Single-cell transcriptomic landscape in Alzheimer’s disease

The gene-regulatory landscape of the brain is highly dynamic in health and disease, coordinating a menagerie of biological processes across distinct cell types. Understanding these regulatory programs requires a holistic experimental and analytical approach. Here, we present a single-cell study of 380,000 nuclei in late-stage Alzheimer’s Disease (AD) using parse biosciences whole transcriptome kit, profiling gene expression in thousands of genes and uncovering vast neuronal and glial heterogeneity in late-stage AD. We introduce a co-expression network analysis strategy for single-cell data (hd-WGCNA) to perform a systems-level meta-analysis of AD transcriptomics to uncover underlying regulatory architecture. hd-WGCNA is based on a meta-analytical approach to jointly form co-expression networks in metacells constructed from the integrated snRNA-seq dataset as well as bulk-tissue RNA-seq data of the human cortex, where each edge in a co-expressed module is supported by both bulk RNA-seq data and snRNA-seq data. Finally, this work provides an unbiased single-cell atlas of transcriptomic regulation of AD in distinct brain regions.

Vivek Swarup, PhD
Assistant Professor, Neurobiology and Behavior
School of Biological Sciences
Department of Neurobiology and Behavior
University of California Irvine

Dr. Swarup is an Assistant Professor at the Department of Neurobiology and Behavior at the University of California Irvine. His lab uses multi-omics and functional genomics.