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Assessing Bayesian Phylogenetic Information Content of Morphological Data Using Knowledge From Anatomy Ontologies.
Porto, Diego S; Dahdul, Wasila M; Lapp, Hilmar; Balhoff, James P; Vision, Todd J; Mabee, Paula M; Uyeda, Josef.
Afiliação
  • Porto DS; Department of Biological Sciences, Virginia Polytechnic Institute, State University, 926 West Campus Drive, Blacksburg, VA 24061, USA.
  • Dahdul WM; UCI Libraries, University of California, Irvine, Irvine, CA 92623, USA.
  • Lapp H; Department of Biology, University of South Dakota, 414 East Clark Street, Vermillion, SD 57069, USA.
  • Balhoff JP; Center for Genomic and Computational Biology, Duke University, 101 Science Drive, Durham, NC 27708, USA.
  • Vision TJ; Renaissance Computing Institute, University of North Carolina, 100 Europa Drive, Suite 540, Chapel Hill, NC 27517, USA.
  • Mabee PM; Department of Biology and School of Information and Library Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Uyeda J; Department of Biology, University of South Dakota, 414 East Clark Street, Vermillion, SD 57069, USA.
Syst Biol ; 71(6): 1290-1306, 2022 10 12.
Article em En | MEDLINE | ID: mdl-35285502
ABSTRACT
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 evolutionary patterns can explain the proximity of ontology-annotated characters within an ontology. To do so, we measure phylogenetic information across characters and evaluate if it matches the hierarchical structure given by ontological knowledge-in much the same way as across-species diversity structure is given by phylogeny. 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 data sets 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 explained 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 phylogenetic information does match ontology structure for some anatomical entities, 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 data sets 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 play a role in explaining it phylogeny, development, or convergence. [Apidae; Bayesian phylogenetic information; Ostariophysi; Phenoscape; phylogenetic dissonance; semantic similarity.].
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Artrópodes / Caraciformes Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Artrópodes / Caraciformes Idioma: En Ano de publicação: 2022 Tipo de documento: Article