Tesfaye K Belay, Arne B Gjuvsland, Janez Jenko, Leiv S Eikje, Morten Svendsen, Theo Meuwissen
{"title":"Single-Step Genomic BLUP With Unknown Parent Groups and Metafounders in Norwegian Red Evaluations.","authors":"Tesfaye K Belay, Arne B Gjuvsland, Janez Jenko, Leiv S Eikje, Morten Svendsen, Theo Meuwissen","doi":"10.1111/jbg.12939","DOIUrl":"https://doi.org/10.1111/jbg.12939","url":null,"abstract":"<p><p>The objective of this study was to examine the effects of different methods for handling missing pedigree data on biases, stability, relative increase in accuracy, and genetic trends using national data from Norwegian Red (NRF) cattle. The dataset comprised 8,402,773 milk yield records from 3,896,116 NRF cows, a pedigree with 4,957,544 animals, and a genomic dataset from 170,293 animals with 121,741 SNPs. Missing parents were modelled using three approaches: unknown parent groups (UPG), metafounders (MF), and \"Q-Q<sup>+</sup>\" methods. The UPG method is routinely used for genetic evaluations of NRF cattle by including 52 fixed UPG in the pedigree. In the MF method, two MF were defined: MF14 and MF52, with MF treated as random effects. The MF14 included 6 MF defined by birth year intervals for NRF breed and 8 MF defined by breed origins for other breeds. The MF52 classification included all the 52 UPG as MF considering relationships among them. The \"Q-Q<sup>+</sup>\" approach corrects for the combined effects of UPG and \"J factor\" in non-genotyped animals while avoiding such corrections in genotyped animals. The three approaches, combined with different G matrices (G<sub>rtn</sub> matrix constructed with a 0.5 allele frequency (AF) and 10% weight (w) on A, G<sub>05</sub> constructed using AF = 0.5 and w = 0.0, and G<sub>cal</sub> constructed with observed AF and w = 0.0), led to eight ssGBLUP models being tested. This included one UPG model (using G<sub>rtn</sub>), four MF models (MF14 and MF52 using G<sub>rtn</sub> or G<sub>05</sub>), and three Q-Q+ models (using G<sub>cal</sub>, G<sub>05</sub>, or G<sub>rtn</sub>). The models were evaluated through cross-validation by masking the phenotypes of 5000 genotyped young cows. Results showed that the Q-Q<sup>+</sup> models using the G<sub>cal</sub> or G<sub>05</sub> matrix had significantly (p < 0.05) lower level biases and higher genetic trends than all other models. MF models with 14 or 52 groups using G<sub>05</sub> were second best for level bias and performed similarly or slightly better than Q-Q+ models regarding inflation bias and stability. Increasing the number of MF from 14 to 52 had minimal effects on biases but significantly improved stability and genetic trend estimates. Models with G<sub>rtn</sub> had slightly higher gain in accuracy from adding phenotypic data (2.01%) than G<sub>05</sub> (1.18%), but pedigree-based models showed the highest improvement in accuracy due to adding phenotypic (26%) or genomic (47%) data to the partial dataset. Overall, all models with G<sub>05</sub> showed the least bias (with a small standard error) and most stable predictions, while models using G<sub>rtn</sub> introduced biases and instability. Thus, the Q-Q<sup>+</sup> and MF models combined with G<sub>05</sub> and Q-Q<sup>+</sup> with G<sub>cal</sub> are recommended for their improved validation results and genetic trends.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143765948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zully Ramos, Dorian J Garrick, Hugh T Blair, Ignacio De Barbieri, Gabriel Ciappesoni, Fabio Montossi, Paul R Kenyon
{"title":"Genetic Trends for Production and Reproduction Traits in Ultrafine Merino Sheep of Uruguay.","authors":"Zully Ramos, Dorian J Garrick, Hugh T Blair, Ignacio De Barbieri, Gabriel Ciappesoni, Fabio Montossi, Paul R Kenyon","doi":"10.1111/jbg.12937","DOIUrl":"https://doi.org/10.1111/jbg.12937","url":null,"abstract":"<p><p>Genetic trends were estimated for production and reproduction traits in an Uruguayan Merino genetic nucleus. Two consecutive periods with different selection objectives were studied. During the first period (1999-2010), the selection objective of this flock focused on reducing fibre diameter (FD), while allowing for a slight loss in clean fleece weight (CFW). From 2011 to 2018, the breeding objective was shifted and then focused on maintaining FD, while increasing both CFW and live weight (LW). Data from approximately 5380 yearling lambs and 2000 ewes born between 1999 and 2018 were analysed. Genetic trends were estimated for yearling and adult FD (Y_FD and A_FD, respectively), yearling and adult CFW (Y_CFW and A_CFW, respectively), yearling LW (Y_LW), 2-year-old ewe mating live weight and mating body condition score (2-yo_LWM and 2-yo_BCSM, respectively) and the number of lambs weaned per ewe joined (NLWEJ). Estimated breeding values were predicted to calculate genetic trends for the two periods of selection. From 1999 to 2010, yearling lambs showed significant reductions in FD (-0.210 μm/year, corresponding to -1.28% of the