Single-cell RNA sequencing (scRNA-seq) has transformed how researchers study cellular heterogeneity in complex tissues. However, the quality of a single-cell experiment depends heavily on sample preparation and cell isolation, particularly when working with heterogeneous tissues or rare cell populations. In this guide, we review how cell sorting methods such as fluorescence-activated cell sorting (FACS) can improve data quality in single-cell RNA sequencing workflows.
What is Single-Cell RNA Sequencing (scRNA-seq)?
Single-cell sequencing is a method used to analyze the molecular information of individual cells, such as RNA, DNA, and protein expression. By isolating each cell into droplets or wells of a plate, scientists can use next-generation sequencing techniques to link this molecular data to specific cells. This is done by attaching molecular barcodes to each transcript (in single-cell RNA sequencing, or scRNA-seq), which identify the transcript as a unique molecule and show where it came from. Before this approach, scientists depended on bulk measurements by extracting and analyzing DNA or RNA from a group of cells. This gave an overall profile of DNA or RNA across many cells but masked differences between individual cells. The smoothie-versus-fruit-salad analogy is often used to help visualize this. If you drink a smoothie made of bananas, apples, and blueberries, you might recognize each flavor but not know how much of each fruit contributes to the taste. This is similar to bulk sequencing. On the other hand, eating a fruit salad, where each fruit is clearly distinguishable, is similar to single-cell sequencing.
Figure 1. Comparison of bulk RNA sequencing vs. single-cell RNA sequencing (scRNA-seq)
The most common method for scRNA-seq is droplet-based, where cells are encapsulated in an oil droplet that also contains a gel bead. The gel bead, in turn, carries many oligonucleotides used to barcode RNA transcripts.
To obtain the clearest data, we need to keep as much of the desired signal (RNA transcripts) inside the cell and minimize what escapes outside. In other words, the cells should be healthy, happy, and intact. Any damage to the cell membrane will cause RNA to leak into the suspension. This leaked RNA can be considered ambient RNA contamination—often referred to as “noise”. This is a common challenge in droplet-based single-cell RNA sequencing workflows. We want to detect cell-associated RNA (signal) and distinguish it from the RNA in the environment (noise). Similar to flow cytometry, our goal is to maximize the signal-to-noise ratio.
Cell Isolation for scRNA-seq
To perform a scRNA-seq experiment, the first step is to obtain your cell sample. If the sample is a piece of tissue from an organ, it should be dissociated into a cell suspension using the same steps as for flow cytometry analysis. Dissociation methods can include enzymatic digestion, mechanical lysis, or nuclear extraction.
Best Practices for Preparing Cells for Single-Cell Sequencing
Here are some recommendations for preparing cells for single-cell sequencing.
- Minimize cell handling and dissociation time. Gentle handling is crucial to reduce cell stress, which can change transcriptional profiles.
- Use wide-bore pipette tips to reduce pressure.
- Keep cells at a low temperature whenever possible.
- Include RNase inhibitors, BSA, and EDTA in cell suspension buffers, at amounts recommended by each scRNA-seq kit manufacturer. RNA degradation is a major contributor to poor data.
- It is good practice to follow each manufacturer’s recommended protocol and buffer recipes, which may vary between manufacturers. Reagents that are compatible with one scRNA kit might not work with another. When in doubt, consult the technical support team.
Once a single-cell suspension has been generated, cells can be isolated using several single-cell sequencing capture methods, including:
- Fluorescence-activated cell sorting (FACS)
- Magnetic-activated cell sorting (MACS)
- Droplet microfluidics (i.e. 10x Genomics Chromium)
- Micro- or nanowell capture systems (i.e. BD Rhapsody, Takara iCELL)
- Combinatorial indexing (i.e. Parse Biosciences)
- Vortex-generated droplets (i.e. Illumina PIPseq)
Cell sorting is the most frequently used method to enhance the quality of single-cell experiments. It can enrich for specific cell populations, eliminate dead cells or debris, and connect protein expression with transcriptomics. Additionally, it is often used to deposit individual cells into wells of a plate, as seen in Smart-seq protocols.
