Rushil Chakrabarty

This study uses single-nucleus RNA-seq, ATAC-seq, and Multiome to analyze Alzheimer's disease across multiple brain regions, revealing shared and region-specific cellular vulnerabilities.

The paper presents a barcoded multiplex strategy to screen enhancer AAVs using single-cell RNA sequencing and taxonomy mapping, but finds significant technical and biological noise complicates accurate expression pattern analysis.

The paper maps AD-related pathological changes in the caudate nucleus at cellular resolution, identifying distinct features and cell type-specific responses.

The paper creates a cross-species consensus atlas of primate basal ganglia cell types using multiomic data from human, macaque, and marmoset, identifying 61 conserved cell types and a novel hybrid medium spiny neuron type.

The paper analyzes the transcriptomic and spatial organization of GABAergic neurons in the mouse telencephalon, revealing complex developmental and spatial relationships across multiple brain regions.

The paper identifies enhancers for spinal motor neurons and develops AAV vectors to target these cells in rodents and macaques, enabling functional studies and potential therapeutic applications.

The paper presents an enhancer AAV toolbox for targeting and perturbing striatal cell types and circuits in mice, with validated specificity and cross-species applicability.

The paper develops a toolkit of transgenic mouse lines and enhancer AAVs for selective targeting of cortical cell populations using transcriptomic and epigenomic data.

This study creates an integrated multimodal cell atlas of Alzheimer's disease by analyzing single nuclei transcriptomes, epigenomes, and spatial coordinates across AD stages.

The paper constructs a high-resolution transcriptomic and epigenomic atlas of the developing mouse visual cortex, revealing continuous cell type diversification across embryonic and postnatal stages.

This paper creates a high-resolution transcriptomic and spatial cell type atlas of the whole adult mouse brain, revealing spatial organization and transcription factor codes for cell types.

The paper identifies cell-type-specific molecular signatures of aging in a brain-wide transcriptomic atlas of mice, revealing key changes in non-neuronal cells and specific regions like the hypothalamic third ventricle.