In the realm of genomics, the advent of single-cell sequencing technology has revolutionized our understanding of biological diversity and complexity at the most fundamental level—the individual cell.
Traditional sequencing methods, which rely on bulk samples, often mask the inherent heterogeneity present within tissues or organisms. Single-cell sequencing, however, transcends this limitation by dissecting the genome, transcriptome, or epigenome of individual cells with unprecedented precision. This groundbreaking approach has opened new avenues for exploring cellular dynamics, unraveling rare cell populations, deciphering intricate cellular hierarchies, and gaining insights into the molecular underpinnings of diseases.
Protocols for single-cell sequencing library preparation present several challenges that can impact the accuracy and quality of downstream sequencing results. Making sure you overcome these is essential for not wasting valuable sample and money on failed sequencing runs.
3 most critical challenges to overcome for ensuring a high-quality sequencing run
Ensuring high cell viability (>70%) and that you have intact RNA is crucial for accurate Single-cell analysis. Dead or damaged cells can introduce biases and affect gene expression profiles. Accurate cell counting methods are needed to avoid overestimation or underestimation of cell numbers.
The Moxi V and Moxi GO II can perform instantaneous viability assessments with their fluorescence capabilities using common stains such as Propidium Iodide (PI).
Doublets, which are two or more cells mistakenly encapsulated as one during droplet based Single-cell library preparation, can lead to incorrect cell counts and distorted expression profiles. Developing effective methods to identify and remove doublets is essential.
Using our gold standard Coulter Principle-based microfluidic technology, you can achieve the most accurate measurements of cell size on the market. You can easily distinguish cell aggregates with our instruments due to the volume of a doublet being double the that of a normal cell.
Contamination from non-cellular material, such as debris, cellular aggregates, or extracellular vesicles, can lead to inaccurate cell counts and introduce additional sources of noise in downstream analysis.
With our systems’ size resolution and gating capabilities, it becomes very easy to detect contamination and know when you need further cleanup steps to eliminate debris.
Some other challenges that you might face
Single-cell analysis aims to capture the heterogeneity within a population of cells. However, this heterogeneity can make it challenging to define consistent criteria for cell selection, which can affect the reliability of cell counting and downstream analysis.
The accuracy of our cell sizing technology allows you to distinguish relevant cell populations with ease, enabling you to ensure the heterogeneity you need is present before starting your sequencing run with no compromises on cell counting accuracy.
Variability in library preparation steps, such as reverse transcription efficiency and cDNA amplification, can introduce technical noise and affect the quantification of gene expression levels. Standardizing protocols is critical to minimize this variability.
While our technology cannot guarantee reproducibility after RNA extraction, we provide the best-in-class reproducibility for cell population selection, counting, and sizing. With the lowest variability range of any cell counter on the market, you can be secure in knowing you will be able to use the exact same number of cells each run and use samples with similar heterogeneous populations of cells from run to run. This can be further augmented by our Moxi GO II, which has the ability to detect fluorescently-tagged sub-populations of cells to ensure the same amount of specific cell populations of interest are being added on different runs. This will enable unprecedented abilities for comparison across samples done during different sequencing runs.
Cells come in various sizes and morphologies, which can impact the efficiency of cell capture in microfluidic devices or droplet-based platforms. Larger cells might be less efficiently encapsulated, leading to biased cell counts.
Because our technology is also microfluidics-based, we provide an excellent first-pass assessment of whether your cells that you want to run are too large for downstream single-cell microfluidic and droplet-based devices.