BarleyNet

BarleyNet provides a co-functional gene network and network-based prioritization algorithms to infer gene functions and prioritize candidate genes for systems genetics analysis of cultivated barley (Hordeum vulgare L.).

Key Features:

• Co-Functional Gene Network: A network comprising 26,145 barley genes constructed from integrated genomic and functional data to represent co-functional relationships.
• IBSC_v2 Genomic Integration: Incorporates genomic information from the IBSC_v2 genome assembly and barley-specific gene expression profiles for network construction.
• Bayesian Statistics-Based Approach: Uses Bayesian statistics to combine prior knowledge derived from forward- or reverse-genetics studies with network data for gene prioritization and function inference.
• Three In Silico Gene/Function Prioritization Algorithms: Implements Pathway-Centric Search to identify candidate pathway or trait-associated genes, Gene-Centric Search to infer novel functional concepts for specific genes, and Context-Centric Search to detect genes linked to stress responses.
• Integrated Proteomics and Transcriptomics: Integrates proteomics and transcriptomics data from barley leaves and roots collected under drought and heat stresses.

Scientific Applications:

• Complex trait dissection: Prioritizes candidate genes underlying complex traits, including environmental stress responses such as drought and heat.
• Functional inference: Infers functions for unannotated barley genes by exploiting co-functional links in the network.
• Stress-response genetics: Identifies genes and alleles associated with responses in leaves and roots under drought or heat stresses for downstream genetic and breeding studies.

Methodology:

Construction of a comprehensive co-functional gene network integrating IBSC_v2 genomic data and barley-specific expression data; application of Bayesian statistics to combine prior forward- or reverse-genetics knowledge with network data; and implementation of Pathway-Centric, Gene-Centric, and Context-Centric prioritization algorithms.