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Discovery and characterization of variance QTLs in human induced pluripotent stem cells

ABSTRACT: Discovery and characterization of variance QTLs in human induced pluripotent stem cells

PROVIDER: PRJNA486542 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR7708120.fastq.gz	Fastqsanger.gz
	SRR7708130.fastq.gz	Fastqsanger.gz
	SRR7708140.fastq.gz	Fastqsanger.gz
	SRR7708150.fastq.gz	Fastqsanger.gz
	SRR7708160.fastq.gz	Fastqsanger.gz

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Discovery and characterization of variance QTLs in human induced pluripotent stem cells

Project description:Quantification of gene expression levels at the single cell level has revealed that gene expression can vary substantially even across a population of homogeneous cells. However, it is currently unclear what genomic features control variation in gene expression levels, and whether common genetic variants may impact gene expression variation. Here, we take a genome-wide approach to identify expression variance quantitative trait loci (vQTLs). To this end, we generated single cell RNA-seq (scRNA-seq) data from induced pluripotent stem cells (iPSCs) derived from 53 Yoruba individuals. We collected data for a median of 95 cells per individual and a total of 5,447 single cells, and identified 241 mean expression QTLs (eQTLs) at 10% FDR, of which 82% replicate in bulk RNA-seq data from the same individuals. We further identified 14 vQTLs at 10% FDR, but demonstrate that these can also be explained as effects on mean expression. Our study suggests that dispersion QTLs (dQTLs), which could alter the variance of expression independently of the mean, have systematically smaller effect sizes than eQTLs. We estimate that at least 300 cells per individual and 400 individuals would be required to have modest power to detect the strongest dQTLs in iPSCs. These results will guide the design of future studies on understanding the genetic control of gene expression variance.

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