Journal of Animal Breeding and Genetics最新文献

{"title":"Genetic Relationships Among Resilience, Fertility and Milk Production Traits in Crossbred Dairy Cows Performing in Sub-Saharan Africa.","authors":"R D Oloo, R Mrode, C C Ekine-Dzivenu, J M K Ojango, J Bennewitz, G Gebreyohanes, A M Okeyo, M G G Chagunda","doi":"10.1111/jbg.12933","DOIUrl":"https://doi.org/10.1111/jbg.12933","url":null,"abstract":"<p><p>Change in climate over the past years and its impact on the environment have necessitated the inclusion of resilience traits in the breeding objectives of dairy cattle. However, the relationship between resilience and other traits of economic importance in dairy production is currently not well known. This study examined the genetic parameters and relationships among resilience, fertility and milk production traits in dairy cattle in Kenya. Indicators of general resilience and heat tolerance were defined from the first parity test-day milk yield records. Indicators of general resilience included variance of actual deviations (LnVar1), variance of standardised deviations (LnVar2), lag-1 autocorrelation (r_auto) and skewness (Skew) of standardised deviations in milk yield. Heat tolerance indicators at temperature-humidity index 80 included the slope of the reaction norm (Slope), absolute slope of the reaction norm (Absolute), and the intercept of the reaction norm model (Intercept). Cows with > 50% taurine genes had lower age at first calving (AFC), longer calving intervals (CI) and higher test-day milk yield (MY). The heritability estimates of AFC, CI and MY were 0.17 ± 0.033, 0.06 ± 0.012 and 0.35 ± 0.021, respectively. The repeatability estimates of CI and MY were 0.06 ± 0.012 and 0.47 ± 0.009, respectively. The low heritability and non-significant permanent environmental variance of CI showed that CI is heavily influenced by external factors, such as management practices. AFC was negatively genetically correlated with both CI (-0.88 ± 0.077) and MY (-0.53 ± 0.059) showing that animals that attain sexual maturity earlier exhibit longer CI and higher milk production. A positive genetic correlation (0.62 ± 0.077) between CI and MY shows that high-yielding cows face challenges in maintaining shorter calving intervals. Heritability estimates of nearly all resilience indicators were significant and ranged from 0.05 to 0.34. Heat tolerance indicators showed low to non-significant genetic correlations with general resilience indicators, suggesting that different genetic factors are involved in responses to different types of disturbances. There was a generally positive genetic correlation between resilience and fertility, implying that resilient animals might have better fertility. All indicators, except LnVar1 and LnVar2, revealed an antagonistic genetic relationship between resilience and milk production. The findings present an opportunity for including resilience in the development and application of selection indices in dairy cattle, especially for the tropics.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143544521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic Evaluation of Barrel Racing Performance in Quarter Horses.","authors":"Mário Luiz Santana, Thiago Garcia Botelho Franco, Annaiza Braga Bignardi","doi":"10.1111/jbg.12934","DOIUrl":"https://doi.org/10.1111/jbg.12934","url":null,"abstract":"<p><p>Barrel racing is a competitive timed rodeo event that challenges horses and riders to complete a cloverleaf pattern around three barrels in the fastest time possible. In this study, we aimed to estimate the genetic parameters of barrel racing time (BRT) and evaluate the most suitable statistical model for its analysis. We compared a repeatability model and three random regression models (RRM) to analyse the longitudinal BRT data in Brazilian Quarter Horses. A total of 356,877 BRT records from 14,108 horses that competed in various events held across Brazil between 2010 and 2024 were analysed. The cubic RRM provided the best fit to the data, and therefore, the results from this model were presented in detail. Heritability estimates for BRT varied by age (0.15-0.24), with the highest estimates observed between 36 and 54 months, suggesting that selection at younger ages could be most effective. Genetic correlations between BRT at different ages were generally strong (> 0.8). The lowest mean genetic correlation of 0.65 (0.09) was observed between BRT at 36 and 144 months of age. Thus, selecting the best-performing horses at younger ages should result in favourable genetic progress at older ages. Phenotypic trends showed an improvement in BRT over the years, although no significant genetic progress was observed, likely due to the absence of an official breeding programme and the lack of use of estimated breeding values for BRT. These findings highlight the need for a more strategic approach to genetic selection in Quarter Horses to optimise BRT performance. The substantial genetic variation identified for BRT indicates that, if properly exploited, this trait could be significantly improved in the future, ultimately enhancing competition outcomes for Brazilian Quarter Horses in barrel racing.