Erik Sundström

This study maps spatial dynamics in early human heart development using single-cell and spatial transcriptomics, identifying cell states and novel features like cardiac fibroblasts and chromaffin cells.

OTTR combines live imaging and spatial transcriptomics to link cell behavior to molecular states in human tissues.

The paper generates a single-cell and spatial transcriptomic atlas of human fetal meninges and finds that meningiomas likely originate from dura lineage cells.

The paper develops TRIC-DISCO, a pipeline for whole-brain 3D RNA imaging in adult mice, enabling single-cell resolution of transcriptional signatures and markers without strict RNase-free conditions.

This study maps the spatial organization of the developing human lung using high-parametric protein imaging, revealing cell type composition and temporal changes across five developmental timepoints.

This study creates a comprehensive cell atlas of the first-trimester human brain using single-cell RNA sequencing and spatial transcriptomics, identifying over 600 distinct cell states and their spatial organization.

The paper constructs a single-cell chromatin accessibility atlas of the human first trimester brain, identifies regulatory elements linked to gene expression, and links disease SNPs to potential pathogenic mechanisms.

The paper creates a developmental cell atlas of the human spinal cord using single-cell and spatial transcriptomics, revealing spatiotemporal gene regulation and novel insights into ependymoma cancer stem cells.

This study identifies an early wave of oligodendrogenesis in the human forebrain at PCW 8 using single-cell RNA-Seq and ATAC-Seq, supported by spatial gene expression analysis.

The paper creates a comprehensive topographic atlas of early human lung development, identifying cell states, trajectories, and interactions to understand cell heterogeneity origins.

The paper introduces a method to align spatial transcriptomics data into a common coordinate framework and demonstrates its application on real and synthetic datasets.

This study maps the single-cell transcriptomic dynamics of hESC-RPE differentiation, identifies an intermediate progenitor, and shows in vivo maturation after transplantation.

SCRINSHOT maps cell states in tissue sections at single-cell resolution, showing high correlation with scRNA-Seq data and enabling detailed spatial analysis of cell types.

Unspliced versus spliced mRNA in standard scRNA-seq gives RNA velocity, a per-cell vector predicting future state over hours, validated in neural crest and used to trace mouse hippocampal lineages.