Table 2.
Sequencing-Based ST Technologies
| Method | Inventor | Year established | Sample type | Advantages | Limitations | Gene detection efficiency | Targeted/ transcriptome-wide | Spatial resolution | Commercial platform (vendor) | References |
|---|---|---|---|---|---|---|---|---|---|---|
| ROI-selection-based | ||||||||||
| LCM | Emmert-Buck et al. | 1996 | FF/FFPE | Highly suitable for FFPE, whole transcriptome analysis, high spatial resolution | Time-consuming, low throughput | NA | Targeted or transcriptome-wide | Cellular | LCM(Arcturus, PALM, Leica) | 60 |
| Geo-seq | Chen et al. | 2017 | FF | Robust, more sensitive than LCM | Low throughput, difficult to achieve single-cell spatial resolution | NA | transcriptome-wide | Multicellular | NA | 24 |
| GeoMx DSP | NanoString | 2019 | FF/FFPE | Multiplexing, suitable for FFPE samples, capable of combining multi-omics detection | Limited sensitivity | NA | transcriptome-widea | Variable, minimum up to 10 μm | GeoMx DSP (NanoString) | 61 |
| Spatial barcode-based | ||||||||||
| Visium | 10× Genomics | 2019 | FF/FFPE | Unbiased whole transcriptome analysis, adaptable to FFPE tissues | Limited RNA capture efficiency, limited spatial resolution | >6.9% | transcriptome-widea | 55 μm | Visium (10× Genomics) | 13 |
| Slide-Seq | Rodriques et al. | 2019 | FF | Unbiased whole transcriptome analysis, high spatial resolution | Not suitable for highly heterogeneous samples, low capture efficiency, in situ sequencing is time-consuming | 0.3% | transcriptome-wide | 10 μm | NA | 66 |
| DBiT-seq | Liu et al. | 2020 | FF/FFPE | Unbiased whole transcriptome analysis, variable spatial resolution, suitable for FFPE tissues, detection of RNA and proteins in a spatial context | Limited spatial resolution | ~15.5% | transcriptome-wide | Variable (10 μm, 25 μm, 50 μm) | NA | 68 |
| Slide-seqV2 | Stickels et al. | 2021 | FF | Unbiased whole transcriptome analysis, high spatial resolution, improved capture efficiency | Capture efficiency remains low | Approximately 10 times higher than Slide-seq | transcriptome-wide | 10 μm | Curio Seeker (Curio Biosciences) | 67 |
| Stereo-seq | BGI Genomics | 2021 | FF/FFPE | Unbiased whole transcriptome analysis, very high spatial resolution, large detection area | Capture efficiency remains low | Comparable to Visium | transcriptome-wide | 220 nm | STOmics Stereo-seq, Stereo-seq OMNI (BGI Genomics) | 28,38,228 |
| XYZeq | Lee et al. | 2021 | FF | Unbiased whole transcriptome analysis, true single-cell resolution | Limited spatial resolution | NA | transcriptome-wide | 500 μm (spot-to-spot center distance) | NA | 70 |
| sci-Space | Srivatsan et al. | 2021 | FF | Unbiased whole transcriptome analysis, true single-cell resolution | Limited spatial resolution | NA | transcriptome-wide | ~222 μm (spot-to-spot center distance) | NA | 71 |
| xDBiT | Wirth et al. | 2023 | FF/FFPE | Unbiased whole transcriptome analysis, improved gene detection efficiency and throughput compared to DBiT-seq | Limited spatial resolution | Higher than DBiT-seq | transcriptome-wide | 50 μm | NA | 69 |
| Visium HD | 10×Genomics | 2024 | FFPE | Using about 18 000 probes for near-whole transcriptome level analysis, no gaps in capture area | Only compatible with human and mouse FFPE tissues | NA | transcriptome-widea | 2 μm | Visium HD (10× Genomics) | 229 |
aNear-complete transcriptome coverage can only be achieved in human/mouse samples or evolutionarily similar species