Literature DB >> 34059827

Ultra-high-throughput single-cell RNA sequencing and perturbation screening with combinatorial fluidic indexing.

Paul Datlinger1, André F Rendeiro1, Thorina Boenke1, Martin Senekowitsch1, Thomas Krausgruber1, Daniele Barreca1, Christoph Bock2,3.   

Abstract

Cell atlas projects and high-throughput perturbation screens require single-cell sequencing at a scale that is challenging with current technology. To enable cost-effective single-cell sequencing for millions of individual cells, we developed 'single-cell combinatorial fluidic indexing' (scifi). The scifi-RNA-seq assay combines one-step combinatorial preindexing of entire transcriptomes inside permeabilized cells with subsequent single-cell RNA-seq using microfluidics. Preindexing allows us to load several cells per droplet and computationally demultiplex their individual expression profiles. Thereby, scifi-RNA-seq massively increases the throughput of droplet-based single-cell RNA-seq, and provides a straightforward way of multiplexing thousands of samples in a single experiment. Compared with multiround combinatorial indexing, scifi-RNA-seq provides an easy and efficient workflow. Compared to cell hashing methods, which flag and discard droplets containing more than one cell, scifi-RNA-seq resolves and retains individual transcriptomes from overloaded droplets. We benchmarked scifi-RNA-seq on various human and mouse cell lines, validated it for primary human T cells and applied it in a highly multiplexed CRISPR screen with single-cell transcriptome readout of T cell receptor activation.

Entities:  

Year:  2021        PMID: 34059827     DOI: 10.1038/s41592-021-01153-z

Source DB:  PubMed          Journal:  Nat Methods        ISSN: 1548-7091            Impact factor:   28.547


  23 in total

Review 1.  Tumor immunology CRISPR screening: present, past, and future.

Authors:  Matthew B Dong; Kaiyuan Tang; Xiaoyu Zhou; Jingjia J Zhou; Sidi Chen
Journal:  Trends Cancer       Date:  2021-12-15

Review 2.  A new era in functional genomics screens.

Authors:  Laralynne Przybyla; Luke A Gilbert
Journal:  Nat Rev Genet       Date:  2021-09-20       Impact factor: 53.242

Review 3.  Sample-multiplexing approaches for single-cell sequencing.

Authors:  Yulong Zhang; Siwen Xu; Zebin Wen; Jinyu Gao; Shuang Li; Sherman M Weissman; Xinghua Pan
Journal:  Cell Mol Life Sci       Date:  2022-08-05       Impact factor: 9.207

Review 4.  A guide to systems-level immunomics.

Authors:  Lorenzo Bonaguro; Jonas Schulte-Schrepping; Thomas Ulas; Anna C Aschenbrenner; Marc Beyer; Joachim L Schultze
Journal:  Nat Immunol       Date:  2022-09-22       Impact factor: 31.250

5.  Single-cell RNA-sequencing of peripheral blood mononuclear cells reveals widespread, context-specific gene expression regulation upon pathogenic exposure.

Authors:  Roy Oelen; Dylan H de Vries; Harm Brugge; M Grace Gordon; Martijn Vochteloo; Chun J Ye; Harm-Jan Westra; Lude Franke; Monique G P van der Wijst
Journal:  Nat Commun       Date:  2022-06-07       Impact factor: 17.694

Review 6.  Towards a definition of microglia heterogeneity.

Authors:  Luke M Healy; Sameera Zia; Jason R Plemel
Journal:  Commun Biol       Date:  2022-10-20

Review 7.  New horizons in the stormy sea of multimodal single-cell data integration.

Authors:  Christopher A Jackson; Christine Vogel
Journal:  Mol Cell       Date:  2022-01-20       Impact factor: 17.970

8.  Effective and scalable single-cell data alignment with non-linear canonical correlation analysis.

Authors:  Jialu Hu; Mengjie Chen; Xiang Zhou
Journal:  Nucleic Acids Res       Date:  2022-02-28       Impact factor: 16.971

9.  Inflation-collapse dynamics drive patterning and morphogenesis in intestinal organoids.

Authors:  Naren P Tallapragada; Hailey M Cambra; Tomas Wald; Samantha Keough Jalbert; Diana M Abraham; Ophir D Klein; Allon M Klein
Journal:  Cell Stem Cell       Date:  2021-04-28       Impact factor: 25.269

Review 10.  Deciphering transcriptional and functional heterogeneity in hematopoiesis with single-cell genomics.

Authors:  Jorge D Martin-Rufino; Vijay G Sankaran
Journal:  Curr Opin Hematol       Date:  2021-07-01       Impact factor: 3.218

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