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High-throughput single nucleus total RNA sequencing of formalin-fixed paraffin-embedded tissues by snRandom-seq.

Ziye XuTianyu ZhangHongyu ChenYuyi ZhuYuexiao LvShunji ZhangJiaye ChenHaide ChenLili YangWeiqin JiangShengyu NiFangru LuZhaolun WangHao YangLing DongFeng ChenHong ZhangYu ChenJiong LiuDandan ZhangLongjiang FanGuoji GuoYongcheng Wang
Published in: Nature communications (2023)
Formalin-fixed paraffin-embedded (FFPE) tissues constitute a vast and valuable patient material bank for clinical history and follow-up data. It is still challenging to achieve single cell/nucleus RNA (sc/snRNA) profile in FFPE tissues. Here, we develop a droplet-based snRNA sequencing technology (snRandom-seq) for FFPE tissues by capturing full-length total RNAs with random primers. snRandom-seq shows a minor doublet rate (0.3%), a much higher RNA coverage, and detects more non-coding RNAs and nascent RNAs, compared with state-of-art high-throughput scRNA-seq technologies. snRandom-seq detects a median of >3000 genes per nucleus and identifies 25 typical cell types. Moreover, we apply snRandom-seq on a clinical FFPE human liver cancer specimen and reveal an interesting subpopulation of nuclei with high proliferative activity. Our method provides a powerful snRNA-seq platform for clinical FFPE specimens and promises enormous applications in biomedical research.
Keyphrases
  • single cell
  • high throughput
  • rna seq
  • gene expression
  • genome wide
  • endothelial cells
  • healthcare
  • machine learning
  • hiv infected
  • case report
  • artificial intelligence
  • electronic health record
  • pluripotent stem cells