The yellow boxfish(Ostracion cubicus)exhibits a combination of derived morphological traits specialized for coral reef environments and ancestral characteristics,including a fused dermal plate.Contradictory evolutiona...The yellow boxfish(Ostracion cubicus)exhibits a combination of derived morphological traits specialized for coral reef environments and ancestral characteristics,including a fused dermal plate.Contradictory evolutionary evidence hinders true classification of O.cubicus.To clarify its evolutionary position within Tetraodontiformes,a chromosome-level genome assembly was generated,representing the most contiguous and complete genome to date for this lineage.Notably,O.cubicus possessed the largest genome within the order Tetraodontiformes,primarily due to extensive transposable element expansion.Phylogenetic analysis based on 19 whole genomes and 131 mitochondrial genomes resolved Tetraodontiformes into three major sister groups(Ostraciidae-Molidae,Tetraodontidae,and Balistidae-Monacanthidae).Comparative genomic evidence indicated that O.cubicus diverged early from the common ancestor of modern Tetraodontiformes and retained the highest number of HOX genes among surveyed taxa.Although overall genomic architecture was largely conserved,certain genetic and environmental changes may have contributed to its phenotypic adaptations,including climate cooling during the Miocene-Pliocene Transition,recent DNA and long interspersed nuclear element(LINE)transposon bursts,lineage-specific chromosomal rearrangements,and gene family expansion.Many positively selected genes and rapidly evolving genes were associated with skeletal development,including bmp7,egf7,and bmpr2.Transcriptomic comparisons between carapace and tail skin revealed various candidate genes and pathways related to carapace formation,such as postn,scpp1,and components of the TGF-βsignaling pathway.A derived amino acid substitution in eda,coupled with protein structural modeling,suggested potential molecular convergence in dermal plate formation among teleosts.These findings provide novel insights into the genomic and developmental basis of carapace evolution and coral reef-adaptation in O.cubicus,offering a strong case for evolutionary balance between genomic conservation with regulatory innovation to achieve coral reef specialization.展开更多
Purpose:Due to the incompleteness nature of knowledge graphs(KGs),the task of predicting missing links between entities becomes important.Many previous approaches are static,this posed a notable problem that all meani...Purpose:Due to the incompleteness nature of knowledge graphs(KGs),the task of predicting missing links between entities becomes important.Many previous approaches are static,this posed a notable problem that all meanings of a polysemous entity share one embedding vector.This study aims to propose a polysemous embedding approach,named KG embedding under relational contexts(ContE for short),for missing link prediction.Design/methodology/approach:ContE models and infers different relationship patterns by considering the context of the relationship,which is implicit in the local neighborhood of the relationship.The forward and backward impacts of the relationship in ContE are mapped to two different embedding vectors,which represent the contextual information of the relationship.Then,according to the position of the entity,the entity’s polysemous representation is obtained by adding its static embedding vector to the corresponding context vector of the relationship.Findings:ContE is a fully expressive,that is,given any ground truth over the triples,there are embedding assignments to entities and relations that can precisely separate the true triples from false ones.ContE is capable of modeling four connectivity patterns such as symmetry,antisymmetry,inversion and composition.Research limitations:ContE needs to do a grid search to find best parameters to get best performance in practice,which is a time-consuming task.Sometimes,it requires longer entity vectors to get better performance than some other models.Practical implications:ContE is a bilinear model,which is a quite simple model that could be applied to large-scale KGs.By considering contexts of relations,ContE can distinguish the exact meaning of an entity in different triples so that when performing compositional reasoning,it is capable to infer the connectivity patterns of relations and achieves good performance on link prediction tasks.Originality/value:ContE considers the contexts of entities in terms of their positions in triples and the relationships they link to.It decomposes a relation vector into two vectors,namely,forward impact vector and backward impact vector in order to capture the relational contexts.ContE has the same low computational complexity as TransE.Therefore,it provides a new approach for contextualized knowledge graph embedding.展开更多
