Biology subjects

Uyeda, J.

Publications and source records attributed to Uyeda, J..

8 recordsLinked to original sources

bioRxiv2024

Fundamental constraints on the evolution of vertebrate life histories

Vertebrate life histories evolve in response to selection imposed by abiotic and biotic environmental conditions while being limited by genetic, developmental, physiological, demographic, and phylogenetic processes that constrain adaptation. Despite the well-recognized shifts in selective pressures accompanying transitions among environments, identifying the conditions driving innovation and the consequences for life-history evolution remain an outstanding question. Here, we compare the traits of aquatic and terrestrial vertebrates to infer shifts in demographic and evolutionary constraints that explain differences in life-history optimization. Specifically, our results emphasize the reduced potential for life-history diversification on land, especially that of reproductive strategies. Moreover, our study reveals differences between the evolution of viviparity in the two realms. Transitions from egg laying to live birth represents a major shift across life-history space for aquatic organisms, whereas terrestrial egg-laying organisms evolve live birth without drastic changes in life-history strategy. Whilst trade-offs in the allocation of resources place fundamental constraints on the way life histories can vary, ecological setting influences the position of species within the viable phenotypic space available for adaptive evolution.

evolutionary biology↗

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↗

bioRxiv2023

rphenoscate: An R package for semantic-aware evolutionary analyses of anatomical traits

O_LIOrganismal anatomy is a complex hierarchical system of interconnected anatomical entities often producing dependencies among multiple morphological characters. Ontologies provide a formalized and computable framework for representing and incorporating prior biological knowledge about anatomical dependencies in models of trait evolution. Further, ontologies offer new opportunities for assembling and working with semantic representations of morphological data. C_LIO_LIIn this work we present a new R package--rphenoscate--that enables incorporating ontological knowledge in evolutionary analyses and exploring semantic patterns of morphological data. In conjunction with rphenoscape it also allows for assembling synthetic phylogenetic character matrices from semantic phenotypes of morphological data. We showcase the new package functionalities with three data sets from bees and fishes. C_LIO_LIWe demonstrate that ontology knowledge can be employed to automatically set up ontologyinformed evolutionary models that account for trait dependencies in the context of stochastic character mapping. We also demonstrate how ontology annotations can be explored to interrogate patterns of morphological evolution. Finally, we demonstrate that synthetic character matrices assembled from semantic phenotypes retain most of the phylogenetic information of the original data set. C_LIO_LIOntologies will become an increasingly important tool not only for enabling prior anatomical knowledge to be integrated into phylogenetic methods but also to make morphological data FAIR compliant--a critical component of the ongoing phenomics revolution. Our new package offers key advancements toward this goal. C_LI

evolutionary biology↗

bioRxiv2022

Resolving ubiquitous model congruence in phylogenetics and its application for studying macroevolution

A recent study (Louca and Pennell, 2020) spotlighted the issue of model congruence, or asymptotic unidentifiability, in time-dependent birth-death models used for reconstructing species diversification histories on phylogenetic trees. The present work investigates this issue in state-dependent speciation and extinction (SSE) models, commonly used to study trait-dependent diversification. We found that model unidentifiability is universal due to hidden states, with every SSE belonging to an infinite congruence class. Notably, any trait-independent model is congruent with trait-dependent models, raising concerns for hypothesis testing. To address this, we propose an analytical solution that resolves model selection within a congruence class. Our findings show that this type of congruence is the only one possible, and with our solution in place, model unidentifiability in SSEs becomes absolutely harmless for inference. However, model selection across congruence classes remains challenging due to extremely high false positive rates. The discovered congruence offers a clear explanation of this issue and suggests potential ways forward.

evolutionary biology↗

bioRxiv2022

Exploring Taxonomic and Functional Microbiome of Hawaiian Stream and Spring Irrigation Water Systems Using Illumina and Oxford Nanopore Sequencing Platforms

