Journal of Animal Breeding and Genetics最新文献

{"title":"Phenotypic Responses to Selection in Ross 308 Broiler Breeders: Long-Term Growth Assessed With Nonlinear Models Across Four Generations.","authors":"Lajan Salahaldin Ahmed, Haval Ismail Aziz","doi":"10.1111/jbg.70053","DOIUrl":"https://doi.org/10.1111/jbg.70053","url":null,"abstract":"<p><p>Phenotypic responses to selection in growth performance of Ross 308 broiler breeders were evaluated using longitudinal body weight records from hatch to 64 weeks across four successive generations (G1-G4). The effects of generation, sex, and their interaction on body weight were examined, and sex-specific growth trajectories were modelled using eight nonlinear growth functions (Gompertz, Richards, Logistic, Brody, von Bertalanffy, Weibull, Hossfeld, and López). Generation and sex exerted highly significant effects on body weight across most ages (p ≤ 0.0001), with males consistently heavier than females and sexual dimorphism becoming evident after 4 weeks of age. At 60 weeks, fourth-generation birds exhibited higher body weights than first-generation birds (males: 5036.5 vs. 4744.3 g; females: 4152.2 vs. 3858.3 g), indicating progressive phenotypic improvement across generations. A significant generation × sex interaction (p ≤ 0.05) indicated that the magnitude of sexual dimorphism varied among generations. Model performance was evaluated using the coefficient of determination (R²), adjusted R² ( <math> <semantics> <mrow><msubsup><mi>R</mi> <mi>adj</mi> <mn>2</mn></msubsup> </mrow> <annotation>$$ {R}_{mathrm{adj}}^2 $$</annotation></semantics> </math> ), mean square error (MSE), root mean square error (RMSE), Akaike's Information Criterion (AIC), and Bayesian Information Criterion (BIC). All nonlinear models adequately described the growth patterns of Ross 308 broiler breeders. Among them, the Gompertz function generally provided the best fit across generations and sexes (R² = 0.9978-0.999; <math> <semantics> <mrow><msubsup><mi>R</mi> <mi>adj</mi> <mn>2</mn></msubsup> </mrow> <annotation>$$ {R}_{mathrm{adj}}^2 $$</annotation></semantics> </math>  = 0.9974-0.999; MSE = 1521.5-1988.5; RMSE = 39.03-44.59), while the Richards model effectively captured sex- and generation-specific variation in growth trajectories. Inflection point weights ranged from 1819.5 to 2012.5 g in males and from 1433.7 to 1573.4 g in females. Predicted values were closely aligned with observed data across models, indicating good descriptive performance of the fitted functions. These findings highlight consistent phenotypic improvement in growth traits across generations and demonstrate that the Gompertz model provides a practical and robust framework for describing and monitoring growth dynamics in broiler breeder populations, supporting its use in selection and management decisions.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147846400","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 and Sex-Specific Architecture of Observed and Latent Fertility Phenotypes in a Closed Breeding Nucleus of an Arctic Salmonid.","authors":"Fotis Pappas, Martin Johnsson, Paul Vincent Debes, Christos Palaiokostas","doi":"10.1111/jbg.70051","DOIUrl":"https://doi.org/10.1111/jbg.70051","url":null,"abstract":"<p><p>Successful reproduction is a key factor for efficient breeding schemes and sustainable animal farming. Aquaculture breeding programs rely heavily on small fractions of selected breeders to yield large production stocks, given the high fecundity typically observed in these species. In Sweden, Arctic charr (Salvelinus alpinus) is a salmonid with notable commercial potential, with a selective breeding program operating for 10 generations under a growth-rate focused breeding goal. Despite significant gains, the nucleus faces challenges with low and fluctuating fertility impeding expansion efforts. In this study, we estimate genetic parameters for charr milt quality phenotypes measured with specialised cytometry and Computer-Assisted Sperm Analysis (CASA). At the same time, we assess the sex-specific architecture governing egg count and sperm concentration along body size. Finally, we propose a novel analytical framework for the analysis of realised fertilisation success rates by considering a multiplicative system of latent maternal and paternal contributions. Low to moderate heritability estimates and genetic correlations were obtained from multi-trait modelling for traits reflecting sperm quality along with high estimates for fork length. Genetic correlations among sperm kinematic parameters appeared strong, while the same traits showed weak positive and weak negative correlations with sperm concentration and fork length, respectively. Furthermore, a negative genetic correlation between sperm concentration and both male body size and egg count suggests a complex interplay of a possible trade-off and sexual antagonism. Our latent fertility analytical approach returned low to moderate heritability estimates depending on the modelling configuration. Overall, our study demonstrated the complexity characterising the heritable portions of reproductive traits in Arctic charr and tested alternative tools that have the potential for integration into selective breeding programs.