Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads

High-throughput single-cell RNA-seq methods assign limited unique molecular identifier (UMI) counts as gene expression values to single cells from shallow sequence reads and detect limited gene counts. We thus developed a high-throughput single-cell RNA-seq method, Quartz-Seq2, to overcome these issues. Our improvements in the reaction steps make it possible to effectively convert initial reads to UMI counts, at a rate of 30–50%, and detect more genes. To demonstrate the power of Quartz-Seq2, we analyzed approximately 10,000 transcriptomes from in vitro embryonic stem cells and an in vivo stromal vascular fraction with a limited number of reads.

[1]  Hongshan Guo,et al.  Single-cell RNA-seq transcriptome analysis of linear and circular RNAs in mouse preimplantation embryos , 2015, Genome Biology.

[2]  H. Wachi Role of Elastic Fibers on Cardiovascular Disease , 2011 .

[3]  I. Nikaido,et al.  Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads , 2017, bioRxiv.

[4]  Aleksandra A. Kolodziejczyk,et al.  Classification of low quality cells from single-cell RNA-seq data , 2016, Genome Biology.

[5]  Hagen U. Tilgner,et al.  Erratum to: Promoter-like epigenetic signatures in exons displaying cell type-specific splicing , 2016, Genome Biology.

[6]  Ludovic Vallier,et al.  The Cell-Cycle State of Stem Cells Determines Cell Fate Propensity , 2014, Cell.

[7]  R. Suuronen,et al.  The Potential of Adipose Stem Cells in Regenerative Medicine , 2011, Stem Cell Reviews and Reports.

[8]  A. Oudenaarden,et al.  Validation of noise models for single-cell transcriptomics , 2014, Nature Methods.

[9]  H. Okano,et al.  Prospective Isolation of Murine and Human Bone Marrow Mesenchymal Stem Cells Based on Surface Markers , 2013, Stem cells international.

[10]  Gwendolyn M. Jang,et al.  Meta- and Orthogonal Integration of Influenza "OMICs" Data Defines a Role for UBR4 in Virus Budding. , 2015, Cell host & microbe.

[11]  Evan Z. Macosko,et al.  Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets , 2015, Cell.

[12]  H. Geiger,et al.  Adipose-Derived Mesenchymal Stromal/Stem Cells: Tissue Localization, Characterization, and Heterogeneity , 2012, Stem cells international.

[13]  Mauro J. Muraro,et al.  A Single-Cell Transcriptome Atlas of the Human Pancreas , 2016, Cell systems.

[14]  A. Butte,et al.  Microfluidic single-cell transcriptional analysis rationally identifies novel surface marker profiles to enhance cell-based therapies , 2016, Nature Communications.

[15]  Christoph Ziegenhain,et al.  powsimR: Power analysis for bulk and single cell RNA-seq experiments , 2017, bioRxiv.

[16]  L. Casteilla,et al.  Mouse adipose tissue stromal cells give rise to skeletal and cardiomyogenic cell sub-populations , 2014, Front. Cell Dev. Biol..

[17]  Alan W. Stitt,et al.  Endothelial Progenitors as Tools to Study Vascular Disease , 2012, Stem cells international.

[18]  Catalin C. Barbacioru,et al.  mRNA-Seq whole-transcriptome analysis of a single cell , 2009, Nature Methods.

[19]  I. Amit,et al.  Massively Parallel Single-Cell RNA-Seq for Marker-Free Decomposition of Tissues into Cell Types , 2014, Science.

[20]  Kazuki Kurimoto,et al.  SC3-seq: a method for highly parallel and quantitative measurement of single-cell gene expression , 2015, Nucleic acids research.

[21]  M. Won,et al.  Multiple paracrine factors secreted by mesenchymal stem cells contribute to angiogenesis. , 2014, Vascular pharmacology.

[22]  T. Hashimshony,et al.  CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification. , 2012, Cell reports.

[23]  Tilo Buschmann,et al.  DNABarcodes: an R package for the systematic construction of DNA sample tags , 2017, Bioinform..

[24]  Brad T. Sherman,et al.  Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists , 2008, Nucleic acids research.

[25]  I. Hellmann,et al.  Comparative Analysis of Single-Cell RNA Sequencing Methods , 2016, bioRxiv.

[26]  F. Wagner GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge , 2015, PloS one.

[27]  Chuzhong Li,et al.  The expression of TGF-β1, Smad3, phospho-Smad3 and Smad7 is correlated with the development and invasion of nonfunctioning pituitary adenomas , 2014, Journal of Translational Medicine.

