Cross-expression meta-analysis of mouse brain slices reveals coordinated gene expression across spatially adjacent cells.

ABSTRACT:

Background

Spatial transcriptomics allow us to ask a fundamental question: how do nearby cells orchestrate their gene expression? Rather than focus on how these cells (samples) communicate with each other, we reframe the problem to investigate how genes (features) coordinate their expression between neighboring cells. To this end, we introduce "cross-expression," which models the degree to which genes coordinate their expression across spatially adjacent cells, avoiding the use of curated databases and cell type labels while controlling for cell-intrinsic processes.

Results

We use multiple atlas-scale adult mouse brain datasets (~25 million cells, 695 slices from 52 brains, 8 technologies) to create an integrated, meta-analytic cross-expression network, whose communities are

SUBMITTER: Sarwar A 

PROVIDER: S-EPMC12570847 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature