immediate early genes (IEGs) such as Fos, Arc and Egr1. SnRNA-seq of mouse dentate granule cells reveals large-scale changes in the activated neuronal transcriptome after brief novel environment exposure, including induction of MAPK pathway genes. In addition, we observe a continuum of activation states, revealing a pseudotemporal pattern of activation from gene expression alone. In summary, snRNA-seq of activated neurons enables the examination of gene expression beyond IEGs, allowing for novel insights into neuronal activation patterns in vivo.

A protocol is described for sequencing the transcriptome of a cell nucleus. Nuclei are isolated from specimens and sorted by FACS, cDNA libraries are constructed and RNA-seq is performed, followed by data analysis. Some steps follow published methods (Smart-seq2 for cDNA synthesis and Nextera XT barcoded library preparation) and are not described in detail here. Previous single-cell approaches for RNA-seq from tissues include cell dissociation using protease treatment at 30 °C, which is known to alter the transcriptome. We isolate nuclei at 4 °C from tissue homogenates, which cause minimal damage. Nuclear transcriptomes can be obtained from postmortem human brain tissue stored at −80 °C, making brain archives accessible for RNA-seq from individual neurons. The method also allows investigation of biological features unique to nuclei, such as enrichment of certain transcripts and precursors of some noncoding RNAs. By following this procedure, it takes about 4 d to construct cDNA libraries that are ready for sequencing.

Significance One of the central goals of developmental biology and medicine is to ascertain the relationships between the genotype and phenotype of cells. Single-cell transcriptome analysis represents a powerful strategy to reach this goal. We advance these strategies to single nuclei from neural progenitor cells and dentate gyrus tissue, from which it is very difficult to recover intact cells. This provides a unique means to carry out RNA sequencing from individual neurons that avoids requiring isolation of single-cell suspensions, eliminating potential changes in gene expression due to enzymatic-cell dissociation methods. This method will be useful for analysis of processes occurring in the nucleus and for gene-expression studies of highly interconnected cells such as neurons.