Spatial Single-Cell Mapping of Transcriptional Differences Across Genetic Backgrounds in Mouse Brains

Area of Science:

• Neuroscience
• Genetics
• Bioinformatics

Background:

• Genetic variations impact brain structure and function.
• Comparative analysis of mouse brains requires scalable, high-resolution spatial transcriptomic data.
• Current technologies face challenges in generating atlas-scale, single-cell data with replicates.

Purpose of the Study:

• Introduce Atlas-scale Transcriptome Localization using Aggregate Signatures (ATLAS), a scalable tissue mapping method.
• Enable comparative statistical analysis of mouse brains across genetic backgrounds.
• Facilitate organ-level structure-function analysis of neurological disease models.

Main Methods:

• ATLAS learns transcriptional signatures from single-cell RNA sequencing (scRNAseq) data.
• Transcriptional signatures are encoded in situ using oligonucleotide probes.
• Cell types and transcriptomes are inferred by decoding probe signals.

Main Results:

• ATLAS was validated against MERFISH measurements and four other technologies.
• Over 40 million cells were profiled across 400+ coronal sections from C57BL/6J and BTBR mice.
• Over 40 significant differences in cell type distributions and 16 regional composition changes were identified between sexes and strains.

Conclusions:

• ATLAS provides a scalable solution for generating atlas-scale spatial transcriptomic data.
• The method enables systematic comparative studies of brain structure and function.
• ATLAS facilitates the analysis of genetic variations and disease models in the brain.