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Improved methods for genotypic data analysis

Project start date: 15 May 2013
Project end date: 09 April 2014
Publication date: 01 November 2013
Project status: Completed
Livestock species: Grassfed cattle, Grainfed cattle
Relevant regions: National
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​Genomic selection is becoming a standard tool in livestock breeding programs, particularly for traits that are hard to measure. Accuracy of genomic selection can be improved by increasing quantity and quality of data and potentially by improving analytical methods. Adding genotypes and phenotypes from additional breeds or crosses often improves the accuracy of genomic predictions, but will require specific methodology.
A method was developed to incorporate breed composition estimated from genotypes into genomic selection models. This method was applied to age-at-puberty data (as estimated from age at first observation of a corpus luteum) from a mix of Brahman and Tropical Composite beef cattle. In this data set the new model incorporating breed composition did not increase the accuracy of genomic selection. However the breeding values exhibited slightly less bias (as assessed by deviation of regression of phenotype and genomic breeding values from the expected value of 1). Adding additional Brahman animals to the Tropical Composite analysis increased the accuracy of genomic predictions and did not affect the accuracy of the Brahman predictions

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Project manager: Mick Quirk
Primary researcher: University of Queensland