Optimised fluorescence-activated nuclei sorting for epigenomic analysis of cortical cell types.

Authors

Barry Chioza, Stefania Policicchio, Joe Burrage, Georgina E T Blake, Rosemary A Bamford, Alice Franklin, Darren Soanes, Philippa M Wells, Ann Babtie, Marina Flores Payan, Jonathan P Davies, Anthony Klokkaris, Emma M Walker, Joy N Ismail, Paulina Urbanaviciute, Sarah J Marzi, Eilis Hannon, Jonathan Mill, Emma L Dempster

Published in

PloS one. Volume 21. Issue 10. Pages e0359643. Epub Oct 06, 2026.

Abstract

Increased understanding of the functional complexity of the genome has led to growing recognition of the role of non-sequence-based regulatory variation in disorders of the human central nervous system. Most genomic analyses of the brain are limited by the use of bulk tissue, which comprises a heterogeneous mix of different neural cell types with distinct epigenetic profiles, thereby limiting the ability to attribute regulatory changes to specific cell populations. Given the limited availability of human post-mortem tissue resources and the importance of integrating multi-omic data from the same samples, there is a critical need for methods that enable parallel, cell-type-resolved genomic profiling. We present optimised protocols using fluorescence-activated nuclei sorting (FANS) to isolate nuclei from different human and mouse brain cell types for downstream multi-omic analysis. Our approach enables the robust purification of neuronal, oligodendrocyte, microglial and other glial-origin nuclei from both adult and fetal brain tissue. We demonstrate that FANS-isolated nuclei are compatible with a wide range of genomic assays, including profiling of DNA modifications, histone modifications, chromatin accessibility, and gene expression. This protocol maximises the utility of limited post-mortem tissue resources and provides a unified workflow for comprehensive, cell-type-specific interrogation of molecular mechanisms involved in the brain.

PMID:
42837428
Bibliographic data and abstract were imported from PubMed on 07 Oct 2026.

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