Journal ArticleDOI
Single-cell barcoding and sequencing using droplet microfluidics
Rapolas Zilionis,Rapolas Zilionis,Juozas Nainys,Adrian Veres,Virginia Savova,David Zemmour,Allon M. Klein,Linas Mazutis +7 more
TLDR
InDrops is a robust and scalable platform, and it is unique in its ability to capture and profile >75% of cells in even very small samples, on a scale of thousands or tens of thousands of cells.Abstract:
Single-cell RNA sequencing has recently emerged as a powerful tool for mapping cellular heterogeneity in diseased and healthy tissues, yet high-throughput methods are needed for capturing the unbiased diversity of cells. Droplet microfluidics is among the most promising candidates for capturing and processing thousands of individual cells for whole-transcriptome or genomic analysis in a massively parallel manner with minimal reagent use. We recently established a method called inDrops, which has the capability to index >15,000 cells in an hour. A suspension of cells is first encapsulated into nanoliter droplets with hydrogel beads (HBs) bearing barcoding DNA primers. Cells are then lysed and mRNA is barcoded (indexed) by a reverse transcription (RT) reaction. Here we provide details for (i) establishing an inDrops platform (1 d); (ii) performing hydrogel bead synthesis (4 d); (iii) encapsulating and barcoding cells (1 d); and (iv) RNA-seq library preparation (2 d). inDrops is a robust and scalable platform, and it is unique in its ability to capture and profile >75% of cells in even very small samples, on a scale of thousands or tens of thousands of cells.read more
Citations
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Integrating single-cell transcriptomic data across different conditions, technologies, and species.
TL;DR: An analytical strategy for integrating scRNA-seq data sets based on common sources of variation is introduced, enabling the identification of shared populations across data sets and downstream comparative analysis.
Journal ArticleDOI
Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment.
Elham Azizi,Ambrose J. Carr,Ambrose J. Carr,George Plitas,Andrew E. Cornish,Catherine Konopacki,Sandhya Prabhakaran,Juozas Nainys,Juozas Nainys,Kenmin Wu,Vaidotas Kiseliovas,Vaidotas Kiseliovas,Manu Setty,Kristy Choi,Rachel M. Fromme,Phuong Dao,Peter T. McKenney,Peter T. McKenney,Ruby C. Wasti,Krishna Kadaveru,Linas Mazutis,Alexander Y. Rudensky,Dana Pe'er +22 more
TL;DR: A preprocessing pipeline, SEQC, and a Bayesian clustering and normalization method, Biscuit, are developed to address computational challenges inherent to single-cell data and support a model of continuous activation in T cells and do not comport with the macrophage polarization model in cancer.
Journal ArticleDOI
Recovering Gene Interactions from Single-Cell Data Using Data Diffusion.
David van Dijk,Roshan Sharma,Roshan Sharma,Juozas Nainys,Juozas Nainys,Kristina Yim,Pooja Kathail,Pooja Kathail,Ambrose J. Carr,Ambrose J. Carr,Cassandra Burdziak,Kevin R. Moon,Christine L. Chaffer,Diwakar R. Pattabiraman,Brian Bierie,Linas Mazutis,Guy Wolf,Smita Krishnaswamy,Dana Pe'er +18 more
TL;DR: MAGIC as mentioned in this paper is a Markov affinity-based graph imputation of cells that shares information across similar cells, via data diffusion, to denoise the cell count matrix and fill in missing transcripts.
Journal ArticleDOI
Single-Cell Transcriptomics of Human and Mouse Lung Cancers Reveals Conserved Myeloid Populations across Individuals and Species.
Rapolas Zilionis,Rapolas Zilionis,Camilla Engblom,Christina Pfirschke,Virginia Savova,David Zemmour,Hatice D. Saatcioglu,Indira Krishnan,Indira Krishnan,Giorgia Maroni,Giorgia Maroni,Giorgia Maroni,Claire V. Meyerovitz,Clara M. Kerwin,Sun Choi,William G. Richards,Assunta De Rienzo,Daniel G. Tenen,Daniel G. Tenen,Raphael Bueno,Elena Levantini,Elena Levantini,Elena Levantini,Mikael J. Pittet,Allon M. Klein +24 more
TL;DR: The lung TIM landscape is determined and sets the stage for future investigations into the potential of TIMs as immunotherapy targets by using single-cell RNA sequencing to map TIMs in non-small-cell lung cancer patients.
