Applicability of single-step genomic evaluation with a random regression model for reproductive traits in turkeys (Meleagris gallopavo)

Genetic Strategies for Enhancing Rooster Fertility in Tropical and Humid Climates: Challenges and Opportunities

Native chickens are important both economically and for the preservation of genetic diversity, especially for optimizing the reproductive performance of male chickens, which plays an important role in genetic propagation. However, hot and humid weather affects the quality of semen and the breeding ability of male chickens. One method used to solve this problem is genetic selection using genomic technology, which improves accuracy and shortens the breed selection time. Therefore, we collected and analyzed data from relevant research to review the genetic improvement approach for male chickens using genomic technology. We compared popular genomic selection models, such as GBLUP, ssGBLUP, Bayesian approaches, RR-GBLUP, WGBLUP, and MTGBLUP, as well as genome-wide association studies (GWASs), to identify genes associated with semen quality and heat tolerance. The results of this analysis suggested that the use of genomic data can enhance genetic selection and enable breeding to occur more quickly and accurately. We addressed the trends and scientific developments in male chicken genetic selection, together with the benefits and constraints of each method. This will help breeders and researchers to create the most successful genetic selection plans for the next generation of chickens.

Short communication: Evaluating laying curve models and estimating genetic parameters for egg production traits in chickens

The Qingyuan partridge chicken, a highly valued indigenous breed in China, requires optimised egg production traits to maximise economic returns. This study analysed weekly egg production data from 6 776 Qingyuan partridge chickens to compare the Grossman and Wood models in fitting individual egg-laying curves and identify the most robust model for estimating egg production persistency. Genetic parameters were estimated for three key traits: age at first egg (AFE), cumulative egg number up to 28 weeks (EN), and persistency derived from the Wood model, alongside weekly egg numbers using a random regression model. Results demonstrated the Wood model's superior performance, achieving successful curve fits for more individuals with comparable residual SEs. Moderate heritability estimates were observed for AFE (0.37 ± 0.02) and EN (0.28 ± 0.02), while persistency exhibited lower heritability (0.09 ± 0.06). Moderate to high genetic correlations emerged between AFE and EN (-0.63 ± 0.002), AFE and persistency (-0.51 ± 0.008), and EN and persistency (0.58 ± 0.008). The heritability of weekly egg numbers from weeks 1 to 28 followed a W-shaped trajectory, ranging from 0.07 to 0.19. Notably, genetic correlations between weekly egg numbers at weeks 16-19 and EN exceeded 0.91. These findings highlight the importance of selecting for egg production persistency alongside AFE and EN. Selection based on weekly egg numbers during weeks 16-19 offers a practical alternative to selection based on cumulative egg numbers, enabling early selection in breeding programmes.

Genetic Architecture of Abdominal Fat Deposition Revealed by a Genome-Wide Association Study in the Laying Chicken

Fat has a high energy density, and excessive fatness has been recognized as a problem for egg production and the welfare of chickens. The identification of a genetic polymorphism controlling fat deposition would be helpful to select against excessive fatness in the laying hen. This study aimed to estimate genomic heritability and identify the genetic architecture of abdominal fat deposition in a population of chickens from a Dongxiang blue-shelled local breed crossbred with the White Leghorn. A genome-wide association study was conducted on abdominal fat percentage, egg production and body weights using a sample of 1534 hens genotyped with a 600 K Chicken Genotyping Array. The analysis yielded a heritability estimate of 0.19 ± 0.04 for abdominal fat percentage; 0.56 ± 0.04 for body weight at 72 weeks; 0.11 ± 0.03 for egg production; and 0.24 ± 0.04 for body weight gain. The genetic correlation of abdominal fat percentage with egg production between 60 and 72 weeks of age was -0.35 ± 0.18. This implies a potential trade-off between these two traits related to the allocation of resources. Strong positive genetic correlations were found between fat deposition and weight traits. A promising locus close to COL12A1 on chromosome 3, associated with abdominal fat percent, was found in the present study. Another region located around HTR2A on chromosome 1, where allele substitution was predicted to be associated with body weight gain, accounted for 2.9% of phenotypic variance. Another region located on chromosome 1, but close to SOX5, was associated with egg production. These results may be used to influence the balanced genetic selection for laying hens.