Journal of Animal Breeding and Genetics最新文献

{"title":"Genetic Parameters for Direct and Maternal Effects on Pre-Weaning Growth and Efficiency-Related Traits in Inter-Cross Lamb.","authors":"Abdul Rahim, Rajni Chaudhary, R Pourouchottamane, Pallavi Chauhan, K S Rajaravindra, G R Gowane, Arun Kumar","doi":"10.1111/jbg.12945","DOIUrl":"https://doi.org/10.1111/jbg.12945","url":null,"abstract":"<p><p>The objective of this investigation was to estimate the (co)variance components and genetic parameters for pre-weaning growth traits in inter-cross sheep maintained at NTRS, ICAR-CSWRI, Garsa, India. Data records of 1891 lambs for birth weight (BW) and 1763 lambs for weaning weight (WW) descending from 183 rams and 667 dams, born between 2012 and 2023, were utilised in the study. The live weight was used for the calculation of pre-weaning average daily weight gain (PDWG), pre-weaning Kleiber ratio (PKR), pre-weaning growth efficiency (PGE) and pre-weaning relative growth rate (PGR). The fixed effects used in the model were birth year, genetic group, sex, type of birth, and parity of dam. Estimation of covariance components was carried out by fitting a series of animal models using the average information restricted maximum likelihood (AIREML) algorithm. The best-fitting model was determined after testing for improvement in log-likelihood values. The overall LSM ± SE for BW, WW, PADG, PKR, PGE, and PGR were 3.29 ± 0.04 kg, 14.83 ± 0.22 kg, 127.87 ± 2.46 g, 16.78 ± 0.13, 357.53 ± 7.13, and 1.66 ± 0.02, respectively. Analysis revealed that pre-weaning traits were significantly (p < 0.05) affected by year of birth, parity of dam, type of birth and sex of the lamb. Direct heritability estimates were 0.11 ± 0.04, 0.16 ± 0.04, 0.16 ± 0.04, 0.15 ± 0.06, 0.18 ± 0.06 and 0.17 ± 0.06 for BW, WW, PADG, PKR, PGE, and PGR, respectively. The corresponding maternal heritability estimates for BW, PKR, PGE, and PGR traits were 0.19 ± 0.03, 0.11 ± 0.04, 0.13 ± 0.04, and 0.12 ± 0.04, respectively. For WW and ADWG, only direct effects were significant. The correlations of WW with efficiency-related traits and among the other traits were quite high and positive. Significant impact of maternal care for early growth traits in this breed indicates the importance of considering both direct and maternal effects for genetic evaluation. The moderate estimate of heritability for WW with high and positive genetic correlations with other traits, makes this trait a candidate for selection in the present flock. We therefore recommend the use of WW as a single trait selection criterion for the overall improvement of the growth traits in the sheep flock.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144210270","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 Insights: Balancing Milk Yield, Fat: Protein Ratio and Fertility in Primiparous Cows From Subtropical Regions.","authors":"Amauri Felipe Evangelista, Altair Antônio Valloto, Lenira El Faro, Rodrigo Junqueira Pereira, Laila Talarico Dias, Rodrigo de Almeida Teixeira","doi":"10.1111/jbg.12944","DOIUrl":"https://doi.org/10.1111/jbg.12944","url":null,"abstract":"<p><p>In this study, we aimed to evaluate the genetic association between fertility traits, milk yield and the fat: protein ratio (FPR) on the test day in primiparous Holstein cows. The analysed traits were milk yield (TDMY) and FPR assessed on the test day, as well as the following fertility traits: period from calving to first service (CFS), days open (DO) and calving interval (CI). Genetic parameters were estimated through bivariate analysis, using a random regression model (considering fourth-order Legendre polynomials) and the Bayesian method, with GIBBS2F90 software. Heritability estimates varied between 0.11 and 0.22 for TDMY, between 0.16 and 0.30 for FPR and between 0.03 and 0.05 for the fertility traits. Correlation estimates between TDMY and fertility traits tended to increase from early lactation until approximately day 100, then decreased slightly before continuing to grow until the end of lactation. Genetic correlations between TDMY and FPR were negative throughout lactation, ranging from -0.04 on day 5 to -0.37 in the final third of this period. The genetic correlations between FPR and fertility traits were positive in early lactation and negative in late lactation (except for CFS). These results indicate that TDMY and FPR are heritable and can be used as selection criteria in Holstein cows in Brazil. However, for fertility traits, genetic gains through direct selection may be slow. Additionally, a high level of milk production and FPRs in early lactation negatively impact fertility traits.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144188497","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":"Estimates of Variance Components and Genetic Parameters for Weekly Weight in Juvenile Dairy Goats Using Random Regression Models.","authors":"Chrilukovian B Wasike, Ruth Wambui Waineina, Kiplangat Ngeno, Sophie A Miyumo, Christine M Kamidi, Josephine M Mwabili, Evans D Ilatsia","doi":"10.1111/jbg.12942","DOIUrl":"https://doi.org/10.1111/jbg.12942","url":null,"abstract":"<p><p>Growth performance of juvenile dairy goats influences their rate of growth and consequently (re)productive performance as mature goats. However, dairy goat improvement programmes focus on milk and fertility traits and seldom growth traits. This study aimed at estimating variance components and genetic parameters for growth in juvenile dairy goats to avail these estimates for inclusion in the national dairy goat improvement program. 