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143532200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bayesian Genetic Estimation Towards Optimising Selection Strategy for Higher Egg Production in White Leghorn Chickens.","authors":"Aneet Kour, R N Chatterjee, K S Rajaravindra, L Leslie Leo Prince, U Rajkumar","doi":"10.1111/jbg.12931","DOIUrl":"https://doi.org/10.1111/jbg.12931","url":null,"abstract":"<p><p>Long-term directional selection in a population can severely reduce the additive genetic variability for the desired trait. Therefore, it is really important to assess the genetic parameters of a population at definite time intervals for designing effective breeding programmes. The present study was designed for the genetic evaluation of a White Leghorn strain (IWI) which has been intensely selected for higher egg numbers up to 64 weeks of age at ICAR-Directorate of Poultry Research, Hyderabad, Telangana, India. The genetic parameters were estimated for egg production up to 24 (EP24), 32 (EP32), 40 (EP40), 52 (EP52), 64 (EP64) and 72 (EP72) weeks of age along with other traits (egg weight, reproductive and body weight traits) utilising six models with different random effects in a Bayesian framework. The normalised mean value for the primary selection trait, EP64, was 218.16 ± 1.24 eggs while the total egg production up to 72 weeks was 242.85 ± 1.72. Comparative evaluation of different models based on Deviance Information Criterion (DIC) revealed that model 6 (including direct additive, maternal genetic and maternal permanent environment effects) was the most accurate for early production traits like EP24, whereas model 3 (including direct additive and maternal genetic effects) was the best-fitted for egg production traits like EP32 and EP40. The trait variance for late egg production traits like EP52, EP64 and EP72 was best defined by model 1, which only included the direct additive effect. Furthermore, it was found that the posterior mean additive heritability of egg production traits declined as the laying cycle progressed. Particularly, for later traits like egg production up to 52 (EP52), 64 (EP64) and 72 (EP72) weeks, the direct additive heritability estimate was very low (0.02 ± 0.009; 0.04 ± 0.01 and 0.02 ± 0.0009 respectively). Subsequently, posterior genetic correlations (r_G) were estimated between late egg production traits and the rest of the traits. It was found that there was a highly negative r_G between egg weight at 40 weeks (EW40), body weight at 52 weeks (BW52) and the later egg production traits (EP52, EP64 and EP72). Therefore, depending on the trait correlations, multivariate analysis was done for improving the accuracy of evaluations. Posterior estimates of direct additive heritability for EP52 increased to 0.08 ± 0.05 when analysed together with EW40 and BW52 traits in a multivariate model, whereas the corresponding estimate for EP64 increased to 0.11 ± 0.05 when analysed with EW40 and BW52. Based on these results, we can conclude that although the additive genetic variability for the selection trait is very low in the population, multitrait evaluations can be more effective for making selection decisions for higher egg production in White Leghorns.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143532177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel Candidate Genes Detection Using Bayesian Network-Based Genome-Wide Association Study of Latent Traits in F2 Chicken Population.","authors":"Siavash Manzoori, Rasoul Vaez Torshizi, Ali Akbar Masoudi, Mehdi Momen","doi":"10.1111/jbg.12926","DOIUrl":"https://doi.org/10.1111/jbg.12926","url":null,"abstract":"<p><p>In chickens, economically important traits are commonly controlled by multiple genes and are often correlated. The genetic mechanisms underlying the correlated phenotypes likely involve pleiotropy or linkage disequilibrium, which is not handled properly in single-trait genome-wide association studies (GWAS). We employed factor analytical models to estimate the value of latent traits to reduce the dimensionality of the adjusted phenotypes. The dataset included phenotypes from 369 F2 chickens, categorised into six observable classes, namely body weight (BW), feed intake (FI), feed efficiency (FE), immunity (IMU), blood metabolites (BMB), and carcass (CC) traits. All birds were genotyped using a 60K SNP Beadchip. A Bayesian network (BN) algorithm was used to discern the recursive causal relationships among the inferred latent traits. Multi-Trait (MT) and Structural Equation Model (SEM) were applied for association analysis. Several candidate genes were detected across six phenotypic classes, namely the IPMK gene for BW and FI, and, the MTERF2 gene for BW and FE. The rs14565514 SNP, close to genes IPMK, UBE2D1, and CISD1, was recognised as a pleiotropic marker by both models. The NRG3 gene, located on chromosome 6, was associated with FI. CRISP2, RHAG, CYP2AC1, and CENPQ genes, located on chromosome 3, were detected for BMB through both MT- and SEM-GWAS. In general, the results indicated that the SEM-GWAS is superior to MT-GWAS due to considering the causal relationships among the traits, correcting the effects of the traits on each other, and also leading to the identification of pleiotropic SNP markers.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143451050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic Parameter Estimates for Carcass and Meat Quality Traits and Their Genetic Associations With Sexual Precocity Indicator Traits in Nellore Cattle.","authors":"Leonardo Machestropa Arikawa, Lucio Flavio Macedo Mota, Patrícia Iana Schmidt, Bruna Maria Salatta, Sindy Liliana Caivio Nasner, João Barbosa da Silva Neto, Larissa Fernanda Simielli Fonseca, Ana Fabrícia Braga Magalhães, Delvan Alves Silva, Roberto Carvalheiro, Luis Artur Loyola Chardulo, Lucia Galvão de Albuquerque","doi":"10.1111/jbg.12927","DOIUrl":"https://doi.org/10.1111/jbg.12927","url":null,"abstract":"<p><p>For developing beef cattle breeding programmes, it is essential to understand the genetic basis of economically relevant traits, such as carcass, meat quality and female sexual precocity. However, the direct selection of most of these traits is a challenge for producers because of the high cost and measurement difficulty. Genetic correlation estimates between carcass and meat quality traits obtained after slaughter and sexual precocity indicator traits in Nellore are limited in the literature. Thus, this study aimed to estimate genetic parameters for longissimus muscle area (LMA), backfat thickness (BF), hot carcass weight (HCW), shear force tenderness (SF), marbling score (MARB), intramuscular fat content (IMF), age at first calving (AFC), heifer pregnancy (HP) and scrotal circumference (SC) in Nellore cattle, using pedigree and genomic information. For this, data from 6910 young bulls with phenotypic information for carcass and meat traits, 230,682 for sexual precocity indicator traits, and 17,850 animals genotyped with or imputed to the Illumina Bovine HD BeadChip were used. The (co)variance components and genetic parameters were estimated considering BLUP and single-step GBLUP (ssGBLUP) models via Bayesian inference using the GIBBSF90+ software. The multi-trait animal model included additive and residual genetic effects as random; the fixed effects of contemporary group (for all traits) and date of analysis as classes (for BF, SF and MARB); and the linear effects of age at slaughter (all carcass and meat traits) and age at yearling (YW and SC) as covariates. Heritability estimates ranged from 0.13 to 0.34 for carcass and meat quality traits, and for SC, AFC and HP, were 0.33, 0.07 and 0.29, respectively. Favourable genetic correlations were estimated between YW-HCW (0.79 ± 0.03), YW-LMA (0.28 ± 0.05), YW-SC (0.35 ± 0.03), HCW-LMA (0.44 ± 0.05), HCW-SF (-0.22 ± 0.09), HCW-SC (0.19 ± 0.05), MARB-IMF (0.90 ± 0.07), SF-IMF (-0.20 ± 0.11), BF-MARB (0.29 ± 0.08), BF-IMF (0.22 ± 0.09), BF-AFC (-0.21 ± 0.07) and BF-HP (0.24 ± 0.10). In general, the correlations between carcass traits and those of meat quality were low to moderate. Additionally, carcass and meat quality traits did not exhibit strong genetic correlations with female precocity indicators. So, to achieve significant genetic advances in female sexual indicator traits, carcass composition and meat quality, these traits must compose selection indices for Nellore cattle.