Project description:A comprehensive cellular anatomy of normal human kidney is crucial to address the cellular origins of renal disease and renal cancer. Some kidney diseases may be cell type-specific, especially renal tubular cells. To investigate the classification and transcriptomic information of human kidney, we performed a method to obtain single-cell suspension of kidney rapidly, and conducted single-cell RNA sequencing (scRNA-seq). We present scRNA-seq data of 23,366 high quality cells from human kidneys of 3 donors. In this dataset, we show 10 clusters of normal human renal cells. Due to the high quality of single cell transcriptomic information, proximal tubule (PT) cells were classified into 3 subtypes and collecting ducts cells into 2 subtypes. Collectively, our data will provide a reliable reference for the studies of renal cell biology and kidney diseases.
Project description:We developed an optimized, low-cost, split-pool barcoding-based multimodal profiling protocol based upon SHARE-seq (concurrent single-cell ATAC/RNA-seq). With SHARE-seq, we profiled human kidney samples from multiple different anatomical regions. Therefore, we develop a large-scale multimodal single-cell atlas for 3D anatomy of the human kidney.