4072 weekly weights records (from 1 week to 16th week of age) were collected on 453 goats born of 35 dams and 15 sires of Saanen, Toggenburg, Alpine and their crossbred genotypes. The records were subjected to univariate random regression analysis fitting direct additive, maternal genetic and permanent environmental [PE] effects as random effects to estimate variance components and genetic parameters. Phenotypic, additive genetic, maternal genetic and PE variances increased along the growth trajectory. Estimates of variance ratios ranged from 0.015 ± 0.14 to 0.469 ± 0.15, 0.097 ± 0.06 to 0.204 ± 0.08 and 0.407 ± 0.13 to 0.641 ± 0.08 for additive genetic, maternal genetic and PE effects, respectively. Correlation estimates were positive. Additive genetic correlations between the weekly weights were high and near unity. Maternal genetic correlations between the weekly weights were equally high. PE correlations were low between early weights and later weights, although correlations between later weights were high. The correlation estimates decreased as the interval between the weights increased for all the random effects. There is sufficient scope of variance in weekly weights to enable selective breeding. Selection to improve later weights could be done based on early weekly weights given the high additive genetic correlations.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144175877","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":"Lactation Curve Modelling and Genetic Parameters Estimation in Murciano-Granadina Goats.","authors":"Morteza Mokhtari, Zahra Roudbari, Ehsan Mohebbinejad, Ali Esmailizadeh","doi":"10.1111/jbg.12940","DOIUrl":"https://doi.org/10.1111/jbg.12940","url":null,"abstract":"<p><p>The present study aims to determine the best non-linear model for describing lactation curves and estimating genetic parameters for the lactation curve traits in the Murciano-Granadina goats in Iran. We compared five mathematical models including the Cappio-Borlino (CB), Cobby and Le Du (CD), Narushin-Takma (NT), Wilmink (WL), and Wood (WD) to characterise the lactation curve in the first and second lactations of Murciano-Granadina does. The dataset consisted of 36,958 and 23,319 milk yield test-day records from 4964 first-parity and 3335 s-parity Murciano-Granadina does, respectively. These records were collected from 2017 to 2024 in a private dairy farm, located in Ghale-Ganj city, Kerman province, southern area of Iran. In both lactation periods, the WD model showed the lowest values for root mean squares of prediction error (RMSE) and Akaike's information criterion (AIC), as well as the highest adjusted coefficient of determination ( <math> <semantics> <mrow> <msub><msup><mi>R</mi> <mn>2</mn></msup> <mi>adj</mi></msub> </mrow> <annotation>$$ {R^2}_{adj} $$</annotation></semantics> </math> ) among the evaluated models. Additionally, positive autocorrelations were observed among the residuals for all the models considered, with the lowest positive autocorrelation obtained under the WD model. Therefore, WD was identified as the best model to characterise the lactation curve of the Murciano-Granadina does in the first and second lactation periods. Consequently, we computed the individual lactation curve traits for does in the ith parity (where i = 1 for the first parity and i = 2 for the second parity), including peak time (PTi), peak milk yield (PYi), and lactation persistency (LPi), using the parameters derived from the WD model. A multivariate animal model utilising a Bayesian approach was employed to estimate the genetic parameters of the lactation curve traits. The posterior means for heritability estimates were 0.07, 0.13, 0.05, 0.05, 0.11, and 0.08 for PT1, PY1, LP1, PT2, PY2, and LP2, respectively. In the first parity, genetic correlations among the lactation curve traits were positive estimates of 0.28, 0.96, and 0.25 for PT1-PY1, PT1-LP1, and PY1-LP1, respectively. In the second parity, the corresponding genetic correlation estimates were 0.88, 0.89, and 0.59 for PT2-PY2, PT2-LP2 and PY2-LP2, respectively. It can be concluded that the low heritability estimates for the investigated lactation curve traits suggest these traits are mainly affected by non-additive genetic and environmental effects. Consequently, direct genetic selection may not effectively modify the shape of the Murciano-Granadina lactation curve. The positive genetic correlation estimates among the traits examined within each parity, as well as among the same traits across the parities, suggest that selecting one trait will also enhance the other traits.