Biology subjects

Cope, O.

Publications and source records attributed to Cope, O..

3 recordsLinked to original sources

bioRxiv2026

Evolution of endogenized densoviral elements across aphid species

AO_SCPLOWBSTRACTC_SCPLOWEndogenous viral elements (EVEs) are widespread across animal genomes, yet the processes governing EVE evolution and diversification remain poorly understood. Here, we characterize the evolution of densoviral EVEs and exogenous densoviruses across the aphid tribe Macrosiphini, an agriculturally important group in which exogenous densoviruses and their endogenous derivatives have been linked to the plastic production of wings. Using new genome assemblies, transcriptomics, and phylogenetic analysis, we find that EVE content varies extensively across species. Moreover, we discovered a novel densovirus that is vertically transmitted, but phylogenetic incongruence between other densoviruses and their hosts suggests that horizontal transmission may also occur. Finally, we show that EVE-mediated regulation of wing plasticity extends across species that use different environmental signals to induce winged offspring. Our study shows that in this system, the evolution of EVEs is highly variable and lineage-specific, generating genomic patterns that cannot be predicted from host evolutionary relationships.

evolutionary biology↗

bioRxiv2025

Extrachromosomal DNA Gives Cancer a New Evolutionary Pathway

During tumor progression, it has been assumed that individual cells that have acquired advantageous mutations overtake the population. Cancers driven by extrachromosomal DNA (ecDNA) do not follow this paradigm. Instead, these tumors have a spectrum of oncogene copy numbers across cells, and graded ecDNA variation may function as a form of bet-hedging that equips tumors with a broad range of phenotypes. Using imaging, single-cell multiomics, and multiplexed proteomics, we systematically characterized ecDNA levels across thousands of single cells. Higher ecDNA dosage produces proportional changes in transcript abundance, chromatin accessibility, protein levels, cell-cycle progression, and proliferation. Genes amplified on ecDNA exhibit distinct transcriptional scaling regimes that shift when the same genes are reintegrated into chromosomal homogeneous staining regions. When we experimentally disrupted the continuum of ecDNA dosage by sorting cells into low- and high-copy number states, the population rapidly recovered its original, continuous distribution. Our time-course data, live-cell imaging, and stochastic models collectively show that restoring this spectrum is an active, deterministic process rather than the passive outcome of random segregation. Together, these findings position ecDNA-mediated expression as a distinct evolutionary mechanism that endows tumors with rapid, population-level adaptability. These findings offer insight into why ecDNA-driven cancers are among the most aggressive and treatment-resistant.

genomics↗

bioRxiv2024

Leveraging AI to Automate Detection and Quantification of Extrachromosomal DNA (ecDNA) to Decode Drug Responses

Traditional drug discovery efforts have largely focused on targeting rapid, reversible protein-mediated adaptations to undermine cancer cells resistance to therapy. However, cancer cells also exploit DNA-based strategies, typically viewed as slow, irreversible, and unpredictable changes like point mutations or the selection of drug-resistant clones. Contrary to this perception, extrachromosomal DNA (ecDNA) represents a form of DNA alteration that is rapid, reversible, and predictable, playing a crucial role in cancers adaptive response. In this study, we present a novel post-processing pipeline for the automated detection and quantification of ecDNA in Fluorescence in situ Hybridization (FISH) images using the Microscopy Image Analyzer (MIA) tool. Our approach is particularly designed to monitor ecDNA dynamics during drug treatment, providing a quantitative framework to understand how ecDNA enables cancer cells to swiftly and reversibly adapt to therapeutic pressure. This pipeline not only offers a valuable resource for researchers aiming to automate ecDNA detection in FISH images but also sheds light on the adaptive mechanisms of ecDNA in response to epigenetic remodeling agents like JQ1.

cancer biology↗