Dataset Information

Shared ecological traits influence shape of the skeleton in flatfishes (Pleuronectiformes).

ABSTRACT: In the age of phylogenetic comparative methods, evolutionary biologists have been able to explore evolutionary trends in form in unique and extraordinarily diverse groups of animals. Pleuronectiformes, commonly known as flatfishes, is a diverse and specialized order of fishes that have remarkable asymmetry induced by ocular migration and a benthic life style. Although flatfishes are unique from other fishes, species within the group are morphologically diverse. The origin of ocular migration has been a primary focus of research; however, little is known about overall shape diversification among the flatfishes. In this study, we use integrative methods to examine how body shape evolved within the flatfishes. Shape was quantified from X-rays using geometric morphometrics for 389 individuals across 145 species. The most recent and robust phylogeny was overlaid onto the morphospace and phylogenetic signal was calculated to ascertain convergence in the morphospace. In addition, phylogenetic linear models were employed to determine if ecological traits were correlated with shape and if size had an effect on overall body shape. Results revealed that the majority of variation evolved recently, within the past 15-10-million-years in the middle Miocene, and is highly variable within the flatfishes. These changes are best summarized by body depth, jaw length and medial fin length. Dorsal and anal fin length are correlated, which may be due to the unique mode of locomotion used by flatfishes. A phylogenetic linear model and phylomorphospace analysis suggested that several ecological traits are correlated with shape, which indicates an ecological role in the diversification of flatfishes.

SUBMITTER: Black CR

PROVIDER: S-EPMC7134016 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Shared ecological traits influence shape of the skeleton in flatfishes (Pleuronectiformes).

Black Corinthia R CR Berendzen Peter B PB

PeerJ 20200403

In the age of phylogenetic comparative methods, evolutionary biologists have been able to explore evolutionary trends in form in unique and extraordinarily diverse groups of animals. Pleuronectiformes, commonly known as flatfishes, is a diverse and specialized order of fishes that have remarkable asymmetry induced by ocular migration and a benthic life style. Although flatfishes are unique from other fishes, species within the group are morphologically diverse. The origin of ocular migration has ...[more]

PMID: 32280569

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Project description:BackgroundNeurons are the basic structural unit of the brain, and their morphology is a key determinant of their classification. The morphology of a neuronal circuit is a fundamental component in neuron modeling. Recently, single-neuron morphologies of the whole brain have been used in many studies. The correctness and completeness of semimanually traced neuronal morphology are credible. However, there are some inaccuracies in semimanual tracing results. The distance between consecutive nodes marked by humans is very long, spanning multiple voxels. On the other hand, the nodes are marked around the centerline of the neuronal fiber, not on the centerline. Although these inaccuracies do not seriously affect the projection patterns that these studies focus on, they reduce the accuracy of the traced neuronal skeletons. These small inaccuracies will introduce deviations into subsequent studies that are based on neuronal morphology files.ResultsWe propose a neuronal digital skeleton optimization method to evaluate and make fine adjustments to a digital skeleton after neuron tracing. Provided that the neuronal fiber shape is smooth and continuous, we describe its physical properties according to two shape restrictions. One restriction is designed based on the grayscale image, and the other is designed based on geometry. These two restrictions are designed to finely adjust the digital skeleton points to the neuronal fiber centerline. With this method, we design the three-dimensional shape restriction workflow of neuronal skeleton adjustment computation. The performance of the proposed method has been quantitatively evaluated using synthetic and real neuronal image data. The results show that our method can reduce the difference between the traced neuronal skeleton and the centerline of the neuronal fiber. Furthermore, morphology metrics such as the neuronal fiber length and radius become more precise.ConclusionsThis method can improve the accuracy of a neuronal digital skeleton based on traced results. The greater the accuracy of the digital skeletons that are acquired, the more precise the neuronal morphologies that are analyzed will be.

Dataset Information

Shared ecological traits influence shape of the skeleton in flatfishes (Pleuronectiformes).

Publications

Shared ecological traits influence shape of the skeleton in flatfishes (Pleuronectiformes).

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