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Unveiling the Genetic Architecture of Semen Traits in Thai Native Roosters: A Comprehensive Analysis Using Random Regression and Spline Function Models
by
and
Iin Mulyawati Daryatmo
1,
Jiraporn Juiputta
1,
Vibuntita Chankitisakul
1,2 and
Wuttigrai Boonkum
1,2,*
1
Department of Animal Science, Faculty of Agriculture, Khon Kean University, Khon Kean 40002, Thailand
2
Network Center for Animal Breeding and Omics Research, Khon Kaen University, Khon Kaen 40002, Thailand
*
Author to whom correspondence should be addressed.
Animals 2024, 14(19), 2853; https://doi.org/10.3390/ani14192853 (registering DOI)
Submission received: 3 September 2024
/
Revised: 29 September 2024
/
Accepted: 2 October 2024
/
Published: 3 October 2024
(This article belongs to the Special Issue Genetics and Breeding Advances in Poultry Health and Production: 2nd Edition)
Simple Summary
Improving the genetic traits influencing rooster semen quality and quantity is crucial for optimizing poultry production. Breeders can identify heritable traits that significantly influence semen characteristics by evaluating genetic parameters, ensuring that only the best roosters are selected for breeding purposes. The development of appropriate genetic models aids in accurately predicting these traits, thereby enhancing selection efficiency. Selection based on these models boosts fertility and hatchability and promotes the propagation of desirable traits across generations. This approach leads to healthier, more productive flocks, increased economic efficiency, and more sustainable poultry farming practices.
Abstract
Improving reproductive traits, particularly semen quality and quantity, is crucial for optimizing poultry production and addressing the current limitations in native chicken reproduction. The aim of this study was to develop a genetic model to estimate genetic parameters guiding the selection of individual Thai native roosters. Using data collected from 3475 records of 242 Thai native grandparent roosters aged 1–4 years, we evaluated semen traits (mass movement, semen volume, and sperm concentration) over 54 weeks. A random regression test–day model incorporating five covariance functions, including a linear spline function with four, five, six, and eight knots (SP4, SP5, SP6, and SP8) and second-order Legendre polynomial function (LG2), was used to estimate genetic parameters. The results showed that the SP8 model consistently outperformed the other models across all traits, with the lowest mean square error, highest coefficient of determination, and superior predictive ability. Heritability estimates for mass movement, semen volume, and sperm concentration ranged from 0.10 to 0.25, 0.22 to 0.25, and 0.11 to 0.24, respectively, indicating moderate genetic influence on these traits. Genetic correlations between semen volume and sperm concentration were highest in the SP8 model, highlighting a strong genetic association between these traits. The SP8 model also revealed a high genetic correlation between mass movement and semen volume, supporting the potential for selecting mass movement as a predictor of semen volume. In conclusion, this study highlights the effectiveness of random regression models with linear spline functions to evaluate the genetic parameters of semen traits in native Thai roosters. The SP8 model is a robust tool for breeders to enhance the reproductive performance of native Thai chickens, contributing to sustainable poultry production systems.
