ECONOMIC CHALLENGES IMPOSED BY CLIMATE CHANGE AND DISEASE ON THE AQUACULTURE INDUSTRYNECESSITATE ADVANCES FOR IMPROVED ANIMAL WELFARE AND RESILIENCY. BIOMARKERS ASSOCIATED WITHENVIRONMENTAL AND DISEASE RESILIENCE TRAITS CAN BE LEVERAGED IN BREEDING AND MANAGEMENTSTRATEGIES. HOWEVER, THEIR DISCOVERY HAS BEEN LIMITED IN PART BY THE COMPLEXITY OF MOLECULARSYSTEMS AND THE COST OF GENOMICS TOOLS USED TO UNDERSTAND THEM. ADVANCES IN COMPUTATIONALAPPROACHES INCLUDING MACHINE LEARNING ALGORITHMS, TOGETHER WITH THE WEALTH OF GENOMIC DATA THATHAS AMASSED, ENABLE POWERFUL META-ANALYSES FOR IMPROVED BIOMARKER DISCOVERY IN AQUACULTURESPECIES. THE PROPOSED PROJECT AIMS TO ADVANCE THE DISCOVERY AND CHARACTERIZATION OF BIOMARKERSTHROUGH MINING PUBLICLY AVAILABLE SHELLFISH GENOMIC DATASETS FROM RESILIENT POPULATIONS. THEOBJECTIVES ARE TO 1) DEVELOP STANDARDIZED OPEN-ACCESS, USER-FRIENDLY, REPRODUCIBLE BIOINFORMATICSPIPELINES FOR RESILIENCE BIOMARKER DISCOVERY THROUGH SYSTEMATIC REANALYSIS, DATA INTEGRATION ANDMETA-ANALYSIS AND 2) BUILD A USER-FRIENDLY OPEN-ACCESS COMPREHENSIVE DATABASE OF CANDIDATERESILIENCE BIOMARKERS THAT IS WIDELY AVAILABLE FOR USE BY THE AQUACULTURE COMMUNITY. THERESULTING DATABASE WILL ENABLE IMPROVED MOLECULAR TOOL DEVELOPMENT FOR MORE EFFICIENTPHENOTYPE SELECTION AND HEALTH MONITORING, RELEVANT TO THE AFRI ANIMAL GENOMICS PROGRAM AREAPRIORITY GOAL OF INCREASING ANIMAL FITNESS AND IMPROVING ANIMAL WELFARE AS WELL AS THE PRIORITY OFIMPLEMENTING SELECTION METHODS THAT USE A SYSTEMS BIOLOGY APPROACH FOR SIMULTANEOUSIMPROVEMENT OF MULTIPLE TRAITS.