Journal of Animal Breeding and Genetics最新文献

{"title":"Multi-Breed Genomic Predictions for Average Daily Gain in Three Italian Beef Cattle Breeds.","authors":"Daniele Colombi, Renzo Bonifazi, Fiorella Sbarra, Andrea Quaglia, Mario P L Calus, Emiliano Lasagna","doi":"10.1111/jbg.70004","DOIUrl":"https://doi.org/10.1111/jbg.70004","url":null,"abstract":"<p><p>Marchigiana, Chianina, and Romagnola are three Italian autochthonous beef cattle breeds that have been historically selected for meat production. Recent advancements suggest that the use of genomic data and multi-breed (MB) models to combine information from different breeds may help to increase the accuracies of genomic predictions, in particular if the available data per breed is limited. This study aimed to evaluate and compare the accuracies of genomic predictions for average daily gain (ADG) in the three Italian breeds. We implemented different scenarios using phenotypes collected on 5303 young bulls in performance tests across the three breeds, 23,793 pedigree records, and 4593 genotypes, and then validated through the linear regression method. The implemented scenarios were: pedigree Best Linear Unbiased Prediction (pBLUP) and single-step Genomic BLUP (ssGBLUP) single-trait single-breed evaluations where each breed was modelled separately; pBLUP and ssGBLUP single-trait multi-breed evaluations where ADG was modelled as the same trait for all breeds, and ssGBLUP multi-trait multi-breed evaluations where ADG was considered as a different correlated trait across breeds. In addition, single- and multi-breed pBLUP and ssGBLUP evaluations were implemented including weight at 1 year of age and muscularity as correlated traits of ADG in a multi-trait approach. Results highlighted the improved accuracies (an average of 5% in ssGBLUP models compared to corresponding pBLUP ones) when incorporating genomic data in the prediction models. Moreover, single-trait multi-breed scenarios resulted in higher accuracy for breeds with lower heritabilities for ADG (an average of 4% for single-trait multi-breed models compared to single-breed ones), confirming the importance of leveraging data from populations with higher heritabilities. Lastly, adding two correlated traits next to ADG in the single- and multi-breed ssGBLUP yielded even higher accuracies than the scenarios only encompassing ADG. The observed increases in accuracy when leveraging data from more populations and/or more traits could be helpful when implementing genomic predictions for innovative traits with limited records per individual or low heritabilities, and for the genetic improvement of local populations where limited data availability represents a challenge for traditional genetic selection.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144638740","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 Reproductive Traits of Ethiopian Sheep Breeds Under Community-Based Breeding Programmes.","authors":"Shanbel Besufkad, Tesfaye Getachew, Zelalem Abate, Shenkute Goshme, Kebede Habtegiorgis, Temesgen Jembere, Armiyas Shibesh, Tusa Gemechu, Barbara Rischkowsky, Berhanu Belay, Moura Rekik, Aynalem Haile","doi":"10.1111/jbg.70003","DOIUrl":"https://doi.org/10.1111/jbg.70003","url":null,"abstract":"<p><p>The evaluation of breeding schemes against established objectives and selection traits is essential for assessing the performance, outputs, and overall impacts of breeding programmes. In Ethiopia, most Community-Based Breeding Programmes (CBBPs) have prioritised growth traits, particularly live weight, as the main selection criteria. However, since productivity relies on both reproductive and growth traits, it is critical to evaluate how these traits are evolving to make necessary adjustments in management practices and breeding schemes. This study considered five indigenous sheep breeds (Menz, Semein, Horro, Bonga and Doyogena), managed under CBBPs since 2009. Fixed effects for reproductive traits were estimated using the GLM procedures of SAS 9.4. Genetic parameters were estimated for all traits using the restricted maximum likelihood (REML) method with WOMBAT software, employing a multivariate repeated model, except for age at first lambing (AFL), which was analysed using a non-repeated multivariate model. Significant effects (p < 0.001) were observed for year of birth, breed of ewe, parity and birth season across all traits in the breeds studied. A general trend of improvement in litter size at birth (LSB), total litter weight at birth (TLWB), litter size at weaning (LSW), total litter weight at weaning (TLWW) and annual reproductive rate (ARR) was noted with increasing ewe parity until the seventh parity, followed by a decline thereafter. Direct heritability estimates for the traits according to the ewe breeds ranged from 0.03 to 0.25 for LSB, 0.02 to 0.16 for LSW, 0.08 to 0.21 for TLWB, 0.07 to 0.22 for TLWW, 0.03 to 0.19 for LI, 0.08 to 0.32 for ARR and 0.15 to 0.36 for AFL. Estimates of direct heritability and repeatability varied by breed and location, generally falling within small to medium ranges. Moderate to high genetic correlations