3-Minute Deep Dive: Single-Cell RNA Sequencing Technology and Product Portfolio

Single-cell transcriptome sequencing technology represents an innovative achievement in the field of single-cell sequencing, marking a transition from "population averages" to "single-cell precision" and from "technical limitations" to "full-scenario adaptability." Its development trajectory is closely aligned with the global evolution of single-cell transcriptome sequencing technologies, while achieving targeted breakthroughs around existing technical pain points. This progression can be divided into five core phases: the foundational phase, the phase of prominent pain points, the core breakthrough phase, the refinement and validation phase, and the global expansion phase.

The core objective of this phase was to overcome the limitations of traditional bulk sequencing, establish the feasibility of transcriptome analysis at the single-cell level, and gradually explore high-throughput technical approaches. In 2009, Tang et al. performed the first single-cell RNA sequencing of mouse blastocysts, marking the official emergence of single-cell RNA sequencing (scRNA-seq) technology. Since then, researchers have continuously explored two key challenges: “single-cell isolation” and “amplification of low-input RNA.” This led to the development of early techniques such as Smart-seq, which improved reverse transcription efficiency through template-switching oligonucleotides (TSOs), thereby enabling the initial capture of full-length transcripts.

In 2015, technologies based on microfluidic water-in-oil droplet systems, such as Drop-seq and inDrop, were introduced. These methods integrated single-cell sorting and barcoding into micrometer-scale droplets for the first time, enabling parallel analysis of thousands of cells and marking the establishment of the prototype for high-throughput single-cell sequencing technology. The technological advancements during this period laid the foundation for the emergence of subsequent commercial platforms and clarified the core technical framework of single-cell sequencing—“physical isolation of single cells + barcode labeling + reverse transcription and amplification of RNA + high-throughput sequencing”—thereby providing underlying logical support for the innovations presented in this patent.

In 2016, 10x Genomics launched a single-cell RNA sequencing technology based on a droplet microfluidics platform. Leveraging its advantages of high throughput and low cost per cell, it rapidly became the mainstream technology in the market. This technology enables large-scale gene expression profiling by co-encapsulating individual cells with gel beads bearing barcodes and unique molecular identifiers (UMIs) within oil droplets, thereby promoting the widespread application of single-cell sequencing in fields such as basic medical research and developmental biology.

However, mainstream technologies represented by 10x Genomics have gradually exposed three core pain points, which have become bottlenecks restricting their further development: First, limitations in RNA capture. Reliance on Poly(dT) primers allows for the capture of only the 3’ end fragments of polyadenylated mRNA, failing to detect non-coding RNAs such as miRNA and lncRNA, as well as degraded mRNA fragments, resulting in a detection sensitivity of less than 10%. Second, poor sample compatibility. These technologies impose stringent requirements on cell viability (requiring >80%), making them incompatible with clinical samples that are commonly fixed, frozen, or formalin-fixed and paraffin-embedded (FFPE). Third, lack of species coverage. Since prokaryotic organisms, such as bacteria, lack poly(A) tails in their RNA, existing technologies cannot be applied to single-cell sequencing of prokaryotes. These pain points have prevented the utilization of valuable clinical samples (such as FFPE sample libraries) and research on special species, thereby creating an urgent need for technological innovation.

As clinical and research demands continue to rise, the three major pain points of existing technologies have become increasingly prominent, driving a surge in technological innovation worldwide. The core breakthroughs during this phase are primarily concentrated in three directions:

1. Breakthrough in Full-Transcript Capture Technology

To overcome the limitation of traditional poly(dT) primers, which can only detect mRNA with poly(A) tails, researchers have developed various poly(A)-independent library preparation strategies, such as random-primed reverse transcription, RNA tailing methods, and optimized template switching. These technologies have enabled the effective capture of lncRNAs, circRNAs, miRNAs, and degraded RNA fragments for the first time, expanding the detection scope from “coding mRNA” to the “whole transcriptome” and significantly improving the detection sensitivity for low-quality or degraded samples.

2. Mature technologies for compatibility with degraded samples and FFPE samples

To address the vast number of FFPE samples available in clinical settings, technology developers have successfully applied single-cell transcriptome sequencing to FFPE samples for the first time by optimizing RNA extraction, fragment repair, A-tailing, and amplification strategies tolerant to degradation. These advancements overcome the limitation of “requiring fresh or cryopreserved single-cell suspensions,” enabling single-cell sequencing to truly enter clinical pathology biobanks and providing new possibilities for research on tumor heterogeneity and the immune microenvironment.

