Enhanced interpretation of immune cell phenotype and function through a rhesus macaque single-cell atlas

Single-cell RNA sequencing (scRNA-seq) allows cell classification using genome-wide transcriptional state; however, high-dimensional transcriptomic profiles, and the unsupervised analyses employed to interpret them, provide a systematically different view of biology than well-established functional/lineage definitions of immunocytes. Understanding these differences and limits is essential for accurate interpretation of these rich data. We present the Rhesus Immune Reference Atlas (RIRA), the first immune-focused macaque single-cell multi-tissue atlas. We contrasted transcriptional profiles against immune lineages, using surface protein and marker genes as ground truth. While the pattern of clustering can align with cell type, this is not always true. Especially within T and natural killer (NK) cells, many functionally distinct subsets lack defining markers, and strong shared expression programs, such as cytotoxicity, result in systematic intermingling by unsupervised clustering. We identified gene programs with high discriminatory/diagnostic value, including multi-gene signatures that model T/NK cell maturation. Directly measuring these diagnostic programs complements unsupervised analyses.

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Publication Details

Journal
Cell Genomics
Published
2025-04-14
DOI
https://doi.org/10.1016/j.xgen.2025.100849
Citations
2
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
1.61
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article

Enhanced interpretation of immune cell phenotype and function through a rhesus macaque single-cell atlas

William Goodwin, Caralyn S. Labriola, Afam A. Okoye, Aaron Barber-Axthelm et al.
2 citations
Cell Genomics
Single-cell and spatial transcriptomics
1.61
article

Enhanced interpretation of immune cell phenotype and function through a rhesus macaque single-cell atlas

William Goodwin, Caralyn S. Labriola, Afam A. Okoye, Aaron Barber-Axthelm, Michael K. Axthelm, S.A. Benjamin, Derick M. Duell, GW McElfresh, Scott G. Hansen, Tyler James Bennett, Candice Nkoy, Andrea N. Selseth, Benjamin N. Bimber, R. Keith Reeves, Gregory J. Boggy, Eisa Mahyari, Louis J. Picker, Jeremy Smedley, Sohita Ojha, Benjamin D. Varco-Merth, Shana Feltham, Maanasa Kaza
article en
2 citations

Abstract

Single-cell RNA sequencing (scRNA-seq) allows cell classification using genome-wide transcriptional state; however, high-dimensional transcriptomic profiles, and the unsupervised analyses employed to interpret them, provide a systematically different view of biology than well-established functional/lineage definitions of immunocytes. Understanding these differences and limits is essential for accurate interpretation of these rich data. We present the Rhesus Immune Reference Atlas (RIRA), the first immune-focused macaque single-cell multi-tissue atlas. We contrasted transcriptional profiles against immune lineages, using surface protein and marker genes as ground truth. While the pattern of clustering can align with cell type, this is not always true. Especially within T and natural killer (NK) cells, many functionally distinct subsets lack defining markers, and strong shared expression programs, such as cytotoxicity, result in systematic intermingling by unsupervised clustering. We identified gene programs with high discriminatory/diagnostic value, including multi-gene signatures that model T/NK cell maturation. Directly measuring these diagnostic programs complements unsupervised analyses.

Cell GenomicsVol. 5(5)
Oregon National Primate Research Center (US), Oregon Health & Science University (US), Duke University (US), Children's Cancer Therapy Development Institute (US)
Zero hunger
Openalex Percentile: Top 18%
Single-cell and spatial transcriptomics
1.61
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