mean of the trait for that period). Before 2010, yearling lambs showed reductions of -0.013 kg/year (-0.62%) in CFW, whereas from 2011 to 2018, this trait increased by 0.052 kg/year (1.88%). The annual genetic gain for Y_LW was greater in the second period than in the first period (0.286 vs. 0.091 kg/year). The genetic trends for FD, CFW and LW were affected by period (p < 0.001), indicating that the change in the selection index applied in the genetic nucleus was effective. Over the entire study period (1999-2018), the total genetic responses for 2-yo_BCSM and NLWEJ were near zero. These results indicate that the breeding programme utilised in the genetic nucleus improved the traits under selection (FD, CFW and LW) and had a marginal impact on 2-yo_BCSM and NLWEJ. To also achieve relevant genetic gains in ewe reproductive performance, in the future, reproduction traits should be incorporated into the selection programme for Uruguayan fine-wool sheep. The results obtained in this study will be used to refine the breeding programmes for Merino sheep in Uruguay.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143674903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
João Vitor Teodoro, Gerson Barreto Mourão, Rachel Santos Bueno Carvalho, Elisângela Chicaroni de Mattos, José Bento Sterman Ferraz, Joanir Pereira Eler
{"title":"Optimal Mating Combination for Directed Breeding in a Racially Composite Cattle Population.","authors":"João Vitor Teodoro, Gerson Barreto Mourão, Rachel Santos Bueno Carvalho, Elisângela Chicaroni de Mattos, José Bento Sterman Ferraz, Joanir Pereira Eler","doi":"10.1111/jbg.12936","DOIUrl":"https://doi.org/10.1111/jbg.12936","url":null,"abstract":"<p><p>Evaluating optimal mating combinations in large populations poses significant combinatorial and computational challenges. To address this, we propose a method to optimise mating combinations in composite cattle populations, incorporating heterosis and genetic variability. Leveraging integer linear programming, our approach maximises expected offspring merit, outperforming random mating systems. A robust mathematical model and specialised software were developed to implement the method, demonstrating its effectiveness on a real dataset. Notably, results reveal a 14.8% superiority over random mating averages and a 12.4% advantage over random mating maxima. The method's flexibility and adaptability enable constraint inclusion and application to diverse species and genomic data, making it an indispensable tool for enhancing mating selection efficiency and effectiveness in composite beef cattle breeding programmes.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143607212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Evan Hartono, Owen W Willems, Xuechun Bai, Benjamin J Wood, Romdhane Rekaya, Samuel E Aggrey
{"title":"Effect of Transformation of Non-Normal Fitness Trait Data on the Estimation of Genetic Parameters in Turkeys.","authors":"Evan Hartono, Owen W Willems, Xuechun Bai, Benjamin J Wood, Romdhane Rekaya, Samuel E Aggrey","doi":"10.1111/jbg.12935","DOIUrl":"https://doi.org/10.1111/jbg.12935","url":null,"abstract":"<p><p>Fitness traits described as a ratio often display non-normal distributions; consequently, transformations are frequently applied to improve normality prior to the estimation of genetic parameters. However, the impact of different transformations on genetic parameter estimates depends on the dataset at hand. The objective of this study was to evaluate the effects of eight common transformations (z-score, log, square root, probit, arcsine, logit, Box-Cox and Yeo-Johnson) on genetic parameter estimates for non-normal fitness traits in turkeys. Three fertility traits in turkeys were analysed. Egg production rate, egg fertility rate and hatch of fertile eggs rate phenotypes were collected on 6667 turkeys. All three phenotypes exhibited a significant level of non-normality. An informative pedigree file for the phenotyped birds was generated and consisted of 8612 animals. A mixed linear model that included the hatch year and regression on body weight at 18 weeks of age as fixed effects was used to analyse the transformed and untransformed phenotypes. To make the untransformed and transformed data comparable, they were all standardised to the same mean and variance. Results showed that the transformations significantly impacted genetic parameter estimates. In fact, the percentage variations in the estimates of the heritabilities of the three traits compared to the non-transformed data ranged from -80% to 45%. Across the different comparison criteria, the Box-Cox transformation seems to have the advantage compared to the other methods. Furthermore, it resulted in the highest heritability estimates. Although the genetic correlations showed fewer differences across transformations, the Spearman rank correlations ranged between 0.87 and 1, indicating some re-ranking. These findings suggest that the choice of data transformation impacts inferences on the genetic properties of non-normal traits, and careful consideration of the transformation method is needed prior to genetic analysis of skewed fitness data in turkeys and potentially other agricultural species. The results provide guidelines for the appropriate choice of transformations given observed levels of deviation from normality.