Biology subjects

Kenworthy, M.

Publications and source records attributed to Kenworthy, M..

6 recordsLinked to original sources

bioRxiv2025

Cell-type-specific transposable element demethylation and TAD remodeling in the aging mouse brain

Aging is a major risk factor for neurodegenerative diseases, yet underlying epigenetic mechanisms remain unclear. Here, we generated a comprehensive single-nucleus cell atlas of brain aging across multiple brain regions, comprising 132,551 single-cell methylomes and 72,666 joint chromatin conformation-methylome nuclei. Integration with companion transcriptomic and chromatin accessibility data yielded a cross-modality taxonomy of 36 major cell types. We observed that age-related methylation changes were more pronounced in non-neuronal cells. Transposable element methylation alone distinguished age groups, showing cell-type-specific genome-wide demethylation. Chromatin conformation analysis demonstrated age-related increases in TAD boundary strength with enhanced accessibility at CTCF binding sites. Spatial transcriptomics across 895,296 cells revealed regional heterogeneity during aging within identical cell types. Finally, we developed novel deep-learning models that accurately predict age-related gene expression changes using multi-modal epigenetic features, providing mechanistic insights into gene regulation. This dataset advances our understanding of brain aging and offers potential translational applications. HighlightsO_LISingle-cell multi-omic profiling maps the epigenetic and spatial transcriptomic landscape of brain aging across multiple regions. C_LIO_LICell-type-specific genome-wide demethylation of retrotransposable elements correlates with increased chromatin accessibility and expression. C_LIO_LIElevated TAD boundary strength emerges as a unique marker of brain aging associated with CTCF gaining accessibility. C_LIO_LIA novel deep-learning model reveals the significance of epigenetic features on age-related transcriptomic changes across genes. C_LI

genomics↗

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

Epigenome erosion in Alzheimer's disease brain cells and induced neurons

Late-onset Alzheimers disease (LOAD) is typically sporadic, correlated only to advanced age, and has no clear genetic risk factors. The sporadic nature of LOAD presents a challenge to understanding its pathogenesis and mechanisms. Here, we comprehensively investigated the epigenome of LOAD primary entorhinal cortex brain tissues via single-cell multi-omics technologies, simultaneously capturing DNA methylation and 3D chromatin conformation. We identified AD-specific DNA methylation signatures and found they interact with bivalent promoters of AD differentially expressed genes. In addition, we discovered global chromosomal epigenome erosion of 3D genome structure within and across brain cell types. Furthermore, to evaluate whether these age- and disease-dependent molecular signatures could be detected in the in vitro cellular models, we derived induced neurons (iNs) converted directly from AD patients fibroblasts and found a set of conserved methylation signatures and shared molecular processes. We developed a machine-learning algorithm to identify robust and consistent methylation signatures of LOAD in vivo primary brain tissues and in vitro fibroblast-derived iNs. The results recapitulate the age- and disease-related epigenetic features in iNs and highlight the power of epigenome and chromatin conformation for identifying molecular mechanisms of neuronal aging and generating biomarkers for LOAD. HIGHLIGHTO_LIAD-specific DNA methylation signatures are identified in entorhinal cortex brain cell types C_LIO_LIThe AD differentially expressed genes linked with differentially methylated regions via loop interactions are enriched in a bivalent chromatin state C_LIO_LIChromosomal epigenome erosion of 3D genome structures occurs in LOAD brain cell types. C_LIO_LIShared and reliable methylation signatures are observed in both in vitro cellular iN models and primary brain tissues. C_LIO_LIMachine learning models identify robust and reliable methylation loci as AD biomarkers across cell types. C_LI

genomics↗

bioRxiv2023

Human Immune Cell Epigenomic Signatures in Response to Infectious Diseases and Chemical Exposures

The epigenomic landscape of human immune cells is dynamically shaped by both genetic factors and environmental exposures. However, the relative contributions of these elements are still not fully understood. In this study, we employed single-nucleus methylation sequencing and ATAC-seq to systematically explore how pathogen and chemical exposures, along with genetic variation, influence the immune cell epigenome. We identified distinct exposure-associated differentially methylated regions (eDMRs) corresponding to each exposure, revealing how environmental factors remodel the methylome, alter immune cell states, and affect transcription factor binding. Furthermore, we observed a significant correlation between changes in DNA methylation and chromatin accessibility, underscoring the coordinated response of the epigenome. We also uncovered genotype-associated DMRs (gDMRs), demonstrating that while eDMRs are enriched in regulatory regions, gDMRs are preferentially located in gene body marks, suggesting that exposures and genetic factors exert differential regulatory control. Notably, disease-associated SNPs were frequently colocalized with meQTLs, providing new cell-type-specific insights into the genetic basis of disease. Our findings underscore the intricate interplay between genetic and environmental factors in sculpting the immune cell epigenome, offering a deeper understanding of how immune cell function is regulated in health and disease.

genomics↗

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↗

bioRxiv2022

Epigenomic complexity of the human brain revealed by single-cell DNA methylomes and 3D genome structures

Delineating the gene regulatory programs underlying complex cell types is fundamental for understanding brain functions in health and disease. Here, we comprehensively examine human brain cell epigenomes by probing DNA methylation and chromatin conformation at single-cell resolution in over 500,000 cells from 46 brain regions. We identified 188 cell types and characterized their molecular signatures. Integrative analyses revealed concordant changes in DNA methylation, chromatin accessibility, chromatin organization, and gene expression across cell types, cortical areas, and basal ganglia structures. With these resources, we developed scMCodes that reliably predict brain cell types using their methylation status at select genomic sites. This multimodal epigenomic brain cell atlas provides new insights into the complexity of cell type-specific gene regulation in the adult human brain.

neuroscience↗