Automated Integration of Trees and Traits: A Case Study Using Paired Fin Loss Across Teleost Fishes

Formalizing Invertebrate Morphological Data: A Descriptive Model for Cuticle-Based Skeleto-Muscular Systems, an Ontology for Insect Anatomy, and their Potential Applications in Biodiversity Research and Informatics

The spectacular radiation of insects has produced a stunning diversity of phenotypes. During the past 250 years, research on insect systematics has generated hundreds of terms for naming and comparing them. In its current form, this terminological diversity is presented in natural language and lacks formalization, which prohibits computer-assisted comparison using semantic web technologies. Here we propose a Model for Describing Cuticular Anatomical Structures (MoDCAS) which incorporates structural properties and positional relationships for standardized, consistent, and reproducible descriptions of arthropod phenotypes. We applied the MoDCAS framework in creating the ontology for the Anatomy of the Insect Skeleto-Muscular system (AISM). The AISM is the first general insect ontology that aims to cover all taxa by providing generalized, fully logical, and queryable, definitions for each term. It was built using the Ontology Development Kit (ODK), which maximizes interoperability with Uberon (Uberon multispecies anatomy ontology) and other basic ontologies, enhancing the integration of insect anatomy into the broader biological sciences. A template system for adding new terms, extending, and linking the AISM to additional anatomical, phenotypic, genetic, and chemical ontologies is also introduced. The AISM is proposed as the backbone for taxon-specific insect ontologies and has potential applications spanning systematic biology and biodiversity informatics, allowing users to: 1) use controlled vocabularies and create semiautomated computer-parsable insect morphological descriptions; 2) integrate insect morphology into broader fields of research, including ontology-informed phylogenetic methods, logical homology hypothesis testing, evo-devo studies, and genotype to phenotype mapping; and 3) automate the extraction of morphological data from the literature, enabling the generation of large-scale phenomic data, by facilitating the production and testing of informatic tools able to extract, link, annotate, and process morphological data. This descriptive model and its ontological applications will allow for clear and semantically interoperable integration of arthropod phenotypes in biodiversity studies.

Stock structure analysis of the endemic fish, Barbodes carnaticus (Jerdon 1849), for conservation in a biodiversity hotspot

The population structure of Barbodes carnaticus species was studied using conventional (based on body morphometrics and meristic) and image-based analysis (truss network system) methods. The study was carried out with four stocks, namely Karnataka (KA) and Tamil Nadu (TN) stocks from the River Cauvery, Kerala (KE) stock from the River Chalakudy and farm-reared stock (CI) from Central Institute of Freshwater Aquaculture, Bangalore. A total of 27 morphometric, 9 meristic and 30 truss measurements were used in the study for the stock structure. Fifteen landmarks were used to generate 30 truss distance measurements. The principal component analysis (PCA), factor analysis (FA), discriminant function analysis (DFA) and cluster analysis (CA) were deployed to determine the variation using both the conventional and truss variables. Variations (86.9%) among the morphometric characters were explained by five principal components, while four principal components explain 96.01% of the variation among the truss distances. DFA using conventional method correctly classified 100% of the original grouped classes of the KA, KE and CI and 93.8% of TN stocks. The DFA employed with truss distance was classified into the stocks CI, KA, KE and TN, and the values are 100, 89.1, 8.6 and 6.1%, respectively. Factor analysis based on truss morphometry showed that factor one is related to body shape and factor two is related to head shape. Two clusters were identified in both the conventional and the truss distance analysis. Truss distance-based cluster showed that the KE and CI stocks are similar compared to the TN stock. In contrary, morphometry-based cluster showed the KE and TN stocks are similar compared to CI stock. The multivariate analysis showed that the farm-reared stock (CI) is different from the wild stocks (KA, KE and TN). This study explained that the combination of the conventional and image-based truss network analysis helps to discriminate various stocks of B. carnaticus. Based on the PCA, bilinear data models were generated using R 3.5.3 software for predicting the stock of each individual. Stock discrimination of this species was mainly due to the geographic isolation, river ecology and temperature variations. The stocks of B. carnaticus are highly exploited from the studied rivers, and the species is an important candidate for species diversification to enhance aquaculture production. Within stock variations are found to be minimum in the present morphometric study, hence the gene pool identification and marker study are required for better understanding of the stocks. This stock structure study may help to develop conservation programmes for this endemic species through a more scientific approach.

