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Phenotypic variability is ubiquitous. This is especially true in bats where families such as Phyllostomidae encompass as much phenotypic variability as some entire orders of mammals. Typically, phenotypic variability is characterized based on cranial morphology with studies of other functionally important aspects of the phenotype such as legs, feet and wings less frequent. We examined patterns of secondary-sexual dimorphism and allometry of wing elements of the fringed fruit-eating bat (Artibeus fimbriatus) as well as examined for the first time modularity of bat wings. Patterns were based on 13 wing measurements taken from 21 female and 15 males from eastern Paraguay. From a multivariate perspective A. fimbriatus exhibited significant secondary-sexual dimorphism. Females were larger than males for all 13 wing characteristics with significant differences involving the last phalanx of the 4th and 5th digits. Female wings were also relatively larger than male wings from a multivariate perspective as well as the last phalanx of the 4th and 5th digit, after adjusting for wing size based on forearm length. Wing elements were highly variable regarding allometric relationships with some exhibiting no allometric patterns, and others exhibiting isometry or hyperallometry depending on the element. Wings exhibited significant modularity with metacarpals, proximal phalanges and distal phalanges each representing a discrete module. Wings of A. fimbriatus exhibit substantive patterns of dimorphism, allometry and modularity. While the Big Mother Hypothesis is a strong theoretical construct to explain wing dimorphism, there is yet no sound theoretical basis to patterns of allometry and modularity of the wing. Indeed, trying to understand the determinants of variation in wing morphology is ripe for future investigation.
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MAPPER: An Open-Source, High-Dimensional Image Analysis Pipeline Unmasks Differential Regulation of Drosophila Wing Features
Phenomics requires quantification of large volumes of image data, necessitating high throughput image processing approaches. Existing image processing pipelines for Drosophila wings, a powerful genetic model for studying the underlying genetics for a broad range of cellular and developmental processes, are limited in speed, precision, and functional versatility. To expand on the utility of the wing as a phenotypic screening system, we developed MAPPER, an automated machine learning-based pipeline that quantifies high-dimensional phenotypic signatures, with each dimension quantifying a unique morphological feature of the Drosophila wing. MAPPER magnifies the power of Drosophila phenomics by rapidly quantifying subtle phenotypic differences in sample populations. We benchmarked MAPPER’s accuracy and precision in replicating manual measurements to demonstrate its widespread utility. The morphological features extracted using MAPPER reveal variable sexual dimorphism across Drosophila species and unique underlying sex-specific differences in morphogen signaling in male and female wings. Moreover, the length of the proximal-distal axis across the species and sexes shows a conserved scaling relationship with respect to the wing size. In sum, MAPPER is an open-source tool for rapid, high-dimensional analysis of large imaging datasets. These high-content phenomic capabilities enable rigorous and systematic identification of genotype-to-phenotype relationships in a broad range of screening and drug testing applications and amplify the potential power of multimodal genomic approaches.
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- Award ID(s):
- 1764421
- PAR ID:
- 10427828
- Date Published:
- Journal Name:
- Frontiers in Genetics
- Volume:
- 13
- ISSN:
- 1664-8021
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/fgene.2022.869719
