Literature DB >> 31603610

Apoptotic Cell Exclusion and Bias-Free Single-Cell Selection Are Important Quality Control Requirements for Successful Single-Cell Sequencing Applications.

Diana Ordoñez-Rueda1, Bianka Baying2, Dinko Pavlinic2, Luca Alessandri3, Yvonne Yeboah1, Jonathan J M Landry2, Raffaele Calogero3, Vladimir Benes2, Malte Paulsen1.   

Abstract

Single-cell sequencing experiments are a new mainstay in biology and have been advancing science especially in the biomedical field. The high pressure to integrate the technology into daily laboratory live requires solid knowledge with respect to potential limitations and precautions to be taken care of before applying it to complex research questions. In the past, we have identified two issues with quality measures neglected by the growing community involving SmartSeq and droplet or micro-well-based scRNASeq methods (1) how to ensure that only single cells are introduced without biasing on light scattering when handling complex cell mixtures and organ preparations or (2) how best to control for (pro-)apoptotic cell contaminations in single-cell sequencing approaches. Sighting of concurrent literature involving single-cell sequencing technologies revealed that these topics are generally neglected or simply approached in silico but not at the bench before generating single-cell data sets. We fear that those important quality aspects are overlooked due to reduced awareness of their importance for guaranteeing the quality of experiments. In this Cytometry rigor issue, we provide experimentally supported guidance on how to circumvent those critical shortcomings in order to promote a better use of the fantastic single-cell sequencing toolbox in biology.
© 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry. © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

Keywords:  10×Genomics; SmartSeq2; apoptosis; cell sorting; in silico analysis; quality controls; single-cell Sequencing

Year:  2019        PMID: 31603610     DOI: 10.1002/cyto.a.23898

Source DB:  PubMed          Journal:  Cytometry A        ISSN: 1552-4922            Impact factor:   4.355


  5 in total

1.  Evidence for Multiple Subpopulations of Herpesvirus-Latently Infected Cells.

Authors:  Justin T Landis; Ryan Tuck; Yue Pan; Carson N Mosso; Anthony B Eason; Razia Moorad; J Stephen Marron; Dirk P Dittmer
Journal:  mBio       Date:  2022-01-04       Impact factor: 7.867

2.  DropletQC: improved identification of empty droplets and damaged cells in single-cell RNA-seq data.

Authors:  Walter Muskovic; Joseph E Powell
Journal:  Genome Biol       Date:  2021-12-02       Impact factor: 13.583

3.  Systematic study of single-cell isolation from musculoskeletal tissues for single-sell sequencing.

Authors:  Manman Gao; Peng Guo; Xizhe Liu; Penghui Zhang; Zhongyuan He; Liru Wen; Shaoyu Liu; Zhiyu Zhou; Weimin Zhu
Journal:  BMC Mol Cell Biol       Date:  2022-07-26

4.  Decoding the transcriptome of calcified atherosclerotic plaque at single-cell resolution.

Authors:  Tom Alsaigh; Doug Evans; David Frankel; Ali Torkamani
Journal:  Commun Biol       Date:  2022-10-12

5.  Double-jeopardy: scRNA-seq doublet/multiplet detection using multi-omic profiling.

Authors:  Bo Sun; Emmanuel Bugarin-Estrada; Lauren Elizabeth Overend; Catherine Elizabeth Walker; Felicia Anna Tucci; Rachael Jennifer Mary Bashford-Rogers
Journal:  Cell Rep Methods       Date:  2021-05-24
  5 in total

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