Title

Genomic Testing and Method R Variance Components Theory of Dairy Cattle

Author(s) Information

Joseph Dewey Coleman, California Polytechnic State University, San Luis ObispoFollow

College - Author 1

College of Agriculture, Food and Environmental Sciences

Department - Author 1

Dairy Science Department

Degree Name - Author 1

BS in Dairy Science

Date

3-2012

Primary Advisor

Stan Henderson

Abstract/Summary

Abstract

The objective of this study is to determine the change in reliability from non genomic evaluations or Parent Averages to genomic evaluations. Due to recent industry popularity of genomic evaluations the California Polytechnic University, San Luis Obispo, decided to participate in the genetic movement of the dairy cattle industry. Genomic evaluations of both Holstein and Jersey cows at the Cal Poly dairy were chosen based on genetic superiority in order to possibly generate more income for the dairy and increase the herd’s popularity. Leading genomic companies such as Pfizer Animal Health, and GenSeek made genomic evaluation of the Cal Poly herd affordable by donating genomic sampling kits. Using the BovineSNP50 Bead Chip and BovineSNP6 Bead Chip, hair and blood samples were taken from the Cal Poly cows and heifers and were sent to the respected companies to generate official genomic evaluations. The data that this project focused on was the change in reliability of health traits such as Productive Life, as well as type and production traits including Net Merit Dollars, Cheese Merit Dollars, Genomic Total Performance Index, and Predicted Transmitting Ability for Type. Increases from traditional parent averages reliabilities to genomic evaluations reliabilities were obtained for all 6 core traits that were evaluated from the tested animals. In 59 Jersey’s that were tested, average reliabilities scores increased from an average of 45% to 69.61%. In addition the 51 tested Holstein females reliabilities raised from 43% to 74%. The genomic evaluations also suggest that the Cal Poly herd is genetically superior, they have two cows in the California top 100 GTPI cow and heifer lists for their respected breed. The gain in reliability of core industry traits and development of genetically superior animals of the Cal Poly herd has in turn increased their popularity of their herd, as well as potentially generating more income from its superior cows and heifers. A genomic based breeding program that Cal Poly has installed will speed up genetic progress of its herd by two years for each generation. The genomic evaluations of the Cal Poly herd will be used as a breeding tool to generate superior genomic bulls and heifers for potential future income.

The algorithm that is used for estimating the variance of genetic components is called Method R, and it will be used to analyze the correlation between Traditional Total Performance Index (TPI) to the Genomic Total Performance Index (GTPI/GJPI). The algorithm Method R, must equal 1 regardless of the sample size in order for the theory to be true (Reverter, 1994). If the computed R is greater than 1, then the variance component ration or slope is underestimated, but if it is less than 1 it is overstated (Reverter, 1994). Moreover the Method R algorithm will essentially prove that if the newly designed, chromosome based, genomic predictions are correlated with the traditional parent averages.

URL: https://digitalcommons.calpoly.edu/dscisp/73