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143191143","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":"Inferring Causal Relationships for Lifetime Reproductive Traits and Modelling Latent Reproductive Performance Variable in Murciano-Granadina Goats.","authors":"Morteza Mokhtari, Ali Esmailizadeh, Mehdi Momen, Rugang Tian, Jing Tian, Meng Zhao, Xiao Wang, Hui Li, Yuan Li, Alireza Bagheripour, Ehsan Mohebbinejad","doi":"10.1111/jbg.12928","DOIUrl":"https://doi.org/10.1111/jbg.12928","url":null,"abstract":"<p><p>The current study investigated the application of structural equation models for genetic analysis of lifetime reproductive traits and latent variable modelling in the Murciano-Granadina goat breed. In the current investigation, data collected between 2016 and 2023 in a private dairy farm of the Murciano-Granadina goat breed in Ghale-Ganj city, located in the southern area of Kerman Iranian province were used. The investigated lifetime reproductive traits included overall litter size at birth (OLSB), overall litter size at weaning (OLSW), overall litter weight at birth (OLWB), and overall litter weight at weaning (OLWW). Four multivariate animal models, including standard (SMM), Inductive Causation algorithm-based structural equation (ICM), ICM with biological modification (ICM-BM), and fully recursive (FRM) models were fitted on the data and compared in terms of predictive ability measures including mean squared prediction error (MSE) and Pearson's correlation coefficient between the observed and predicted values (r(y, <math> <semantics> <mrow><mover><mi>y</mi> <mo>̂</mo></mover> </mrow> <annotation>$$ hat{mathrm{y}} $$</annotation></semantics> </math> )) of records. ICM-BM performed better than other models in terms of the lowest MSE and the highest r(y, <math> <semantics> <mrow><mover><mi>y</mi> <mo>̂</mo></mover> </mrow> <annotation>$$ hat{mathrm{y}} $$</annotation></semantics> </math> ). Under ICM-BM, heritability estimates were low values of 0.08, 0.08, 0.11, and 0.10 for OLSB, OLSW, OLWB, and OLWW, respectively. Genetic correlations among lifetime reproductive traits were positive and varied from 0.72 (OLSB-OLWW) to 0.95 (OLSB-OLWB). The confirmatory factor analysis technique was used to construct a latent variable named reproductive performance (RP) from the investigated lifetime reproductive traits. The posterior mean for heritability of RP was estimated at 0.06. The genetic correlations between RP and the investigated lifetime reproductive traits were high and positive, ranging from 0.92 (RP-OLSB) to 0.99 (RP-OLSW). The corresponding phenotypic correlations were also high and positive, ranging from 0.81 (RP-OLWB) to 0.95 (RP-OLSW). Considering causal structure among the traits detected via ICM-BM had more advantages for genetic evaluation of the lifetime reproductive traits in the Murciano-Granadina goat compared with SMM. The low heritability estimates implied that the studied lifetime reproductive traits and RP were mainly controlled by non-additive genetic and environmental effects which limits the efficiency of direct genetic selection for improving these traits. Furthermore, positive genetic and phenotypic correlations favoured using RP latent variable for breeding purposes.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143191147","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 Breeding Value Estimations and Optimum Contribution Selection in Endangered Dual-Purpose German Black Pied Cattle (DSN) Using a Breed Specific SNP Chip.","authors":"M Wolf, T Yin, G B Neumann, P Kokuć, G A Brockmann, S König","doi":"10.1111/jbg.12929","DOIUrl":"https://doi.org/10.1111/jbg.12929","url":null,"abstract":"<p><p>The aims of the present study were to perform single-step genomic predictions in the dual-purpose German Black Pied cattle (DSN) breed considering a DSN specific SNP chip (DSN_200 K), and to use the corresponding estimated breeding values (EBV) in ongoing optimum genetic contribution (OGC) selection. All results were compared with the application of the commercial Illumina BovineSNP50 BeadChip (50 K). The traits of interest in the present study (due to the differing breeding history of these traits in the past) included 305-day lactation protein percentage (Pro%) of 9029 DSN cows, fat-to-protein ratio (FPR) from the first test-day of 8773 DSN cows, and stature (STAT) measured in cm of 4409 DSN cows. The DSN cows represented the calving years 2008-2019. Genotyping of 2797 DSN animals was conducted using both the DSN_200 K and the 50 K. From the genotyped animals, a subset of 1800 cows had phenotypic records for all three traits FPR, Pro% and STAT. Heritabilities from the single-step genetic parameter estimations were quite large for Pro% (0.69) and STAT (0.78), but small for FPR (0.11). The choice of the SNP chip