Anna Bartlett

The paper maps 3D genome organization and DNA methylation across 86,689 single nuclei from 16 human tissues, revealing cell-type-specific variations and discrepancies between methylation and chromatin structure.

This paper creates a multimodal single-cell atlas of the human basal ganglia, revealing epigenomic and 3D genome features across cell types and linking them to disease-associated genetic risk.

The paper presents an integrated single-cell and epigenomic resource for exploring basal ganglia datasets across species, enabling multi-omics and comparative analysis.

This study identifies how genetic and environmental factors shape the human immune cell epigenome through differential methylation and chromatin accessibility changes.

This study presents a single-cell multi-omic atlas of Alzheimer's disease brain regions, revealing region-specific epigenomic changes and altered cell states.

This study examines DNA methylation changes in blood and muscle across different training programs and timepoints, identifying DMRs linked to exercise adaptation, sex, and physiological functions.

The paper maps epigenetic and spatial transcriptomic changes in aging mouse brain using single-cell multi-omic data and develops deep-learning models to predict age-related gene expression changes.

The paper examines age and sex effects on human cortical neurons using multiomic data, finding age-related changes in gene expression and DNA methylation, and sex differences in gene expression and X-inactivation escape.

The paper generates a single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain, identifying methylation patterns and regulatory networks across cell types and brain regions.

This study identifies AD-specific DNA methylation signatures and chromosomal epigenome erosion in LOAD brain cells and shows their conservation in induced neurons.

The paper identifies gene-CRE pairs in mouse brain cells by integrating single-cell transcriptomes and epigenomes, controlling for gene co-expression.

The paper links single-cell epigenomes and projection patterns of 33,034 mouse neurons to identify transcriptomic and epigenomic properties of projection cell types.

The paper analyzes gene regulatory programs in the neocortex of rodents and primates using single-cell multiomics, finding rapid evolution of cell type-specific gene expression and TE-driven cCREs.

The paper identifies 188 cell types in the human brain using single-cell DNA methylation and 3D genome data, and develops a tool to predict cell types based on methylation patterns.

The paper develops a multi-omic single-nucleus sequencing method and framework to analyze regulatory genome diversity in human cortical cells and link it to disease risk variants.

The paper compares cellular diversity in the primary motor cortex across human, marmoset, and mouse using single-nucleus transcriptomics and epigenomics, finding conserved cell types and species-specific adaptations.

The paper creates a comprehensive atlas of mouse primary motor cortex cell types using integrated transcriptomic and epigenomic data from over 600,000 samples.

The paper constructs a DNA methylation atlas of the mouse brain at single-cell resolution, revealing epigenetic diversity and spatial organization of neuronal subtypes.

The paper links epigenomic properties of cortical projection neurons to their anatomical and projection patterns using single-nucleus DNA methylation sequencing in mice.

The paper develops sn-m3C-seq to profile chromatin conformation and DNA methylation in single nuclei, enabling high-resolution cell-type classification and chromatin map reconstruction in mice.

This paper introduces snmCT-seq, a multi-omic method that profiles transcriptome and DNA methylome from single nuclei, enabling accurate cell type classification in human tissues.