转录组
肾单位
生物
计算生物学
基因表达谱
背景(考古学)
基因表达
基因
细胞生物学
肾
遗传学
古生物学
作者
Arti Raghubar,Duy Pham,Xiao Tan,Laura F. Grice,Joanna Crawford,Pui Yeng Lam,Stacey B. Andersen,Sohye Yoon,Monica Ng,Siok Min Teoh,Samuel Holland,Anne Stewart,Leo Francis,Alexander N. Combes,Andrew J. Kassianos,Helen Healy,Quan Nguyen,Andrew Mallett
标识
DOI:10.1101/2020.09.29.317917
摘要
Abstract Understanding the molecular mechanisms underlying mammalian kidney function requires transcriptome profiling of the interplay between cells comprising nephron segments. Traditional transcriptomics requires cell dissociation, resulting in loss of the spatial context of gene expression within native tissue. To address this problem, we performed spatial transcriptomics (ST) to retain the spatial context of the transcriptome in human and mouse kidneys. The generated ST data allowed spatially resolved differential gene expression analysis, spatial identification of functional nephron segments, cell-to-cell interaction analysis, and chronic kidney disease-associated genetic variant calling. Novel ST thus provides an opportunity to enhance kidney diagnostics and knowledge, by retaining the spatial context of gene expression within intact tissue.
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