3. Emergence of Single-Cell Transcriptomics Technology for Prokaryotes

To address challenges such as the absence of poly(A) tails in prokaryotes like bacteria, RNA susceptibility to degradation, and difficulties in cell isolation, researchers have developed single-cell capture and amplification methods specifically tailored for prokaryotes. These methods include targeted rRNA depletion, specialized lysis buffers, and optimized linear amplification protocols, enabling high-throughput analysis of bacterial single-cell transcriptomes for the first time and advancing microbiome research from “bulk sequencing” to “single-cell resolution.”

Technological breakthroughs during this period have enabled single-cell transcriptome sequencing to evolve from a “research tool” into a mature technology that is “clinically applicable and adaptable to multiple scenarios.”

Following breakthroughs in core technologies, the industry has entered a critical phase of performance optimization and clinical validation. Key progress includes:

1. Continuous Improvement in Sensitivity and Throughput

Novel library preparation methods have improved the sensitivity of genetic testing from approximately 10% to 20–30%, with some technologies achieving even higher levels, by optimizing reverse transcription efficiency, reducing amplification bias, and introducing UMI-based algorithmic improvements. Meanwhile, further upgrades to microfluidic platforms have enabled the capture of millions of cells in a single run, providing support for large-scale cell atlas projects.

2. Deep Integration of Multi-Omics and Spatial Technologies

Single-cell transcriptomics is increasingly being integrated with proteomics, epigenomics, metabolomics, and spatial transcriptomics, giving rise to novel technical frameworks known as “single-cell multi-omics” and “spatial single-cell analysis.” For instance, technologies such as CITE-seq and REAP-seq enable simultaneous detection of the transcriptome and proteome. The integration of spatial transcriptomics with single-cell sequencing allows researchers to resolve cellular heterogeneity and spatial architecture within intact tissue sections.

3. Gradual Establishment of Clinical Validation and Standardization Systems

As single-cell sequencing technology for FFPE samples matures, multiple clinical studies have begun to validate its application value in areas such as tumor classification, prediction of immunotherapy efficacy, and detection of minimal residual disease. Meanwhile, industry organizations and research institutions are promoting data quality control standards, standardized experimental protocols, and analytical workflows, laying the foundation for the integration of this technology into clinical diagnostics.

Driven by technological maturity and clinical demand, single-cell transcriptome sequencing has entered a new phase of global competition and industrial layout.

1. Continued Monopoly and Technological Blockade by International Giants

International industry leaders such as 10x Genomics continue to hold the majority of the global market share, leveraging their first-mover advantage and establishing barriers through patents, chip supply, and software ecosystems. Meanwhile, their technologies are continuously iterating, evolving toward higher throughput, greater sensitivity, and multi-omics integration.

2. The Rapid Rise of Domestic Technologies

Chinese enterprises have achieved comprehensive breakthroughs in microfluidic chips, library preparation reagents, sequencers, and analysis software, launching multiple single-cell sequencing platforms with independent intellectual property rights. These platforms are gradually approaching or even surpassing international standards in terms of throughput, cost, and compatibility, establishing differentiated advantages particularly in the analysis of FFPE samples, prokaryotes, and low-input samples.

3. Diversification of Technical Routes and Comprehensive Expansion of Application Scenarios

Various innovative technical approaches have emerged globally, including single-cell capture systems based on strategies such as microwells, microfluidics, droplets, and chips, as well as specialized technologies for specific sample types (e.g., circulating tumor cells, neurons, and embryonic cells). Application scenarios have expanded from basic scientific research to multiple fields, including oncology, immunology, neuroscience, developmental biology, microbiology, and clinical pathology.

4. The industrial ecosystem is gradually improving

The single-cell sequencing industry chain has formed a complete ecosystem, spanning upstream microfluidic chips and library preparation reagents, midstream sequencing services, and downstream data analysis and clinical applications. Meanwhile, emerging fields such as single-cell multi-omics, spatial omics, and AI-assisted cell typing are becoming new growth drivers.

Comparison of Core Technical Routes: