Genetic Evaluation for Functional Longevity in Nellore Cattle

Area of Science:

• Animal Genetics
• Quantitative Genetics
• Reproductive Biology

Background:

• Traditional stayability (STAY) measures longevity late in life, limiting genetic variability assessment and prolonging generation intervals.
• Random regression models offer a potential solution by utilizing multiple phenotypes across an animal's lifespan for predictive breeding value curves.

Purpose of the Study:

• To compare two phenotypic expressions of functional longevity: functional longevity expressed as stayability (FLSTAY) and functional longevity associated with the number of calvings (FLNC).
• To identify the optimal random regression model for predicting breeding values for these longevity traits in Nellore cows.
• To evaluate the potential of FLNC as an early selection strategy for improving functional longevity.

Main Methods:

• Utilized calving records from 179,001 Nellore cows.
• Compared Legendre orthogonal polynomial models (linear to cubic) for random regression analysis.
• Assessed predictive ability, heritability estimates, and genetic correlations across different ages for FLSTAY and FLNC.

Main Results:

• The cubic polynomial best modeled FLSTAY, while the quadratic polynomial best modeled FLNC.
• Random regression models for FLNC demonstrated superior predictive ability compared to FLSTAY.
• Heritability estimates for FLNC (0.025-0.074) were higher than for FLSTAY (0.004-0.045).
• Stronger genetic correlations across ages were observed for FLNC, reaching 0.88 between 39 and 75 months.

Conclusions:

• Random regression models are feasible for FLNC, enabling its use in early selection strategies.
• FLNC offers a more effective approach for improving functional longevity and reducing generation intervals in Nellore cattle compared to traditional STAY.