Institute of Genetics and Genomics of Geneva
Institute of Genetics and Genomics of Geneva
Santoni F.A.,University of Geneva |
Stamoulis G.,University of Geneva |
Garieri M.,University of Geneva |
Falconnet E.,University of Geneva |
And 4 more authors.
American Journal of Human Genetics | Year: 2017
Genomic imprinting results in parental-specific gene expression. Imprinted genes are involved in the etiology of rare syndromes and have been associated with common diseases such as diabetes and cancer. Standard RNA bulk cell sequencing applied to whole-tissue samples has been used to detect imprinted genes in human and mouse models. However, lowly expressed genes cannot be detected by using RNA bulk approaches. Here, we report an original and robust method that combines single-cell RNA-seq and whole-genome sequencing into an optimized statistical framework to analyze genomic imprinting in specific cell types and in different individuals. Using samples from the probands of 2 family trios and 3 unrelated individuals, 1,084 individual primary fibroblasts were RNA sequenced and more than 700,000 informative heterozygous single-nucleotide variations (SNVs) were genotyped. The allele-specific coverage per gene of each SNV in each single cell was used to fit a beta-binomial distribution to model the likelihood of a gene being expressed from one and the same allele. Genes presenting a significant aggregate allelic ratio (between 0.9 and 1) were retained to identify of the allelic parent of origin. Our approach allowed us to validate the imprinting status of all of the known imprinted genes expressed in fibroblasts and the discovery of nine putative imprinted genes, thereby demonstrating the advantages of single-cell over bulk RNA-seq to identify imprinted genes. The proposed single-cell methodology is a powerful tool for establishing a cell type-specific map of genomic imprinting. © 2017 American Society of Human Genetics.
Villanyi Z.,University of Geneva |
Villanyi Z.,Institute of Genetics and Genomics of Geneva |
Ribaud V.,University of Geneva |
Ribaud V.,Institute of Genetics and Genomics of Geneva |
And 10 more authors.
PLoS Genetics | Year: 2014
Recent studies have suggested that a sub-complex of RNA polymerase II composed of Rpb4 and Rpb7 couples the nuclear and cytoplasmic stages of gene expression by associating with newly made mRNAs in the nucleus, and contributing to their translation and degradation in the cytoplasm. Here we show by yeast two hybrid and co-immunoprecipitation experiments, followed by ribosome fractionation and fluorescent microscopy, that a subunit of the Ccr4-Not complex, Not5, is essential in the nucleus for the cytoplasmic functions of Rpb4. Not5 interacts with Rpb4; it is required for the presence of Rpb4 in polysomes, for interaction of Rpb4 with the translation initiation factor eIF3 and for association of Rpb4 with mRNAs. We find that Rpb7 presence in the cytoplasm and polysomes is much less significant than that of Rpb4, and that it does not depend upon Not5. Hence Not5-dependence unlinks the cytoplasmic functions of Rpb4 and Rpb7. We additionally determine with RNA immunoprecipitation and native gel analysis that Not5 is needed in the cytoplasm for the co-translational assembly of RNA polymerase II. This stems from the importance of Not5 for the association of the R2TP Hsp90 co-chaperone with polysomes translating RPB1 mRNA to protect newly synthesized Rpb1 from aggregation. Hence taken together our results show that Not5 interconnects translation and transcription. © 2014 Villanyi et al.
Borel C.,University of Geneva |
Ferreira P.G.,University of Geneva |
Ferreira P.G.,Institute of Genetics and Genomics of Geneva |
Ferreira P.G.,Swiss Institute of Bioinformatics |
And 19 more authors.
American Journal of Human Genetics | Year: 2015
The study of gene expression in mammalian single cells via genomic technologies now provides the possibility to investigate the patterns of allelic gene expression. We used single-cell RNA sequencing to detect the allele-specific mRNA level in 203 single human primary fibroblasts over 133,633 unique heterozygous single-nucleotide variants (hetSNVs). We observed that at the snapshot of analyses, each cell contained mostly transcripts from one allele from the majority of genes; indeed, 76.4% of the hetSNVs displayed stochastic monoallelic expression in single cells. Remarkably, adjacent hetSNVs exhibited a haplotype-consistent allelic ratio; in contrast, distant sites located in two different genes were independent of the haplotype structure. Moreover, the allele-specific expression in single cells correlated with the abundance of the cellular transcript. We observed that genes expressing both alleles in the majority of the single cells at a given time point were rare and enriched with highly expressed genes. The relative abundance of each allele in a cell was controlled by some regulatory mechanisms given that we observed related single-cell allelic profiles according to genes. Overall, these results have direct implications in cellular phenotypic variability. © 2015 The American Society of Human Genetics.