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ARS Home » Midwest Area » Madison, Wisconsin » U.S. Dairy Forage Research Center » Cell Wall Biology and Utilization Research » Research » Publications at this Location » Publication #361140

Research Project: Investigating Microbial, Digestive, and Animal Factors to Increase Dairy Cow Performance and Nutrient Use Efficiency

Location: Cell Wall Biology and Utilization Research

Title: From sequence of dominette to 10K and 50K SNP chips

item Bickhart, Derek

Submitted to: American Dairy Science Association Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 2/20/2019
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Genetic markers based on interrogated nucleotide variant sites have been used in cattle genetics since the late 1990’s. Owing partly to the excessive cost and labor-intensive means of assessing marker sites, such as microsatellite repeats, their commercial use was relatively limited. Additionally, genotyping accuracy was error-prone and did not cover the cattle genome evenly. In this presentation, we highlight two specific improvements that started the modern genomics era. The development of high resolution DNA sequence maps of the cattle genome and the adaptation of microarrays for high throughput genotyping served as the catalysts for data collection for modern cattle genomic selection. Simultaneously, the development of computational methods for associating animal SNP genotypes with productive trait phenotypes improved the accuracy of animal selective breeding values by providing higher resolution of allelic transmission to offspring. The efficacy of these tandem improvements has generated incredible value for the modern cattle breeder; however, many challenges and questions persist. Linkage between genetic markers and their associated causal genetic mutations can be further improved by genotyping the actual mutation itself. There is additional novel sequence within the cattle pan-genome that is currently not represented in the cattle reference genome assembly which may not be tracked by current genetic markers. Finally, methods need to be developed that efficiently incorporate whole genome DNA sequence data into genomic selection. Future techniques and technologies that may address these challenges will be discussed.