Biology subjects

Wang, B.-A.

Publications and source records attributed to Wang, B.-A..

4 recordsLinked to original sources

bioRxiv2023

Cell type-specific effects of age and sex on human cortical neurons

Excitatory and inhibitory neurons establish specialized identities early in life through cell type-specific patterns of epigenetic regulation and gene expression. Although cell types are largely stable throughout the lifespan, altered transcriptional and epigenetic regulation may contribute to cognitive changes with advanced age. Using single-nucleus multiomic DNA methylation and transcriptome sequencing (snmCT-seq) in frontal cortex samples from young adult and aged donors, we found widespread age- and sex-related variability in specific neuronal cell types. The proportion of GABAergic inhibitory cells, including SST and VIP expressing cells, was reduced in aged donors. On the other hand, excitatory neurons had more profound age-related changes in their gene expression and DNA methylation compared with inhibitory cells. Hundreds of genes involved in synaptic activity were downregulated, while genes located in subtelomeric regions were upregulated with age and anti-correlated with telomere length. We further mapped sex differences in autosomal gene expression and escape from X-inactivation in specific neuron types. Multiomic single-nucleus epigenomes and transcriptomes provide new insight into the effects of age and sex on human neurons.

neuroscience↗

bioRxiv2023

Single-cell DNA Methylome and 3D Multi-omic Atlas of the Adult Mouse Brain

Cytosine DNA methylation is essential in brain development and has been implicated in various neurological disorders. A comprehensive understanding of DNA methylation diversity across the entire brain in the context of the brains 3D spatial organization is essential for building a complete molecular atlas of brain cell types and understanding their gene regulatory landscapes. To this end, we employed optimized single-nucleus methylome (snmC-seq3) and multi-omic (snm3C-seq1) sequencing technologies to generate 301,626 methylomes and 176,003 chromatin conformation/methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell type taxonomy that contains 4,673 cell groups and 261 cross-modality-annotated subclasses. We identified millions of differentially methylated regions (DMRs) across the genome, representing potential gene regulation elements. Notably, we observed spatial cytosine methylation patterns on both genes and regulatory elements in cell types within and across brain regions. Brain-wide multiplexed error-robust fluorescence in situ hybridization (MERFISH2) data validated the association of this spatial epigenetic diversity with transcription and allowed the mapping of the DNA methylation and topology information into anatomical structures more precisely than our dissections. Furthermore, multi-scale chromatin conformation diversities occur in important neuronal genes, highly associated with DNA methylation and transcription changes. Brain-wide cell type comparison allowed us to build a regulatory model for each gene, linking transcription factors, DMRs, chromatin contacts, and downstream genes to establish regulatory networks. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a companion whole-brain SMART-seq3 dataset. Our study establishes the first brain-wide, single-cell resolution DNA methylome and 3D multi-omic atlas, providing an unparalleled resource for comprehending the mouse brains cellular-spatial and regulatory genome diversity.

genomics↗

bioRxiv2019

Single nucleus multi-omics links human cortical cell regulatory genome diversity to disease risk variants

Single-cell technologies enable measure of unique cellular signatures, but are typically limited to a single modality. Computational approaches allow integration of diverse single-cell datasets, but their efficacy is difficult to validate in the absence of authentic multi-omic measurements. To comprehensively assess the molecular phenotypes of single cells in tissues, we devised single-nucleus methylCytosine, Chromatin accessibility and Transcriptome sequencing (snmC2T-seq) and applied it to post-mortem human frontal cortex tissue. We developed a computational framework to validate fine-grained cell types using multi-modal information and assessed the effectiveness of computational integration methods. Correlation analysis in individual cells revealed distinct relations between methylation and gene expression. Our integrative approach enabled joint analyses of the methylome, transcriptome, chromatin accessibility and conformation for 63 human cortical cell types. We reconstructed regulatory lineages for cortical cell populations and found specific enrichment of genetic risk for neuropsychiatric traits, enabling prediction of cell types with causal roles in disease.

genomics↗

bioRxiv2018

Multi-omic profiling of transcriptome and DNA methylome in single nuclei with molecular partitioning

Single-cell transcriptomic and epigenomic analyses provide powerful strategies for unbiased determination of cell types in mammalian tissues. Although previous studies have identified cell types using individual molecular signatures, the generation of consensus cell type classification requires the integration of multiple data types. Most existing single-cell techniques can only make one type of molecular measurement. Here we describe single-nucleus methylcytosine and transcriptome sequencing (snmCT-seq), a multi-omic method that requires no physical separation of DNA and RNA molecules. We demonstrated that snmCT-seq profiles generated from single cells or nuclei robustly distinguish human cell types and accurately measures cytosine DNA methylation and gene expression signatures of each cell type.

genomics↗