Biology subjects

Jagoda, E.

Publications and source records attributed to Jagoda, E..

7 recordsLinked to original sources

bioRxiv2025

An unbiased survey of distal element-gene regulatory interactions with direct-capture targeted Perturb-seq

Identifying the impact of distal regulatory elements on gene expression is a core challenge in human genetics. Large-scale CRISPR screens have not captured lower effect size element-gene interactions due to selection bias and limited statistical power. We developed a framework for highly powered CRISPR screens, consisting of Direct-Capture Targeted Perturb-seq (DC-TAP-seq), unbiased target selection, and a pipeline accounting for statistical power. Surveying 10,000 random distal element-gene pairs revealed most element-gene interactions have effect sizes <10%, which were virtually undetectable in prior studies. Most interactions occur within 100kb, many elements bind CTCF without classical enhancer chromatin, and housekeeping genes have similar frequencies of distal regulatory elements but with weaker effects. We also highlight limitations of predictive models and suggest that new models consider elements with smaller effect sizes. Our study provides an expanded view of distal regulatory elements and a framework for building more comprehensive maps of distal regulation.

genomics↗

bioRxiv2024

Mapping enhancer-gene regulatory interactions from single-cell data

Mapping enhancers and their target genes in specific cell types is crucial for understanding gene regulation and human disease genetics. However, accurately predicting enhancer-gene regulatory interactions from single-cell datasets has been challenging. Here, we introduce a new family of classification models, scE2G, to predict enhancer-gene regulation. These models use features from single-cell ATAC-seq or multiomic RNA and ATAC-seq data and are trained on a CRISPR perturbation dataset including >10,000 evaluated element-gene pairs. We benchmark scE2G models against CRISPR perturbations, fine-mapped eQTLs, and GWAS variant-gene associations and demonstrate state-of-the-art performance at prediction tasks across multiple cell types and categories of perturbations. We apply scE2G to build maps of enhancer-gene regulatory interactions in heterogeneous tissues and interpret noncoding variants associated with complex traits, nominating regulatory interactions linking INPP4B and IL15 to lymphocyte counts. The scE2G models will enable accurate mapping of enhancer-gene regulatory interactions across thousands of diverse human cell types.

genetics↗

bioRxiv2024

Complex regulatory interactions at GDF5 shape joint morphology and osteoarthritis disease risk

Our ability to pinpoint causal variants using GWAS is dependent on understanding the dynamic epigenomic and epistatic context of each associated locus. Being the best studied skeletal locus, GDF5 associates with many diseases and has a complex cis-regulatory architecture. We interrogate GDF5 regulatory interactions and model disease variants in vitro and in vivo. For all regulatory regions we see that local epigenetic activation/repression impacts patterns of joint-specific expression and disease risk. By modeling the most cited risk variant in mice we found that it had no impact on expression, joint morphology, or disease. Yet, we identified significant epistatic expression interactions between this risk variant and others lying within regulatory regions subject to repression or activation. These findings are important lessons on how regulatory interactions and local epistasis work in the etiology of disease risk, and that assessment of individual variants of high GWAS significance need not alone be considered causal. TeaserGenetic interactions at the most studied skeletal disease locus reveal hidden complexities in pinpointing causal mutations.

genetics↗

bioRxiv2024

Cohesin-mediated 3D contacts tune enhancer-promoter regulation

Enhancers are key drivers of gene regulation thought to act via 3D physical interactions with the promoters of their target genes. However, genome-wide depletions of architectural proteins such as cohesin result in only limited changes in gene expression, despite a loss of contact domains and loops. Consequently, the role of cohesin and 3D contacts in enhancer function remains debated. Here, we developed CRISPRi of regulatory elements upon degron operation (CRUDO), a novel approach to measure how changes in contact frequency impact enhancer effects on target genes by perturbing enhancers with CRISPRi and measuring gene expression in the presence or absence of cohesin. We systematically perturbed all 1,039 candidate enhancers near five cohesin-dependent genes and identified 34 enhancer-gene regulatory interactions. Of 26 regulatory interactions with sufficient statistical power to evaluate cohesin dependence, 18 show cohesin-dependent effects. A decrease in enhancer-promoter contact frequency upon removal of cohesin is frequently accompanied by a decrease in the regulatory effect of the enhancer on gene expression, consistent with a contact-based model for enhancer function. However, changes in contact frequency and regulatory effects on gene expression vary as a function of distance, with distal enhancers (e.g., >50Kb) experiencing much larger changes than proximal ones (e.g., <50Kb). Because most enhancers are located close to their target genes, these observations can explain how only a small subset of genes -- those with strong distal enhancers -- are sensitive to cohesin. Together, our results illuminate how 3D contacts, influenced by both cohesin and genomic distance, tune enhancer effects on gene expression.