Droplet-based systems typically do not require sorting cells before capture. However, when the cells of interest are rare or the samples are highly heterogeneous, enrichment of populations of interest will help improve sequencing efficiency and reduce “wasted” reads.
Sometimes, obtaining high-quality, viable cells from a tissue sample is not possible. For example, tissues that have been frozen or those from the brain or liver typically require nuclei isolation. This can be done by sorting samples stained with a DNA dye such as DAPI or AO/PI. Alternatively, cells can be fixed using paraformaldehyde or DSP-methanol fixation. While this method preserves cells, not all single-cell platforms are compatible with fixed samples. Moreover, not all flow cytometry antibodies work with every fixative, so it is important to check compatibility for both the single-cell assay and the sorting strategy.
Best Practices for Sorting Cells Upstream of Single-Cell Sequencing
Careful optimization and thorough planning are crucial for the success of your experiment. In addition to following the best practices for cell handling listed above, it is also important to select the appropriate sorting method and adjust the sorter settings for your cell or sample type.
Sorter settings to adjust:
- Bigger is better when it comes to nozzle size, especially for fragile cells.
- Use the lowest sheath pressure and flow rate settings to minimize cell stress.
- Perform drop delay calibration before each sort.
Some cell sorters are better suited for single-cell genomics workflows because of their low pressure and flow rates. These include Miltenyi’s MACSQuant® Tyto® and Sony Biotechnology’s SH800S. Traditional droplet-based sorters enable high-speed, multiparameter gating, allowing users to quickly sort large numbers of cells. However, the cells can be damaged and have lower RNA quality due to sorter-induced cell stress1, 2.
Quality Control for Single-Cell RNA Sequencing Experiments
It is often said that if you put garbage into your scRNA-seq experiments, you will get garbage out. But how can cell health and membrane integrity be measured? There are several quality control checks that can be done prior to cell capture, including:
- Monitor viability during and after sorting by using a live/dead stain.
- Gate on singlets using FSC-A vs FSC-H
- Remove debris
- Check cell size and granularity
- Determine RNA quality by checking the RIN score3
- After sorting, check cells with a microscope and cell dye (i.e. Trypan blue or AO/PI). The cell or nucleus membrane should be intact with no blebbing.
Key Considerations When Planning a Cell Sorting Experiment
How do you determine when to use cell sorting before scRNA-seq? Keep the following in mind when planning your experiment:
- Biological question
- Are you trying to find a new or rare cell type?
- Are you creating a cell atlas?
- Would sorting cells create a biased sample?
- Populations of interest
- What is the frequency of the cell population of interest within the starting material?
- Sample size and complexity
- How many cells are you starting with?
- Are you starting with a tissue sample that will have high amounts of dissociation-associated debris?
- Are there many cell populations within your starting sample?
- Are your cells large, fragile, or have a non-round shape?
- Cells with dendrites or those that are long and spindly may clog microfluidics.
- Fragile cells may not survive high-pressure sorting.
- Downstream scRNA-seq platform
- Plate-based methods require sorting one cell into one well.
- Droplet-based methods will encapsulate individual cells from the cell suspension. For these workflows, sorting is typically used to enrich for a particular population of interest or to clean up debris prior to cell capture.
Ultimately, the choice of whether to sort cells depends on whether it addresses a sample quality problem or a biological question, such as enriching rare cell types or removing debris and dead or dying cells. Before starting the cell capture part of the experiment, it’s helpful to do a small pilot test to compare sorted and unsorted samples or to practice the cell handling and dissociation steps.
Supporting Your Research – Integrating Flow Cytometry with Single-Cell Sequencing
Fluorescence-based cell sorting and phenotyping are often critical steps in single-cell sequencing workflows, especially when enriching rare populations, removing debris or dead cells, or validating markers identified from scRNA-seq data. FluoroFinder helps researchers design optimized flow cytometry panels by identifying compatible antibodies and fluorophores for specific instruments and experimental goals. By simplifying antibody discovery and panel design, FluoroFinder enables scientists to efficiently integrate flow cytometry, FACS sorting, and multiomic approaches such as CITE-seq into their single-cell sequencing workflows while improving data quality and reproducibility.
