1a. Objectives (from AD-416):
Create and maintain a phenotypic and genomic database for cattle in industry populations that will be used for the validation of DNA associations found in the research population at USMARC. Characterize said populations and analyze data as appropriate for validation.
1b. Approach (from AD-416):
Collaborators with USMARC scientists are developing external validation populations comprised of industry animals. Data from these populations are collected by collaborators and by breed associations. These data will be transferred to Cornell’s Animal Science department for quality assessment, summary analysis, storage and retrieval. DNA samples for these animals will be analyzed for SNP genotypes from the standard 50K and HD Illumina SNP assays. Associations between SNP genotypes and SNP effects discovered in the USMARC discovery population will be made to create Molecular Breeding Value (MBV) estimates for individual animals. Data will be analyzed for the association of the MBV’s with Expected Progeny Differences (EPD) or phenotypic information.
3. Progress Report:
This report is related to the original project 5438-31000-012-00D and bridging project 5438-31000-088-00D. During this time period, a Systems Analyst at Cornell University conducted data collection activities related to beef production and processed electronically storing as databases on a secure server at Cornell University. The work involved multiple breeds and was performed at a high level of accuracy. Conversion of legacy data from the Rex Ranch Commercial Ranch Project to a relational database system was completed. Storage and management of phenotypic and genotypic data was done for genetic evaluation and research purposes. Designed database management systems related to the Weight Trait and Feed Efficiency Project which entailed partnering with 7 National Beef Breed Associations, genotyping agencies, and researchers. Storage and maintenance of phenotypic, pedigree and genotypic data was completed. Built substantial on demand business applications by designing, defining and maintaining support for DB2 Universal Database system; key functions include managing data for research run schedules, quality control, data consistency, data security, and data recovery. The Systems Analyst assisted with research on database management, data extraction, and statistical reports for Structured Query Language queries intended for electronic file generation.