4.8 Article

Identifying transposable element expression dynamics and heterogeneity during development at the single-cell level with a processing pipeline scTE

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NATURE COMMUNICATIONS
卷 12, 期 1, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41467-021-21808-x

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资金

  1. Guangzhou Branch of the Supercomputing Center of Chinese Academy of Sciences
  2. Center for Computational Science and Engineering of Southern University of Science and Technology
  3. Cloud Computing Center of Chinese Academy of Sciences
  4. National Key R&D Program of China [2019YFA0110200]
  5. Frontier Science Research Program of the CAS [ZDBS-LY-SM007]
  6. Key Research and Development Program of Guangzhou Regenerative Medicine and Health Guangdong Laboratory [2018GZR110104003, 2019GZR110108001]
  7. National Natural Science Foundation of China [31970589, 31801217, 31850410463, 31850410486]
  8. Science and Technology Planning Project of Guangdong Province, China [2020B1212060052]
  9. Science and Technology Program of Guangzhou [201804020052]
  10. Guangdong Science and Technology Commission [2019A050510004]
  11. Shenzhen Peacock plan [201701090668B]

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This study developed a pipeline to quantify TE expression from single cell data, showing dynamic expression of TEs in various biological contexts including embryonic stem cells and somatic cells. The results demonstrate the important role of TEs in cell heterogeneity.
Transposable elements (TEs) make up a majority of a typical eukaryote's genome, and contribute to cell heterogeneity in unclear ways. Single-cell sequencing technologies are powerful tools to explore cells, however analysis is typically gene-centric and TE expression has not been addressed. Here, we develop a single-cell TE processing pipeline, scTE, and report the expression of TEs in single cells in a range of biological contexts. Specific TE types are expressed in subpopulations of embryonic stem cells and are dynamically regulated during pluripotency reprogramming, differentiation, and embryogenesis. Unexpectedly, TEs are expressed in somatic cells, including human disease-specific TEs that are undetectable in bulk analyses. Finally, we apply scTE to single-cell ATAC-seq data, and demonstrate that scTE can discriminate cell type using chromatin accessibly of TEs alone. Overall, our results classify the dynamic patterns of TEs in single cells and their contributions to cell heterogeneity. How transposable elements (TE) contribute to cell fate changes is unclear. Here, the authors generate a pipeline to quantify TE expression from single cell data. They show the dynamic expression of TEs from gastrulation to somatic cell reprogramming and human disease

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