Irrigation water is a potential source of contamination that carries plant and foodborne human pathogens and provides a niche for survival and proliferation of microbes in agricultural settings. This project investigated bacterial communities and their functions in the irrigation water from wetland taro farms on Oahu, Hawaii using different DNA sequencing platforms. Irrigation water samples (stream, spring, and tank stored water) were collected from North, East, and West sides of Oahu and subjected to high quality DNA isolation, library preparation and sequencing of the V3-V4 region, full length 16S rRNA, and shotgun metagenome sequencing using Illumina iSeq100, Oxford Nanopore MinION and Illumina NovaSeq, respectively. Illumina reads provided the most comprehensive taxonomic classification at the phylum level where Proteobacteria was identified as the most abundant phyla in river stream source and associated wet taro field water samples. Cyanobacteria was also a dominant phylum from tank and spring water, whereas Bacteroidetes were most abundant in wetland taro fields irrigated with spring water. However, over 50% of the valid short amplicon reads remained unclassified and inconclusive at the species level. Whereas samples sequenced for full length 16S rRNA and shotgun metagenome, clearly illustrated that Oxford Nanopore MinION is a better choice to classify the microbes to the genus and species levels. In terms of functional analyses, only 12% of the genes were shared by two consortia. Total 95 antibiotic resistant genes (ARGs) were detected with variable relative abundance. Description of microbial communities and their functions are essential for the development of better water management strategies to produce safer fresh produce and to protect plant, animal, human and environmental health. This project identified analytical tools to study microbiome of irrigation water.

microbiology↗

bioRxiv2022

Assessing Bayesian Phylogenetic Information Content of Morphological Data Using Knowledge from Anatomy Ontologies

Morphology remains a primary source of phylogenetic information for many groups of organisms, and the only one for most fossil taxa. Organismal anatomy is not a collection of randomly assembled and independent parts, but instead a set of dependent and hierarchically nested entities resulting from ontogeny and phylogeny. How do we make sense of these dependent and at times redundant characters? One promising approach is using ontologies--structured controlled vocabularies that summarize knowledge about different properties of anatomical entities, including developmental and structural dependencies. Here we assess whether the proximity of ontology-annotated characters within an ontology predicts evolutionary patterns. To do so, we measure phylogenetic information across characters and evaluate if it is hierarchically structured by ontological knowledge--in much the same way as phylogeny structures across-species diversity. We implement an approach to evaluate the Bayesian phylogenetic information (BPI) content and phylogenetic dissonance among ontology-annotated anatomical data subsets. We applied this to datasets representing two disparate animal groups: bees (Hexapoda: Hymenoptera: Apoidea, 209 chars) and characiform fishes (Actinopterygii: Ostariophysi: Characiformes, 463 chars). For bees, we find that BPI is not substantially structured by anatomy since dissonance is often high among morphologically related anatomical entities. For fishes, we find substantial information for two clusters of anatomical entities instantiating concepts from the jaws and branchial arch bones, but among-subset information decreases and dissonance increases substantially moving to higher level subsets in the ontology. We further applied our approach to address particular evolutionary hypotheses with an example of morphological evolution in miniature fishes. While we show that ontology does indeed structure phylogenetic information, additional relationships and processes, such as convergence, likely play a substantial role in explaining BPI and dissonance, and merit future investigation. Our work demonstrates how complex morphological datasets can be interrogated with ontologies by allowing one to access how information is spread hierarchically across anatomical concepts, how congruent this information is, and what sorts of processes may structure it: phylogeny, development, or convergence.

evolutionary biology↗

bioRxiv2020

Causal modeling refutes Hockett's hypothesis that bite configuration affects human sound evolution

Blasi et al. (Research article, 15 March 2019) argue in support of Hocketts hypothesis - that languages of hunter-gatherers are less likely to develop labiodental sounds than those of agricultural societies due to the formers heavy-wear diet that favors edge-to-edge bite, thereby decreasing likelihood of labiodental articulation. We reanalyze the data in Blasi et al. and find little to no support in favor of the Hocketts hypothesis. The negative association between labiodentals and hunter-gatherers instead appears to be an artifact of labiodental decline with increasing distance from Africa, which is a general trend of language phonemes.

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↗