scRNA-seq assessment of the human lung, spleen, and esophagus tissue stability after cold preservation

The Human Cell Atlas is a large international collaborative effort to map all cell types of the human body. Single-cell RNA sequencing can generate high-quality data for the delivery of such an atlas. However, delays between fresh sample collection and processing may lead to poor data and difficulties in experimental design. This study assesses the effect of cold storage on fresh healthy spleen, esophagus, and lung from ≥ 5 donors over 72 h. We collect 240,000 high-quality single-cell transcriptomes with detailed cell type annotations and whole genome sequences of donors, enabling future eQTL studies. Our data provide a valuable resource for the study of these 3 organs and will allow cross-organ comparison of cell types. We see little effect of cold ischemic time on cell yield, total number of reads per cell, and other quality control metrics in any of the tissues within the first 24 h. However, we observe a decrease in the proportions of lung T cells at 72 h, higher percentage of mitochondrial reads, and increased contamination by background ambient RNA reads in the 72-h samples in the spleen, which is cell type specific. In conclusion, we present robust protocols for tissue preservation for up to 24 h prior to scRNA-seq analysis. This greatly facilitates the logistics of sample collection for Human Cell Atlas or clinical studies since it increases the time frames for sample processing.

[1]  Heng Li,et al.  A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data , 2011, Bioinform..

[2]  Shuqiang Li,et al.  A practical solution for preserving single cells for RNA sequencing , 2017, Scientific Reports.

[3]  J. C. Love,et al.  Seq-Well: A Portable, Low-Cost Platform for High-Throughput Single-Cell RNA-Seq of Low-Input Samples , 2017 .

[4]  D. Tautz,et al.  Tracing the dynamics of gene transcripts after organismal death , 2017, Open Biology.

[5]  Huanming Yang,et al.  Full-length single-cell RNA-seq applied to a viral human cancer: applications to HPV expression and splicing analysis in HeLa S3 cells , 2015, GigaScience.

[6]  Paul Flicek,et al.  Variant calling on the GRCh38 assembly with the data from phase three of the 1000 Genomes Project. , 2019, Wellcome open research.

[7]  Chao Liu,et al.  Mast cells participate in regulation of lung‐gut axis during Staphylococcus aureus pneumonia , 2019, Cell proliferation.

[8]  Kerstin B. Meyer,et al.  BBKNN: fast batch alignment of single cell transcriptomes , 2019, Bioinform..

[9]  H. Swerdlow,et al.  Single-cell stabilization method identifies gonadotrope transcriptional dynamics and pituitary cell type heterogeneity , 2018, Nucleic acids research.

[10]  Lars Feuk,et al.  The Database of Genomic Variants: a curated collection of structural variation in the human genome , 2013, Nucleic Acids Res..

[11]  Samantha Riesenfeld,et al.  EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data , 2019, Genome Biology.

[12]  I. Amit,et al.  Transcriptional Heterogeneity and Lineage Commitment in Myeloid Progenitors , 2015, Cell.

[13]  I. Amit,et al.  Transcriptional Heterogeneity and Lineage Commitment in Myeloid Progenitors , 2016, Cell.

[14]  I. Amit,et al.  Single-cell transcriptome conservation in cryopreserved cells and tissues , 2016, Genome Biology.

[15]  Jay W. Shin,et al.  The Human Cell Atlas: Technical approaches and challenges , 2017, Briefings in functional genomics.

[16]  Matthew D. Young,et al.  SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data , 2018, bioRxiv.

[17]  Salah Ayoub,et al.  Cell fixation and preservation for droplet-based single-cell transcriptomics , 2017, BMC Biology.

[18]  M. Ryan,et al.  A mitochondrial specific stress response in mammalian cells , 2002, The EMBO journal.

[19]  Stephen R. Quake,et al.  High fidelity hypothermic preservation of primary tissues in organ transplant preservative for single cell transcriptome analysis , 2017, BMC Genomics.

[20]  Y. Gilad,et al.  RNA-seq: impact of RNA degradation on transcript quantification , 2014, BMC Biology.

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

[22]  Heng Li Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM , 2013, 1303.3997.

[23]  Fabian J Theis,et al.  A cellular census of human lungs identifies novel cell states in health and in asthma , 2019, Nature Medicine.

[24]  J. C. Love,et al.  Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput , 2017, Nature Methods.

[25]  Kerstin B. Meyer,et al.  Single-cell reconstruction of the early maternal–fetal interface in humans , 2018, Nature.

[26]  Sarah A Teichmann,et al.  Computational assignment of cell-cycle stage from single-cell transcriptome data. , 2015, Methods.

[27]  Vincent A. Traag,et al.  From Louvain to Leiden: guaranteeing well-connected communities , 2018, Scientific Reports.

[28]  Dmitri D. Pervouchine,et al.  The effects of death and post-mortem cold ischemia on human tissue transcriptomes , 2018, Nature Communications.

[29]  M. Hemberg,et al.  scmap: projection of single-cell RNA-seq data across data sets , 2018, Nature Methods.

[30]  Adele M Doyle,et al.  Fixed single-cell transcriptomic characterization of human radial glial diversity , 2015, Nature Methods.

[31]  J. Kere,et al.  Single-cell transcriptome analysis of endometrial tissue , 2016, Human reproduction.

[32]  Hilde van der Togt,et al.  Publisher's Note , 2003, J. Netw. Comput. Appl..

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

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

[35]  B. Rubinsky Principles of Low Temperature Cell Preservation , 2003, Heart Failure Reviews.

[36]  N. Chiba,et al.  Mast Cells Play an Important Role in Chlamydia pneumoniae Lung Infection by Facilitating Immune Cell Recruitment into the Airway , 2015, The Journal of Immunology.

[37]  Mark Danielsen,et al.  An Introduction to the Analysis of Single-Cell RNA-Sequencing Data , 2018, Molecular therapy. Methods & clinical development.

[38]  K. Shianna,et al.  Using ERDS to infer copy-number variants in high-coverage genomes. , 2012, American journal of human genetics.

[39]  Allon M. Klein,et al.  A single cell atlas of the tracheal epithelium reveals the CFTR-rich pulmonary ionocyte , 2018, Nature.

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

[41]  J H Southard,et al.  Principles of solid-organ preservation by cold storage. , 1988, Transplantation.

[42]  Roland Eils,et al.  The Human Cell Atlas , 2017, bioRxiv.

[43]  S. Potter,et al.  Psychrophilic proteases dramatically reduce single-cell RNA-seq artifacts: a molecular atlas of kidney development , 2017, Development.

[44]  A. van Oudenaarden,et al.  Single-cell sequencing reveals dissociation-induced gene expression in tissue subpopulations , 2017, Nature Methods.

[45]  Hans Clevers,et al.  Single-cell messenger RNA sequencing reveals rare intestinal cell types , 2015, Nature.

[46]  S. Linnarsson,et al.  Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq , 2015, Science.

[47]  Sarah A Teichmann,et al.  Intrinsic transcriptional heterogeneity in B cells controls early class switching to IgE , 2017, The Journal of experimental medicine.

[48]  Fabian J Theis,et al.  SCANPY: large-scale single-cell gene expression data analysis , 2018, Genome Biology.

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

[50]  Ellen T. Gelfand,et al.  The Genotype-Tissue Expression (GTEx) project , 2013, Nature Genetics.