Transcriptomes of individual cells. C. Borel, P. G. Ferreira, E. Falconnet, P. Ribaux, S. E. Antonarakis, E. T. Dermitzakis Dept Genetic Medicine, Univ Geneva Medical Sch, Geneva, Switzerland.
We sequenced hundreds of single-cell transcriptomes to decipher significant and stochastic cell-to-cell transcriptional variation. Here, we aim to uncover the extent of cell specific alternative splicing, allele specific gene expression (ASE) and the dynamic of gene expression in the transcriptome of individual cells. Starting from a homogeneous cell population of human female primary fibroblasts from one individual, we used the C1 Single Cell Auto Prep System to capture individual cells and to generate high quality of individual pre-amplified cDNA for next-generation sequencing. Single-cell mRNA-seq librairies were deep sequenced (PE, 100bp) on Illumina HiSeq 2000 sequencer. On average, we obtained 30 millions of reads per single cell, of which more than 60% mapped uniquely to GENCODE annotated exons with GEM aligner. In total, ~ 130,000 transcripts were detected per single cell (RPKM>=0.5), representing ~40% of the total transcripts expressed by the bulk sample containing millions of cells. First, we noted a wide spectrum of transcriptional heterogeneity. Although most of the same transcripts are expressed in all individual cells, we observed a signature of expressed genes that are cell specific. The analysis of their biological function by gene ontology analysis revealed a clustering into different biological processes. Second, we identified cell-specific novel exons, multitude of alternative spliced isoforms and 3UTR isoforms due to alternative polyadenylation. To further assess the differential allelic expression at the single cell level, whole genome sequencing has been performed on this sample. We are currently identifying genome-wide the number of transcripts with detectable SNPs displaying differential ASE. We are expecting that genes with the highest allelic imbalance are located on the X-chromosome. The data also provide a comprehensive survey of X inactivation and escape. Insight gained from this study is the unprecedented understanding of genetic variability and gene expression at single-cell level. Single cell transcriptomic is likely to become an important tool in Genetics, Cell Biology, Development, Immunity and Cancer. S.E.A and E.T.D. laboratories contributed equally.
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