By comparing CoPA projection patterns between normal and pathological human brain samples using differential CoPA, this work identifies gene coexpression modules that are uniformly and reproducibly dysregulated in specific neocortical cell types in Alzheimer’s disease or schizophrenia.
Abstract
Understanding which genes are reproducibly dysregulated in which cell types is foundational knowledge for efforts to slow or reverse pathologies. For neuropathologies, such efforts rely primarily on differential expression analysis of single-nucleus RNA-seq (snRNA-seq) data. However, this strategy suffers from experimental and statistical challenges that limit marker gene reproducibility. We describe a novel strategy called Covariation Projection Analysis (CoPA) that combines the power of bulk sampling with the precision of single-cell methods. By ‘projecting’ bulk gene coexpression modules onto pseudobulked snRNA-seq cell types, CoPA reveals the cellular origins of highly reproducible genomic programs and their relative importance among cell types. By comparing CoPA projection patterns between normal and pathological human brain samples using differential CoPA (dCoPA), we identify gene coexpression modules that are uniformly and reproducibly dysregulated in specific neocortical cell types in Alzheimer’s disease or schizophrenia. We share our findings through a novel web application called CoPA Cabana (https://oldhamlab.shinyapps.io/copacabana/).
It is demonstrated that pathology-defined cell states provide a more reproducible framework for studying ALS transcriptomic alterations than conventional case-control comparisons and an interactive browser is provided to facilitate exploration and comparison of ALS snRNA-seq datasets.
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Neurodegenerative and neuropsychiatric diseases impose a considerable societal and public health burden. However, our understanding of the molecular mechanisms underlying these highly complex conditions remains limited1,2. Here, to gain deeper insights into the aetiology of different brain diseases, we used specimens f...
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Interindividual heterogeneity in Alzheimer’s disease (AD) remains poorly understood, as disparate single-cell studies leave it unclear whether findings reflect shared architecture or dataset-specific idiosyncrasies. Here, we present panAD, a transcriptomic atlas of >3 million nuclei from 791 individuals across 13 studi...
Negin Rahimzadeh, S. Morabito, S. Khullar et al.· bioRxiv· 0 citations
These findings provide a cell-type-resolved and ancestry-aware atlas of genetically regulated expression in the human prefrontal cortex and illustrate how single-nucleus transcriptomics can sharpen gene discovery and therapeutic target prioritization for complex brain disorders.
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A scalable, cell-type-resolved in vivo CRISPR interference (CRISPRi) platform enabling systematic gene function profiling in the mouse brain is developed and the CRISPRinvivo data portal is established as a community resource for in vivo screening.
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