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A single-cell RNA sequencing dataset of cardiac aging in African Turquoise Killifish

Baul Yoon, Yifeng Xu, Ping Zhu, Yuji Zhang, Xiaolei Xu

Scientific Data · 2026

Abstract

Aging is a major contributor to functional decline of the heart and various cardiovascular diseases. Alterations across different cardiac cell types must be tightly orchestrated during the normative aging process that has begun to be mapped at the transcriptional level through single-cell RNA-sequencing. However, current rodent models are limited in their capacity to experimentally test large numbers of candidate differentially expressed genes (DEGs). As an attractive alternative, the African Turquoise Killifish (ATK) promises more efficient genetic studies of cardiac aging because it has the shortest lifespan among vertebrates. Despite its experimental advantages, single-cell transcriptomic studies on cardiac aging in ATK have not yet been conducted. Here, we generated scRNA-seq profiles of hearts from young and old GRZ strain ATK and demonstrated changes in cellular composition, gene expression, functional pathways, and intercellular communication during cardiac aging. This dataset not only recapitulates previously characterized cardiac aging hallmarks but also highlights the contribution of underappreciated cardiovascular cell types, such as epicardium and immune cell types, to cardiac aging.

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Provenance

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OpenAlex
DOI
10.1038/s41597-026-07449-z
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2026-10-13 MST

Cite this

APA
Yoon, B., Xu, Y., Zhu, P., Zhang, Y., &amp; Xu, X. (2026). A single-cell RNA sequencing dataset of cardiac aging in African Turquoise Killifish. <em>Scientific Data</em>. https://doi.org/10.1038/s41597-026-07449-z
Vancouver
Yoon B, Xu Y, Zhu P, Zhang Y, Xu X. A single-cell RNA sequencing dataset of cardiac aging in African Turquoise Killifish. Scientific Data. 2026. doi:10.1038/s41597-026-07449-z.
BibTeX
@article{baul2026Asingl, title = {A single-cell RNA sequencing dataset of cardiac aging in African Turquoise Killifish}, author = {Baul Yoon and Yifeng Xu and Ping Zhu and Yuji Zhang and Xiaolei Xu}, journal = {Scientific Data}, year = {2026}, doi = {10.1038/s41597-026-07449-z}, }

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