Widespread sex dimorphism across single-cell transcriptomes of adult African turquoise killifish tissues

被引:2
|
作者
Teefy, Bryan B. [1 ]
Lemus, Aaron J. J. [1 ,2 ]
Adler, Ari [1 ]
Xu, Alan [1 ,3 ]
Bhala, Rajyk [1 ]
Hsu, Katelyn [1 ,2 ]
Benayoun, Berenice A. [1 ,2 ,4 ,5 ,6 ]
机构
[1] Univ Southern Calif, Leonard Davis Sch Gerontol, Los Angeles, CA 90089 USA
[2] USC Dornsife Coll Letters Arts & Sci, Mol & Computat Biol Dept, Los Angeles, CA 90089 USA
[3] USC Dornsife Coll Letters Arts & Sci, Quantitat & Computat Biol Dept, Los Angeles, CA 90089 USA
[4] USC Keck Sch Med, Biochem & Mol Med Dept, Los Angeles, CA 90089 USA
[5] USC Norris Comprehens Canc Ctr, Epigenet & Gene Regulat, Los Angeles, CA 90089 USA
[6] USC Stem Cell Initiat, Los Angeles, CA 90089 USA
来源
CELL REPORTS | 2023年 / 42卷 / 10期
关键词
EXPRESSION; EVOLUTION; REVEALS; DIFFERENTIATION; MECHANISMS; HALLMARKS; INSIGHTS; PLATFORM; PACKAGE; GENOME;
D O I
10.1016/j.celrep.2023.113237
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
The African turquoise killifish (Nothobranchius furzeri), the shortest-lived vertebrate that can be bred in captivity, is an emerging model organism for aging research. Here, we describe a multitissue, single-cell gene expression atlas of female and male blood, kidney, liver, and spleen. We annotate 22 cell types, define marker genes, and infer differentiation trajectories. We find pervasive sex-dimorphic gene expression across cell types. Sex-dimorphic genes tend to be linked to lipid metabolism, consistent with clear differences in lipid storage in female vs. male turquoise killifish livers. We use machine learning to predict sex using sin-gle-cell gene expression and identify potential markers for molecular sex identity. As a proof of principle, we show that our atlas can be used to deconvolute existing bulk RNA sequencing (RNA-seq) data to obtain accurate estimates of cell type proportions. This atlas can be a resource to the community that could be leveraged to develop cell-type-specific expression in transgenic animals.
引用
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页数:27
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