- Q What are the advantages of using FFPE samples for single-cell transcriptome analysis?A
FFPE samples offer several advantages for single-cell transcriptome analysis:
1. Convenient Handling and Storage: FFPE samples can be stored at room temperature or 4℃ for extended periods. This simplifies logistics and storage conditions compared to fresh and frozen samples, which often require more stringent and costly storage solutions.
2. Facilitation of Retrospective Studies: FFPE samples are relatively easier to access in biorepositories compared to fresh samples. They often come with well-documented pathological characteristics and associated clinical outcomes, providing valuable insights without the extensive preprocessing required for fresh samples. This can also significantly shorten the sample collection process for clinical studies.
3. Minimizing Batch Effects: The ease of storing FFPE samples allows for simultaneous processing of multiple batches. This largely reduces batch effects compared to fresh samples, which must be processed immediately, thereby minimizing variability and improving data consistency.
4. Simplified Sample Preparation: FFPE samples offer an efficient way to handle tissues that are difficult to dissociate, such as brain, liver, and pancreatic tissues. The fixation and embedding process maintains tissue integrity and cellular characteristics, simplifying sample preparation for analysis.
- Q Does the deparaffinization, rehydration, and dissociation process of FFPE samples affect the transcriptional state of the cells?A
No, these experimental steps do not affect the transcriptional state of cells in FFPE samples as the cells have already undergone fixation during the preservation process.
- Q What quality control measures are necessary for FFPE samples before initiating the VITA single-cell experiment?A
It is advisable to utilize FFPE samples within 3 years of storage as significant RNA degradation may occur over extended storage periods. We recommend performing DV200 quality control to evaluate RNA degradation levels prior to experiments.
DV200 > 40%: Qualified
DV200 ≤ 40%: Risky
DV200 ≤ 30%: Not recommended to proceed - Q What is the recommended thickness for FFPE slides in VITA single-cell experiments??A
The required thickness depends on the tissue type. For most tissues, a slice thickness of 20 µm is recommended. Immune organs (e.g., spleen and lymph nodes) require a slice thickness of 10 µm, while muscle fibers (e.g., heart or skin) require a slice thickness of 50 µm.
- Q How is ribosomal RNA handled when performing single-cell transcriptome sequencing with random primers?A
In single-nuclei transcriptome profiling with random primers, excess ribosomal RNA (rRNA) is typically not a concern since the majority of rRNA is located in the cytoplasm rather than in the nuclei. During nuclei extraction, the cytoplasmic content, including rRNA, is removed, eliminating the need for rRNA depletion. However, in whole-cell profiling, where the entire cell content is analyzed, rRNA depletion is necessary.
- Q Is fixation required for fresh cells in the VITA single-cell experimental procedure?A
Yes, fixation is a standard prerequisite in the M20 Seq protocol to preserve the transcriptional state of the cell, ensuring accurate in situ reverse transcription.
- Q Are there significant differences in the single-cell transcriptome results between fresh and FFPE samples?A
Based on our extensive data, there is no significant difference between the results derived from fresh and FFPE samples. Acomparative analysis, published in on of our articles [1] demonstrated a robust correlation exceeding 90% between the single-cell RNA profiles of fresh and FFPE samples from the same mouse kidney specimens.
[1] Xu, Z., Zhang, T., Chen, H. et al. High-throughput single nucleus total RNA sequencing of formalin-fixed paraffin-embedded tissues by snRandom-seq. Nat Commun 14, 2734 (2023). https://doi.org/10.1038/s41467-023-38409-5
- Q What is the recommended cell count to capture and sequencing depth?A
For optimal cost-effectiveness, we typically recommend capturing 5,000 to 10,000 cells per sample with a sequencing depth of 300-450 million reads. However, the VITA platform can capture up to 20,000 cells per sample, allowing the flexibility to adjust cell counts based on specific experimental objectives and needs.