基金supported by the Basic and Applied Basic Research Foundation of Guangdong Province(2020A1515110882)National Science Fund for Distinguished Young Scholars(32225049)。
文摘The yellow boxfish(Ostracion cubicus)exhibits a combination of derived morphological traits specialized for coral reef environments and ancestral characteristics,including a fused dermal plate.Contradictory evolutionary evidence hinders true classification of O.cubicus.To clarify its evolutionary position within Tetraodontiformes,a chromosome-level genome assembly was generated,representing the most contiguous and complete genome to date for this lineage.Notably,O.cubicus possessed the largest genome within the order Tetraodontiformes,primarily due to extensive transposable element expansion.Phylogenetic analysis based on 19 whole genomes and 131 mitochondrial genomes resolved Tetraodontiformes into three major sister groups(Ostraciidae-Molidae,Tetraodontidae,and Balistidae-Monacanthidae).Comparative genomic evidence indicated that O.cubicus diverged early from the common ancestor of modern Tetraodontiformes and retained the highest number of HOX genes among surveyed taxa.Although overall genomic architecture was largely conserved,certain genetic and environmental changes may have contributed to its phenotypic adaptations,including climate cooling during the Miocene-Pliocene Transition,recent DNA and long interspersed nuclear element(LINE)transposon bursts,lineage-specific chromosomal rearrangements,and gene family expansion.Many positively selected genes and rapidly evolving genes were associated with skeletal development,including bmp7,egf7,and bmpr2.Transcriptomic comparisons between carapace and tail skin revealed various candidate genes and pathways related to carapace formation,such as postn,scpp1,and components of the TGF-βsignaling pathway.A derived amino acid substitution in eda,coupled with protein structural modeling,suggested potential molecular convergence in dermal plate formation among teleosts.These findings provide novel insights into the genomic and developmental basis of carapace evolution and coral reef-adaptation in O.cubicus,offering a strong case for evolutionary balance between genomic conservation with regulatory innovation to achieve coral reef specialization.
基金supported by the Key R&D Program Project of Zhejiang Province under Grant no.2019 C01004 and 2021C02004.
文摘Purpose:Due to the incompleteness nature of knowledge graphs(KGs),the task of predicting missing links between entities becomes important.Many previous approaches are static,this posed a notable problem that all meanings of a polysemous entity share one embedding vector.This study aims to propose a polysemous embedding approach,named KG embedding under relational contexts(ContE for short),for missing link prediction.Design/methodology/approach:ContE models and infers different relationship patterns by considering the context of the relationship,which is implicit in the local neighborhood of the relationship.The forward and backward impacts of the relationship in ContE are mapped to two different embedding vectors,which represent the contextual information of the relationship.Then,according to the position of the entity,the entity’s polysemous representation is obtained by adding its static embedding vector to the corresponding context vector of the relationship.Findings:ContE is a fully expressive,that is,given any ground truth over the triples,there are embedding assignments to entities and relations that can precisely separate the true triples from false ones.ContE is capable of modeling four connectivity patterns such as symmetry,antisymmetry,inversion and composition.Research limitations:ContE needs to do a grid search to find best parameters to get best performance in practice,which is a time-consuming task.Sometimes,it requires longer entity vectors to get better performance than some other models.Practical implications:ContE is a bilinear model,which is a quite simple model that could be applied to large-scale KGs.By considering contexts of relations,ContE can distinguish the exact meaning of an entity in different triples so that when performing compositional reasoning,it is capable to infer the connectivity patterns of relations and achieves good performance on link prediction tasks.Originality/value:ContE considers the contexts of entities in terms of their positions in triples and the relationships they link to.It decomposes a relation vector into two vectors,namely,forward impact vector and backward impact vector in order to capture the relational contexts.ContE has the same low computational complexity as TransE.Therefore,it provides a new approach for contextualized knowledge graph embedding.
