Biology subjects

Perez, E. M.

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

5 recordsLinked to original sources

bioRxiv2026

Adaptation in the eye and brain contributes to species divergence in visual perception in Heliconius butterflies

Sensory systems mediate the interaction between organisms and their environment, but how complex sensory pathways evolve and relate to variation in perception and behavior across ecological contexts, remains poorly understood, especially for terrestrial taxa. Here, we investigate whole-visual-system adaptation in Heliconius erato butterflies. Using continent-wide sampling, we demonstrate that within H. erato, facet count significantly decreased with increasing elevation. Common-garden rearing of low-elevation H. erato populations from Ecuador and their high-elevation sister species, H. himera, showed that eye and brain morphology are heritable, and comparisons to genomic measures of divergence indicates that this variation is due to divergent selection. Parallel comparisons from Colombia involving H. chestertonii (high elevation) and H. erato venus (low elevation) further revealed that eye and brain morphology can evolve as independent, decoupled traits. For both locations, differences in visual acuity correlated with variation in facet count. We also observed parallel evolution of spectral sensitivity, with independent high-elevation populations having fewer red-reflecting lateral filtering pigments. To experimentally link visual system morphology to behavior, we assessed visual acuity in second-generation H. erato cyrbia-H. himera hybrids. Overall, acuity was influenced by facet count, and when analyzed together with brain morphology, by a positive interaction between facet count and optic lobe volume, demonstrating that structural investment in the eye and neural expansion combine to maximize visual perception. This work shows that visual adaptation is a multi-layered process whereby sensory traits can evolve independently under localized ecological pressures, but evolution across the visual pathway contributes to refinements in behavioral performance.

evolutionary 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↗

bioRxiv2022

Losartan controls immune checkpoint blocker-induced edema and improves survival in glioblastoma

Immune checkpoint blockers (ICBs) have failed in all Phase III glioblastoma trials. Here, we found that ICBs induce cerebral edema in some patients and mice with glioblastoma. Through single-cell RNA sequencing, intravital imaging, and T cell blocking studies in mice, we demonstrated that this edema results from an inflammatory response following anti-PD1 antibody treatment that disrupts the blood-tumor-barrier. Used in lieu of immunosuppressive corticosteroids, the angiotensin receptor blocker losartan prevented this ICB-induced edema and reprogrammed the tumor microenvironment, curing 20% of mice which increased to 40% in combination with standard of care treatment. Using a bihemispheric tumor model, we identified a "hot" tumor immune signature prior to losartan+anti-PD1 therapy that predicted long-term survival. Our findings provide the rationale and associated biomarkers to test losartan with ICBs in glioblastoma patients. One-Sentence SummaryLosartan prevents immunotherapy-associated edema and enhances the outcome of immunotherapy in glioblastoma.

cancer biology↗

bioRxiv2019

Activity-by-Contact model of enhancer specificity from thousands of CRISPR perturbations

Mammalian genomes harbor millions of noncoding elements called enhancers that quantitatively regulate gene expression, but it remains unclear which enhancers regulate which genes. Here we describe an experimental approach, based on CRISPR interference, RNA FISH, and flow cytometry (CRISPRi-FlowFISH), to perturb enhancers in the genome, and apply it to test >3,000 potential regulatory enhancer-gene connections across multiple genomic loci. A simple equation based on a mechanistic model for enhancer function performed remarkably well at predicting the complex patterns of regulatory connections we observe in our CRISPR dataset. This Activity-by-Contact (ABC) model involves multiplying measures of enhancer activity and enhancer-promoter 3D contacts, and can predict enhancer-gene connections in a given cell type based on chromatin state maps. Together, CRISPRi-FlowFISH and the ABC model provide a systematic approach to map and predict which enhancers regulate which genes, and will help to interpret the functions of the thousands of disease risk variants in the noncoding genome.

genetics↗

bioRxiv2017

Cohesin Loss Eliminates All Loop Domains, Leading To Links Among Superenhancers And Downregulation Of Nearby Genes

The human genome folds to create thousands of intervals, called \"contact domains,\" that exhibit enhanced contact frequency within themselves. \"Loop domains\" form because of tethering between two loci - almost always bound by CTCF and cohesin - lying on the same chromosome. \"Compartment domains\" form when genomic intervals with similar histone marks co-segregate. Here, we explore the effects of degrading cohesin. All loop domains are eliminated, but neither compartment domains nor histone marks are affected. Loci in different compartments that had been in the same loop domain become more segregated. Loss of loop domains does not lead to widespread ectopic gene activation, but does affect a significant minority of active genes. In particular, cohesin loss causes superenhancers to co-localize, forming hundreds of links within and across chromosomes, and affecting the regulation of nearby genes. Cohesin restoration quickly reverses these effects, consistent with a model where loop extrusion is rapid.

genomics↗