Biology subjects

Barr, K. A.

Publications and source records attributed to Barr, K. A..

7 recordsLinked to original sources

bioRxiv2026

Genetic Determinants of Cell-Type-Specific Responses to Cardiotoxic Chemotherapeutic Agents

Doxorubicin (DOX) and 5-fluorouracil (5-FU) are effective for treating a variety of cancers, yet many patients taking these drugs experience adverse cardiovascular events that are severe enough to pause treatment, often prolonging the course of chemotherapy and reducing its efficacy. Individual risk for drug-induced cardiotoxicity is likely mediated, at least in part, by genetic variants that control how the heart and vasculature respond to drug-induced perturbations. To identify loci associated with drug-induced cardiotoxicity, we developed an in vitro model that allows us to characterize the effects of chemotherapeutic drugs on a wide range of cardiac cell types, including cardiomyocytes, endothelial cells, and fibroblasts. Using single-cell RNA-seq, we profiled responses to DOX and 5-FU across 46 individuals and 14 cell types, identifying hundreds of expression quantitative trait loci that modify cardiovascular transcription in response to each drug (response eQTLs). Drug-responsive eQTL genes include genes that were previously linked to drug-induced cardiotoxicity and cardiovascular disease, such as ABCB4, HAS3, TNFRSF1A, and OGFR. Over a third of drug-responsive genes are shared between the DOX and 5-FU treatments, suggesting that genes predictive of DOX-induced cardiotoxicity may extend to 5-FU. Among the credible colocalizations we identified between GWAS signals and drug-response eQTLs, we discovered a locus associated with ischemic heart disease that is also a DOX-responsive eQTL for IL6R. IL6R was previously nominated as a druggable target for heart disease, and its binding partner IL6 is a candidate biomarker for anthracycline-induced cardiotoxicity. These findings advance the discovery of genetic variants underlying cardiotoxicity and support development of genotype-based predictors for treating cancer.

genomics↗

bioRxiv2025

CrossFilt: A Cross-species Filtering Tool that Eliminates Alignment Bias in Comparative Genomics Studies

Comparative functional genomic studies are often affected by biased read mapping across species due to inter-species differences in genome structure, sequence composition, and annotation quality. We developed CrossFilt, a filtering strategy that retains only sequencing reads that map reciprocally between genomes, ensuring that quantification of read counts is based on directly comparable genomic features. Using both real and simulated RNA-sequencing data from primates, we show that CrossFilt outperforms five alternative approaches that are commonly used, resulting in more accurate inference of gene expression differences. Our results highlight the impact of preprocessing strategies on the analysis of cross-species functional genomics data.

genomics↗

bioRxiv2024

Cell-type and dynamic state govern genetic regulation of gene expression in heterogeneous differentiating cultures

Identifying the molecular effects of human genetic variation across cellular contexts is crucial for understanding the mechanisms underlying disease-associated loci, yet many cell-types and developmental stages remain underexplored. Here we harnessed the potential of heterogeneous differentiating cultures (HDCs), an in vitro system in which pluripotent cells asynchronously differentiate into a broad spectrum of cell-types. We generated HDCs for 53 human donors and collected single-cell RNA-sequencing data from over 900,000 cells. We identified expression quantitative trait loci in 29 cell-types and characterized regulatory dynamics across diverse differentiation trajectories. This revealed novel regulatory variants for genes involved in key developmental and disease-related processes while replicating known effects from primary tissues, and dynamic regulatory effects associated with a range of complex traits.

genomics↗

bioRxiv2023

Guided Differentiation of Pluripotent Stem Cells for Cardiac Cell Diversity

In principle, induced pluripotent stem cells (iPSCs) can differentiate into any cell type in the body. The challenge is to find a way to rapidly expand the dimensionality of cell types and cell states we can characterize. To address this, we developed a guided differentiation protocol to produce heterogeneous differentiating cultures of cardiac cell types (cardiac HDCs) in 16 days. Cardiac HDCs are three-dimensional, rhythmically contracting cell aggregates that harbor a temporally and functionally diverse range of cardiac-relevant cell types. We characterize cardiac HDCs from 47 iPSC lines using single-cell RNA-sequencing to identify cardiomyocytes, epicardial cells, cardiac fibroblasts, endothelial cells, and hematopoietic cells, along with both ectodermal and endodermal derivatives. This guided differentiation approach prioritizes simplicity by minimizing the reagents and steps required, thereby enabling rapid and cost-effective experimental throughput. We expect cardiac HDCs to provide a scalable cardiac model for population-level studies of gene regulatory variation and gene-by-environment interactions.

