TY - JOUR T1 - CellTag Indexing: genetic barcode-based sample multiplexing for single-cell genomics JF - bioRxiv DO - 10.1101/335547 SP - 335547 AU - Chuner Guo AU - Wenjun Kong AU - Kenji Kamimoto AU - Guillermo C. Rivera-Gonzalez AU - Xue Yang AU - Yuhei Kirita AU - Samantha A Morris Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/03/18/335547.abstract N2 - Single-cell technologies have seen rapid advancements in recent years, presenting new analytical challenges and opportunities. These high-throughput assays increasingly require special consideration in experimental design, sample multiplexing, batch effect removal, and data interpretation. Here, we describe a lentiviral barcode-based multiplexing approach, ‘CellTag Indexing’, where we transduce and label samples that can then be pooled together for downstream experimentation and analysis. By introducing predefined genetic barcodes that are transcribed and readily detected, we can reliably read out sample identity and transcriptional state via single-cell profiling. We validate and demonstrate the utility of CellTag Indexing by sequencing transcriptomes at single-cell resolution using a variety of cell types including mouse pre-B cells, primary mouse embryonic fibroblasts, and human HEK293T cells. A unique feature of CellTag Indexing is that the barcodes are heritable. This enables cell populations to be tagged, pooled and tracked over time within the same experimental replicate, then processed together to minimize unwanted biological and technical variation. We demonstrate this feature of CellTagging in long-term tracking of cell engraftment and differentiation, in vivo, in a mouse model of competitive transplant into the large intestine. Together, this presents CellTag Indexing as a broadly applicable genetic multiplexing tool that is complementary with existing single-cell technologies. ER -