This method was invented and optimized by Michael Hagemann-Jensen, Christoph Ziegenhain, and Rickard Sandberg in 2021: All information and figures in this page are adopted from this publication.

Smart-seq3xpress is a plate-based single-cell RNA-sequencing methods with full-transcript coverage.

Advantages of plate-based single-cell transcriptomics over microfluidics-based 10X genomics sequencing :

  • Single-cell transcriptomics on single cells sorted onto 96-, 384- or 1536-well plates. In research settings in which cell sorting is needed anyways before single-cell transcriptomics, it is a small extra effort to individualize the cells in wells of a well plate.
  • Smart-seq3xpress is suited to untangle and characterize small cell populations for which the number of available cells is less than the number required for 10X genomics single-cell transcriptomics sequencing. The latter method needs a suspension of approximately 10.000 living cells as input.
  • Sorting of the cells of interest into the well-plates can be separate in space and time from the subsequent transcriptomic library preparation as the filled well-plates can be frozen until further processing. In a 10X genomics experiment, the viable cell suspension needs to be processed immediately on the 10X chromium, which is often a logistic problem.
  • The flow sorter obtains immunostaining measurements from each cell. As each sorted cell’s position on the plate is known and gets a known barcode, those measurements can be combined with the cell’s
    transcriptomics data.
  • Apart from gene expression, smart-seq3xpress allows full-length transcript profiling and the reconstruction of T-cell receptor sequences, distinguishing several cell types and states, including unconventional T-cell populations like MAIT, and gamma-delta T-cells.
  • Smart-seq3xpress allows deeper sequencing, providing quantitative data from more genes.
  • Unique Molecular Identifiers (UMIs) are used to account for PCR-bias and it can be tailored which percentage of the reads contain UMIs (quantitative reads) and which percentage are covering the gene body.
Scalable full-transcript coverage scRNA-seq with Smart-seq3xpress. (a) Schematic outline of the Smart-seq3 and Smart-seq3xpress workflows. (b) Smart-seq3xpress is buffered for use with various amounts of pre-amplification PCR cycles. For each dot, the median number of Genes is calculated from the indicated number of raw sequencing reads in at least n>= 8 HEK293FT cells.
Optimization of a nanoliter Smart-seq3 workflow. (a) Schematic of nanoliter cDNA synthesis reactions performed in wells of 384-well PCR plates with 3 μL hydrophobic overlay. (b) Illustration of the volume reduction experiment with the exact lysis, reverse transcription (RT) and PCR volumes used. (c) Reduction of reaction volumes in single HEK293FT cells. Shown are the number of reads detected per cell at each reaction volume when sampling 100,000 sequencing reads (n = 100, 19, 32, 28 cells, respectively). P-value represents a t test between the 10 μL and 1 μL conditions. (d) Reduction of reaction volumes in single K562 cells. Shown are the number of reads detected per cell at each reaction volume when sampling 100,000 sequencing reads (n = 63, 39, 55, 53 cells, respectively). P-value represents a t test between the 10 μL and 1 μL conditions. (e) Replacement of the bead-based cDNA cleanup by dilution in single HEK293FT (n = 58, 52, respectively) and K562 (n = 57, 38, respectively) cells. Shown are the number of reads detected per cell for each condition at 100,000 reads with a p-value for a t-test within cell types.
Smart-seq3xpress analysis of human PBMCs. (a). Dimensional reduction (UMAP) of 16,349 human PBMCs from 4 donors produced with Smart-seq3xpress (KAPA) colored and annotated by cell type. (EM = Effector Memory), (CM = Central Memory), (NK = Natural Killer), (ILC = Innate Lymphoid Cells), (HSPC = Hematopoietic Stem and Progenitor Cell), (MAIT = Mucosal Associated Invariant T-cell). (b) Overlay onto UMAP of presence of detected of T-cell Receptor (TCR) using TRaCeR to reconstruct the TCR info from the sequenced Smart-seq3xpress data. (c) Distribution of cell type abundances as a percentage of all cells from each of the 4 donors. (d) Differential gene expression analysis between Naïve CD4 T-cell cluster (n=2,064) and Clonal CD4 T-cell cluster (n=384). Indicated are the top four TCR genes driving the clonal CD4 T cell cluster separation. (e) Dotplot showing expression of selected marker genes for MAIT, gamma-delta and clonal CD4 T cells in all annotated clusters with size of the dot denoting the detection of a gene within the cells of the cluster and color scale denoting the average expression level.


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