Single nucleus multi-omics identifies human cortical cell regulatory genome diversity

Area of Science:

• Neuroscience
• Genomics
• Epigenetics

Background:

• Single-cell technologies offer insights into cellular heterogeneity but are often limited to one data type.
• Validating computational methods for fusing multi-omic single-cell data is challenging without true multi-omic measurements.

Purpose of the Study:

• To develop and validate a novel multi-modal single-cell sequencing technology.
• To comprehensively assess molecular phenotypes and cell types in the human frontal cortex.
• To enable joint analysis of epigenomic and transcriptomic data.

Main Methods:

• Devised single-nucleus methylcytosine, chromatin accessibility, and transcriptome sequencing (snmCAT-seq).
• Applied snmCAT-seq to postmortem human frontal cortex tissue.
• Developed a cross-validation framework using multi-modal data for cell type validation and computational method assessment.

Main Results:

• snmCAT-seq successfully integrated methylome, transcriptome, and chromatin accessibility data for 63 human cortical cell types.
• Correlation analysis revealed distinct relationships between DNA methylation and gene expression within individual cells.
• Reconstructed regulatory lineages of cortical cell populations.

Conclusions:

• The study presents a validated multi-omic single-cell technology for deep molecular phenotyping of the human brain.
• Identified specific enrichment of genetic risk factors for neuropsychiatric disorders in distinct cortical cell types.
• The findings enable prediction of cell types associated with neuropsychiatric diseases, paving the way for targeted therapeutic strategies.