Biology subjects

iPSCORE Consortium,

Publications and source records attributed to iPSCORE Consortium,.

6 recordsLinked to original sources

bioRxiv2025

Genetics of growth rate in induced pluripotent stem cells

Human induced pluripotent stem cells (iPSCs) have transformed biomedical research by enabling the generation of diverse cell types from accessible somatic tissues. However, certain fundamental biological properties, such as the genetic and epigenetic determinants of iPSC proliferation, remain poorly characterized. We measured the growth of iPSC lines derived from 602 unique donors using high-throughput time-lapse imaging, quantified proliferation through a growth Area-Under-the-Curve (gAUC) phenotype, and correlated gAUC with the gene expression and genotype of the cell lines. We identified 3,091 genes associated with gAUC, many of which are well established regulators of cell proliferation. We also found that rare deleterious variants in WDR54 were associated with reduced iPSC growth and that WDR54 was differentially expressed with respect to gAUC. Although no common variants showed a genome-wide association with gAUC, iPSC lines from monozygotic twins were highly correlated, and common genetic variation explained approximately 71-75% of the variance in iPSC growth rates. These results indicate a complex genetic architecture of iPSC growth rates, where rare, large-effect variants in important growth regulators, including WDR54, are layered onto a highly polygenic background. These findings have important implications for the design of pooled iPSC-based studies and disease models, which may be confounded by intrinsic growth differences.

developmental biology↗

bioRxiv2024

IFN-γ activates an immune-like regulatory network in the cardiac vascular endothelium

The regulatory mechanisms underlying the response to pro-inflammatory cytokines in cardiac diseases are poorly understood. Here, we use iPSC-derived cardiovascular progenitor cells (CVPCs) to model the response to interferon gamma (IFN{gamma}) in human cardiac tissue. We generate RNA-seq and ATAC-seq for four CVPCs that were treated with IFN{gamma} and compare them with paired untreated controls. Transcriptional differences after treatment show that IFN{gamma} initiates an innate immune cell-like response, shifts the CVPC transcriptome towards coronary artery and aorta profiles, and stimulates expression of endothelial cell-specific genes. Analysis of the accessible chromatin shows that IFN{gamma} is a potent chromatin remodeler and establishes an IRF-STAT immune-cell like regulatory network. Finally, we show that 11 GWAS risk variants for 8 common cardiac diseases overlap IFN{gamma}-upregulated ATAC-seq peaks. Our findings reveal insights into IFN{gamma}-induced activation of an immune-like regulatory network in the cardiac vascular endothelium and the potential role that regulatory elements in this pathway play in common cardiac diseases. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/592380v2_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@e66966org.highwire.dtl.DTLVardef@111da44org.highwire.dtl.DTLVardef@110a8f5org.highwire.dtl.DTLVardef@c4997b_HPS_FORMAT_FIGEXP M_FIG C_FIG Paired RNA-seq and ATAC-seq was generated for induced pluripotent stem cell derived cardiovascular progenitor cells (CVPCs) treated with interferon-gamma (IFN{gamma}) and matched controls to model the effect of the pro-inflammatory cytokine on human cardiac tissue. Using the RNA-seq, transcriptomic changes were characterized by performing differential gene expression analysis, integrating gene expression data from hundreds of samples of adult cardiac tissues, and using single cell RNA-seq to evaluate cell type-specificity. Using the ATAC-seq, epigenomic changes were characterized by performing differential chromatin accessibility and transcription factor binding analyses, and annotating ATAC-seq peaks with chromatin states from over 800 tissues. Genetic variants in risk loci associated with cardiac diseases were intersected with ATAC-seq peaks to evaluate whether they were in chromatin that is only accessible after IFN{gamma} treatment. The findings demonstrate the utility of using CVPCs to model the effects of cytokines on cardiac tissues and provide the framework for conducting large scale studies to further evaluate GWAS loci that are explained by context-specific regulatory variation.

bioinformatics↗

bioRxiv2024

Multi-omic QTL mapping in early developmental tissues reveals phenotypic and temporal complexity of regulatory variants underlying GWAS loci

