Leveraging the effect of natural genetic variation in order to study human microglia

Identification: Holtman, Inge


Description

Leveraging the effect of natural genetic variation in order to study human microglia
 
Inge R. Holtman1,4, Johannes Schlachetzki1, Claudia Z. Han1, Alexi Nott1, David Gosselin1, Verena M. Link1, Nicole G Coufal2, Miao Yu1, Bethany R. Fixsen1, Suely K.N. Marie3, Graham McVicker2, Erik. W.G.M. Boddeke4, Richard Ransohoff5, Bing Ren1, Bart J.L. Eggen4, Christopher K. Glass1
1Department of Cellular and Molecular Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0651, USA; 2Laboratory of Genetics, The Salk Institute for Biological Studies, 10010 N Torrey Pines Road, La Jolla, CA 92037-1002, USA; 3Department of Neurology, Laboratory of Molecular and Cellular Biology, School of Medicine, University of São Paulo, São Paulo, Brazil; 4Department of Neuroscience, section Medical Physiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands; 5Third Rock Ventures, Boston, MA
 
Microglia, the brain-specific macrophages, are increasingly implicated to play key roles in neurodegenerative conditions, but the underlying molecular mechanisms that regulate human microglia are still largely unknown. Here, we investigated the effect of natural genetic variation on gene expression and enhancers in human microglia by addressing the following aims. First, we tested whether the transcription factor PU.1, the master regulator of the myeloid lineage, and a set of collaborating transcription factors drive the selection of enhancers that determine microglia identity and regulatory potential. We used ChIP-seq and ATAC-seq methods to define enhancer atlases in freshly isolated human microglia and performed Mutation Analysis of Regulatory Genomic Elements (MARGE-analysis) and identified putative collaborative partners. Second, we identified enhancer promoter-interactions in human microglia and neurons using Proximity-Assisted Ligation ChIP-seq (PLAC)-seq, linking disease associated genetic variants to promoters of genes. Third, we used natural genetic variation across individuals to identify quantitative trait loci (QTL) that disrupt enhancers or alter gene expression. These experiments establish the functional importance of conserved transcription factors and provide important information on the effects of disease associated natural genetic variation on microglia.
 

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