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143607190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Similarity Matrix for Preserving Haplotype Diversity Amongst Parents in Genomic Selection.","authors":"Abdulraheem A Musa, Norbert Reinsch","doi":"10.1111/jbg.12930","DOIUrl":"https://doi.org/10.1111/jbg.12930","url":null,"abstract":"<p><p>In genomic selection, balancing genetic gain with the preservation of genetic diversity is a critical challenge, requiring innovative approaches to parent selection. Traditional methods risk losing valuable genetic diversity by not fully accounting for the complex patterns of haplotype distribution. To address this, we developed a novel haplotype similarity measure that estimates the genetic similarity amongst offspring from parent pairs by analysing segregating marker patterns and the covariance of additive genetic effects between potential parental gametes. This measure is encapsulated in a novel similarity matrix that quantifies parental genetic relationships and their Mendelian sampling variance, facilitating the selection of parents with diverse haplotypes to maintain genetic diversity. Our method was evaluated through simulation studies and empirical data analysis, indicating that the similarity matrix can help preserve haplotype diversity and potentially improve long-term genetic gains compared to traditional selection methods. These results suggest that the similarity matrix could contribute to more efficient and sustainable genomic selection programs, although further research is necessary to fully understand its impact.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143544516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eduarda da Silva Oliveira, Larissa Bordin Temp, Gabriel Gubiani, Miller Teodoro, Gustavo Roberto Dias Rodrigues, Maria Paula Marinho de Negreiros, Letícia Silva Pereira, Cláudio Ulhôa Magnabosco, Fernando Baldi
{"title":"Genetic Parameters and Genomic Prediction for Calving Ease in Primiparous Nellore Heifers.","authors":"Eduarda da Silva Oliveira, Larissa Bordin Temp, Gabriel Gubiani, Miller Teodoro, Gustavo Roberto Dias Rodrigues, Maria Paula Marinho de Negreiros, Letícia Silva Pereira, Cláudio Ulhôa Magnabosco, Fernando Baldi","doi":"10.1111/jbg.12932","DOIUrl":"https://doi.org/10.1111/jbg.12932","url":null,"abstract":"<p><p>The calving ease (CE) trait has recently been introduced in animal breeding programs, and studies on its genetic variability have proven essential for the genetic advancement of animals. An increase in dystocia rates in primiparous heifers has been observed due to the birth of heavier calves. As this is a new trait, no established model exists for its analysis. Thus, this study developed different statistical models to evaluate CE, aiming to estimate genetic parameters and perform genomic predictions for this trait. A total of 39,664 records of CE from primiparous Nellore heifers born between 2010 and 2017 were collected, belonging to the animal breeding program of the Nellore breed in Brazil, managed by the National Association of Breeders and Researchers (ANCP, Ribeirão Preto, Brazil). The results showed that direct heritability estimates ranged from 0.11 to 0.24, while maternal heritability estimates ranged from 0.09 to 0.11. Despite these low to moderate heritability estimates, the trait has potential for direct selection. Models incorporating the heifer category (HC) (early or traditional) and birth weight (BW), as well as the dam age at calving (DAC) and BW, were more suitable for estimating variance components. On the other hand, the model that considered only the HC and the model that included the DAC excelled in predictive ability, making them more appropriate for genomic predictions.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143544517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R D Oloo, R Mrode, C C Ekine-Dzivenu, J M K Ojango, J Bennewitz, G Gebreyohanes, A M Okeyo, M G G Chagunda
{"title":"Genetic Relationships Among Resilience, Fertility and Milk Production Traits in Crossbred Dairy Cows Performing in Sub-Saharan Africa.","authors":"R D Oloo, R Mrode, C C Ekine-Dzivenu, J M K Ojango, J Bennewitz, G Gebreyohanes, A M Okeyo, M G G Chagunda","doi":"10.1111/jbg.12933","DOIUrl":"https://doi.org/10.1111/jbg.12933","url":null,"abstract":"<p><p>Change in climate over the past years and its impact on the environment have necessitated the inclusion of resilience traits in the breeding objectives of dairy cattle. However, the relationship between resilience and other traits of economic importance in dairy production is currently not well known. This study examined the genetic parameters and relationships among resilience, fertility and milk production traits in dairy cattle in Kenya. Indicators of general resilience and heat tolerance were defined from the first parity test-day milk yield records. Indicators of general resilience included variance of actual deviations (LnVar1), variance of standardised deviations (LnVar2), lag-1 autocorrelation (r<sub>auto</sub>) and skewness (Skew) of standardised deviations in milk yield. Heat tolerance indicators at temperature-humidity index 80 included the slope of the reaction norm (Slope), absolute slope of the reaction norm (Absolute), and the intercept of the reaction norm model (Intercept). Cows with > 50% taurine genes had lower age at first calving (AFC), longer calving intervals (CI) and higher test-day milk yield (MY). The heritability estimates of AFC, CI and MY were 0.17 ± 0.033, 0.06 ± 0.012 and 0.35 ± 0.021, respectively. The repeatability estimates of CI and MY were 0.06 ± 0.012 and 0.47 ± 0.009, respectively. The low heritability and non-significant permanent environmental variance of CI showed that CI is heavily influenced by external factors, such as management practices. AFC was negatively genetically correlated with both CI (-0.88 ± 0.077) and MY (-0.53 ± 0.059) showing that animals that attain sexual maturity earlier exhibit longer CI and higher milk production. A positive genetic correlation (0.62 ± 0.077) between CI and MY shows that high-yielding cows face challenges in maintaining shorter calving intervals. Heritability estimates of nearly all resilience indicators were significant and ranged from 0.05 to 0.34. Heat tolerance indicators showed low to non-significant genetic correlations with general resilience indicators, suggesting that different genetic factors are involved in responses to different types of disturbances. There was a generally positive genetic correlation between resilience and fertility, implying that resilient animals might have better fertility. All indicators, except LnVar1 and LnVar2, revealed an antagonistic genetic relationship between resilience and milk production. The findings present an opportunity for including resilience in the development and application of selection indices in dairy cattle, especially for the tropics.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143544521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Genetic Evaluation of Barrel Racing Performance in Quarter Horses.","authors":"Mário Luiz Santana, Thiago Garcia Botelho Franco, Annaiza Braga Bignardi","doi":"10.1111/jbg.12934","DOIUrl":"https://doi.org/10.1111/jbg.12934","url":null,"abstract":"<p><p>Barrel racing is a competitive timed rodeo event that challenges horses and riders to complete a cloverleaf pattern around three barrels in the fastest time possible. In this study, we aimed to estimate the genetic parameters of barrel racing time (BRT) and evaluate the most suitable statistical model for its analysis. We compared a repeatability model and three random regression models (RRM) to analyse the longitudinal BRT data in Brazilian Quarter Horses. A total of 356,877 BRT records from 14,108 horses that competed in various events held across Brazil between 2010 and 2024 were analysed. The cubic RRM provided the best fit to the data, and therefore, the results from this model were presented in detail. Heritability estimates for BRT varied by age (0.15-0.24), with the highest estimates observed between 36 and 54 months, suggesting that selection at younger ages could be most effective. Genetic correlations between BRT at different ages were generally strong (> 0.8). The lowest mean genetic correlation of 0.65 (0.09) was observed between BRT at 36 and 144 months of age. Thus, selecting the best-performing horses at younger ages should result in favourable genetic progress at older ages. Phenotypic trends showed an improvement in BRT over the years, although no significant genetic progress was observed, likely due to the absence of an official breeding programme and the lack of use of estimated breeding values for BRT. These findings highlight the need for a more strategic approach to genetic selection in Quarter Horses to optimise BRT performance. The substantial genetic variation identified for BRT indicates that, if properly exploited, this trait could be significantly improved in the future, ultimately enhancing competition outcomes for Brazilian Quarter Horses in barrel racing.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143532200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aneet Kour, R N Chatterjee, K S Rajaravindra, L Leslie Leo Prince, U Rajkumar
