Cell Reports · 2020 · 349 citations · 43 references
Life SciencesNeurobiologyNeuroscienceGene ExpressionMolecular NeuroscienceTranscriptomicsMicroglia BiologyNeuroinflammationSingle-cell AnalysisSingle-cell GenomicsSingle-cell Rna Sequencing AnalysisSingle-cell TranscriptomicsCellular Activation StatesMicroglial Activation Gene ExpressionMicroglial Single-cell TranscriptomicsSingle-cell Rna SequencingSingle-cell Transcriptomics In NeuroscienceSingle-nucleus Rna SequencingSingle-nucleus SequencingSingle-nucleus Transcriptomics
Single-nucleus RNA sequencing (snRNA-seq) is used as an alternative to single-cell RNA-seq, as it allows transcriptomic profiling of frozen tissue. However, it is unclear whether snRNA-seq is able to detect cellular state in human tissue. Indeed, snRNA-seq analyses of human brain samples have failed to detect a consistent microglial activation signature in Alzheimer's disease. Our comparison of microglia from single cells and single nuclei of four human subjects reveals that, although most genes show similar relative abundances in cells and nuclei, a small population of genes (∼1%) is depleted in nuclei compared to whole cells. This population is enriched for genes previously implicated in microglial activation, including APOE, CST3, SPP1, and CD74, comprising 18% of previously identified microglial-disease-associated genes. Given the low sensitivity of snRNA-seq to detect many activation genes, we conclude that snRNA-seq is not suited for detecting cellular activation in microglia in human disease.
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Comprehensive Integration of Single-Cell Data
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