[28]  R. Sandberg,et al.  Full-Length mRNA-Seq from single cell levels of RNA and individual circulating tumor cells , 2012, Nature Biotechnology.

[29]  S. P. Fodor,et al.  Combinatorial labeling of single cells for gene expression cytometry , 2015, Science.

[30]  L. Steinmetz,et al.  Human haematopoietic stem cell lineage commitment is a continuous process , 2017, Nature Cell Biology.

[31]  Ambrose Carr,et al.  Scalable microfluidics for single-cell RNA printing and sequencing , 2015, Genome Biology.

[32]  M. Madrigal,et al.  A review of therapeutic effects of mesenchymal stem cell secretions and induction of secretory modification by different culture methods , 2014, Journal of Translational Medicine.

[33]  Millie Hughes-Fulford,et al.  The role of FGF-2 and BMP-2 in regulation of gene induction, cell proliferation and mineralization , 2011, Journal of orthopaedic surgery and research.

[34]  Åsa K. Björklund,et al.  Smart-seq2 for sensitive full-length transcriptome profiling in single cells , 2013, Nature Methods.

[35]  S. Linnarsson,et al.  Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq. , 2011, Genome research.

[36]  Geppino Falco,et al.  Zscan4 regulates telomere elongation and genomic stability in ES cells , 2010, Nature.

[37]  Aaron M. Streets,et al.  Microfluidic single-cell whole-transcriptome sequencing , 2014, Proceedings of the National Academy of Sciences.

[38]  Guangchuang Yu,et al.  ReactomePA: an R/Bioconductor package for reactome pathway analysis and visualization. , 2016, Molecular bioSystems.

[39]  Alan Trounson,et al.  Stem Cell Therapies in Clinical Trials: Progress and Challenges. , 2015, Cell stem cell.

[40]  Allon M. Klein,et al.  Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells , 2015, Cell.

[41]  Kazuki Kurimoto,et al.  An improved single-cell cDNA amplification method for efficient high-density oligonucleotide microarray analysis , 2006, Nucleic acids research.

[42]  D. Cacchiarelli,et al.  Characterization of directed differentiation by high-throughput single-cell RNA-Seq , 2014, bioRxiv.

[43]  Brad T. Sherman,et al.  Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.

[44]  A. Camus,et al.  Erratum to “Periostin as a Biomarker of the Amniotic Membrane” , 2013, Stem Cells International.

[45]  H. Ueda,et al.  Erratum to: Quartz-Seq: a highly reproducible and sensitive single-cell RNA sequencing method, reveals non-genetic gene-expression heterogeneity , 2017, Genome Biology.

[46]  N. Neff,et al.  Quantitative assessment of single-cell RNA-sequencing methods , 2013, Nature Methods.

[47]  F. Tang,et al.  MR-seq: measuring a single cell's transcriptome repeatedly by RNA-seq. , 2017, Science bulletin.

[48]  P. Baer Adipose-derived mesenchymal stromal/stem cells: An update on their phenotype in vivo and in vitro. , 2014, World journal of stem cells.

[49]  Valentine Svensson,et al.  Power Analysis of Single Cell RNA-Sequencing Experiments , 2016, Nature Methods.

[50]  Hitoshi Niwa,et al.  Extra-embryonic endoderm cells derived from ES cells induced by GATA Factors acquire the character of XEN cells , 2007, BMC Developmental Biology.

[51]  Monika S. Kowalczyk,et al.  Single-cell RNA-seq reveals changes in cell cycle and differentiation programs upon aging of hematopoietic stem cells , 2015, Genome research.

[52]  Jung Hun Lee,et al.  Current use of autologous adipose tissue-derived stromal vascular fraction cells for orthopedic applications , 2017, Journal of Biomedical Science.

[53]  Shuqiang Li,et al.  CEL-Seq2: sensitive highly-multiplexed single-cell RNA-Seq , 2016, Genome Biology.

[54]  Grace X. Y. Zheng,et al.  Massively parallel digital transcriptional profiling of single cells , 2016, Nature Communications.

[55]  Gioele La Manno,et al.  Quantitative single-cell RNA-seq with unique molecular identifiers , 2013, Nature Methods.

[56]  Xinmin Li,et al.  Awakened by Cellular Stress: Isolation and Characterization of a Novel Population of Pluripotent Stem Cells Derived from Human Adipose Tissue , 2013, PloS one.