{"title":"Bayesian Genetic Estimation Towards Optimising Selection Strategy for Higher Egg Production in White Leghorn Chickens.","authors":"Aneet Kour, R N Chatterjee, K S Rajaravindra, L Leslie Leo Prince, U Rajkumar","doi":"10.1111/jbg.12931","DOIUrl":"https://doi.org/10.1111/jbg.12931","url":null,"abstract":"<p><p>Long-term directional selection in a population can severely reduce the additive genetic variability for the desired trait. Therefore, it is really important to assess the genetic parameters of a population at definite time intervals for designing effective breeding programmes. The present study was designed for the genetic evaluation of a White Leghorn strain (IWI) which has been intensely selected for higher egg numbers up to 64 weeks of age at ICAR-Directorate of Poultry Research, Hyderabad, Telangana, India. The genetic parameters were estimated for egg production up to 24 (EP24), 32 (EP32), 40 (EP40), 52 (EP52), 64 (EP64) and 72 (EP72) weeks of age along with other traits (egg weight, reproductive and body weight traits) utilising six models with different random effects in a Bayesian framework. The normalised mean value for the primary selection trait, EP64, was 218.16 ± 1.24 eggs while the total egg production up to 72 weeks was 242.85 ± 1.72. Comparative evaluation of different models based on Deviance Information Criterion (DIC) revealed that model 6 (including direct additive, maternal genetic and maternal permanent environment effects) was the most accurate for early production traits like EP24, whereas model 3 (including direct additive and maternal genetic effects) was the best-fitted for egg production traits like EP32 and EP40. The trait variance for late egg production traits like EP52, EP64 and EP72 was best defined by model 1, which only included the direct additive effect. Furthermore, it was found that the posterior mean additive heritability of egg production traits declined as the laying cycle progressed. Particularly, for later traits like egg production up to 52 (EP52), 64 (EP64) and 72 (EP72) weeks, the direct additive heritability estimate was very low (0.02 ± 0.009; 0.04 ± 0.01 and 0.02 ± 0.0009 respectively). Subsequently, posterior genetic correlations (r<sub>G</sub>) were estimated between late egg production traits and the rest of the traits. It was found that there was a highly negative r<sub>G</sub> between egg weight at 40 weeks (EW40), body weight at 52 weeks (BW52) and the later egg production traits (EP52, EP64 and EP72). Therefore, depending on the trait correlations, multivariate analysis was done for improving the accuracy of evaluations. Posterior estimates of direct additive heritability for EP52 increased to 0.08 ± 0.05 when analysed together with EW40 and BW52 traits in a multivariate model, whereas the corresponding estimate for EP64 increased to 0.11 ± 0.05 when analysed with EW40 and BW52. Based on these results, we can conclude that although the additive genetic variability for the selection trait is very low in the population, multitrait evaluations can be more effective for making selection decisions for higher egg production in White Leghorns.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143532177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Siavash Manzoori, Rasoul Vaez Torshizi, Ali Akbar Masoudi, Mehdi Momen
{"title":"Novel Candidate Genes Detection Using Bayesian Network-Based Genome-Wide Association Study of Latent Traits in F2 Chicken Population.","authors":"Siavash Manzoori, Rasoul Vaez Torshizi, Ali Akbar Masoudi, Mehdi Momen","doi":"10.1111/jbg.12926","DOIUrl":"https://doi.org/10.1111/jbg.12926","url":null,"abstract":"<p><p>In chickens, economically important traits are commonly controlled by multiple genes and are often correlated. The genetic mechanisms underlying the correlated phenotypes likely involve pleiotropy or linkage disequilibrium, which is not handled properly in single-trait genome-wide association studies (GWAS). We employed factor analytical models to estimate the value of latent traits to reduce the dimensionality of the adjusted phenotypes. The dataset included phenotypes from 369 F2 chickens, categorised into six observable classes, namely body weight (BW), feed intake (FI), feed efficiency (FE), immunity (IMU), blood metabolites (BMB), and carcass (CC) traits. All birds were genotyped using a 60K SNP Beadchip. A Bayesian network (BN) algorithm was used to discern the recursive causal relationships among the inferred latent traits. Multi-Trait (MT) and Structural Equation Model (SEM) were applied for association analysis. Several candidate genes were detected across six phenotypic classes, namely the IPMK gene for BW and FI, and, the MTERF2 gene for BW and FE. The rs14565514 SNP, close to genes IPMK, UBE2D1, and CISD1, was recognised as a pleiotropic marker by both models. The NRG3 gene, located on chromosome 6, was associated with FI. CRISP2, RHAG, CYP2AC1, and CENPQ genes, located on chromosome 3, were detected for BMB through both MT- and SEM-GWAS. In general, the results indicated that the SEM-GWAS is superior to MT-GWAS due to considering the causal relationships among the traits, correcting the effects of the traits on each other, and also leading to the identification of pleiotropic SNP markers.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143451050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}