Biological samples are heterogeneous. Upon exposure to a stimulant, different cells in a biological material respond differently. Scientists focus on eliminating much of these complexities but disintegrating the sample and studying cells one at a time. Single-cell profiling is an ideal approach to reveal responses that may go unnoticed in traditional sample analysis. Single-cell profiling may reveal new cells and subtypes and correlate them with biological pathways and expression networks.
Today, real-time qPCR is one of the most powerful techniques to study single-cell gene expression. qPCR services offer different PCR solutions such as ddPCR analysis, qPCR analysis, and much more. Digital PCR services focus on approaches like the ddPCR method to quantify gene expression and copy number variation. The current article focuses on qPCR services for single-cell gene expression profiling. However, similar to ELISA peptide assays, qPCR analysis requires adequate method development and validation approaches.
Single-cell qPCR analysis for gene expression profiling
Cytomics involves analyzing cell systems and using the measured data to identify molecular phenotypes resulting from specific genotypes and environmental exposure. Tissues consist of several cell types. These cells have specialized functions and respond to different stimuli. Studying environmental changes in a specific organ based on traditional assessment with thousands of cells will give data on the cell population present in the sample. However, if only a minority of cell types is influenced, their response may not be detected against the background of other nonresponsive cells.
By disintegrating tissues into individual cells, scientists can sort and profile each of them individually. Besides, analyzing single cells may generate more detailed information about the response. Additionally, homogenous cell mixtures may exhibit highly variable responses to specific stimuli. For example, a single-cell qPCR expression profiling study demonstrated that homogenous cells had highly skewed transcript distribution. A similar pattern is observed in studies involving all kinds of cell transcripts, suggesting a fundamental underlying behavior.
Studying expression dynamics in single cells has revealed its underlying mechanism. Data suggest that expression occurs in bursts with rapid increase in concentration followed by a decay. qPCR analysis is increasingly employed in single-cell gene expression profiles. However, large-scale cell-based studies using a single-cell profiling approach include a small number of biological samples. Hence, single-cell assessment requires highly optimized and validated experimental work, including sample selection and cell collection protocols.
Single-cell expression analysis has been an advantageous tool in biomedical research. Single-cell profiling provides measurements on individual cells that cannot be calculated or deduced from bulk analysis. These features of single-cell profiling assays have the potential to understand newer insights into biology and possibly novel discoveries. Particularly, characterizing cell types and evaluating their proliferation and differentiation is an exciting avenue in biomedical research. Today, defining the exact cell type is challenging. Factors such as external stimuli, hormones, waste products, cell cycle, oxygen, chromosomal rearrangements, and many more affect the molecular activities of a cell. Hence, having robust methods such as qPCR analysis for single-cell gene expression profiles is critical for advancing clinical and biomedical research.
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