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NEW APPROACH FOR SINGLE-CELL PROFILING

Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding
 
Alexander B. Rosenberg,1*† Charles M. Roco,2* Richard A. Muscat,1 Anna Kuchina,1 Paul Sample,1 Zizhen Yao,3 Lucas T. Graybuck,3 David J. Peeler,2 Sumit Mukherjee,1 Wei Chen,4 Suzie H. Pun,2 Drew L. Sellers,2,5 Bosiljka Tasic,3 Georg Seelig1,4,6†
 
1Department of Electrical Engineering, University of Washington,Seattle, WA, USA. 2Department of Bioengineering, University of Washington, Seattle, WA, USA. 3Allen Institute for Brain Science, Seattle, WA, USA. 4Molecular Engineering and Sciences Institute, University of Washington, Seattle, WA, USA. 5Institute for Stem Cell and Regenerative Medicine, Seattle, WA, USA. 6Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA.
*These authors contributed equally to this work.
 
 
To facilitate scalable profiling of single cells, we developed split-pool ligation-based transcriptome sequencing (SPLiT-seq), a single-cell RNA-seq (scRNA-seq) method that labels the cellular origin of RNA through combinatorial barcoding. SPLiT-seq is compatible with fixed cells or nuclei, allows efficient sample multiplexing, and requires no customized equipment. We used SPLiT-seq to analyze 156,049 single-nucleus transcriptomes from postnatal day 2 and 11 mouse brains and spinal cords. More than 100 cell types were identified, with gene expression patterns corresponding to cellularfunction, regional specificity, and stage of differentiation. Pseudotime analysis revealed transcriptional programs driving four developmental lineages, providing a snapshot ofearly postnatal development in the murine central nervous system. SPLiT-seq providesa path toward comprehensive single-cell transcriptomic analysis of other similarly complex multicellular systems.
 
The new approach split-pool ligation-based transcriptome sequencing (SPLiT-seq) is a low-cost, scRNA-seq method that enables transcriptional profiling of hundreds of thousands of fixed cells or nuclei in a single experiment. SPLiT-seq does not require partitioning single cells into individual compartments (droplets, microwells, or wells) but relies on the cells themselves as compartments. The entire workflow before sequencing consists just of pipetting steps, and no complex instruments are needed.
 
In SPLiT-seq, individual transcriptomes are uniquely labeled by passing a suspension of formaldehyde-fixed cells or nuclei through four rounds of combinatorial barcoding. In the first round of barcoding, cells are distributed into a 96-well plate, and cDNA is generated with an in-cell reverse transcription (RT) reaction using well-specific barcoded primers. Each well can contain a different biological sample, thereby enabling multiplexing of up to 96 samples in a single experiment. After this step, cells from all wells are pooled and redistributed into a new 96-well plate, where an in-cell ligation reaction appends a second well-specific barcode to the cDNA. The third-round barcode, which also contains a unique molecular identifier (UMI), is then appended with another round of pooling, splitting, and ligation. After three rounds of barcoding, the cells are pooled and split into sublibraries, and sequencing barcodes are introduced by polymerase chain reaction (PCR). This final step provides a fourth barcode, while also making it possible to sequence different numbers of cells in each sublibrary. After sequencing, each transcriptome is assembled by combining reads containing the same four-barcode combination.
 
 

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