Abstract

Genomic selection using single nucleotide polymorphisms (SNPs) is a powerful new tool for genetic selection. In cattle, SNP profiles for individual animals are generated using a small plastic chip that is diagnostic for up to 50 000 SNPs spaced throughout the genome. Phenotypes, usually averaged over offspring of bulls, are matched with SNP profiles of bulls mathematically so that animals can be ranked for siring desirable phenotypes via their SNP profiles. For many traits in dairy cattle, the rate of genetic improvement can be nearly doubled when SNP information is used in addition to current methods of genetic evaluation. Separate SNP analyses need to be developed for different populations (e.g. the system for Holsteins is not useful for Jerseys). In addition, the value of these systems is very dependent on the number of accurate phenotypes matched with SNP profiles; for example, increasing the number of North American Holstein bulls evaluated from 1151 to 3576 quadrupled the additional genetic gain in net merit from this approach. Thus, the available information will be insufficient to exploit this technology fully for most populations. However, once a valid SNP evaluation system is developed, any animal in that population, including embryos, can be evaluated with similar accuracy. Biopsying embryos and screening them via SNP analysis will greatly enhance the value of this technology by minimising generation intervals.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.