A Logical Model of Homology for Comparative Biology

There is a growing body of research on the evolution of anatomy in a wide variety of organisms. Discoveries in this field could be greatly accelerated by computational methods and resources that enable these findings to be compared across different studies and different organisms and linked with the genes responsible for anatomical modifications. Homology is a key concept in comparative anatomy; two important types are historical homology (the similarity of organisms due to common ancestry) and serial homology (the similarity of repeated structures within an organism). We explored how to most effectively represent historical and serial homology across anatomical structures to facilitate computational reasoning. We assembled a collection of homology assertions from the literature with a set of taxon phenotypes for the skeletal elements of vertebrate fins and limbs from the Phenoscape Knowledgebase. Using seven competency questions, we evaluated the reasoning ramifications of two logical models: the Reciprocal Existential Axioms (REA) homology model and the Ancestral Value Axioms (AVA) homology model. The AVA model returned all user-expected results in addition to the search term and any of its subclasses. The AVA model also returns any superclass of the query term in which a homology relationship has been asserted. The REA model returned the user-expected results for five out of seven queries. We identify some challenges of implementing complete homology queries due to limitations of OWL reasoning. This work lays the foundation for homology reasoning to be incorporated into other ontology-based tools, such as those that enable synthetic supermatrix construction and candidate gene discovery. [Homology; ontology; anatomy; morphology; evolution; knowledgebase; phenoscape.].

Using text-mined trait data to test for cooperate-and-radiate co-evolution between ants and plants

Mutualisms may be “key innovations” that spur lineage diversification by augmenting niche breadth, geographic range, or population size, thereby increasing speciation rates or decreasing extinction rates. Whether mutualism accelerates diversification in both interacting lineages is an open question. Research suggests that plants that attract ant mutualists have higher diversification rates than non-ant associated lineages. We ask whether the reciprocal is true: does the interaction between ants and plants also accelerate diversification in ants, i.e. do ants and plants cooperate-and-radiate? We used a novel text-mining approach to determine which ant species associate with plants in defensive or seed dispersal mutualisms. We investigated patterns of lineage diversification across a recent ant phylogeny using BiSSE, BAMM, and HiSSE models. Ants that associate mutualistically with plants had elevated diversification rates compared to non-mutualistic ants in the BiSSE model, with a similar trend in BAMM, suggesting ants and plants cooperate-and-radiate. However, the best-fitting model was a HiSSE model with a hidden state, meaning that diversification models that do not account for unmeasured traits are inappropriate to assess the relationship between mutualism and ant diversification. Against a backdrop of diversification rate heterogeneity, the best-fitting HiSSE model found that mutualism actually decreases diversification: mutualism evolved much more frequently in rapidly diversifying ant lineages, but then subsequently slowed diversification. Thus, it appears that ant lineages first radiated, then cooperated with plants.

Many plants and animals depend on other species for nutrition, protection, or dispersal, a type of ecological interaction known as mutualism. Mutualisms often help organisms thrive in new or harsh environments, thereby increasing their ecological success. We studied whether mutualism also increases evolutionary success by affecting lineage diversification, or the net result of the formation and loss of species over evolutionary time (i.e., speciation minus extinction). We focused on the widespread mutualism between ants and plants, in which ants act as protective ‘bodyguards’ or seed dispersers for plants and gain food or shelter in return. Previous research has found that the evolution of ant-plant mutualisms increased plant diversification. Here, we asked whether the same is true for ant diversification. We used a novel, automated approach to gather trait data from the abstracts of over 89,000 scientific articles about ants, and identified 432 mutualistic ant species and 2,909 non-mutualistic ant species. We then used this trait information to model how mutualism has evolved and influenced diversification across a recent ant phylogeny. Our analysis suggests that instead of causally enhancing diversification, mutualism evolves more often in lineages that are already diversifying quickly and then slows ant diversification.

Genome Sequencing of the Japanese Eel (Anguilla japonica) for Comparative Genomic Studies on tbx4 and a tbx4 Gene Cluster in Teleost Fishes

Limbs originated from paired fish fins are an important innovation in Gnathostomata. Many studies have focused on limb development-related genes, of which the T-box transcription factor 4 gene (tbx4) has been considered as one of the most essential factors in the regulation of the hindlimb development. We previously confirmed pelvic fin loss in tbx4-knockout zebrafish. Here, we report a high-quality genome assembly of the Japanese eel (Anguilla japonica), which is an economically important fish without pelvic fins. The assembled genome is 1.13 Gb in size, with a scaffold N50 of 1.03 Mb. In addition, we collected 24 tbx4 sequences from 22 teleost fishes to explore the correlation between tbx4 and pelvic fin evolution. However, we observed complete exon structures of tbx4 in several pelvic-fin-loss species such as Ocean sunfish (Mola mola) and ricefield eel (Monopterus albus). More interestingly, an inversion of a special tbx4 gene cluster (brip1-tbx4-tbx2b- bcas3) occurred twice independently, which coincides with the presence of fin spines. A nonsynonymous mutation (M82L) was identified in the nuclear localization sequence (NLS) of the Japanese eel tbx4. We also examined variation and loss of hindlimb enhancer B (HLEB), which may account for pelvic fin loss in Tetraodontidae and Diodontidae. In summary, we generated a genome assembly of the Japanese eel, which provides a valuable genomic resource to study the evolution of fish tbx4 and helps elucidate the mechanism of pelvic fin loss in teleost fishes. Our comparative genomic studies, revealed for the first time a potential correlation between the tbx4 gene cluster and the evolutionary development of toxic fin spines. Because fin spines in teleosts are usually venoms, this tbx4 gene cluster may facilitate the genetic engineering of toxin-related marine drugs.