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147789464","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":"Better Multi-Breed Genomic Predictions for Tropical Bull Fertility Using a Breed-Adjusted Genomic Relationship Matrix.","authors":"Antonio Reverter, Pâmela A Alexandre, Marina R S Fortes, Laercio R Porto-Neto","doi":"10.1111/jbg.70052","DOIUrl":"https://doi.org/10.1111/jbg.70052","url":null,"abstract":"<p><p>The pressing requirement for agricultural systems to adopt climate change adaptation strategies specifically designed for tropical environments underscores the significance of implementing sustainable bull breeding practices in beef cattle operations. We consider alternative approaches to generation of single- and multi-breed genomic predictions for a population of Brahman (N = 1051), Santa Gertrudis (N = 929) and UltraBlack (N = 844) bulls with genotypes at high-density and phenotypes for scrotal circumference (SCC; mean ± SD = 31.82 ± 4.32 cm), sheath score (SHS; 3.70 ± 1.98) and percent normal sperm (PNS; 63.34% ± 28.22%). We examined five genomic prediction models: three single breed and two multi-breed. The later contained a multi-breed genomic relationship matrix computed without (GRM_u) or adjusting (GRM_a) for breed-specific allele frequencies. Bias, dispersion and accuracy of the genomic predictions across the five models was computed based on cross-validation and using the LR method. The elements of the multi-breed GRM_u revealed anomalies including a multi-modal distribution of diagonal and off-diagonal elements with all diagonal values above one (range: 1.022 to 1.524) and averaging 1.163. Instead, GRM_a values were consistent with expectations: diagonals with a single mass around one (range: 0.844 to 1.391) and off-diagonal values with a single mass around zero. Estimates of heritability (h² ± SE) with the GRM_u model were 0.501 ± 0.037, 0.458 ± 0.037 and 0.362 ± 0.030, for SCC, SHS and PNS, respectively; while h² estimates using GRM_a were comparable for SCC (0.434 ± 0.037), and SHS (0.439 ± 0.038), and possibly lower for PNS (0.226 ± 0.032). Estimates of genetic correlation (r_g) were similar for both models, except for the r_g between SHS and PNS which moved from -0.095 ± 0.119 using GRM_u to -0.298 ± 0.113 using GRM_a. For all traits, the correlation between GEBV from GRM_u and GRM_a was > 0.90, indicating similar ranking of animals regardless of the relationship matrix used. However, a random cross-validation scheme showed that using GRM_a increased GEBV accuracies from 0.550 to 0.571 (or 3.7%) for SCC, from 0.496 to 0.509 (or 2.6%) for SHS and from 0.335 to 0.423 (or 26.2%) for PNS. Multi-breed genomic predictions for tropical bull fertility are feasible alternative to individual single-breed evaluation systems. Furthermore, the computational effort required to adjust the genomic relationship matrix for breed-specific allele frequencies is justified by the significant improvement in prediction accuracy, ultimately enhancing the selection of bulls in tropical environments. Collectively these results enable very early in-life selection for bull fertility traits, supporting genetic improvement strategies currently taking place within tropical beef production systems in northern Australia.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147789332","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 Relationships Between Residual Gain and Economically Important Traits in Nellore Cattle.","authors":"Miller Teodoro, Gabriel Gubiani, Letícia Pereira, Amanda Santos Gubiani, Angélica Simone Cravo Pereira, Roberto Sainz, Cláudio Ulhôa Magnabosco, Fernando Baldi","doi":"10.1111/jbg.70050","DOIUrl":"https://doi.org/10.1111/jbg.70050","url":null,"abstract":"<p><p>Sustainable beef production requires identifying animals with superior feed efficiency to reduce environmental impact and production costs. This study aimed to estimate heritability and genetic correlations between residual gain (RG) and growth, reproductive, carcass and feed efficiency traits