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

View ORCID ProfileChuner Guo, Wenjun Kong, Kenji Kamimoto, View ORCID ProfileGuillermo C. Rivera-Gonzalez, Xue Yang, Yuhei Kirita, View ORCID ProfileSamantha A Morris
doi: https://doi.org/10.1101/335547
Chuner Guo
1Department of Developmental Biology; Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
2Department of Genetics; Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
3Center of Regenerative Medicine, Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
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Wenjun Kong
1Department of Developmental Biology; Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
2Department of Genetics; Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
3Center of Regenerative Medicine, Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
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Kenji Kamimoto
1Department of Developmental Biology; Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
2Department of Genetics; Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
3Center of Regenerative Medicine, Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
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Guillermo C. Rivera-Gonzalez
1Department of Developmental Biology; Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
2Department of Genetics; Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
3Center of Regenerative Medicine, Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
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Xue Yang
1Department of Developmental Biology; Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
2Department of Genetics; Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
3Center of Regenerative Medicine, Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
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Yuhei Kirita
2Department of Genetics; Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
4Division of Nephrology, Department of Medicine. Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA.
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Samantha A Morris
1Department of Developmental Biology; Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
2Department of Genetics; Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
3Center of Regenerative Medicine, Washington University School of Medicine in St. Louis. 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA
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  • For correspondence: s.morris@wustl.edu
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ABSTRACT

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.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted March 18, 2019.
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CellTag Indexing: genetic barcode-based sample multiplexing for single-cell genomics
Chuner Guo, Wenjun Kong, Kenji Kamimoto, Guillermo C. Rivera-Gonzalez, Xue Yang, Yuhei Kirita, Samantha A Morris
bioRxiv 335547; doi: https://doi.org/10.1101/335547
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CellTag Indexing: genetic barcode-based sample multiplexing for single-cell genomics
Chuner Guo, Wenjun Kong, Kenji Kamimoto, Guillermo C. Rivera-Gonzalez, Xue Yang, Yuhei Kirita, Samantha A Morris
bioRxiv 335547; doi: https://doi.org/10.1101/335547

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