Dataset Information

Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment.

ABSTRACT: The cell types that trigger the primary pathology in many brain diseases remain largely unknown. One route to understanding the primary pathological cell type for a particular disease is to identify the cells expressing susceptibility genes. Although this is straightforward for monogenic conditions where the causative mutation may alter expression of a cell type specific marker, methods are required for the common polygenic disorders. We developed the Expression Weighted Cell Type Enrichment (EWCE) method that uses single cell transcriptomes to generate the probability distribution associated with a gene list having an average level of expression within a cell type. Following validation, we applied EWCE to human genetic data from cases of epilepsy, Schizophrenia, Autism, Intellectual Disability, Alzheimer's disease, Multiple Sclerosis and anxiety disorders. Genetic susceptibility primarily affected microglia in Alzheimer's and Multiple Sclerosis; was shared between interneurons and pyramidal neurons in Autism and Schizophrenia; while intellectual disabilities and epilepsy were attributable to a range of cell-types, with the strongest enrichment in interneurons. We hypothesized that the primary cell type pathology could trigger secondary changes in other cell types and these could be detected by applying EWCE to transcriptome data from diseased tissue. In Autism, Schizophrenia and Alzheimer's disease we find evidence of pathological changes in all of the major brain cell types. These findings give novel insight into the cellular origins and progression in common brain disorders. The methods can be applied to any tissue and disorder and have applications in validating mouse models.

SUBMITTER: Skene NG

PROVIDER: S-EPMC4730103 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment.

Skene Nathan G NG Grant Seth G N SG

Frontiers in neuroscience 20160127

The cell types that trigger the primary pathology in many brain diseases remain largely unknown. One route to understanding the primary pathological cell type for a particular disease is to identify the cells expressing susceptibility genes. Although this is straightforward for monogenic conditions where the causative mutation may alter expression of a cell type specific marker, methods are required for the common polygenic disorders. We developed the Expression Weighted Cell Type Enrichment (EW ...[more]

PMID: 26858593

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Project description:Purpose: Transport processes in the renal collecting duct are responsible for precise regulation of blood pressure and body fluid composition. The collecting duct is composed of at least three cell types, type A intercalated cells (A-IC), type B intercalated cells (B-IC) and principal cells (PC). To identify the genes that are selectively expressed in each cell type, including cell-surface receptors, transcription factors, transporters and secreted proteins, we used cell surface markers necessary for isolation of each of the three cell types using fluorescence-activated cell sorting and carried out single-cell RNA-Seq to measure the mRNA species in each of these cell types. Methods: We enriched each of the three cell types using fluorescence-activated cell sorting. Subsequently, we carried out single-cell RNA-Seq of those cells using a microfluidic chip (Fluidigm C1 system). Single-cell cDNA libraries were constructed for paired-end sequencing and sequenced on Illumina HiSeq3000 platform. In addition, we also microdissected mouse CCDs and cTALs and carried out single-tubule RNA-Seq. Reads were mapped to mouse Ensembl Genome by STAR and transcript abundances were calculated in the units of transcripts per million (TPM) using RSEM (https://github.com/deweylab/RSEM). Single-cell RNA-Seq data anaysis were carried out using Seurat package in R. Results and conclusion: Single-cell cDNA libraries were constructed for paired-end sequencing and at least 10-million sequence reads per cell were mapped to the mouse genome (Ensembl, GRCm38.p5). On average, cells were sequenced to a depth of 3000 genes (TPM>1). Unsupervised clustering analysis revealed five different cell types, namely type A intercalated cells (n=87), type B intercalated cells (n=23), principal cells (74), proximal tubule cells (n=19), and non-epithelial cells (n=32). The identified patterns of gene expression among A-ICs, B-ICs and PCs provide a foundation for understanding physiological regulation and pathophysiology in the renal collecting duct.

Dataset Information

Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment.

Publications

Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment.

Similar Datasets

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