Document Type
Article
Publication Date
2-9-2021
Keywords
JMG
JAX Source
Cell Rep 2020 Feb 9; 34(6):108739
Volume
34
Issue
6
First Page
108739
Last Page
108739
ISSN
2211-1247
PMID
33567283
DOI
https://doi.org/10.1016/j.celrep.2021.108739
Grant
AG051496, AG055104
Abstract
Genetic and genome-wide association studies suggest a central role for microglia in Alzheimer's disease (AD). However, single-cell RNA sequencing (scRNA-seq) of microglia in mice, a key preclinical model, has shown mixed results regarding translatability to human studies. To address this, scRNA-seq of microglia from C57BL/6J (B6) and wild-derived strains (WSB/EiJ, CAST/EiJ, and PWK/PhJ) with and without APP/PS1 demonstrates that genetic diversity significantly alters features and dynamics of microglia in baseline neuroimmune functions and in response to amyloidosis. Results show significant variation in the abundance of microglial subtypes or states, including numbers of previously identified disease-associated and interferon-responding microglia, across the strains. For each subtype, significant differences in the expression of many genes are observed in wild-derived strains relative to B6, including 19 genes previously associated with human AD including Apoe, Trem2, and Sorl1. This resource is critical in the development of appropriately targeted therapeutics for AD and other neurological diseases.
Recommended Citation
Yang H,
Onos KD,
Choi K,
Keezer K,
Skelly D,
Carter GW,
Howell G.
Natural genetic variation determines microglia heterogeneity in wild-derived mouse models of Alzheimer's disease. Cell Rep 2020 Feb 9; 34(6):108739
Comments
We gratefully acknowledge the contribution of Sandy Daigle, Michael Samuels, and Paul Robson at the Single Cell Biology Laboratory at The Jackson Laboratory (JAX) for expert assistance with this publication. We thank Duy Pham from the Churchill lab at JAX for advice on pre-processing of scRNA-seq data on high-performance computing cluster. We thank Christoph Preuss from the Carter lab at JAX for advice on analysis using human AD-relevant GWAS genes. We thank Sandeep Namburi at JAX research IT for installing essential packages and troubleshooting on RStudio server. We thank Jane Cha from JAX Creative for the design and creation of our graphical abstract.
This is an open access article under the CC BY license.