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144027002","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 Weight, Carcass and Stayability in Nellore Females.","authors":"Isabella Silva de Carvalho, Sirlene Fernandes Lázaro, Eula Regina Carrara, Matheus Rodrigues de Souza, Humberto Tonhati","doi":"10.1111/jbg.12941","DOIUrl":"https://doi.org/10.1111/jbg.12941","url":null,"abstract":"<p><p>Traits related to growth, carcass quality and stayability are key components in enhancing the profitability and sustainability of Nelore cattle production systems. This study aimed to estimate heritabilities and genetic and environmental correlations for these traits using a Bayesian approach. Data from 94,703 females were analysed for weights at 210, 365 and 450 days of age (W210, W365 and W450), loin eye area (LEA), subcutaneous fat thickness in the loin (LFT) and rump (REFT) and stayability at 48, 54 and 72 months (STAY48, STAY54 and STAY72). Heritability estimates (± standard error) were 0.14 ± 0.03 for LEA, 0.20 ± 0.03 for LFT, 0.43 for REFT, 0.12 ± 0.02 for STAY54, and 0.18 ± 0.02 for STAY72. Moderate heritabilities for W210, W365, W450, LFT and REFT indicate a substantial additive genetic component, whereas lower estimates for LEA and stayability suggest a predominant influence of environmental factors. Genetic trends were generally positive but moderate: 0.14 kg/generation (W210), 1.40 kg/generation (W365), 1.77 kg/generation (W450), 0.016 cm²/generation (LEA) and 0.0081 months/generation (STAY72). In contrast, STAY48 showed a slightly negative trend (-0.0073 months/generation). Direct selection for W450 yielded a genetic gain of 9.837 kg, whereas indirect selection via correlated traits resulted in gains ranging from 0.125 to 9.272 kg. These findings highlight the relevance of environmental effects on traits with low heritability, such as LEA and stayability, and reinforce the effectiveness of selection for weight-related traits due to their moderate heritability and favourable genetic trends.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144060776","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":"On the Identifiability of Genetic Parameters for Growth in Mice With a Massively Deep Pedigree.","authors":"X Ding, A A Musa, N Reinsch","doi":"10.1111/jbg.12938","DOIUrl":"https://doi.org/10.1111/jbg.12938","url":null,"abstract":"<p><p>In models with direct and maternal genetic effects, structural features of the data are a potential source of bias and low accuracy of estimates for genetic covariance parameters. One of the well-known reasons for such poor practical identifiability is the lack of dams with own observations. So far, however, no attention has been paid to the impact close relationships may have. Therefore, this genetic-statistical analysis of growth traits in two unselected mouse lines includes investigations on practical identifiability of genetic (co-)variances in the light of the observed high levels of co-ancestry, resulting from massively deep pedigrees. Body weight data had been collected over 33 years (from 1978 to 2011; 145 and 118 generations per line), amounting to approximately 115,000 observations in total for body weight at three developmental stages. Additional analyses of simulated data using the original pedigree structure of one line provided insight into the bias and precision of estimates. Further, closeness to pair-wise structural non-identifiability of genetic (co-)variances was quantified. In univariate analyses, we found genetic correlations between direct and maternal effects all positive for body mass traits at different ages up to mating, except for a single small negative estimate. Overall, multivariate analyses returned somewhat stronger correlations, whereby signs remained unchanged. Simulations showed a tendency toward an upward bias of the direct-maternal genetic correlations and other parameters, especially when the true correlations were higher. For all traits indicators for structural non-identifiability were narrowly close (> 0.998) to unity, the point at which a pair of covariance components no longer can be identified. This narrowness was stronger for separate partitions of data from later generations with higher average inbreeding and within-generation co-ancestry. In conclusion, in models with direct and maternal genetic effects, strong co-ancestry between parents is another feature of the data structure that may result in bias and inflated standard errors of estimated genetic parameters.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144046630","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":"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⁺\" 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⁺\" 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_rtn matrix constructed with a 0.5 allele frequency (AF) and 10% weight (w) on A, G₀₅ constructed using AF = 0.5 and w = 0.0, and G_cal constructed with observed AF and w = 0.0), led to eight ssGBLUP models being tested. This included one UPG model (using G_rtn), four MF models (MF14 and MF52 using G_rtn or G₀₅), and three Q-Q+ models (using G_cal, G₀₅, or G_rtn). The models were evaluated through cross-validation by masking the phenotypes of 5000 genotyped young cows. Results showed that the Q-Q⁺ models using the G_cal or G₀₅ 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 G₀₅ 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_rtn had slightly higher gain in accuracy from adding phenotypic data (2.01%) than G₀₅ (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 G₀₅ showed the least bias (with a small standard error) and most stable predictions, while models using G_rtn introduced biases and instability. Thus, the Q-Q⁺ and MF models combined with G₀₅ and Q-Q⁺ with G_cal 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}

{"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}

{"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}

{"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}