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.
Project description:A growing body of single-cell multi-omic tools enables a better understanding of gene regulation underlying development and disease. Tools mapping chromatin and gene expression (such as SHARE-seq) are limited in sensitivity and scalability. Here, we describe SHARE-seqV2 and its associated cloud-computing resource, enabling single-cell analysis at improved quality, robustness, and scale. We apply SHARE-seqV2 across various cell lines, primary tissues, and immune cells, demonstrating a generalizable platform for single-cell multi-omics.
