Awards issued prior to january 20, 2025, were funded under previous administrations and may not reflect the priorities and policies of the current administration.** economic challenges imposed by…

Awards issued prior to january 20, 2025, were funded under previous administrations and may not reflect the priorities and policies of the current administration.** economic challenges imposed by climate change and disease on the aquaculture industry necessitate advances for improved animal welfare and resiliency. Biomarkers associated with environmental and disease resilience traits can be leveraged in breeding and management strategies. However, their discovery has been limited in part by the complexity of molecular systems and the cost of genomics tools used to understand them. Advances in computational approaches including machine learning algorithms, together with the wealth of genomic data that has amassed, enable powerful meta-analyses for improved biomarker discovery in aquaculture species. The proposed project aims to advance the discovery and characterization of biomarkers through mining publicly available shellfish genomic datasets from resilient populations. The objectives are to 1) develop standardized open-access, user-friendly, reproducible bioinformatics pipelines for resilience biomarker discovery through systematic reanalysis, data integration and meta-analysis and 2) build a user-friendly open-access comprehensive database of candidate resilience biomarkers that is widely available for use by the aquaculture community. The resulting database will enable improved molecular tool development for more efficient phenotype selection and health monitoring, relevant to the afri animal genomics program area priority goal of increasing animal fitness and improving animal welfare as well as the priority of implementing selection methods that use a systems biology approach for simultaneous improvement of multiple traits.