PearMODB: a multiomics database for pear (Pyrus) genomics, genetics and breeding study

Area of Science:

• Plant genomics
• Bioinformatics
• Agricultural science

Background:

• Pear (Pyrus ssp.) is a globally significant fruit crop facing challenges with increasing multiomics data.
• Effective data integration and analysis are crucial for advancing pear research and breeding.

Purpose of the Study:

• To construct a comprehensive Pear Multiomics Database (PearMODB).
• To provide an accessible platform for analyzing integrated genome, transcriptome, epigenome, and population variation data in pear.
• To facilitate research in pear genomics, genetics, and breeding.

Main Methods:

• Integrated multiomics data including genome, transcriptome, epigenome, and population variation.
• Developed a web portal with tools for gene search, BLAST, JBrowse, expression heatmap, synteny analysis, and primer design.
• Identified and compiled gene families (transcription factors, regulators, disease resistance) and biosynthetic gene clusters (BGCs).

Main Results:

• Successfully constructed PearMODB, a centralized resource for pear multiomics data.
• Implemented interactive tools for data retrieval, visualization, and analysis, including custom JBrowse for DNA methylation and SNP data.
• Discovered and cataloged gene families and BGCs, enabling deeper insights into metabolic diversity and genetic variation.
• Database URL: http://pearomics.njau.edu.cn.

Conclusions:

• PearMODB serves as a valuable platform for advancing pear genomics, genetics, and breeding studies.
• The database facilitates exploration of genotype-phenotype relationships and metabolic diversity.
• Provides essential resources for researchers working on pear improvement and understanding genetic diversity.