Mapping molar shapes on signaling pathways

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dc.contributor.author Morita, Wataru
dc.contributor.author Morimoto, Naoki
dc.contributor.author Jernvall, Jukka
dc.date.accessioned 2021-01-08T14:14:01Z
dc.date.available 2021-01-08T14:14:01Z
dc.date.issued 2020-12
dc.identifier.citation Morita , W , Morimoto , N & Jernvall , J 2020 , ' Mapping molar shapes on signaling pathways ' , PLoS Computational Biology , vol. 16 , no. 12 , 1008436 . https://doi.org/10.1371/journal.pcbi.1008436
dc.identifier.other PURE: 158814551
dc.identifier.other PURE UUID: b1aef804-e067-4636-9c56-ff648d5c6f84
dc.identifier.other WOS: 000600141200011
dc.identifier.uri http://hdl.handle.net/10138/324316
dc.description.abstract A major challenge in evolutionary developmental biology is to understand how genetic mutations underlie phenotypic changes. In principle, selective pressures on the phenotype screen the gene pool of the population. Teeth are an excellent model for understanding evolutionary changes in the genotype-phenotype relationship since they exist throughout vertebrates. Genetically modified mice (mutants) with abnormalities in teeth have been used to explore tooth development. The relationship between signaling pathways and molar shape, however, remains elusive due to the high intrinsic complexity of tooth crowns. This hampers our understanding of the extent to which developmental factors explored in mutants explain developmental and phenotypic variation in natural species that represent the consequence of natural selection. Here we combine a novel morphometric method with two kinds of data mining techniques to extract data sets from the three-dimensional surface models of lower first molars: i) machine learning to maximize classification accuracy of 22 mutants, and ii) phylogenetic signal for 31 Murinae species. Major shape variation among mutants is explained by the number of cusps and cusp distribution on a tooth crown. The distribution of mutant mice in morphospace suggests a nonlinear relationship between the signaling pathways and molar shape variation. Comparative analysis of mutants and wild murines reveals that mutant variation overlaps naturally occurring diversity, including more ancestral and derived morphologies. However, taxa with transverse lophs are not fully covered by mutant variation, suggesting experimentally unexplored developmental factors in the evolutionary radiation of Murines. Author summary Teeth are found in almost all vertebrates, and they show many different morphologies. In mammals, especially the cheek teeth or molars are highly diverse in shape, reflecting a vast range of dietary habits and efficiency of occlusion. As teeth are the most durable part of the body, they preserve well in the fossil record. The diversity of molar fossils has been useful in reconstructing the diet and phylogeny of extinct mammals. Genetically modified mice (mutants) show diverse modifications of their molar morphology, but we lack computational tools to test to what extent mutant morphologies account for the natural diversity found in the wild. We developed data mining using machine learning and phylogeny-based methods to analyze three-dimensional molar shapes in mouse mutants and natural species. Although many mutants and species have comparable features, most of the mutant molar variation covers the more evolutionarily ancestral than the more evolutionary derived shapes. Yet to be explored developmental factors may underly the more extreme shapes. en
dc.format.extent 14
dc.language.iso eng
dc.relation.ispartof PLoS Computational Biology
dc.rights cc_by
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject PHYLOGENETIC SIGNAL
dc.subject TOOTH DEVELOPMENT
dc.subject R PACKAGE
dc.subject SIMILARITY
dc.subject BIOLOGY
dc.subject TEETH
dc.subject 1184 Genetics, developmental biology, physiology
dc.title Mapping molar shapes on signaling pathways en
dc.type Article
dc.contributor.organization Department of Geosciences and Geography
dc.contributor.organization Biosciences
dc.contributor.organization Institute of Biotechnology
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.1371/journal.pcbi.1008436
dc.relation.issn 1553-734X
dc.rights.accesslevel openAccess
dc.type.version publishedVersion

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