Hanqing Liu

Bolero predicts cell-state-specific gene regulation from DNA across species by integrating cell-state embeddings and biological variables.

This study shows that maternal immune activation disrupts DNA methylation and transcriptome of cortical excitatory neurons, delaying their maturation and affecting synapse-related genes.

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.

The paper constructs an integrative single-cell epigenomic atlas of the adult mouse brain, mapping chromatin states and gene regulatory programs across 100 cell subclasses.

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

The paper identifies cell type-specific aneuploidy in the adult mouse brain, finding a strong enrichment of chromosome 16 trisomy in non-neuronal cells.

This study identifies cell-type-specific chromatin accessibility and gene expression changes in the hippocampus following novel environment exposure using single-nucleus multiomics and bulk RNA-seq.

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.

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 provides a guide to the BRAIN Initiative Cell Census Network (BICCN) data ecosystem, its tools, and resources for analyzing brain cell types across species.

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 identifies 491,818 candidate cis regulatory elements in adult mouse brain sub-types and links them to target genes and transcriptional regulators involved in various pathways.

The paper generates a multimodal cell census and atlas of the mammalian primary motor cortex, revealing a unified molecular genetic landscape and cross-species taxonomy of cell types.

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 identifies astrocyte synapse-regulating genes in the developing mouse visual cortex and shows their expression is modulated by neuronal activity and calcium signaling.

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.