Journal ArticleDOI
A single-cell atlas of the airway epithelium reveals the CFTR-rich pulmonary ionocyte
Lindsey W. Plasschaert,Rapolas Žilionis,Rapolas Žilionis,Rayman Choo-Wing,Virginia Savova,Judith Knehr,Guglielmo Roma,Allon M. Klein,Aron B. Jaffe +8 more
TL;DR: Single-cell RNA sequencing analysis is used to identify cell types in the tracheal epithelium, including previously unidentified ionocytes, which express high levels of the cystic fibrosis transmembrane conductance regulator, CFTR.
References
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Fiji: an open-source platform for biological-image analysis
Johannes Schindelin,Ignacio Arganda-Carreras,Erwin Frise,Verena Kaynig,Mark Longair,Tobias Pietzsch,Stephan Preibisch,Curtis Rueden,Stephan Saalfeld,Benjamin Schmid,Jean-Yves Tinevez,Daniel J. White,Volker Hartenstein,Kevin W. Eliceiri,Pavel Tomancak,Albert Cardona +15 more
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Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets
Evan Z. Macosko,Evan Z. Macosko,Anindita Basu,Anindita Basu,Rahul Satija,Rahul Satija,James Nemesh,James Nemesh,Karthik Shekhar,Melissa Goldman,Melissa Goldman,Itay Tirosh,Allison R. Bialas,Nolan Kamitaki,Nolan Kamitaki,Emily M. Martersteck,John J. Trombetta,David A. Weitz,Joshua R. Sanes,Alex K. Shalek,Alex K. Shalek,Alex K. Shalek,Aviv Regev,Aviv Regev,Aviv Regev,Steven A. McCarroll,Steven A. McCarroll +26 more
TL;DR: Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together.
Journal ArticleDOI
The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells
Cole Trapnell,Davide Cacchiarelli,Davide Cacchiarelli,Jonna Grimsby,Prapti Pokharel,Shuqiang Li,Michael A. Morse,Michael A. Morse,Niall J. Lennon,Kenneth J. Livak,Tarjei S. Mikkelsen,Tarjei S. Mikkelsen,John L. Rinn,John L. Rinn,John L. Rinn +14 more
TL;DR: Monocle is described, an unsupervised algorithm that increases the temporal resolution of transcriptome dynamics using single-cell RNA-Seq data collected at multiple time points that revealed switch-like changes in expression of key regulatory factors, sequential waves of gene regulation, and expression of regulators that were not known to act in differentiation.
Journal ArticleDOI
Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma
Anoop P. Patel,Itay Tirosh,John J. Trombetta,Alex K. Shalek,Shawn M. Gillespie,Hiroaki Wakimoto,Daniel P. Cahill,Brian V. Nahed,William T. Curry,Robert L. Martuza,David N. Louis,Orit Rozenblatt-Rosen,Mario L. Suvà,Mario L. Suvà,Aviv Regev,Aviv Regev,Aviv Regev,Bradley E. Bernstein,Bradley E. Bernstein,Bradley E. Bernstein +19 more
TL;DR: The genome sequence of single cells isolated from brain glioblastomas was examined, which revealed shared chromosomal changes but also extensive transcription variation, including genes related to signaling, which represent potential therapeutic targets.
Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets
Evan Z. Macosko,Evan Z. Macosko,Anindita Basu,Anindita Basu,Rahul Satija,Rahul Satija,James Nemesh,James Nemesh,Karthik Shekhar,Melissa Goldman,Melissa Goldman,Itay Tirosh,Allison R. Bialas,Nolan Kamitaki,Nolan Kamitaki,Emily M. Martersteck,John J. Trombetta,David A. Weitz,Joshua R. Sanes,Alex K. Shalek,Alex K. Shalek,Alex K. Shalek,Aviv Regev,Aviv Regev,Aviv Regev,Steven A. McCarroll,Steven A. McCarroll +26 more
TL;DR: Drop-seq as discussed by the authors analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts' cell of origin, and identifies 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes.
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