were found between TLWW and other traits suggesting that selection for TLWW may significantly influence reproductive performances across most sheep breeds, with the exception of Menz sheep. The variations in genetic estimates across different breeds and locations indicate that genetic influences may vary depending on the specific context. Moderate to high genetic correlations between TLWW and other reproductive traits suggest that prioritising selection for TLWW could have a significant positive impact on reproductive performance across most sheep breeds, though the Menz breed may not exhibit the same expected benefits. These findings emphasise the need to integrate genetic selection with effective management practices tailored to each breed's specific needs, recommending the culling of unproductive ewes after the seventh parity to enhance the sustainability and productivity of CBBPs in Ethiopia.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144592982","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":"Comparative Analysis of Recursive and Alternative Modelling Approaches Considering Body Condition Score for Genetic Evaluation of Mature Cow Weight.","authors":"Ayooluwa O Ojo, Henrique A Mulim, Andre Garcia, Kelli Retallick-Riley, Stephen P Miller, Hinayah R Oliveira","doi":"10.1111/jbg.70002","DOIUrl":"https://doi.org/10.1111/jbg.70002","url":null,"abstract":"<p><p>Mature cow size, often defined by mature cow weight (MWT), height (MHT) and body condition score (BCS), is crucial to cow-calf profitability, maintenance efficiency and reproductive performance. Although MWT and MHT are often included in national cattle evaluations by many breed organisations, BCS adjustments are applied less consistently. This study investigated the impact of different modelling approaches on the estimation of breeding values for MWT, with a focus on how BCS is accounted for across models. The dataset provided by American Angus Association comprised 382,156 MWT and BCS records from 209,491 cows. Four modelling approaches were evaluated: Model 1 does not consider BCS; Model 2 treated BCS as a categorical fixed effect; Model 3 used pre-adjusted records standardised for BCS and age; and Model 4 used a recursive model to assess MWT as a genetically independent trait from BCS. Spearman correlations between breeding values predicted across models ranged from 0.79 (between Models 1 and 4) to 0.95 (between Models 1 and 2), indicating that 5%-21% of bulls could have different rankings depending on the model used. Concordance in sire selection was assessed between the top 10% of sires in each model, and model-pair comparison revealed differences ranging from 19% (between Models 1 and 2) to 40% (between Models 3 and 4). These differences highlight the potential for model choice to influence the selection outcomes. Model selection can significantly affect the sire rankings, highlighting the importance of carefully selecting the model that best aligns with the selection objectives and the underlying biology of the traits being evaluated. Although Model 4 offers theoretical advantages, this study does not allow for a definitive conclusion on its overall effectiveness, as no simulations were performed. Additional research is needed to confirm its advantages.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144531193","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 Parameters of Resilience Indicators Across Growth in Beef Heifers and Their Associations With Weight, Reproduction, Calf Performance and Pre-Weaning Survival.","authors":"Gustavo R D Rodrigues, Júlia P S Valente, Vanessa T Rezende, Luis F C Araújo, João B Silvaneto, Lúcio F M Mota, Mário L Santana, Roberta C Canesin, Sarah F M Bonilha, Lucia G Albuquerque, Maria E Z Mercadante, Joslaine N S G Cyrillo","doi":"10.1111/jbg.70001","DOIUrl":"https://doi.org/10.1111/jbg.70001","url":null,"abstract":"<p><p>In tropical extensive beef cattle systems, heifers raised on pasture are exposed to various environmental challenges that affect their growth and reproductive performance during the first breeding. Resilience indicators derived from deviations in longitudinal traits can quantify the magnitude of these challenges and the ability of an animal to recover after disturbances. Hence, this study aimed to estimate genetic parameters for resilience indicators derived from weight deviations across growth in Nellore heifers, and their genetic correlations with yearling weight (YW), reproductive traits, calf performance and pre-weaning survival (PWS^c). Phenotypic records were available for 3072 heifers, while 3226 animals were genotyped with 383,856 SNP markers (after quality control). A total of 30,720 weight records were used for growth curve modelling across three developmental phases: yearling, first breeding and first calf weaning. The resilience indicators derived and analysed were as follows: (i) natural logarithm of residual variance (LnVar); (ii) lag^-1 autocorrelation of residuals (r_auto); and (iii) skewness of residuals. The weight, reproductive, calf performance and survival traits analysed were as follows: YW, weight at the beginning of the breeding season (WBS), heifer pregnancy (HP), calves birth weight (BW^c), calves weaning weight (WW^c), calves average daily gain from birth to weaning (ADG^c) and PWS^c. Genetic parameters were estimated using the ssGBLUP method under a Bayesian framework. Heritability estimates (h²) were highest for LnVar, ranging from 0.32 ± 0.03 (calf weaning) to 0.42 ± 0.03 (breeding). Moderate h² values were observed for r_auto (0.22 ± 0.03 to 0.29 ± 0.03), whereas skewness had low heritability (0.08 ± 0.02 to 0.13 ± 0.02). Genetic correlations (r_g) between LnVar and weight traits were unfavourable. In contrast, r_auto exhibited favourable correlations with YW (-0.29 ± 0.08 to -0.50 ± 0.08). LnVar at breeding showed favourable and moderate r_g with HP (-0.37 ± 0.10). All resilience indicators were favourably correlated with PWS^c, with the strongest estimate observed for LnVar at calf weaning (-0.28 ± 0.15). These findings provide novel insights into the genetic basis of resilience in growing beef heifers. LnVar and r_auto, in particular, emerge as promising traits for selecting animals better adapted to environmental variability. Additionally, favourable genetic correlations with fertility and survival traits suggest that more resilient heifers are more likely to become pregnant during their first breeding season and raise calves with higher survival rates until weaning.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144477938","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 Heterogeneity of Residual Variance for Foot Score Traits in American Angus Cattle.","authors":"Sabrina T Amorim, Kelli J Retallick, André Garcia, Noelia Ibañez-Escriche, Gota Morota","doi":"10.1111/jbg.12949","DOIUrl":"10.1111/jbg.12949","url":null,"abstract":"<p><p>Foot conformation is one of the main breeding goals in recent beef cattle breeding programs because it directly affects productivity, economic losses, animal welfare and longevity. Genetic heterogeneity of residual variance can be used to improve production uniformity in animal breeding programs because recent studies have shown that residual variance is partially under genetic control, allowing reduction of variability through selection. Despite being an important breeding goal, research on genetic heterogeneity of residual variance for conformation traits, such as foot angle and foot claw, is still scarce in livestock species. The objectives of our study were (1) to investigate the extent of genetic heterogeneity of residual variances on two conformation traits: foot angle (FA) and claw set (CS) in Angus cattle using genetic homogeneity (M1) and two genetic heterogeneity of residual variance models, including a double hierarchical generalised linear model (DHGLM, M2) and a genetically structured environmental variance model (M3). Genetic parameters for means and residual variances were estimated using M2 and M3. The dataset included 45,667 phenotypic records for FA and CS (scores from 1 to 9 with 5 being ideal) of American Angus cattle recorded from 2009 to 2021. M1 and M2 were fitted using average information restricted maximum likelihood, and M3 was fitted using Markov chain Monte Carlo. Heritability estimates for the means of FA (0.19 ± 0.007 for M1, 0.11 ± 0.005 for M2 and 0.09 ± 0.003) and CS (0.16 ± 0.005 for M1, 0.10 ± 0.004 for M2 and 0.08 ± 0.03) were within the range reported in the literature, but M2 and M3 estimates were lower than M1. Genetic heterogeneity of residual variance was assessed using three parameters: heritability for residual variance, genetic coefficient of variation, and correlation between mean and residual variance. Although heritability estimates for residual variance in M2 were low (0.08 for FA and 0.001 for CS), our results suggest that residual variance is partially under genetic control. The genetic coefficients of variation estimates were 0.08 (M2) and 0.06 (M3) for FA, and 0.06 (M2) and 0.02 (M3) for CS, indicating that selection on the trait mean would also change the residual variance. Our results for FA and CS showed moderate positive genetic correlations in M2 (0.52 for FA and 0.41 for CS) and M3 (0.35 for FA and 0.33 for CS) between mean and residual variance. Positive correlations may limit the response to selection unless other breeding strategies, such as selection indices, are used. FA and CS are promising traits for uniformity or resilience indicators because they are phenotypes that can be collected throughout the production cycle using traditional or digital data recording systems. Our results demonstrate the potential to modulate variability through breeding strategies and present an opportunity to evaluate the uniformity of foot score traits in beef cattle.