genomics↗

bioRxiv2022

Embryoid bodies facilitate comparative analysis of gene expression in humans and chimpanzees across dozens of cell types

Comparative gene expression studies in apes are fundamentally limited by the challenges associated with sampling across different tissues. Here, we used single-cell RNA-sequencing of embryoid bodies (EBs) to collect transcriptomic data from over 70 cell types in three humans and three chimpanzees. We found hundreds of genes whose regulation is conserved across cell types, as well as genes whose regulation likely evolves under directional selection in one or a handful of cell types. Using EBs from a human-chimpanzee fused cell line, we also inferred the proportion of inter-species regulatory differences due to changes in cis and trans elements between the species. Thus, we present the most comprehensive dataset of comparative gene expression from humans and chimpanzees to date, including a catalog of regulatory mechanisms associated with inter-species differences.

genomics↗

bioRxiv2021

Human embryoid bodies as a novel system for genomic studies of functionally diverse cell types

Most disease-associated loci, though located in putatively regulatory regions, have not yet been confirmed to affect gene expression. One reason for this could be that we have not examined gene expression in the most relevant cell types or conditions. Indeed, even large-scale efforts to study gene expression broadly across tissues are limited by the necessity of obtaining human samples post-mortem, and almost exclusively from adults. Thus, there is an acute need to expand gene regulatory studies in humans to the most relevant cell types, tissues, and states. We propose that embryoid bodies (EBs), which are organoids that contain a multitude of cell types in dynamic states, can provide an answer. Single cell RNA-sequencing now provides a way to interrogate developmental trajectories in EBs and enhance the potential to uncover dynamic regulatory processes that would be missed in studies of static adult tissue. Here, we examined the properties of the EB model for the purpose mapping inter-individual regulatory differences in a large variety of cell types.

genomics↗

bioRxiv2019

An in silico analysis of robust but fragile gene regulation links enhancer length to robustness

1Organisms must ensure that expression of genes is directed to the appropriate tissues at the correct times, while simultaneously ensuring that these gene regulatory systems are robust to perturbation. This idea is captured by a mathematical concept called r-robustness, which says that a system is robust to a perturbation in up to r - 1 randomly chosen parameters. In this work we use this idea to investigate the robustness of gene regulation using a sequence level model of the Drosophila melanogaster gene even-skipped. We find that gene regulation can be remarkably sensitive to changes in transcription factor concentrations at the boundaries of expression features, while it is robust to perturbation elsewhere. We also find that the length of sequence used to control an expression feature correlates negatively with the number of nucleotides that are sensitive to mutation in both natural and in silico predicted enhancers. In all cases, the exact degree of robustness obtained is dependent not only on DNA sequence, but also on the local concentration of regulatory factors. By analyzing both natural and synthetic sequences, we provide strong quantitative evidence that increased sequence length makes gene regulatory systems more robust to genetic perturbation.\n\n2 Author SummaryRobustness assures that organisms can survive when faced with unpredictable environments or genetic mutations. In this work, we characterize the robustness of gene regulation using an experimentally validated model of the regulation of the Drosophila gene even-skipped. We use a mathematically precise definition of robustness that allows us to make quantitative comparisons of robustness between different genetic sequences or between different nuclei. From this analysis, we found that genetic sequences that were not previously known to be important for gene regulation reduce sensitivity to genetic perturbation. In contrast, we found that gene regulation can be very sensitive to the levels of regulators. This extreme sensitivity was only observed at the boundaries of expression features, where switch-like behavior is desirable. This highlights the importance of considering context when assessing robustness.

systems biology↗