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Researchers have developed a groundbreaking method for performing single cell/nucleus RNA sequencing (sc/snRNA-seq) on formalin-fixed paraffin-embedded (FFPE) tissues. The technique, called snRandom-seq, utilizes droplet-based sequencing technology and random primers to capture full-length total RNAs from FFPE samples. This breakthrough offers a powerful platform for analyzing clinical FFPE specimens, enabling a better understanding of cellular heterogeneity and population dynamics in various diseases. The study was published in a recent issue of Nature.
FFPE tissues are widely used in clinical settings due to their abundant availability and valuable patient data. However, the irreversible modifications caused by formalin fixation make it challenging to extract high-quality RNA for molecular biology applications. Previous methods for transcription profiling in FFPE samples have shown some success, but they were limited in capturing non-polyadenylated RNAs and had lower sensitivity. The snRandom-seq technique overcomes these limitations by effectively capturing a broader range of RNAs and achieving higher RNA coverage compared to existing high-throughput scRNA-seq technologies.
To implement snRandom-seq, the researchers developed a protocol for isolating single intact nuclei from FFPE tissues. This involved deparaffinization, rehydration, and gentle nucleus extraction. The team also implemented a single-strand DNA-blocking step to prevent genome contamination during the sequencing process. By capturing total RNAs using random primers and performing poly(A) tailing on the first strand cDNAs, the researchers achieved efficient and high-quality sequencing results.
The performance of snRandom-seq was validated using a human-mouse mixture sample and demonstrated a minor doublet rate of only 0.3%. The sensitivity of snRandom-seq was comparable to advanced high-throughput scRNA-seq technologies. They further applied snRandom-seq on FFPE mouse tissues, successfully detecting a median of over 3000 genes per nucleus and identifying 25 distinct cell types, including hepatocytes, germ cells, fibroblasts, and cardiomyocytes.
In a significant application of snRandom-seq, the researchers analyzed a clinical FFPE human liver cancer specimen and discovered a subpopulation of nuclei with high proliferative activity. This finding could have implications for cancer research and potentially lead to the identification of novel therapeutic targets.
The development of snRandom-seq represents a major advancement in the field of single-cell/nucleus RNA sequencing, particularly for FFPE tissues. This new technique overcomes previous limitations and provides a powerful platform for analyzing clinical specimens. The ability to perform high-throughput, high-sensitivity, and high-coverage snRNA-seq on FFPE tissues has vast implications for biomedical research and clinical practice. It opens up possibilities for identifying predictive biomarkers, characterizing rare cell types, and improving precision diagnostics, treatment, and prognosis of human diseases.
As researchers continue to explore the potential of snRandom-seq, it is expected to accelerate discoveries in the field of cellular biology and contribute to advancements in personalized medicine.
Read the official publication here.
FFPE tissues are widely used in clinical settings due to their abundant availability and valuable patient data. However, the irreversible modifications caused by formalin fixation make it challenging to extract high-quality RNA for molecular biology applications. Previous methods for transcription profiling in FFPE samples have shown some success, but they were limited in capturing non-polyadenylated RNAs and had lower sensitivity. The snRandom-seq technique overcomes these limitations by effectively capturing a broader range of RNAs and achieving higher RNA coverage compared to existing high-throughput scRNA-seq technologies.
To implement snRandom-seq, the researchers developed a protocol for isolating single intact nuclei from FFPE tissues. This involved deparaffinization, rehydration, and gentle nucleus extraction. The team also implemented a single-strand DNA-blocking step to prevent genome contamination during the sequencing process. By capturing total RNAs using random primers and performing poly(A) tailing on the first strand cDNAs, the researchers achieved efficient and high-quality sequencing results.
The performance of snRandom-seq was validated using a human-mouse mixture sample and demonstrated a minor doublet rate of only 0.3%. The sensitivity of snRandom-seq was comparable to advanced high-throughput scRNA-seq technologies. They further applied snRandom-seq on FFPE mouse tissues, successfully detecting a median of over 3000 genes per nucleus and identifying 25 distinct cell types, including hepatocytes, germ cells, fibroblasts, and cardiomyocytes.
In a significant application of snRandom-seq, the researchers analyzed a clinical FFPE human liver cancer specimen and discovered a subpopulation of nuclei with high proliferative activity. This finding could have implications for cancer research and potentially lead to the identification of novel therapeutic targets.
The development of snRandom-seq represents a major advancement in the field of single-cell/nucleus RNA sequencing, particularly for FFPE tissues. This new technique overcomes previous limitations and provides a powerful platform for analyzing clinical specimens. The ability to perform high-throughput, high-sensitivity, and high-coverage snRNA-seq on FFPE tissues has vast implications for biomedical research and clinical practice. It opens up possibilities for identifying predictive biomarkers, characterizing rare cell types, and improving precision diagnostics, treatment, and prognosis of human diseases.
As researchers continue to explore the potential of snRandom-seq, it is expected to accelerate discoveries in the field of cellular biology and contribute to advancements in personalized medicine.
Read the official publication here.