PearMODB

PearMODB provides an integrated multi-omics database for pear (Pyrus ssp.) genomics, genetics, and breeding by consolidating genome sequences, transcriptome profiles, epigenomic data, and population variation.

Key Features:

• Data Integration: Consolidates genome sequences, transcriptome profiles, epigenomic information, and population variation data for pear (Pyrus ssp.).
• Gene Search: Enables querying of specific genes within pear genomes.
• BLAST (Basic Local Alignment Search Tool): Facilitates sequence alignment searches against pear genomic datasets.
• JBrowse Visualization: Visualizes genomic features including DNA methylation sites and single-nucleotide polymorphisms (SNPs).
• Expression Heatmap: Visualizes transcriptome-derived gene expression patterns across tissues and conditions.
• Synteny Analysis: Identifies conserved genomic regions to support evolutionary and comparative studies among Rosaceae species.
• Primer Design Tool: Designs PCR primers for specific genomic regions.
• Genetic Polymorphism Exploration: Provides SNP and DNA methylation site annotations accessible via JBrowse for investigation of polymorphisms associated with phenotypic variation.
• Gene Family Compilation: Curates gene families including transcription factors, transcription regulators, and disease resistance genes such as nucleotide-binding site leucine-rich repeat proteins.
• Biosynthetic Gene Clusters (BGCs): Identifies BGCs within pear genomes and provides detailed pages describing clusters and their putative roles in secondary metabolite biosynthesis.

Scientific Applications:

• Genomic Research: Supports genome-wide association studies (GWAS) and comparative genomics to identify genetic markers linked to traits.
• Breeding Programs: Informs selection of parent lines by providing genetic variation and trait-associated data for hybridization decisions.
• Functional Genomics: Enables exploration of gene function and regulation using transcriptome and epigenetic datasets.
• Metabolic Pathway Analysis: Facilitates investigation of biosynthetic pathways and secondary metabolite diversity to study fruit quality and resistance traits.

Methodology:

PearMODB integrates genome sequences, transcriptomes, epigenomic data, and population variation with computational features including BLAST sequence alignment, JBrowse genome visualization, synteny analysis, expression heatmaps, primer design, gene family curation, biosynthetic gene cluster identification, and annotated SNP and DNA methylation sites.