CellTag Indexing: genetic barcode-based sample multiplexing for single-cell genomics

Abstract

High-throughput single-cell 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, which uses predefined genetic barcodes that are heritable, enabling cell populations to be tagged, pooled, and tracked over time in the same experimental replicate. We demonstrate the utility of CellTag Indexing by sequencing transcriptomes using a variety of cell types, including long-term tracking of cell engraftment and differentiation in vivo. Together, this presents CellTag Indexing as a broadly applicable genetic multiplexing tool that is complementary with existing single-cell technologies. Electronic supplementary material The online version of this article (10.1186/s13059-019-1699-y) contains supplementary material, which is available to authorized users.

CellOracle: Dissecting cell identity via network inference and in silico gene perturbation

“…Indeed, we find that addition of Yap1 to the Hnf4a-Foxa1 significantly enhances reprogramming efficiency, where addition of both Fos and Yap1 increase colony formation by almost three-fold, accompanied by significant increases in iEP marker expression ( Figure 7E-F; Figure S8I, P < 0.001, t-test, one-sided). Further supporting a role for Yap1 in the establishment of iEP identity are previous studies demonstrating a role for this pathway in liver regeneration (Pepe-Mooney et al, 2019;Yimlamai et al, 2014) and regeneration of the colonic epithelium (Yui et al, 2018), in line with the known potential of iEPs to functionally engraft the liver and intestine (Guo et al, 2019;Morris et al, 2014;Sekiya and Suzuki, 2011). In summary, CellOracle analysis and in silico prediction, in combination with experimental validation, has revealed several new factors and putative regulatory mechanisms to enhance the efficiency and fidelity of reprogramming.…”

“…Considering that Yap1 plays a central role in liver regeneration (Pepe-Mooney et al, 2019;Yimlamai et al, 2014), these results raise the possibility that iEPs represent a regenerative cell type, explaining their Yap1 activity, self-renewal in vitro, and capacity to functionally engraft liver (Sekiya and Suzuki, 2011), and intestine (Guo et al, 2019;Morris et al, 2014). Altogether, these new mechanistic insights have been enabled by CellOracle analysis, placing it as a powerful tool for the dissection of cell identity, aiding improvements in reprogramming efficiency and fidelity.…”

“…The resulting cells, initially described as hepatocyte-like cells, can functionally engraft the liver (Sekiya and Suzuki, 2011). However, we previously demonstrated that these cells also harbor intestinal identity and can functionally engraft the colon in a mouse model of acute colitis, prompting their re-designation as iEPs (Guo et al, 2019;Morris et al, 2014). Building on these studies, our recent single-cell lineage tracing of this protocol revealed two distinct trajectories arising during MEF to iEP conversion: one to a successfully reprogrammed state, and one to a dead-end state, where cells fail to fully convert to iEPs (Biddy et al, 2018).…”

“…To test this hypothesis, we use CellOracle to perform knockout simulations, followed by experimental knockout validation in an established iEP cell line. Here, we leverage the ability to culture iEPs, long-term, where they retain a range of phenotypes (from fibroblast-like to iEP states; Figure S8F) and functional engraftment potential (Guo et al, 2019;Morris et al, 2014). Simulation of Fos knockout using these long-term cultured iEP GRN configurations predicts the attenuation of iEP identity upon factor knockout ( Figure 7A).…”

No detectable alloreactive transcriptional responses during donor-multiplexed single-cell RNA sequencing of peripheral blood mononuclear cells

“…However, traditional applications of scRNA-seq workflows (e.g., 10x Genomics) require individual samples to be processed in parallel, which translates to prohibitively-high assay costs for populationscale studies requiring large numbers of samples. Several scRNA-seq sample multiplexing technologies have been developed which enable users to circumvent this limitation by processing samples in a pooled format [2][3][4][5][6][7][8] . By avoiding the usual requirement for processing distinct samples individually, these technologies increase scRNA-seq cell and sample throughput while minimizing technical confounders (e.g., doublets and batch effects).…”