Dataset Information

NextGen/GENESiPS

ABSTRACT:

Variability in induced pluripotent stem cell (iPSC) lines remains a roadblock for disease modeling and regenerative medicine. Through linear mixed models we have described different sources of gene expression variability from RNA sequencing data in 317 human iPSC lines from 101 individuals. We found that ~50% of genome-wide expression variability is explained by variation across individuals and identified a set of expression quantitative trait loci that contribute to this variation. These analyses coupled with allele specific expression show that iPSCs retain a subject-specific gene expression pattern. Pathway enrichment and key driver analyses, based on predictive causal gene networks, found that Polycomb targets explain a significant part of the non-genetic variability present in iPSCs within and across individuals. These publically available iPSC lines and genetic datasets will be a resource to the scientific community and will open new avenues to reduce variability in iPSCs and improve their utility in disease modeling.

SNP array data from individuals included in RNA-seq transcriptome profiling study of human induced pluripotent stem cells to characterize gene expression variation across individuals and within multiple iPSC lines from the same individual. Genotyping was performed on patient blood.

Data availability:

SNP-genotyping: dbGaP - current study
RNA-seq counts: GEO - GSE79636
FASTQ files: SRA - SRP072417

PROVIDER: phs001139 | dbGaP |

SECONDARY ACCESSION(S): PRJNA324736PRJNA324735

REPOSITORIES: dbGaP

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	GapExchange_phs001139.v1.p1.xml	Xml
	dbGaPEx2.1.5.xsd	Other
	Study_Report.phs001139.GENESiPS_InsulinResistance.v1.p1.MULTI.pdf	Pdf
	manifest_phs001139.GENESiPS_InsulinResistance.v1.p1.c1.GRU-IRB.pdf	Pdf
	datadict_v2.xsl	Other

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Project description:Renewable in vitro cell cultures, such as lymphoblastoid cell lines (LCLs), have facilitated studies that contributed to our understanding of genetic influence on human traits. However, the degree to which cell lines faithfully maintain differences in donor-specific phenotypes is still debated. We have previously reported that standard cell line maintenance practice results in a loss of donor-specific gene expression signatures in LCLs. An alternative to the LCL model is the induced pluripotent stem cell (iPSC) system, which carries the potential to model tissue-specific physiology through the use of differentiation protocols. Still, existing LCL banks represent an important source of starting material for iPSC generation, and it is possible that the disruptions in gene regulation associated with long-term LCL maintenance could persist through the reprogramming process. To address this concern, we studied the effect of reprogramming mature LCLs to iPSCs on the ensuing gene expression patterns within and between six unrelated donor individuals. We show that the reprogramming process results in a recovery of donor-specific gene regulatory signatures. Since environmental contributions are unlikely to be a source of individual variation in our system of highly passaged cultured cell lines, our observations suggest that the effect of genotype on gene regulation is more pronounced in the iPSCs than in the LCL precursors. Our observations indicate that iPSCs can be a powerful model system for studies of phenotypic variation across individuals in general, and the genetic association with variation in gene regulation in particular. We further conclude that LCLs are an appropriate starting material for iPSC generation. Whole genome gene expression data was collected for 34 samples including 17 iPSC lines and 17 LCL lines on the Illumina HT-12 v4 Expression BeadChip array platform. Three biological replicates of each individual were included in the study, except for one individual for which only two replicates were obtained.

Dataset Information

NextGen/GENESiPS

Dataset's files

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