Skip to main content
ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Plant and Animal Genetic Resources Preservation » Research » Publications at this Location » Publication #350062

Research Project: National Animal Germplasm Program

Location: Plant and Animal Genetic Resources Preservation

Title: Heritability estimations for inner muscular fat in Hereford cattle using random regressions

Author
item Delgadillo Liberona, Jose - Texas A&M Agricultural Experiment Station
item Langdon, J - Texas A&M Agricultural Experiment Station
item Riley, D - Texas A&M Agricultural Experiment Station
item Blackburn, Harvey
item Speidel, Scott - Colorado State University
item Krehbiel, Bethany
item Sanders, J - Texas A&M Agricultural Experiment Station
item Herring Andy, D - Texas A&M Agricultural Experiment Station

Submitted to: Journal of Animal Science
Publication Type: Abstract Only
Publication Acceptance Date: 12/15/2017
Publication Date: N/A
Citation: N/A

Interpretive Summary: Random regressions make possible to make genetic predictions and parameters estimation across a gradient of environments, allowing a more accurate and beneficial use of animals as breeders in specific environments. The objective of this study was to use random regression models to estimate heritabilities for inner muscular fat (IMF) in Hereford cattle, across a gradient of longitude coordinates in the United States. Records were obtained from the American Hereford Association (n=169,440), incorporating pedigree information from 227,902 animals. Three models were evaluated using ASReml, a quadratic random regression, a linear random regression, and a model without random regression. For all models, the fixed component involve the effects of contemporary group and ecoregion, where ecoregions were defined based on temperature and humidity differences across the United States. The random component considered the random effect of the animal by itself or interacting with a linear or quadratic regression, using the longitude coordinates where the animal was raised as the regressor variable. The fit of the models was evaluated through likelihood-ratio tests, where the quadratic regression model proved to have significant advantages in comparison to the rest (p < 0.01). Heritability estimates using the quadratic model ranged from 0.31 to 0.54 (Figure 1), having its maximum value at the western coordinate evaluated (124.09 degrees west). Then, advancing from west to east the heritability starts to decrease reaching its minimum value at 99 degrees west. After this point heritability begins to increase, reaching values of 0.47 at the eastern coordinate evaluated (71.47 degrees west). These results indicate that the use of quadratic random regressions make possible to improve the genetic predictions and parameter estimations for IMF, providing at the same time valuable information which could help to generate selection indexes that fit in a more precise manner to cattle population across different sectors of the United States. Finally, the observed differences in IMF heritabilities could also be happening for other economical relevant traits; for this reason, further research is needed to uncover the additive genetic component behavior of such traits across environments.

Technical Abstract: Random regressions make possible to make genetic predictions and parameters estimation across a gradient of environments, allowing a more accurate and beneficial use of animals as breeders in specific environments. The objective of this study was to use random regression models to estimate heritabilities for inner muscular fat (IMF) in Hereford cattle, across a gradient of longitude coordinates in the United States. Records were obtained from the American Hereford Association (n=169,440), incorporating pedigree information from 227,902 animals. Three models were evaluated using ASReml, a quadratic random regression, a linear random regression, and a model without random regression. For all models, the fixed component involve the effects of contemporary group and ecoregion, where ecoregions were defined based on temperature and humidity differences across the United States. The random component considered the random effect of the animal by itself or interacting with a linear or quadratic regression, using the longitude coordinates where the animal was raised as the regressor variable. The fit of the models was evaluated through likelihood-ratio tests, where the quadratic regression model proved to have significant advantages in comparison to the rest (p < 0.01). Heritability estimates using the quadratic model ranged from 0.31 to 0.54 (Figure 1), having its maximum value at the western coordinate evaluated (124.09 degrees west). Then, advancing from west to east the heritability starts to decrease reaching its minimum value at 99 degrees west. After this point heritability begins to increase, reaching values of 0.47 at the eastern coordinate evaluated (71.47 degrees west). These results indicate that the use of quadratic random regressions make possible to improve the genetic predictions and parameter estimations for IMF, providing at the same time valuable information which could help to generate selection indexes that fit in a more precise manner to cattle population across different sectors of the United States. Finally, the observed differences in IMF heritabilities could also be happening for other economical relevant traits; for this reason, further research is needed to uncover the additive genetic component behavior of such traits across environments.