in Nellore cattle. A total of 217,333 phenotypic records from animals born between 1980 and 2024, raised in diverse Brazilian regions, were analysed using Bayesian inference with a multi-trait mixed animal model. Heritability estimates for reproductive traits were low, while feed efficiency, growth and carcass traits showed moderate heritabilities. Residual gain exhibited a moderate positive genetic correlation with adjusted weight at 450 days (W450), supporting its potential as a selection criterion for growth efficiency. Genetic correlations between RG and carcass, reproductive and feed efficiency traits were generally low or near zero. However, a negative low genetic correlation and a moderate positive phenotypic correlation with early conception probability indicate complex effects on reproduction. Selection for RG may increase yearling weight and maintenance energy requirements, which can reduce early reproductive performance under restricted nutritional conditions, presenting trade-offs to consider in extensive systems. Conversely, RG may be particularly suitable for intensive systems such as feedlot or finishing operations, where nutritional management can mitigate these limitations. The negative genetic correlation between RG and residual feed intake further highlights RG's ability to identify animals that grow efficiently without increased feed intake. These results confirm that RG is a largely independent trait and shows sufficient genetic variability to respond to selection in Nellore cattle. Using it as a selection criterion can enhance feed efficiency without negatively impacting other economically important traits.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147640738","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":"Estimation of Genetic Variance and Breeding Values for Infectious Disease Susceptibility From Simulated Longitudinal Data Using Generalized Linear Mixed Models Based on Transmission Dynamics.","authors":"A D Hulst, R Pong-Wong, A Doeschl-Wilson, M C M De Jong, P Bijma","doi":"10.1111/jbg.70049","DOIUrl":"https://doi.org/10.1111/jbg.70049","url":null,"abstract":"<p><p>Recent theoretical work shows that the potential of genetic selection to reduce the prevalence of infectious diseases is much larger than expected from classical quantitative genetic theory, due to indirect genetic effects that arise in the transmission process. However, to fully benefit from these indirect effects, we need to estimate genetic parameters and breeding values, which requires statistical methods tailored to the transmission process. Here, we evaluate Generalized-Linear-Mixed Models (GLMMs) implemented using software commonly used in animal breeding to estimate genetic parameters and breeding values for susceptibility of hosts to infection, using simulated data of epidemics. Longitudinal records of individuals' infection state provide information on the order of infection, as well as on the exposure dose of non-infected animals. Such information can be harnessed to estimate genetic parameters for susceptibility, and can be included in a GLMM as a so-called offset. Therefore, we used longitudinal records of individual infection state to assess the impact of sampling interval, population structure, infection characteristics, and model formulation on the estimated genetic variance and breeding values for susceptibility. The results show that a GLMM fitted to longitudinal records of individual binary infection state can produce accurate and unbiased estimates of genetic variance, as well as good prediction accuracies of breeding values for susceptibility to an infectious disease. Of the data requirements, the time interval between consecutive observations on individual infection state was the main factor affecting estimation, while group size had a limited effect. The required observation interval depends on the infection and recovery rates of individuals. The GLMM thus seems an accurate and easily implementable model to estimate genetic parameters and breeding values for susceptibility when dense longitudinal records on individual infection status are available.