Determining the genetic basis of anthracycline-cardiotoxicity by molecular response QTL mapping in induced cardiomyocytes.

Anthracycline-induced cardiotoxicity (ACT) is a key limiting factor in setting optimal chemotherapy regimes, with almost half of patients expected to develop congestive heart failure given high doses. However, the genetic basis of sensitivity to anthracyclines remains unclear. We created a panel of iPSC-derived cardiomyocytes from 45 individuals and performed RNA-seq after 24 hr exposure to varying doxorubicin dosages. The transcriptomic response is substantial: the majority of genes are differentially expressed and over 6000 genes show evidence of differential splicing, the later driven by reduced splicing fidelity in the presence of doxorubicin. We show that inter-individual variation in transcriptional response is predictive of in vitro cell damage, which in turn is associated with in vivo ACT risk. We detect 447 response-expression quantitative trait loci (QTLs) and 42 response-splicing QTLs, which are enriched in lower ACT GWAS [Formula: see text]-values, supporting the in vivo relevance of our map of genetic regulation of cellular response to anthracyclines.

Impact of regulatory variation across human iPSCs and differentiated cells.

Induced pluripotent stem cells (iPSCs) are an essential tool for studying cellular differentiation and cell types that are otherwise difficult to access. We investigated the use of iPSCs and iPSC-derived cells to study the impact of genetic variation on gene regulation across different cell types and as models for studies of complex disease. To do so, we established a panel of iPSCs from 58 well-studied Yoruba lymphoblastoid cell lines (LCLs); 14 of these lines were further differentiated into cardiomyocytes. We characterized regulatory variation across individuals and cell types by measuring gene expression levels, chromatin accessibility, and DNA methylation. Our analysis focused on a comparison of inter-individual regulatory variation across cell types. While most cell-type-specific regulatory quantitative trait loci (QTLs) lie in chromatin that is open only in the affected cell types, we found that 20% of cell-type-specific regulatory QTLs are in shared open chromatin. This observation motivated us to develop a deep neural network to predict open chromatin regions from DNA sequence alone. Using this approach, we were able to use the sequences of segregating haplotypes to predict the effects of common SNPs on cell-type-specific chromatin accessibility.

Expression Quantitative Trait Locus Mapping Studies in Mid-secretory Phase Endometrial Cells Identifies HLA-F and TAP2 as Fecundability-Associated Genes.

Fertility traits in humans are heritable, however, little is known about the genes that influence reproductive outcomes or the genetic variants that contribute to differences in these traits between individuals, particularly women. To address this gap in knowledge, we performed an unbiased genome-wide expression quantitative trait locus (eQTL) mapping study to identify common regulatory (expression) single nucleotide polymorphisms (eSNPs) in mid-secretory endometrium. We identified 423 cis-eQTLs for 132 genes that were significant at a false discovery rate (FDR) of 1%. After pruning for strong LD (r2 >0.95), we tested for associations between eSNPs and fecundability (the ability to get pregnant), measured as the length of the interval to pregnancy, in 117 women. Two eSNPs were associated with fecundability at a FDR of 5%; both were in the HLA region and were eQTLs for the TAP2 gene (P = 1.3x10-4) and the HLA-F gene (P = 4.0x10-4), respectively. The effects of these SNPs on fecundability were replicated in an independent sample. The two eSNPs reside within or near regulatory elements in decidualized human endometrial stromal cells. Our study integrating eQTL mapping in a primary tissue with association studies of a related phenotype revealed novel genes and associated alleles with independent effects on fecundability, and identified a central role for two HLA region genes in human implantation success.

Genetic Variation, Not Cell Type of Origin, Underlies the Majority of Identifiable Regulatory Differences in iPSCs.

The advent of induced pluripotent stem cells (iPSCs) revolutionized human genetics by allowing us to generate pluripotent cells from easily accessible somatic tissues. This technology can have immense implications for regenerative medicine, but iPSCs also represent a paradigm shift in the study of complex human phenotypes, including gene regulation and disease. Yet, an unresolved caveat of the iPSC model system is the extent to which reprogrammed iPSCs retain residual phenotypes from their precursor somatic cells. To directly address this issue, we used an effective study design to compare regulatory phenotypes between iPSCs derived from two types of commonly used somatic precursor cells. We find a remarkably small number of differences in DNA methylation and gene expression levels between iPSCs derived from different somatic precursors. Instead, we demonstrate genetic variation is associated with the majority of identifiable variation in DNA methylation and gene expression levels. We show that the cell type of origin only minimally affects gene expression levels and DNA methylation in iPSCs, and that genetic variation is the main driver of regulatory differences between iPSCs of different donors. Our findings suggest that studies using iPSCs should focus on additional individuals rather than clones from the same individual.