molecular biology↗

bioRxiv2023

An encyclopedia of enhancer-gene regulatory interactions in the human genome

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the impact of human genetic variation on disease1-6. Here we create and evaluate a resource of >13 million enhancer-gene regulatory interactions across 352 cell types and tissues, by integrating predictive models, measurements of chromatin state and 3D contacts, and large-scale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,411 element-gene pairs measured in CRISPR perturbation experiments, >30,000 fine-mapped eQTLs, and 569 fine-mapped GWAS variants linked to a likely causal gene. Using this framework, we develop a new predictive model, ENCODE-rE2G, that achieves state-of-the-art performance across multiple prediction tasks, demonstrating a strategy involving iterative perturbations and supervised machine learning to build increasingly accurate predictive models of enhancer regulation. Using the ENCODE-rE2G model, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, which reveals global properties of enhancer networks, identifies differences in the functions of genes that have more or less complex regulatory landscapes, and improves analyses to link noncoding variants to target genes and cell types for common, complex diseases. By interpreting the model, we find evidence that, beyond enhancer activity and 3D enhancer-promoter contacts, additional features guide enhancer-promoter communication including promoter class and enhancer-enhancer synergy. Altogether, these genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models, and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

genomics↗

bioRxiv2021

Regulatory dissection of the severe COVID-19 risk locus introgressed by Neanderthals

Individuals infected with the SARS-CoV-2 virus present with a wide variety of phenotypes ranging from asymptomatic to severe and even lethal outcomes. Past research has revealed a genetic haplotype on chromosome 3 that entered the human population via introgression from Neanderthals as the strongest genetic risk factor for the severe COVID-19 phenotype. However, the specific variants along this introgressed haplotype that contribute to this risk and the biological mechanisms that are involved remain unclear. Here, we assess the variants present on the risk haplotype for their likelihood of driving the severe COVID-19 phenotype. We do this by first exploring their impact on the regulation of genes involved in COVID-19 infection using a variety of population genetics and functional genomics tools. We then perform an locus-specific massively parallel reporter assay to individually assess the regulatory potential of each allele on the haplotype in a multipotent immune-related cell line. We ultimately reduce the set of over 600 linked genetic variants to identify 4 introgressed alleles that are strong functional candidates for driving the association between this locus and severe COVID-19. These variants likely drive the locus impact on severity by putatively modulating the regulation of two critical chemokine receptor genes: CCR1 and CCR5. These alleles are ideal targets for future functional investigations into the interaction between host genomics and COVID-19 outcomes.

genetics↗

bioRxiv2017

Impact of non-LTR retrotransposons in the differentiation and evolution of Anatomically Modern Humans

Transposable Elements are biologically important components of eukaryote genomes. In particular, non-LTR retrotransposons (N-LTRrs) extensively shaped the human genome throughout evolution. In this study, we compared retrotransposon insertions differentially present in the genomes of Anatomically Modern Humans, Neanderthals, Denisovans and Chimpanzees, in order to assess the possible impact of retrotransposition in the differentiation of the human lineage. Briefly, we first identified species-specific N-LTRrs and established their distribution in present day human populations. These analyses shortlisted a group of N-LTRr insertions that were found exclusively in Anatomically Modern Humans. Notably, these insertions targeted genes more frequently than randomly expected and are associated with an increase in the number of transcriptional/splicing variants of those genes they inserted in. The analysis of the functionality of genes targeted by human-specific N-LTRr insertions seems to reflect phenotypic changes that occurred during human evolution. Furthermore, the expression of genes containing the most recent N-LTRr insertions is enriched in the brain, especially in undifferentiated neurons, and these genes associate in networks related to neuron maturation and migration. Additionally, we also identified candidate N-LTRr insertions that have likely produced new functional variants exclusive to modern humans, which show traces of positive selection and are now fixed in all present-day human populations. In sum, our results strongly suggest that N-LTRr impacted our differentiation as a species and have been a constant source of genomic variability all throughout the evolution of the human lineage.

genomics↗