Biology subjects

Miko, I.

Publications and source records attributed to Miko, I..

4 recordsLinked to original sources

bioRxiv2025

Untangling the Evolutionary Dynamics of the Phenome in Megadiverse Hymenoptera

How complex phenotypes evolve across the Tree of Life remains poorly understood because phenotypic evolution unfolds across multiple hierarchical and developmental scales. Hymenoptera (ants, wasps, and bees) represent one of the largest animal radiations (>150,000 species), yet the origin of their remarkable phenotypic diversity remains unclear. Here, we reconstruct the evolution of the hymenopteran skeletomuscular phenome and analyze its dynamics across anatomical hierarchies and developmental stages. We show that hymenopteran adaptive radiation was a phenome-wide process facilitated by evolutionary decoupling between adults and larvae and the semi-independent evolution of adult anatomical systems. Phenotypic and lineage diversification was driven not simply by key innovations or elevated phenomic rates, but by the partitioning of evolutionary innovation across anatomical systems, generating a broader repertoire of adaptive solutions. These findings extend the classical view of adaptive radiation from individual key innovations to phenome-wide reorganization.

evolutionary biology↗

bioRxiv2024

Unique cuticular morphology of a truly marine insect, Echinophthirius horridus von Olfers, 1816 (Phthiraptera: Echinophthiriidae)

Echinophthiriidae is a family of aquatic lice parasitizing aquatic carnivorans, each member distinguished by their uniquely modified, curved setae. Echinophthirius horridus is known to parasitize a wide range of phocid (earless) seals as opposed to exhibiting the more species-specific parasitism of other echinophthiriid lice. In this study, we use a combination of bright field microscopy, confocal laser scanning microscopy (CLSM), and line drawings to provide a detailed description of the general body setae of E. horridus and discuss its possible significance as an adaptation to a marine lifestyle.

physiology↗

bioRxiv2023

ontophylo: Reconstructing the evolutionary dynamics of phenomes using new ontology-informed phylogenetic methods

1. Reconstructing ancestral states for discrete characters is essential for understanding trait evolution in organisms. However, most existing methods are limited to individual characters and often overlook the hierarchical and interactive nature of traits. Recent advances in phylogenetics now offer the possibility of integrating knowledge from anatomy ontologies to reconstruct multiple discrete character histories. However, practical applications that fully harness the potential of these new approaches are still lacking. 2. This paper introduces ontophylo, an R package that extends the PARAMO pipeline to address these limitations. Ontophylo enables the reconstruction of phenotypic entities composed of amalgamated characters, such as entire phenomes or anatomical regions. It offers three new applications: (1) reconstructing evolutionary rates of amalgamated characters using phylogenetic non-homogeneous Poisson process (pNHPP), allowing for rate variation and shifts over time and phylogeny; (2) explicit reconstruction of morphospace dynamics; and (3) direct visualization of evolutionary rates and statistics on vector images of organisms. Ontophylo incorporates ontological knowledge to facilitate these applications. 3. Benchmarking confirms the accuracy of pNHPP in estimating character rates under different evolutionary scenarios, and example applications demonstrate the utility of ontophylo in studying morphological evolution in Hymenoptera using simulated data. 4. Ontophylo is easily integrated with other ontologyoriented and general-purpose R packages and offers new opportunities to examine morphological evolution on a phenomic level using new and legacy data.

evolutionary biology↗

bioRxiv2019

PARAMO pipeline: reconstructing ancestral anatomies using ontologies and stochastic mapping

Comparative phylogenetics has been largely lacking a method for reconstructing the evolution of phenotypic entities that consist of ensembles of multiple discrete traits - entire organismal anatomies or organismal body regions. In this study, we provide a new approach named PARAMO (Phylogenetic Ancestral Reconstruction of Anatomy by Mapping Ontologies) that appropriately models anatomical dependencies and uses ontology-informed amalgamation of stochastic maps to reconstruct phenotypic evolution at different levels of anatomical hierarchy including entire phenotypes. This approach provides new opportunities for tracking phenotypic radiations and evolution of organismal anatomies.

evolutionary biology↗