Single-Cell miRNA Sequencing Service

Single-Cell miRNA Sequencing is a revolutionary technology used to analyze miRNA expression in individual cells. Unlike traditional bulk cell samples, single-cell miRNA sequencing reveals cellular heterogeneity and provides unique miRNA information for each cell, helping to understand how miRNAs regulate gene expression and influence disease development, progression, and therapeutic response. This technology is widely used in cancer research, immunology, neuroscience, and developmental biology.

 

The analysis process typically involves several key steps: first, single cells are isolated from the sample using microfluidics or single-cell sorting techniques. Small RNA is then extracted from each cell and efficiently processed into libraries. High-throughput sequencing technologies are employed to obtain the miRNA expression data for each individual cell. Finally, bioinformatics methods are used to perform data analysis, quantify miRNA expression profiles, and identify differentially expressed miRNAs across various cell states or disease conditions, linking them to their biological functions.

 



Jovic, D. et al. Clin Transl Med. 2022.

Figure 1. The Workflow of Single-Cell miRNA Sequencing

 

MtoZ Biolabs' single-cell miRNA sequencing service offers high-quality single-cell miRNA sequencing analysis, using state-of-the-art platforms and optimized workflows to ensure accuracy and efficiency. Our Single-Cell miRNA Sequencing Service provides the following core offerings:

Single-cell miRNA analysis: Comprehensive quantitative analysis of miRNA in individual cells, revealing the diversity and variability of miRNA expression.

Cell heterogeneity study: Analysis of miRNA expression differences across different cell types or subpopulations, helping to identify important biomarkers.

Differential expression analysis: Identifying miRNAs that are upregulated or downregulated under different experimental conditions or disease states.

Functional association analysis: Exploring the relationship between miRNAs and their target genes to uncover cellular functions and pathologies.

Bioinformatics support: Advanced data analysis methods to mine miRNA profiles, including miRNA target prediction and pathway analysis.

 

Our service provides a full range of support, from sample preparation to data analysis, offering customized solutions. Whether identifying potential biomarkers in cancer research or exploring immune cell molecular mechanisms in immunology, MtoZ Biolabs provides robust technical support to drive scientific discoveries and clinical translation. Free project evaluation, welcome to learn more details.

 

Service Advantages

1. High-Precision miRNA Expression Profiling  

The single-cell miRNA sequencing service enables miRNA expression analysis at the single-cell level, avoiding the signal loss caused by population averaging in traditional miRNA sequencing methods. This service is particularly suitable for highly heterogeneous biological samples, such as the tumor microenvironment, neural system cells, and immune cell populations, helping researchers accurately identify differences in miRNA expression across individual cells.  

 

2. High Sensitivity for Detecting Low-Abundance miRNAs

MtoZ Biolabs' single-cell miRNA sequencing service leverages high-throughput sequencing technology to detect low-abundance miRNA molecules, revealing key regulatory miRNAs that are expressed at low levels in specific physiological or pathological conditions. This makes the service especially useful for identifying crucial molecular biomarkers in disease progression, driving advancements in personalized medicine research.  

 

3. Comprehensive miRNA Regulatory Network Analysis

The single-cell miRNA sequencing service not only provides miRNA expression profiling at the single-cell level but also integrates bioinformatics analysis to construct miRNA-mRNA regulatory networks and predict potential target genes and signaling pathways. This service offers strong technical support for disease mechanism research, drug screening, and biomarker discovery, facilitating the translation of basic research into clinical applications.

 

Case Study

1. Single-cell microRNA-mRNA co-sequencing reveals non-genetic heterogeneity and mechanisms of microRNA regulation

Single-cell miRNA-mRNA co-sequencing has uncovered non-genetic heterogeneity among cells and elucidated the regulatory mechanisms of miRNAs. The study found that even in genetically identical cells, miRNA expression levels and functions exhibit significant differences, with these non-genetic factors contributing to the complexity of gene regulatory networks. By jointly analyzing miRNA and mRNA expression patterns, the study further revealed how miRNAs regulate gene expression through different pathways, highlighting their role in cellular functional diversity. Single-cell miRNA sequencing service enables the analysis of miRNA expression at the single-cell level, combined with mRNA co-expression analysis, to reveal non-genetic heterogeneity among cells and the regulatory mechanisms of miRNAs.

 



Wang, N. et al. Nat Commun. 2019. 

Figure 2. Profiling of miRNAs from Half-Cell Lysate

 

FAQ

1. What are the challenges in classifying cell types and subtypes with precision in single cell miRNA sequencing?

While single cell miRNA sequencing can reveal miRNA expression differences at the single-cell level, it still faces challenges in classifying cell types and subtypes precisely. First, the heterogeneity between cells means that even cells from the same tissue can exhibit significant differences in miRNA expression, especially in tumors or the immune system. Additionally, single-cell data often contains technical noise and variability, which can affect the accuracy of classification. Similar cells may be misclassified, particularly when handling high-throughput data. Furthermore, the current data analysis methods may not completely eliminate technical biases, such as variations in library construction. Therefore, improving classification accuracy requires finer optimization of algorithms and data processing to remove noise and reduce bias.

 

2. How can the sensitivity of detecting low-abundance miRNAs in single cell miRNA sequencing be improved?

The sensitivity of detecting low-abundance miRNAs in single cell miRNA sequencing can be improved using several strategies. First, optimizing library construction methods, such as using specific primers for low-abundance miRNAs and efficient amplification techniques, can enhance their capture rate. Second, increasing sequencing depth can capture low-abundance miRNAs by providing higher coverage, although this may increase cost and data processing complexity. Lastly, adopting high-sensitivity sequencing platforms, such as single-molecule sequencing technologies, can significantly improve the detection sensitivity for low-abundance miRNAs. By combining these methods, the challenges in detecting low-abundance miRNAs can be effectively addressed, improving the precision of the data.

 

Deliverables

1. Comprehensive Experimental Details

2. Materials, Instruments, and Methods

3. Relevant Liquid Chromatography and Mass Spectrometry Parameters

4. The Detailed Information of Single-Cell miRNA Sequencing

5. Mass Spectrometry Image

6. Raw Data