Hayai-Annotation: A functional gene prediction tool that integrates orthologs and gene ontology for network analysis in plant species

被引:0
|
作者
Ghelfi, Andrea [1 ]
Isobe, Sachiko [2 ,3 ]
机构
[1] Natl Inst Genet, Bioinformat & DDBJ Ctr, Yata 1111, Mishima, Shizuoka 4118540, Japan
[2] Kazusa DNA Res Inst, Kazusa Kamatari 2-6-7, Kisarazu, Chiba 2920818, Japan
[3] Univ Tokyo, Grad Sch Agr & Life Sci, 1-1-1 Yayoi, Tokyo 1138657, Japan
来源
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL | 2025年 / 27卷
关键词
Functional annotation; Network analysis; GO enrichment; Ortholog inferences; Co-occurrence of orthologs and Gene; Ontologies;
D O I
10.1016/j.csbj.2024.12.011
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Hayai-Annotation, an annotation tool powered by the R-shinydashboard browser interface, implements a workflow that integrates sequence alignment using DIAMOND against UniProtKB Plants and ortholog inference using OrthoLoger. We here propose a pipeline to explore genome evolution and adaptation from a different perspective, by creating a network considering orthologs and gene ontology as nodes, with edges based on the annotation for each gene. This approach aims to improve the visualization of conserved biological processes and functions, highlight species-specific adaptations, and enhance the ability to infer the functions of uncharacterized genes by comparing edge patterns across species. To our knowledge, this is the first attempt to build a network using annotated OrthoDB orthologs and Gene Ontology terms (Molecular Function and Biological Process) as nodes, providing a comprehensive view of gene distribution and function in plant species. The GO annotation accuracy was assessed by the CAFA-evaluator, demonstrating that the accuracy of this version of HayaiAnnotation exceeded that of the benchmark, InterProScan. The updated Hayai-Annotation enhances ortholog analysis functionality, allowing for evolutionary insights from gene sequences, and is expected to contribute significantly to the future development of plant genome analysis.
引用
收藏
页码:117 / 126
页数:10
相关论文
empty
未找到相关数据