Title | Deep sequencing reveals cell-type-specific patterns of single-cell transcriptome variation. |
Publication Type | Journal Article |
Year of Publication | 2015 |
Authors | Dueck H, Khaladkar M, Kim TKyung, Spaethling JM, Francis C, Suresh S, Fisher SA, Seale P, Beck SG, Bartfai T, Kühn B, Eberwine J, Kim J |
Journal | Genome Biol |
Volume | 16 |
Issue | 1 |
Pagination | 122 |
Date Published | 2015 Jun 09 |
ISSN | 1474-760X |
Keywords | Animals, Cells, Cultured, Gene Expression Profiling, Genetic Variation, High-Throughput Nucleotide Sequencing, Mice, Mice, Inbred C57BL, Rats, Rats, Sprague-Dawley, RNA Stability, Sequence Analysis, RNA, Single-Cell Analysis, Transcriptome |
Abstract | BACKGROUND: Differentiation of metazoan cells requires execution of different gene expression programs but recent single-cell transcriptome profiling has revealed considerable variation within cells of seeming identical phenotype. This brings into question the relationship between transcriptome states and cell phenotypes. Additionally, single-cell transcriptomics presents unique analysis challenges that need to be addressed to answer this question. RESULTS: We present high quality deep read-depth single-cell RNA sequencing for 91 cells from five mouse tissues and 18 cells from two rat tissues, along with 30 control samples of bulk RNA diluted to single-cell levels. We find that transcriptomes differ globally across tissues with regard to the number of genes expressed, the average expression patterns, and within-cell-type variation patterns. We develop methods to filter genes for reliable quantification and to calibrate biological variation. All cell types include genes with high variability in expression, in a tissue-specific manner. We also find evidence that single-cell variability of neuronal genes in mice is correlated with that in rats consistent with the hypothesis that levels of variation may be conserved. CONCLUSIONS: Single-cell RNA-sequencing data provide a unique view of transcriptome function; however, careful analysis is required in order to use single-cell RNA-sequencing measurements for this purpose. Technical variation must be considered in single-cell RNA-sequencing studies of expression variation. For a subset of genes, biological variability within each cell type appears to be regulated in order to perform dynamic functions, rather than solely molecular noise. |
DOI | 10.1186/s13059-015-0683-4 |
Alternate Journal | Genome Biol |
PubMed ID | 26056000 |
PubMed Central ID | PMC4480509 |
Grant List | U01 MH098953 / MH / NIMH NIH HHS / United States K08 HL085143 / HL / NHLBI NIH HHS / United States DP1 OD004117 / OD / NIH HHS / United States 5U01MH098953 / MH / NIMH NIH HHS / United States R01HL106302 / HL / NHLBI NIH HHS / United States 5R01MH088849 / MH / NIMH NIH HHS / United States R01 MH088849 / MH / NIMH NIH HHS / United States R01 HL106302 / HL / NHLBI NIH HHS / United States |