Biology subjects

Mendenhall, E. M.

Publications and source records attributed to Mendenhall, E. M..

4 recordsLinked to original sources

bioRxiv2026

Trex-QTL: A mixture-model for identification of genetic effects with global effects on molecular phenotypes

While thousands of cis expression quantitative trait loci (cis-eQTLs) have been reliably identified, detecting trans-eQTL effects has proven to be challenging due to insufficient statistical power, lack of comparable tissues and cohorts, and low reproducibility across studies. Here, we present Trex-QTL, a novel trans-eQTL detection method that models eQTL summary statistics as a mixture consisting of both target gene and null associations. Compared to other recently developed methods, Trex-QTL has improved power for trans-eQTL detection and employs a simplified framework, requiring only eQTL association summary statistics as input. We performed extensive simulations to characterize the conditions under which trans-eQTLs are detectable by Trex-QTL across a range of effect sizes and numbers of target genes. We applied Trex-QTL to the Depression Genes and Networks (DGN) dataset and replicated two well-established trans-eQTLs at ARHGEF3 and IKZF1. We then applied Trex-QTL to the deeply characterized heterogeneous stock (HS) rat cohort with matched brain transcriptomic and genomic data, identifying 7 top-scoring, linkage disequilibrium-independent trans-eQTLs. One previously unreported trans-eQTL is at the locus harboring Jag2, a critical ligand for the Notch signaling pathway, which is associated with decreased Jag2 expression and decreased expression of multiple downstream genes including known Notch targets. A second example is a strong trans-eQTL overlapping a cluster of interferon genes associated with interferon-response genes including C4a and Parp14. We show evidence that this signal is mediated by a cis-eQTL for a cluster of interferon ligand genes that operate upstream of interferon receptor signaling. Both of these signals co-localize with association signals for a range of other phenotypes measured in this cohort. Overall, we demonstrate that Trex-QTL represents a powerful method to identify trans-eQTLs with global effects on molecular phenotypes and identify novel biologically compelling examples of such loci.

genomics↗

bioRxiv2024

Comparative atlas of genome-wide chromatin-associated protein co-occupancy

Accurate transcriptional regulation and chromatin dynamics requires the coordination and activity of chromatin-associated proteins (CAPs) at distinct loci. While the combinatorial activity of a select set of CAPs has been previously examined, these studies are limited by the underrepresentation of proteins and cell types explored, making it difficult to identify the global associations as well as the conservation of these associations across different cell types. Here, we performed 270 CAP chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq) experiments in both K562 and HepG2 cancer cell lines and explored the relationship between cell identity and CAP co-association using three distinct approaches. We employed a machine learning algorithm to organize the genome-wide binding profiles into 56 and 70 interpretable co-association modules for HepG2 and K562 cell lines, respectively. We found CAP co-association modules are mostly cell type-specific, however those present in both cell lines are largely comprised of TFs from a single TF family and anchor to unique loci via lineage-specific factors. While enhancer-associated co-binding modules were largely composed of cell type-specific CAPs, we found regulatory activity at promoter-enhancer module contacts to be enriched for chromatin remodeling proteins. Additionally, we used colocalization information derived from co-association models in conjunction with neural network models of transcription factor (TF) activity to identify high-confidence candidate TF cooperative pairs. Finally, through comparing CAP enrichment in high occupancy target (HOT) regions in K562 and HepG2 cell lines, we found cell type-specific HOT sites, but not common HOT sites, are selectively enriched at high copy number loci. Overall, this study uncovers principles of sequence-level and large-scale CAP genomic organization and demonstrates how this contributes to cell type-specific regulatory mechanisms and cellular functions.

genomics↗

bioRxiv2023

Allele biased transcription factor binding across human brain regions gives mechanistic insight into eQTLs

Transcription Factors (TFs) influence gene expression by facilitating or disrupting the formation of transcription initiation machinery at particular genomic loci. Because genomic localization of TFs is in part driven by TF recognition of DNA sequence, variation in TF binding sites can disrupt TF-DNA associations and affect gene regulation. To identify variants that impact TF binding in human brain tissues, we quantified allele bias for 93 TFs analyzed with ChIP-seq experiments of multiple structural brain regions from two donors. Using graph genomes constructed from phased genomic sequence data, we compared ChIP-seq signal between alleles at heterozygous variants within each tissue sample from each donor. Comparison of results from different brain regions within donors and the same regions between donors provided measures of allele bias reproducibility. We identified thousands of DNA variants that show reproducible bias in ChIP-seq for at least one TF. We found that alleles that are rarer in the general population were more likely than common alleles to exhibit large biases, and more frequently led to reduced TF binding. Combining ChIP-seq with RNA-seq, we identified TF-allele interaction biases with RNA bias in a phased allele linked to 6,709 eQTL variants identified in GTEx data, 3,309 of which were found in neural contexts. Our results provide insights into the effects of both common and rare variation on gene regulation in the brain. These findings can facilitate mechanistic understanding of cis-regulatory variation associated with biological traits, including disease.

genomics↗

bioRxiv2018

Occupancy patterns of 208 DNA-associated proteins in a single human cell type

Genome-wide occupancy maps of transcriptional regulators are important for understanding gene regulation and its effects on diverse biological processes, but only a small fraction of the >1,600 transcription factors (TFs) encoded in the human genome has been assayed. Here we present data and analyses of ChIP-seq experiments for 208 DNA-associated proteins (DAPs) in the HepG2 hepatocellular carcinoma line, spanning nearly a quarter of its expressed TFs, transcriptional co-factors, and chromatin regulator proteins. The DAP binding profiles classify into major groups associated predominantly with promoters or enhancers, or with both. We confirm and expand the current catalog of DNA sequence motifs; 77 factors showed similar motifs to those previously described using in vivo and/or in vitro methods, and 17 yielded novel motifs. We also describe motifs corresponding to other TFs that co-enrich with the primary ChIP target. FOX family motifs are, for example, significantly enriched in ChIP-seq peaks of 37 other DAPs. We show that promoters and enhancers can be discriminated based on motif content and occupancy patterns. This large catalog reveals High Occupancy Target (HOT) regions at which many DAPs associate, although each contains motifs for only a minority of the numerous associated DAPs. These analyses provide a deeper and more complete overview of the gene regulatory networks that define this cell type.

genomics↗