A new approach to 3′ single-cell RNA-seq multiplexing — designed to simplify workflows, broaden sample compatibility, and scale biological discovery.
Part 1
Single-cell research is growing. Are our experiments keeping up?
Single-cell research is moving toward increasingly ambitious questions. Understanding disease heterogeneity, identifying rare cell populations, and uncovering treatment responses often requires more than profiling a single sample. Researchers need to compare multiple donors, experimental conditions, and time points — sometimes across hundreds of samples in one study.
But scaling up single-cell experiments is not always straightforward.
We need more flexibility in how we allocate samples and cells within single-cell experiments.
This is where multiplexing opens up new possibilities.
Part 2
Multiplexing: more than just saving costs
At its core, sample multiplexing is a simple concept: assign each sample a unique molecular identity before pooling, process the samples together, and recover their original identities during downstream data analysis.
Instead of treating every sample as an independent experiment, researchers can bring multiple samples into a shared workflow. This reduces variation between experimental runs, makes better use of sequencing resources, and enables researchers to explore more donors, conditions, and biological comparisons within a single experiment.
However, not all multiplexing approaches work in the same way. Their flexibility depends largely on one important design question:
The design question
Where does the sample barcode attach?
Part 3
The barcode makes the difference
Cell-surface antibody-based methods
These methods identify samples through specific surface proteins. While effective in suitable experimental settings, their application can depend on available surface markers, antibody compatibility, and species-specific reagents.
Probe-based approaches
These approaches use predefined target sequences to distinguish samples. Although they can provide targeted identification, their flexibility may be limited by probe design and the selected target panel.
For a more broadly applicable approach, sample identification needs to move beyond dependence on surface epitopes and predefined gene panels.
The question
What if the barcode could be attached directly to the mRNA molecules?
This is the principle behind SeekGene’s SimpliPlex.
Part 4
Introducing SimpliPlex: a new approach to 3′ single-cell multiplexing
SimpliPlex is a 3′ multiplexing scRNA-seq solution that uses sample-specific barcodes to identify individual samples through direct hybridization to poly(A)+ mRNA.
Rather than relying on cell-surface markers or predefined gene-specific probe panels, SimpliPlex takes advantage of the same poly(A) tails that serve as natural capture targets in conventional 3′ single-cell RNA sequencing.
By attaching sample labels to mRNA before pooling, each sample carries its molecular identity into the shared single-cell workflow.
How does it work?
The SimpliPlex workflow consists of five main steps:
1. Methanol fixation
Individual samples undergo methanol fixation, which helps preserve cellular material, permeabilize cell membranes, and stabilize the transcriptome for subsequent processing. Fixed samples can be stored at −80°C; storage stability has currently been validated for up to one month.
2. Sample barcode hybridization
A specially designed oligonucleotide containing a poly(dT) sequence, UMI, sample label (M), and linker is introduced. The poly(dT) region hybridizes to the poly(A) tails of mRNA, enabling sample identification at the molecular level.
3. Sample pooling
Once barcoded, samples can be combined according to the experimental design. Up to eight samples can be pooled into one channel.
4. Droplet-based single-cell processing
The pooled samples enter the droplet-based workflow. Within individual droplets, molecular barcodes are incorporated during ligation and reverse transcription, followed by template-switching extension to generate the complete barcode structure.
5. Library preparation and demultiplexing
After droplet processing, libraries are prepared for sequencing. During data analysis, sample identities are recovered using the M barcode, allowing individual cells to be assigned to their original samples.
The resulting data contain three levels of molecular identification:
M barcode — sample identity
Which original sample does the cell belong to?
Cell barcode (CB) — cell identity
Which individual cell does the molecule originate from?
UMI — molecular identity
Which individual captured transcript does the read represent?
Part 5
Designed for flexibility. Built around the biology.
Direct barcoding of mRNA
Sample identification is based on hybridization to poly(A)+ mRNA rather than cell-surface epitopes, potentially broadening compatibility across sample types and species.
Still the poly(A)-binding principle
The sample barcode is designed to work with poly(A)+ mRNA capture, without requiring a predefined gene-specific probe panel.
A simple and familiar workflow
The sample preparation adds fixation and barcode hybridization, while downstream droplet processing follows the standard workflow.
Whole-cell and nuclei compatibility
Designed to work with both whole cells and isolated nuclei, SimpliPlex offers greater flexibility across sample types and experimental needs.
Part 6
From multiplexing to meaningful single-cell data
A flexible multiplexing strategy is only valuable if it preserves the biological information researchers need.
To evaluate SimpliPlex, internal validation experiments were performed using human peripheral blood mononuclear cells (PBMCs) and mouse spleen samples, including comparisons with corresponding fresh-sample 3′ RNA-seq references.
1. Can the system accurately identify samples?
>99%
valid barcode rate
2. Can the system preserve cellular diversity?
14
immune cell populations retained in PBMC
12
major cell populations retained in mouse spleen
Cell-type marker expression and population composition remain consistent with the fresh reference.
3. What is the data sensitivity?
Sample
SimpliPlex median genes detected
Fresh reference
PBMC
2,215–2,283
2,495
Mouse spleen
1,662–2,198
2,584
Despite a moderate reduction in sensitivity, cell clustering, population composition, and representative marker expression patterns remained highly consistent with the corresponding fresh references.
Together, these results demonstrate the potential of SimpliPlex to balance sample multiplexing, barcode identification, and preservation of meaningful single-cell transcriptomic information.
Part 7
Expanding the questions researchers can ask
From large-scale cohort studies to rare cell discovery, SimpliPlex offers researchers greater flexibility in designing their experiments.
Disease and control
Compare cellular composition and gene expression across patient and healthy cohorts.
Treatment response
Explore how cells respond to different drugs, doses, or therapeutic conditions.
Donor heterogeneity
Investigate inter-individual variation across larger cohorts.
Rare cell populations
Increase the number of cells analyzed to improve the opportunity to capture rare populations.
Part 8
Closing
The future of single-cell research is not only about profiling individual cells in greater detail. It is also about designing experiments that can capture more biological diversity — across samples, conditions, and cellular populations.
SimpliPlex brings a new perspective to single-cell multiplexing — not simply processing more samples, but creating more flexibilities and possibilities for discovery. Researchers are free to scale their experiments in two directions: more samples per run, or more cells per sample.
Simplify the Workflow.
Increase the Throughput.
Expand the Possibilities.
Discover how SimpliPlex can help you scale your next single-cell experiment.