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147640728","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":"Impact of Model Parameterisation and Variance Component Estimates on Genomic Predictions of Carcass Traits in Montana Composite Cattle","authors":"Caroline Assis Almeida,&nbsp;Felipe Eguti de Carvalho,&nbsp;Flávia Cristina Bis,&nbsp;Rachel Santos Bueno Carvalho,&nbsp;Elisângela Chicaroni de Mattos,&nbsp;Rafael Espigolan,&nbsp;Joanir Pereira Eler,&nbsp;Luís Telo da Gama,&nbsp;Fernando Baldi,&nbsp;José Bento Sterman Ferraz","doi":"10.1111/jbg.70032","DOIUrl":"10.1111/jbg.70032","url":null,"abstract":"<p>This study evaluated the influence of variance component (VC) estimates, obtained from different models and two relationship matrices, pedigree-based (BLUP) and genomic information-based (ssGBLUP), on genomic predictions of carcass traits in Montana composite cattle. Phenotypic records from 14,422 animals were analysed for ribeye area, rump fat thickness, backfat thickness and marbling, along with pedigree information from 193,129 animals and genomic data from 3911 animals genotyped with 49,457 SNPs. Variance components and heritability estimates were calculated using restricted maximum likelihood under single-trait linear models. Across five models (M1–M5), fixed effects included contemporary group, embryo transfer, age at ultrasound and cow age at calving, while random effects included direct genetic effect and residual. From model M2 onwards, biological type, heterosis and both combined and specific recombination effects were also considered. The Akaike information criterion (AIC) was used to identify the best-fitting model. Different VC estimates were applied in ssGBLUP predictions to evaluate predictive ability based on accuracy, bias and dispersion. Variance component and heritability estimates were similar between methods, although ssGBLUP yielded higher direct additive genetic variances and heritabilities. More parameterised models using ssGBLUP provided a better fit according to AIC. However, less parameterised models showed superior predictive ability, regardless of whether VCs were estimated by BLUP or ssGBLUP. When comparing predictive ability across sources, pedigree-based VC estimates resulted in more accurate predictions. Thus, the choice of model complexity should be guided by the analysis objective and the available data structure.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":"143 3","pages":"431-442"},"PeriodicalIF":1.9,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13054125/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145589584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic Evaluation of Beef Sires Using a Beef-on-Dairy Crossbred Reference Population","authors":"Julius Mugambe,&nbsp;Christin Schmidtmann,&nbsp;Jorge Hidalgo,&nbsp;Rana Ahmed,&nbsp;Georg Thaller","doi":"10.1111/jbg.70030","DOIUrl":"10.1111/jbg.70030","url":null,"abstract":"<p>In recent years, Beef-on-Dairy (BoD) crossbreeding programs have gained momentum to enhance dairy cattle's economic and genetic merits while meeting the demand for high-quality beef. However, bulls with superior growth potential can lead to calving problems; thus, Holstein dairy farmers must decide which semen to use to avoid calving problems while producing heavier BoD calves. In this study, our objective was to genetically evaluate beef sires using a BoD crossbred reference population for three major economic traits, i.e., gestation length (GL), birth weight (BW), and calving ease (CE). A population comprising 4420 BoD calves sired by bulls from Angus (ANG), Limousin (LIM), Wagyu (WAG), and White-Belgian Blue (WBB) was used to perform a joint genetic evaluation of the sire for traits. Univariate and bivariate (linear-linear or threshold-linear) models were applied to estimate variance components and genomic breeding values using single-step methods. Estimates from CE models were transformed from the liability to the observable scale for more straightforward interpretation. Direct heritabilities for GL, BW, and CE (after transformations) ranged from 0.33 to 0.35, 0.33 to 0.37, and 0.02 to 0.14, respectively, while maternal heritabilities ranged from 0.11 to 0.17 for all traits. Generally, male BoD calves had higher probabilities for calving difficulty, with calvings being more difficult if sired by LIM (13%) as compared to ANG (7%) and WBB (9%) when considering male calves. The bivariate models outperformed the univariate models. For CE, the accuracy of predictions was up by 95% with a reduction in bias and dispersion. WBB sires were preferred when crossing with higher parity cows compared to ANG sires. These findings demonstrate that a well-structured BoD reference population enables accurate genomic evaluation of beef sires, facilitating the selection of sires that produce economically viable calves with reduced calving difficulties.