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144340667","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":"Optimising the Use of Cryopreserved Genetic Resources for the Selection and Conservation of Animal Populations.","authors":"Alicia Jacques, Michèle Tixier-Boichard, Gwendal Restoux","doi":"10.1111/jbg.70000","DOIUrl":"https://doi.org/10.1111/jbg.70000","url":null,"abstract":"<p><p>Genetic diversity is essential for the sustainability and adaptability of populations, and is thus a central pillar of the agro-ecological transition. However, within a population, it is inevitable that some amount of genetic variability is lost, and efforts must be made to limit this as much as possible. A valuable tool in this endeavour could be the use of cryopreserved genetic resources in cryobanks, which could assist in the management of various animal populations in the contexts of both selection and conservation. We performed simulations that revealed that the most appropriate use of ex situ genetic resources depends on characteristics of the target population and its management objectives. For populations under conservation, the aim is to maintain genetic diversity, which was best achieved by the regular use of cryopreserved genetic resources at each generation. For populations under selection, instead, the concern is the addition of additive genetic variability, which benefited from the use of cryopreserved collections over only a few generations based primarily on the genetic values of donors. The use of cryopreserved semen had a beneficial effect when breeding objectives were changed. In both cases, the use of cryopreserved individuals in animal populations requires a large amount of reproductive material: for breeds under selection because the number of offspring is high, and for breeds under conservation because the frozen semen is used repeatedly over a long period. The use of cryopreserved material appears to be an effective means of managing the genetic variability of an animal population, either by slowing down the erosion of variability or by helping to redirect a selection objective. However, care must be taken with populations under selection to limit the disadvantages associated with the reintroduction of old genetic material, in particular the gap in breeding values for traits of interest. Finally, our study highlights the need for a sufficiently large stock of cryopreserved material in collections (e.g., number of doses, straws) to ensure the most efficient use.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144327703","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":"An Increase in Male Recombination Rate With Age in Dairy Cattle Is Heritable and Polygenic.","authors":"Evelyn Jade, Mathew D Littlejohn, Katie Eketone, Richard J Spelman, Jessica Stapley, Anna W Santure","doi":"10.1111/jbg.12948","DOIUrl":"https://doi.org/10.1111/jbg.12948","url":null,"abstract":"<p><p>Meiotic recombination is an essential process for shuffling genetic diversity in sexually reproducing organisms, can vary within and between individuals in response to intrinsic and extrinsic factors, and can be heritable. Interestingly, recombination rate has been found to vary with age in some species, but to date, there have been no assessments of the heritability and genetic architecture of this age effect. Here, we leverage a large pedigree of SNP chip-genotyped Aotearoa New Zealand Holstein-Friesian and Jersey dairy cattle to test for an effect of age on male recombination rate, the heritability of recombination rate and of any such age effect on recombination, and the genetic architecture underlying these two phenotypes. We found a significant, albeit small, increase in the average number of male autosomal recombinations with age. Consistent with previous studies, we found moderate heritability (h² ≈ 0.15) of sire recombination rate and detected association with several regions on chromosome 10 encompassing genes such as REC8, REC114, RNF212B and NEK9. Further, we found novel evidence of some heritability (h² ≈ 0.05) in the rate of change in recombination with age in sires. Variation in the rate of change with age is likely also polygenic, but there is a region on chromosome 1 that is weakly associated with the rate of change. It is unclear whether the heritability of age-related recombination rate change is widespread across species, and we encourage studies in other taxa to assess its prevalence and evolutionary significance.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144295388","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":"Study of Genetic Progress in the Context of Disconnection Between Two Originally Connected Populations.","authors":"M Wicki, A Legarra, J Raoul","doi":"10.1111/jbg.12946","DOIUrl":"https://doi.org/10.1111/jbg.12946","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Genetic progress of breeding programs is highly dependent on the size of reference populations and the relatedness between reference populations and selection candidates. Many reasons can lead a population to split into several subpopulations (sanitary, physiological, political reasons, etc.). More specifically, alternative (e.g., organic) farming may lead to farms breaking away from the conventional scheme to form a distinct breeding scheme, especially in organic sheep farming where the ban on hormones makes the use of artificial insemination (AI) difficult. However, these potential splits of the population into several smaller