Table 1 Summary of important scRNA-seq technologies and platforms
From: Advances in single-cell RNA sequencing and its applications in cancer research
Technology | Year | Single-cell isolation | Gene coverage | Library amplification | Throughput | Advantages | Disadvantages | References |
|---|---|---|---|---|---|---|---|---|
10x- Genomics | 2017 | Droplet | 3′ or 5′ | PCR | Very high (> 10,000) | High throughput; identifies cells well; ease of use; high cell flux; short library construction cycle; ultra-high capture efficiency | Many steps for DNA library construction; high sample requirements; specialized experimental equipment; non full-length information | [35] |
CEL-seq | 2012 | Micromanipulation | 3′ | In vitro transcription | Low (1–200) | High specificity and accuracy; first method to use IVT for the amplification | Low efficiency; reduced sensitivity for low expression transcripts | [31] |
CEL-seq2 | 2016 | FACS | 3′ | In vitro transcription | Low (1–200) | High sensitivity; low cost; low hands-on input | Strong 3′ preference; high-abundance transcripts are preferentially amplified | [32] |
Cyto-seq | 2015 | Microwell platform | 3′ | PCR | High (1000–10000) | Direct analysis of complex samples | Expensive and time-consuming | [233] |
Drop-seq | 2015 | Droplet | 3′ | PCR | High (1000–10000) | High throughput; low cost; fast amplification; equipment is easily obtained | Low mRNA capture efficiency and low sensitivity | [33] |
FLASH-seq | 2022 | FACS | Full length | PCR | High (1000–10000) | Increased sensitivity and reduced hands-on time compared to Smart-seq3 | High manual technical requirements | [62] |
inDrop | 2015 | Droplet | 3′ | In vitro transcription | High (1000–10000) | High throughput; low cost; strong cell capture capabilities; simplified process | Extremely low cell capture efficiency | [34] |
MARS-seq | 2014 | FACS | 3′ | In vitro transcription | Median | Reduced amplification bias and labeling errors; high reproducibility | High manual technical requirement | [41] |
MARS-seq2 | 2019 | FACS | 3′ | In vitro transcription | High (1000–10000) | Greatly reduced background noise compared with MARS-seq; minimizes sampling bias and simplifies steps | High manual technical requirement | [44] |
MATQ-seq | 2017 | Micromanipulation | Full length | PCR | Low (100–200) | High sensitivity and accuracy; high transcript capture rate | Inefficient cell lysis | |
Microwell-seq | 2018 | FACS | 3′ | PCR | High (1000–10000) | High throughput; low cost; high sequencing quality | Presence of 3′ bias; FACS requires skilled operators | [52] |
Microwell-seq2 | 2020 | FACS | 3′ | PCR | High (1000–10000) | Higher utilization of micropores and higher throughput than Microwell-seq; high sensitivity and stability | Presence of 3′ bias; FACS requires skilled operators | [53] |
Quartz-seq | 2013 | FACS | Full length | PCR | Low (1–200) | High sensitivity and high reproducibility | High manual technical requirements | [26] |
Quartz-seq2 | 2018 | Droplet | Full length | PCR | High (1000–10000) | High sensitivity; high reproducibility; high accuracy | High manual technical requirements | [36] |
SCAN-seq | 2020 | Dilution | Full length | PCR | Low (1–200) | High sensitivity and accuracy | Low throughput; high cost; high error rate of Nanopore sequencing, | [65] |
SCAN-seq2 | 2023 | FACS | Full length | PCR | High (1000–10000) | High throughput and sensitivity; much cheaper than SCAN-seq | Relatively more expensive and lower throughput compared with drop-based scRNA-seq | [66] |
sci-Plex | 2019 | In situ barcoding | 3′ | PCR | Very high (> 10,000) | Massively multiplex platform; cost-effective; high throughput for drug screening; high resolution | Low UMIs per cell; low cell recovery rate, | |
Sci-RNA-seq | 2017 | In situ barcoding | 3′ | PCR | Very high (> 10,000) | Minimized perturbation of RNA integrity | Some cell types cannot be defined | [54] |
Sci-RNA-seq3 | 2019 | In situ barcoding | 3′ | PCR | Very high (> 10,000) | Higher throughput; lower cost; nuclei are extracted directly from fresh tissues without enzymatic treatment | Tn5 transposome loaded with specific oligos is not commercially available; reduced gene detection rate compared with 10 × Genomics | |
Seq-Well | 2017 | Microwell platform | 3′ | PCR | High (1000–10000) | Easy-to-use; portable; low-cost; efficient cell lysis and transcriptome capture | Low cell capture efficiency | [48] |
Seq-Well S3 | 2020 | Microwell platform | 3′ | PCR | Very high (> 10,000) | High-throughput; high-fidelity | Short cDNA; presence of 3 'bias | [50] |
SMART-seq | 2012 | FACS | Full length | PCR | Low (1–200) | Full-length coverage | Low efficiency; limited throughput and read coverage | [27] |
SMART-seq2 | 2013 | FACS | Full length | PCR | Median (100–1000) | Higher sensitivity and higher transcription coverage; cell capture visualization; low amplification bias; low variability and low noise; analysis of rare cell populations | No early multiplexing; low reproducibility; extremely high manual technical requirements | [28] |
SMART-seq3 | 2020 | FACS | Full length | PCR | Median (100–1000) | Much more sensitive and higher throughput than SMART-seq2; provides cost-effective RNA analysis at isoform resolution | No early multiplexing; extremely high manual technical requirements | [59] |
Smart-seq3xpress | 2022 | FACS | Full length | PCR | High (1000–10000) | Shortens and streamlines the Smart-seq3 protocol to substantially reduce reagent use and increase cellular throughput | No early multiplexing; extremely high manual technical requirements | [60] |
SPLit-seq | 2018 | In situ barcoding | 3′ | PCR | Very high (> 10,000) | Low cost and minimal equipment requirements; no need for cell isolation; suitable for fixed cells and fixed nuclei | Not enough genes | [55] |
STRT-seq | 2011 | FACS | 5′ | PCR | Median (100–1000) | Multiplexable; can be used to study many different single cells at a time; reduced cross-contamination | PCR biases; nonlinear PCR amplification | [37] |
VASA-seq | 2022 | Plate-based formats and droplet microfluidics | Full length | PCR | High (1000–10000) | The only single-cell sequencing technology that combines high sensitivity, full-length transcriptome coverage; with high throughput; cost-effective; compatible with all sample types | Integration with other datasets (which necessitates batch corrections), and creation of specialized data analysis pipelines |