@article{94603,
  keywords = {Seq-Well, acne, alopecia areata, granuloma annulare, leprosy, psoriasis, scRNA-seq, single-cell RNA sequencing, skin inflammation},
  author = {Hughes TK and Wadsworth M and Gierahn T and Do T and Weiss D and Andrade P and Ma F and Silva B and Shao S and Tsoi L and Ordovas-Montanes J and Gudjonsson J and Modlin R and Love CJ and Shalek A},
  title = {Second-Strand Synthesis-Based Massively Parallel scRNA-Seq Reveals Cellular States and Molecular Features of Human Inflammatory Skin Pathologies.},
  abstract = {<p>High-throughput single-cell RNA-sequencing (scRNA-seq) methodologies enable characterization of complex biological samples by increasing the number of cells that can be profiled contemporaneously. Nevertheless, these approaches recover less information per cell than low-throughput strategies. To accurately report the expression of key phenotypic features of cells, scRNA-seq platforms are needed that are both high fidelity and high throughput. To address this need, we created Seq-Well S ("Second-Strand Synthesis"), a massively parallel scRNA-seq protocol that uses a randomly primed second-strand synthesis to recover complementary DNA (cDNA) molecules that were successfully reverse transcribed but to which a second oligonucleotide handle, necessary for subsequent whole transcriptome amplification, was not appended due to inefficient template switching. Seq-Well S increased the efficiency of transcript capture and gene detection compared with that of previous iterations by up to 10- and 5-fold, respectively. We used Seq-Well S to chart the transcriptional landscape of five human inflammatory skin diseases, thus providing a resource for the further study of human skin inflammation.</p>},
  year = {2020},
  journal = {Immunity},
  volume = {53},
  pages = {878-894.e7},
  month = {10/2020},
  issn = {1097-4180},
  url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7562821/},
  doi = {10.1016/j.immuni.2020.09.015},
  language = {eng},
}