Most GWAS loci are presumed to affect gene regulation, however, only [~]43% colocalize with expression quantitative trait loci (eQTLs). To address this colocalization gap, we identify eQTLs, chromatin accessibility QTLs (caQTLs), and histone acetylation QTLs (haQTLs) using molecular samples from three early developmental (EDev) tissues. Through colocalization, we annotate 586 GWAS loci for 17 traits by QTL complexity, QTL phenotype, and QTL temporal specificity. We show that GWAS loci are highly enriched for colocalization with complex QTL modules that affect multiple elements (genes and/or peaks). We also demonstrate that caQTLs and haQTLs capture regulatory variations not associated with eQTLs and explain [~]49% of the functionally annotated GWAS loci. Additionally, we show that EDev-unique QTLs are strongly depleted for colocalizing with GWAS loci. By conducting one of the largest multi-omic QTL studies to date, we demonstrate that many GWAS loci exhibit phenotypic complexity and therefore, are missed by traditional eQTL analyses.

genomics↗

bioRxiv2023

Unsupervised Machine Learning Identifies Chromatin Accessibility Regulatory Networks that Define Cell State Transitions in Pluripotency

Stem cells exist in vitro in a spectrum of interconvertible pluripotent states. Analyzing hundreds of hiPSCs derived from different individuals, we show the proportions of these pluripotent states vary considerably across lines. We discovered 13 gene network modules (GNMs) and 13 regulatory network modules (RNMs), which were highly correlated with each other suggesting that the coordinated co-accessibility of regulatory elements in the RNMs likely underlied the coordinated expression of genes in the GNMs. Epigenetic analyses revealed that regulatory networks underlying self-renewal and pluripotency have a surprising level of complexity. Genetic analyses identified thousands of regulatory variants that overlapped predicted transcription factor binding sites and were associated with chromatin accessibility in the hiPSCs. We show that the master regulator of pluripotency, the NANOG-OCT4 Complex, and its associated network were significantly enriched for regulatory variants with large effects, suggesting that they may play a role in the varying cellular proportions of pluripotency states between hiPSCs. Our work captures the coordinated activity of tens of thousands of regulatory elements in hiPSCs and bins these elements into discrete functionally characterized regulatory networks, shows that regulatory elements in pluripotency networks harbor variants with large effects, and provides a rich resource for future pluripotent stem cell research.

genomics↗

bioRxiv2021

Regulatory variants active in iPSC-derived pancreatic progenitor cells are associated with Type 2 Diabetes in adults

Pancreatic progenitor cells (PPC) are an early developmental multipotent cell type that give rise to mature endocrine, exocrine, and ductal cells. To investigate the extent to which regulatory variants active in PPC contribute to pancreatic complex traits and disease in the adult, we derived PPC from induced pluripotent stem cells (iPSCs) of nine unrelated individuals and generated single cell profiles of chromatin accessibility (snATAC- seq) and transcriptome (scRNA-seq). While iPSC-PPC differentiation was asynchronous and included cell types from early to late developmental stages, we found that the predominant cell type consisted of NKX6-1+ progenitors. Genetic characterization using snATAC-seq identified 86,261 regulatory variants that either displayed chromatin allelic bias and/or were predicted to affect active transcription factor (TF) binding sites. Integration of these regulatory variants with 380 fine-mapped type 2 diabetes (T2D) risk loci identified regulatory variants in 209 of these loci that are functional in iPSC-PPC, either by affecting transcription factor binding or through association with allelic effects on chromatin accessibility. The PPC active regulatory variants in 65 of these loci showed strong evidence of causally underlying the association with T2D. Our study shows that studying the functional associations of regulatory variation in iPSC-PPC enables the identification and characterization of causal SNPs for adult Type 2 Diabetes.

genetics↗

bioRxiv2019

Systematic assessment of regulatory effects of human disease variants in pluripotent cells

Identifying regulatory genetic effects in pluripotent cells provides important insights into disease variants with potentially transient or developmental origins. Combining existing and newly-generated data, we characterized 1,367 iPSC lines from 948 unique donors, collectively analyzed within the \"Integrated iPSC QTL\" (i2QTL) Consortium. The sample size of our study allowed us to derive the most comprehensive map of quantitative trait loci (QTL) in pluripotent human cells to date. We mapped the effects of nearby common genetic variants on five expression phenotypes, identifying cis-QTL at gene-, exon-level and transcript-, splicing-, alternative polyadenylation-ratio (APA) for a total of 18,556 genes. For gene-level, we further quantified the effects of rare and singleton variants, and the effect of distal variants that act in trans (trans-eQTL), which we replicated in independent samples. Our data are a valuable community resource, uncovering novel regulatory effects that have not previously been described in differentiated cells and tissues. Building on this regulatory map, we functionally explore GWAS signals for over 4,336 trait loci, finding evidence for colocalization with common and rare iPSC QTL for traits such as height and BMI, and diseases, such as cancer and coronary artery disease.

genomics↗