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":"143 3","pages":"390-402"},"PeriodicalIF":1.9,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13054129/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145524760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of Genomic Random Regression Models for Genetic Parameter Estimations of Female Fertility Traits in Different Parities in German Holsteins","authors":"Sina Sakhaei-far,&nbsp;Tong Yin,&nbsp;Sven König","doi":"10.1111/jbg.70027","DOIUrl":"10.1111/jbg.70027","url":null,"abstract":"&lt;p&gt;The aim of the present study was to infer genetic (co) variance components and to estimate parity-specific breeding values for the female fertility traits non-return rate after 56 days, the interval from calving to first service and days open by applying random regression models on a time-dependent parity scale. In this regard, we considered a female fertility dataset comprising 592,829 records on 190,269 German Holstein cows and heifers kept in 45 large-scale dairy contract herds. From a subset of 21,316 cattle with phenotypic records, (imputed) 50 K genotypes were available. The applied genomic random regression model considered Legendre polynomials of order 2 for the additive-genetic effects along the parity scale, and combined pedigree and genomic relationships through the &lt;b&gt;H&lt;/b&gt;-matrix. Results were compared with genetic parameter estimates from a multiple-trait model, considering the same fertility trait in different parities as different traits. From both modelling approaches, we observed the trend of increasing genetic variances and heritabilities with increasing parity. Especially for the non-return rate, the genetic variance in heifers was substantially smaller than in all parities of cows. With regard to the random regression model, genetic correlations between the same fertility traits from adjacent parities were close to 1, but gradually declined with increasing parity distances. Small genetic correlations were also estimated between non-return rates in heifers with non-return rates in all cow parities, i.e., 0.50 with parity 1, 0.44 with parity 2, 0.41 with parity 3, 0.35 with parity 4, 0.33 with parity 5, and 0.25 with parity 6. A similar pattern for genetic correlations in the same traits across parities was confirmed from the multiple-trait model application. Estimated breeding values for all fertility traits in different parities of sires with at least 10 phenotyped daughters per trait (estimates from the random regression model) were correlated with their official breeding indexes from the national genetic evaluation. In this regard, moderate differences were observed when comparing breeding value correlations for non-return rates in heifers with respective correlations in all cow parities. From a practical breeding perspective, the most important results were the rather small genetic correlations for the same traits in different parities (e.g., 0.24 between calving to first service in parities 1 and 6), and differing breeding value correlations with other breeding indexes in different parities. These findings suggest the implementation of specific genetic evaluations for specific cow parities, as an extension to the existing separation between heifer and cow fertility traits. Parity-specific breeding value correlations from the random regression and the multiple-trait model considering the sires with at least 10 daughters were larger than 0.85, suggesting only minor re-rankings of sires from the two different modeling app","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":"143 3","pages":"377-389"},"PeriodicalIF":1.9,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13054121/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145514535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic Parameter Estimation for Plasma Biomarkers Associated With Energy Reserves During Critical Physiological Stages in Sheep","authors":"Agnes Nyamiel,&nbsp;Andres Legarra,&nbsp;Didier Marcon,&nbsp;Christian Durand,&nbsp;Sébastien Douls,&nbsp;Gaetan Bonnafe,&nbsp;Anne Tesnière,&nbsp;Eliel González-García,&nbsp;Dominique Hazard","doi":"10.1111/jbg.70028","DOIUrl":"10.1111/jbg.70028","url":null,"abstract":"<p>The ability of ruminants to mobilise and restore body reserves (BR) over time, referred to as BR dynamics, is currently considered an interesting biological component to be included in breeding programs targeting enhanced BR resilience. However, genetic studies of proxies for BR levels and BRD remain scarce, particularly in small ruminants. The aim of this study was to estimate the genetic parameters for key plasma biomarker concentrations in sheep at critical physiological stages (PhySt i.e., mating; mid-pregnancy, before-lambing, after-lambing, and weaning), and their changes over time. Non-esterified fatty acids (NEFA), β-hydroxybutyrate (BHB), triiodothyronine (T3) and insulin (INS) were monitored at those PhySt in successive production cycles. A total of 659 productive Romane ewes were phenotyped for one (<i>n</i> = 252, multiparous) or two (<i>n</i> = 407, primiparous and multiparous) cycles. BR mobilisation was observed from the second half of pregnancy and during suckling while BR accretion was more evident from weaning until the next mid-pregnancy. Considering biomarkers concentrations as repeated measurements through the whole production cycle, heritability estimates were 0.07, 0.09, 0.15, and 0.10 for NEFA, BHB, T3, and INS, respectively. Heritability estimates for plasma biomarkers at key PhySt ranged from 0.08 to 0.16 for NEFA, 0.07 to 0.12 for BHB, 0.09 to 0.18 for T3, and 0.04 to 0.15 for INS. Heritability estimates for biomarker changes over time ranged from 0.01 to 0.23. Genetic correlation estimates between different PhySt were positive for each plasma biomarker and ranged from 0.19 to 0.87 for NEFA, from 0.50 to 0.89 for BHB, from 0.54 to 0.95 for T3 and from 0.34 to 0.90 for INS. Most genetic correlation estimates between biomarkers at a given PhySt were generally low to moderate (<i>r</i>_<i>g</i> = −0.52 to 0.59), with few showing strong negative or positive values beyond 0.60 in magnitude. Considering changes over time, correlations were similarly low to moderate (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>r</mi>\u0000 <mi>g</mi>\u0000 </msub>\u0000 </mrow>\u0000 </semantics></math> = −0.59 to 0.53), with only a few estimates reaching high values (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>r</mi>\u0000 <mi>g</mi>\u0000 </msub>\u0000 </mrow>\u0000 </semantics></math> = −0.60 to −0.97 and 0.67 to 0.97). This study demonstrates that blood biomarkers related to energy BR have genetic variation, indicating their potential for implementation in sheep breeding programs aimed at improving BR use and build-up.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":"143 3","pages":"443-456"},"PeriodicalIF":1.9,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13054124/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145643179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Changes in Genetic Parameters and Genomic Selection of Lambing Rate in Hu Sheep Following Marker-Assisted Selection","authors":"Yuan Zhao,&nbsp;XiaoXue Zhang,&nbsp;FaDi Li,&nbsp;Huibin Tian,&nbsp;DeYin Zhang,&nbsp;Xiaolong Li,&nbsp;YuKun Zhang,&nbsp;JiangBo Cheng,&nbsp;ZongWu Ma,&nbsp;ChangChun Lin,&nbsp;XiWen Zeng,&nbsp;LiMing Zhao,&nbsp;WeiMin Wang","doi":"10.1111/jbg.70036","DOIUrl":"10.1111/jbg.70036","url":null,"abstract":"<div>\u0000 \u0000 <p>The identification of quantitative trait locus (QTL) or genes responsible for key agronomic traits has significantly enhanced genetic improvement through marker-assisted selection (MAS). However, the impacts of MAS on genetic parameters and subsequent selection processes have not been thoroughly characterised. Here, through genome-wide selective sweep analysis, we identified a diverse set of genes involved in oocyte meiosis, including <i>PPP3CA</i>, <i>AR</i>, <i>PPP1CB</i>, <i>SPDYA</i>, <i>MAD1L1</i>, and <i>BMPR1B</i>. The genome-wide association study (GWAS) further identified three genes <i>UNC5C</i>, <i>BMPR1B</i>, and <i>PDLIM5</i> as being associated with lambing rate in Hu sheep. From these analyses, the <i>FecB</i> loci emerged as a potential molecular marker for lambing rate. with an increase of 0.5 lambs per G allele. The heritability of the lambing rate was estimated to be 0.19 (±0.02). Moreover, based on 10-fold cross-validation, the accuracy of genomic selection (GS) was found to be 0.30. Simulated MAS resulted in a reduction of the additive genetic variance components, with estimated heritability dropping to 0.14 (±0.02) and GS accuracy decreasing to 0.18—representing a decline of 26.42% and 34.81%, respectively. To address the reduced GS accuracy, we performed GWAS on the reference set to identify weighted single nucleotide polymorphisms (SNPs). This method has the potential to increase accuracy by 13.8%. Our study found that MAS has a negative impact on GS. To address this issue, we integrated prior information on SNPs from GWAS, which exhibit pleiotropic genetic architecture. This integration enables us to utilise genetic markers for complex traits more effectively, thereby improving the accuracy and efficiency of GS.</p>\u0000 </div>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":"143 3","pages":"465-478"},"PeriodicalIF":1.9,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145702895","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}