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一份全面的小鼠肾脏图谱有助于对稀有细胞群体进行表征并发现可靠的标志物。

A comprehensive mouse kidney atlas enables rare cell population characterization and robust marker discovery.

作者信息

Novella-Rausell Claudio, Grudniewska Magda, Peters Dorien J M, Mahfouz Ahmed

机构信息

Department of Human Genetics, Leiden University Medical Centre, 2333 ZA Leiden, the Netherlands.

GenomeScan, 2333 BZ Leiden, the Netherlands.

出版信息

iScience. 2023 May 18;26(6):106877. doi: 10.1016/j.isci.2023.106877. eCollection 2023 Jun 16.

Abstract

The kidney's cellular diversity is on par with its physiological intricacy; yet identifying cell populations and their markers remains challenging. Here, we created a comprehensive atlas of the healthy adult mouse kidney (MKA: Mouse Kidney Atlas) by integrating 140.000 cells and nuclei from 59 publicly available single-cell and single-nuclei RNA-sequencing datasets from eight independent studies. To harmonize annotations across datasets, we built a hierarchical model of the cell populations. Our model allows the incorporation of novel cell populations and the refinement of known profiles as more datasets become available. Using MKA and the learned model of cellular hierarchies, we predicted previously missing cell annotations from several studies. The MKA allowed us to identify reproducible markers across studies for poorly understood cell types and transitional states, which we verified using existing data from micro-dissected samples and spatial transcriptomics.

摘要

肾脏的细胞多样性与其生理复杂性相当;然而,识别细胞群体及其标志物仍然具有挑战性。在这里,我们通过整合来自八项独立研究的59个公开可用的单细胞和单细胞核RNA测序数据集的140000个细胞和细胞核,创建了一个健康成年小鼠肾脏的综合图谱(MKA:小鼠肾脏图谱)。为了协调各数据集之间的注释,我们构建了一个细胞群体的层次模型。随着更多数据集的出现,我们的模型允许纳入新的细胞群体并完善已知的细胞图谱。利用MKA和学到的细胞层次模型,我们预测了几项研究中先前缺失的细胞注释。MKA使我们能够在多项研究中识别出针对了解较少的细胞类型和过渡状态的可重复标志物,我们使用来自显微切割样本和空间转录组学的现有数据对其进行了验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28f5/10238935/6bd8e1d3ade1/fx1.jpg

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