10x Genomics is a microfluidics-based method of single-cell RNA sequencing. The technique makes use of the Chromium system, a device that enables single-cell sequencing with their Next GEM technology.
The biology behind 10x Genomics
10x Genomics offers multiple products that can be used on the chromium controller or chromium X, each with their own applications. Currently, we offer Single Cell Gene Expression and Single Cell Immune Profiling.
This how the Next GEM technology in the 10x Chromium works:
- A pool of Gel Beads, coated with barcoded primers, cells and enzymes are loaded on the 10x Genomics microfluidics chip and placed in the chromium controller.
- Within the Chromium controller, barcoded Gel Beads are mixed with cells or nuclei, enzymes, and partitioning oil to form “GEMs” (Gel Bead-in-emulsion), which are single-cell emulsion droplets.
- Within the GEM, a reaction takes place where GEL beads are dissolved and molecules from a single cell are captured and barcoded.
- Barcoded fragments are pooled for downstream reactions to create sequencing libraries.
- After sequencing, reads are mapped back to the corresponding single cell.
Advantages of 10x Genomics
- High-throughput single-cell sequencing
The 10x Genomics systems allows for targeting of thousands of cells per sample. This results in a low cost per cell in the case of high-throughput projects. - Multi-dimensional single-cell data
10x Genomics offers multiple products, of which some can be combined. Combining products allows for obtaining single-cell data with multiple dimensions. - It’s the leading microfluidics platform
The platform has currently been used in more than 1,000 publications, so you are far from alone. Whatever species or tissue you are working on, you are probably not the first to use 10x Genomics.
10x Genomics Information Guide
Download our 10x genomics information guide, to get an overview of Single Cell Discoveries, 10x genomics, how to get started, and more.
Offered solutions
Currently, we offer two solutions of 10x Genomics: Single Cell Gene Expression, Single Cell Gene Expression Flex, and Single Cell Immune Profiling. For all solutions, we are a Certified Service Provider.
Single Cell Gene Expression
The Single Cell Gene Expression solution provides single-cell transcriptomics data. It allows you to measure the 3’ gene expression for 3,000 –10,000 cells per sample. This high-throughput solution has a cost-effective price per cell.
Applications of this solution are, for example:
- Identify different cell types
- Determine the heterogeneity of your sample.
- Compare samples before and after treatment
Sometimes, this solution is not the best one for your project. An alternative platform is SORT-seq, which is highly versatile, adaptable for customization, closely compatible with FACS sorting, works well when you can only retrieve a small population of cells of interest, and is sensitive so can detect low transcript numbers.
Read more about applications of 10x Genomics single cell gene expression in our case study, ‘Immune Profiling of Atherosclerosis Reveals New Therapeutic Potential’.
Single Cell Gene Expression Flex
The Single Cell Gene Expression Flex solution provides single-cell transcriptomics data for formaldehyde-fixed and FFPE tissue. It allows you to measure the 3’ gene expression for up to 1,024,000 fixed single cells over 16 samples in one run. This high-throughput solution has a cost-effective price per cell and is highly compatible with large-scale projects.
Applications of this solution are, for example:
- Identify different cell types in fixed tissue
- Determine the heterogeneity of sensitive samples that require immediate preservation
- Compare samples over a time-course experiment
We have also developed a protocol for sequencing mixed mouse and human probes in fixed PDx samples.
Read more about Gene Expression Flex in our detailed blog, ‘Fixed RNA Profiling of Single Cells: Benefits and Limitations’
Single Cell Immune Profiling
The Single Cell Immune Profiling solution provides you with data on the immune repertoire and gene expression. Just like the Single Cell Gene Expression solution, you can do this for 3,000 – 10,000 cells per sample. The solution allows for analyzing both the T-cell and B-cell receptor.
You can use this solution to:
- Reveal immune cell clonality, diversity, antigen specificity, and cellular context
- Characterize individual T-cells and B-cells
- Identify V(D)J gene sequences
- Pair α and β chain TCR sequences from individual T-cells
- Pair heavy and light chain immunoglobulin sequences from individual B-cells
- Simultaneously measure TCR, B cell Ig, cell surface protein expression, antigen specificity, and 5’ gene expression
Read more about applying 10x Genomics Single Cell Immune Profiling in our case study, ‘Single-Cell Atlas of the Human Cornea’.
Cell recovery: why is it not what I aimed for?
Unfortunately, the number of cells that end up in your data might not be the number you initially aimed for. There are two main factors that influence cell recovery after we load your cells on the microchip: the capture of cells by GEMs and the number of cells loaded.
Cell capture by GEMs
Single cells are partitioned into Gel Beads-in-emulsion (GEMs) inside the
microfluidic chip. In the chip, barcoded gel beads, cells and partitioning oil are combined.
To establish single cell resolution and minimize doublets (two cells in a GEM), a limiting cell dilution is used. By doing this, only 1-10% of GEMs will contain a cell, whereas 90-99% of GEMs will remain empty. Because of this low percentage, it is necessary to overload an accurate number of cells.
Cell loading number
Correct determination of the cell loading number and therefore cell recovery is highly dependent on two factors: cell viability and accurate cell counting.
Non-viable cells may decrease the recovery rate in the Chromium Controller. The accuracy of our cell counts might be affected by cell size, cell concentration, and fractions of cell aggregates. Therefore, the real cell loading number might differ from what we have determined.
Read more in these technical notes by 10x Genomics: