GenoBridge streamlines plant trait prediction with a simplified genomic analysis pipeline
The rapid increase in the availability of genomic data has transformed plant breeding by enabling the prediction of complex traits directly from DNA markers. Genomic prediction provides a means to accelerate selection decisions, reduce phenotyping costs and shorten breeding cycles. Despite its promise, the practical implementation of genomic prediction remains challenging because prediction…
GenoBridge is an open-source analytical pipeline developed to simplify plant trait prediction through genomic analysis. As genomic data becomes more abundant, predicting complex traits from DNA markers has become crucial for plant breeding. However, implementing genomic prediction remains challenging due to varying performance across datasets and traits, requiring extensive expertise and computational resources.
GenoBridge integrates genomic prediction and genome-wide association analysis, automating model selection, performance evaluation, and trait-specific genetic discovery. The pipeline considers sample size and genetic architecture to determine analytical settings and evaluates multiple prediction methods using cross-validation. By evaluating prediction accuracy and uncertainty estimates, GenoBridge helps researchers assess model consistency.
Distinct from GWAS, GenoBridge assesses genomic predictability before proceeding to genetic association studies. Tested on datasets from Arabidopsis, rice, wheat, and grape, GenoBridge achieved comparable prediction accuracy to established methods without manual model selection. The pipeline successfully recovered known genetic associations, demonstrating its biological relevance and highlighting the complementary nature of prediction accuracy and association significance.
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