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Berson, Eloise; Sreenivas, Anjali; Phongpreecha, Thanaphong; Perna, Amalia; Grandi, Fiorella C; Xue, Lei; Ravindra, Neal G; Payrovnaziri, Neelufar; Mataraso, Samson; Kim, Yeasul; Espinosa, Camilo; Chang, Alan L; Becker, Martin; Montine, Kathleen S; Fox, Edward J; Chang, Howard Y; Corces, M Ryan; Aghaeepour, Nima; Montine, Thomas J
Nature communications, 08/2023, Letnik: 14, Številka: 1Journal Article
Assay for Transposase Accessible Chromatin by sequencing (ATAC-seq) accurately depicts the chromatin regulatory state and altered mechanisms guiding gene expression in disease. However, bulk sequencing entangles information from different cell types and obscures cellular heterogeneity. To address this, we developed Cellformer, a deep learning method that deconvolutes bulk ATAC-seq into cell type-specific expression across the whole genome. Cellformer enables cost-effective cell type-specific open chromatin profiling in large cohorts. Applied to 191 bulk samples from 3 brain regions, Cellformer identifies cell type-specific gene regulatory mechanisms involved in resilience to Alzheimer's disease, an uncommon group of cognitively healthy individuals that harbor a high pathological load of Alzheimer's disease. Cell type-resolved chromatin profiling unveils cell type-specific pathways and nominates potential epigenetic mediators underlying resilience that may illuminate therapeutic opportunities to limit the cognitive impact of the disease. Cellformer is freely available to facilitate future investigations using high-throughput bulk ATAC-seq data.
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in: SICRIS
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