H2DB: a heritability database across multiple species by annotating trait-associated genomic loci

Area of Science:

• Genetics
• Bioinformatics
• Database Development

Background:

• Heritability estimates are crucial for understanding trait inheritance in various species.
• Existing research often focuses on individual species (e.g., human twin studies, animal/plant breeding).
• A comprehensive, cross-species heritability database was lacking.

Purpose of the Study:

• To introduce H2DB, a novel annotation database for genetic heritability estimates.
• To consolidate heritability data from diverse species into a single resource.
• To facilitate the connection between phenotypic traits and associated genomic loci.

Main Methods:

• Manual curation of publicly available resources, including PubMed abstracts and journal content.
• Annotation of heritability data with trait descriptions, experimental conditions, and genomic loci.
• Assignment of phenotype ontologies to annotated traits for classification.

Main Results:

• H2DB provides a centralized repository of genetic heritability estimates for multiple species.
• The database includes detailed attribute information, such as trait descriptions and genomic loci (e.g., SNPs from GWAS).
• Phenotype ontologies enable analysis of heritability patterns across different phenotypic classifications.

Conclusions:

• H2DB serves as a valuable knowledge base for researchers studying genetic heritability.
• The database facilitates the identification of trait-associated genomic loci, supporting experimental investigations.
• H2DB promotes a deeper understanding of heritability across species by enabling cross-phenotypic and cross-species comparisons.