subpopulations could decrease genetic progress. The aim of our study was to investigate, using stochastic simulations, the impact of separation of the population into two subpopulations while still applying the same breeding objective and methods. We simulated a breeding program inspired by a dairy program but applicable to different species. We simulated two different initial population sizes with 5400 (10,800) females mated to 90 (180) males and a trait of heritability 0.30. This population was under selection for several discrete generations (G-9 to G-1) as a single population. Then, for the last 11 cycles of selection, the population was either maintained as a unique population (scenario \"NoSep\", which was the reference scenario) or split into two subpopulations with different ratios: 50/50, 60/40, 70/30, 80/20, and 90/10. We studied three scenarios in which the population was split: CE (separation and Common Evaluation), in which the evaluation remained common between both subpopulations; SE (separation and separate evaluation), in which the subpopulations were evaluated individually; and NoSel (Separation and No Selection), in which the breeding males were randomly selected, as opposed to the two previous scenarios in which we selected the males based on their GEBVs. We studied the evolution of differentiation of populations (F&lt;sub&gt;st&lt;/sub&gt;), accuracy of predictions, genetic progress, and rate of inbreeding over generations. We observed a faster genetic divergence in the case of an unbalanced split and separate evaluation (F&lt;sub&gt;st&lt;/sub&gt; in G11 equal to 0.134 for the ratio 90/10 scenario SE). The separate evaluation had a significant, negative effect on both the accuracy and genetic gain of the smallest population (minimal accuracy of 0.53 and maximal loss of 16.6% for ratio 90/10 with 5400 females), whereas the accuracy and genetic gain of the largest population were not impacted. Combining the evaluations led to smaller but still significant deterioration of the genetic gain of the smallest population when the ratio was very unbalanced (loss of genetic gain of 14.3% for a ratio of 90/10 with 5400 females). In conclusion, population separation has a negative impact on genetic gain, particularly for small populations. Although it does help in alleviating divergence and loss of genetic gain, joint evaluation ca","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144259350","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":"Genomic Evaluation in Nellore Cattle for Reproductive Traits: Multiple Ways to Account for Missing Pedigrees.","authors":"Larissa Temp, Gabriel Gubiani, Ludmilla Brunes, Claudio Magnabosco, Fernando Bussiman, Jorge Hidalgo, Daniela Lourenco, Fernando Baldi","doi":"10.1111/jbg.12947","DOIUrl":"https://doi.org/10.1111/jbg.12947","url":null,"abstract":"<p><p>Missing pedigrees are a common problem in most populations. Animals with unknown ancestors are usually treated as founders; however, this can underestimate inbreeding, not properly account for different base populations, and bias breeding values. We aimed to assess the use of unknown parent groups (UPG) or metafounders (MF) to model missing pedigrees in a beef cattle population. Phenotypic and genotypic data from the Nellore improvement programme of the Brazilian Breeders and Researchers Association were used. The pedigree contained 3.8 M animals born between 1970 and 2022, of which 51,752 were genotyped. Records for scrotal circumference at 365 days old (SC365, N = 239,806), age at first calving (AFC, N = 560,785) and accumulated cow productivity (ACP, N = 269,330) were used. Four models were implemented: single-step GBLUP without explicitly dealing with missing pedigree (G0), with UPG (G1), with MF (G2) and with <math> <semantics><mrow><mi>G</mi></mrow> <annotation>$$ mathbf{G} $$</annotation></semantics> </math> accounting for group-specific allele frequencies (G3). UPG and MF were assigned based on commercial and registered herds (S1), uncertain paternity (S2) and patriarchs (S3). The accuracy and bias of predictions were assessed using the linear regression (LR) method. Linear, single-trait animal models were used for SC365 and AFC, and multi-trait for ACP. Heritability estimates ranged from 0.07 to 0.40. Compared to G0, accuracy was slightly higher in G2_S2 and G2_S3 (0.70 vs. 0.71) for SC365, G2_S3 (0.49 vs. 0.51) for AFC, G1_S2 for ACP (0.67 vs. 0.71). Bias was small in all the scenarios (≤ 0.06 SD), except of ACP that presented a great bias, including MF. Overall, G1 and G2 had similar accuracy, possibly because of the limited number of genotyped animals linked to MF. Centring the genomic relationship matrix by patriarchs' allelic frequencies resulted in similar accuracy and bias to the MF models. Replicating the study with a larger database containing more genotyped animals connected to MF could help improve the MF estimates, and thus, prediction accuracy and bias.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144235922","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 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}