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In the face of 21st-century agricultural challenges, our mission is clear: we must produce more food, feed, and fiber for a growing population with evolving dietary preferences, while dealing with limited rural labor and agricultural land, and the need for bio-energy sources. Moreover, climate change introduces more frequent biotic and abiotic stresses. While global crop productivity has matched these challenges, we must intensify our efforts to sustain this progress. This is especially vital as we navigate the rest of the century. To address these pressing needs, our team of experts, spanning crop and livestock breeding, genetics, biochemistry, and data science, is forging ahead. We're developing innovative tools to decode the genetic basis of traits in crops like maize, soybean, sorghum, and in pigs. Our advanced statistical models, enhancing methods like GWAS, TWAS, and eQTL mapping, empower biologists to explore data in groundbreaking ways, uncovering new i nsights. We are bridging the gap between genetics and traits, from crop yields to Vitamin B levels in maize. Our research probes the interplay of genetics, weather, and environment using diverse data. This newfound knowledge will steer enhancements in crucial U.S. crops and livestock. Our ambitious endeavor extends beyond discovery. It entails crafting novel statistical tools to comprehend essential genes in both livestock and crops, applicable across species. Aligned with the USDA's strategic goals, our work contributes to an equitable, resilient, and prosperous U.S. agricultural system, ensuring accessible, wholesome food for all. Through education and outreach, we'll empower crop and livestock breeders and cultivate the human capital needed to fulfill these aspirations.

Data sharing and collaboration are of increasing importance to enable validation, further research, and joint analysis of multiple data sets. However, these processes are often complicated or even prevented because public data may have limited visibility and accessibility, and private data often contain confidential or proprietary information, especially in the case of industry data. Our proposed research takes a tiered approach to facilitate access to and sharing of data for genomic and phenomic analyses.

To effectively promote open science in agriculture while addressing confidentiality concerns, we advocate for the following multifaceted strategy: (1) fostering streamlined data sharing of public data, (2) innovating data sharing methods that protect confidentiality, and (3) enabling collaborative research without data sharing. With the long-term goal of enabling efficient and effective AG2P research and applications to advance livestock and crop production, these strategies form the first three specific aims of our proposal, with a strong integrated education component as the fourth aim.