Biotechnology Bulletin ›› 2024, Vol. 40 ›› Issue (2): 313-324.doi: 10.13560/j.cnki.biotech.bull.1985.2023-0748

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Trait-regulated-genes Ontology Model Construction and Application by Integrating Cross-species Scientific Data

ZHANG Dan-dan1(), ZHAO Rui-xue1,2(), XIAN Guo-jian1,3, XIONG He1   

  1. 1. Agricultural Information Institute of Chinese Academy of Agricultural Sciences, Beijing 100081
    2. Key Laboratory of Agricultural Integration Publishing Knowledge Mining and Knowledge Service, National Press and Publication Administration, Beijing 100081
    3. Key Laboratory of Agricultural Big Data, Ministry of Agriculture and Rural Affairs, Beijing 100081
  • Received:2023-08-05 Online:2024-02-26 Published:2024-03-13
  • Contact: ZHAO Rui-xue E-mail:zhangdandan01@caas.cn;zhaoruixue@caas.cn

Abstract:

【Objective】 With the proliferation of breeding data brought by new technologies and the new demand for knowledge services in computational breeding, in order to solve the problem of inefficient cross-species subject knowledge acquisition and difficult discovery of elite pleiotropic genes in crop breeding knowledge service.【Method】 We constructed trait-regulated-genes ontology model framework, and defined entity hierarchical structure and entity attributes in ontology model. Taking staple crops rice, corn, wheat and model plant Arabidopsis thalliana as data collection objects, a knowledge graph with trait-regulated-genes ontology model as model layer is constructed and experimented.【Result】 Finally, the trait-regulated-genes ontology model covering 13 entities, 16 data attributes and 14 object attributes was formed. This model is used as the knowledge graph of ontology layer to realize cross-species subject knowledge association retrieval, mining of elite pleiotropic genes and prediction of gene function across species.【Conclusion】 The method of trait-regulated-genes ontology model construction proposed in our study may achieve the correlation discovery of trait regulatory genes across species, improve the efficiency of cross-species subject knowledge acquisition, and support the gene discovery results of multi-dimensional data analysis. This study provides a feasible method path for the mining of pleiotropic genes and gene function prediction, and provides effective data support services for crop breeding scientific research.

Key words: ontology model, knowledge discovery, knowledge graph, cross-species, regulatory gene