Systematic cell-type resolved transcriptomes of 8 tissues in 8 lab and wild-derived mouse strains capture global and local expression variation

Mapping the impact of genomic variation on gene expression provides insight into the molecular basis of complex phenotypic traits and disease predisposition. Mouse models offer a controlled framework to capture genomic diversity across tissues. As part of the IGVF consortium, we profiled the transcriptomes of eight tissues from each founder strain of the Collaborative Cross using single-nucleus RNA sequencing. The resulting "8-cube" dataset contains 5.2 million nuclei across 106 cell types and cell states. Transcriptome variation correlated with genetic divergence, highest in the wild-derived strains. Heart and brain were relatively similar, whereas gonads, adrenal gland, skeletal muscle, kidney, and liver showed greater divergence. Variation often concentrated in specific cell types and states, especially those linked to immune and metabolic traits. The founder 8-cube dataset provides rich transcriptome signatures to help explain strain-specific traits and disease states and serves as a foundation for deeper analysis of these tissues across diverse mouse genotypes.

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Publication Details

Journal
Cell Genomics
Published
2025-12-01
DOI
https://doi.org/10.1016/j.xgen.2025.101108
Citations
1
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.81
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article

Systematic cell-type resolved transcriptomes of 8 tissues in 8 lab and wild-derived mouse strains capture global and local expression variation

Elisabeth Rebboah, Maria G. Carilli, Nikhila Swarna, Diane Trout et al.
1 citations
Cell Genomics
Single-cell and spatial transcriptomics
0.81
article

Systematic cell-type resolved transcriptomes of 8 tissues in 8 lab and wild-derived mouse strains capture global and local expression variation

Elisabeth Rebboah, Maria G. Carilli, Nikhila Swarna, Diane Trout, Ghassan Filimban, Heidi Yahan Liang, Parvin Mahdipoor, Rebekah K. Loving, Shimako Kawauchi, B Wold, Delaney K. Sullivan, Ingileif B. Hallgrímsdóttir, Grant R. MacGregor, Ryan Weber, Haoran Zhang, Romina Mojaverzargar, Erisa Taghizadeh, Negar Mojgani, Elnaz Abdollahzadeh, Fairlie Reese, Negar Fattahi, Margaret Duffield, Brian A. Williams, Ali Mortazavi, Lior Pachter, A. Sina Booeshaghi
article en
1 citations

Abstract

Mapping the impact of genomic variation on gene expression provides insight into the molecular basis of complex phenotypic traits and disease predisposition. Mouse models offer a controlled framework to capture genomic diversity across tissues. As part of the IGVF consortium, we profiled the transcriptomes of eight tissues from each founder strain of the Collaborative Cross using single-nucleus RNA sequencing. The resulting "8-cube" dataset contains 5.2 million nuclei across 106 cell types and cell states. Transcriptome variation correlated with genetic divergence, highest in the wild-derived strains. Heart and brain were relatively similar, whereas gonads, adrenal gland, skeletal muscle, kidney, and liver showed greater divergence. Variation often concentrated in specific cell types and states, especially those linked to immune and metabolic traits. The founder 8-cube dataset provides rich transcriptome signatures to help explain strain-specific traits and disease states and serves as a foundation for deeper analysis of these tissues across diverse mouse genotypes.

Cell Genomics
California Institute of Technology (US), University of California, Los Angeles (US), University of California, Irvine (US), University of California, Berkeley (US)
Openalex Percentile: Top 20%
Single-cell and spatial transcriptomics
0.81
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