only had minor effects on variance components, heritabilities and EBVs. Furthermore, genetic parameters were very similar from genetic-statistical models additionally considering a linear regression on pedigree-based inbreeding coefficients. OGC selection was applied to a pool of 1125 pre-selected bull sires (BS) and bull dams (BD). A more relaxed genetic relationship constraint was associated with favourable effects on the average EBVs for Pro%, FPR and STAT, and a declining number of selected BS. The gains in genetic merit were marginal when relaxing the constraint at 0.06 for the genetic relationships or higher. The same associations were found for an overall breeding index (I-DSN), considering the three traits with equal weights. Consequently, we suggested OGC applications with a genetic relationship constraint of 0.06, which contributed to genetic gain in I-DSN of 17.9%, and to increased diversity due to an increased number of BS, when compared to the current practical elite animal selection scheme. A large number of finally selected BS and BD was identical when either using EBV from the DSN_200 K or from the 50 K. From such perspective, we only see marginal extra value for the specific DSN SNP-chip application.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143076560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Recursive Model Approach to Include Epigenetic Effects in Genetic Evaluations Using Simulated DNA Methylation Effects.","authors":"Adrián López-Catalina, Mohamed Ragab, Antonio Reverter, Oscar González-Recio","doi":"10.1111/jbg.12925","DOIUrl":"https://doi.org/10.1111/jbg.12925","url":null,"abstract":"<p><p>The advancement of epigenetics has highlighted DNA methylation as an intermediate-omic influencing gene regulation and phenotypic expression. With emerging technologies enabling the large-scale and affordable capture of methylation data, there is growing interest in integrating this information into genetic evaluation models for animal breeding. This study used methylome information from six dairy cows to simulate the methylation profile of 13,183 genotyped animals. The liability to methylation was treated as an additive trait, while a trait moderated by methylation effects was also simulated. A multiomic model (GOBLUP) was adapted to incorporate methylation data in genomic and genetic evaluations, using the traditional BLUP method as a benchmark. The GOBLUP accurately recovered heritability estimates for the liability to methylation in all low, medium and high heritability scenarios and was consistent at estimating the heritability for the epigenetics-moderated trait of interest at a low-medium heritability of 0.14. The genetic variance recovered by the BLUP model was influenced by the h² of the liability to methylation, and a part of the methylation variance for the phenotypic trait was captured as additive. The h² of the phenotypic trait partially relies on the h² value for the methylation windows in the traditional model. A newly proposed estimated epigenetic value (EEV) combines the traditional additive genetic information from genotyping arrays with epigenetic information. The correlation between the traditional estimated breeding value (EBV) and EEV was high (0.92-0.99 depending on the scenario), but the correlation of the EEV with the true breeding value was higher than the correlation between the traditional EBV and the TBV (0.85 vs. 0.75, 0.71 vs. 0.66 and 0.61 vs. 0.62 depending on the scenario). This study demonstrates that the GOBLUP multiomic recursive model can effectively separates additive and epigenetic variances, enabling improved breeding decisions by accounting for genetic liability to DNA methylation. This enables more informed breeding decisions, optimising selection for desired traits. Emerging sequencing techniques offer new opportunities for cost-effective simultaneous acquisition of genetic and epigenetic data, further enhancing breeding accuracy.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143048854","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":"Graphical Model Selection to Infer the Partial Correlation Network of Allelic Effects in Genomic Prediction With an Application in Dairy Cattle.","authors":"Carlos A Martínez, Kshitij Khare, Syed Rahman, Giovanni M Báez","doi":"10.1111/jbg.12921","DOIUrl":"https://doi.org/10.1111/jbg.12921","url":null,"abstract":"<p><p>We addressed genomic prediction accounting for partial correlation of marker effects, which entails the estimation of the partial correlation network/graph (PCN) and the precision matrix of an unobservable m-dimensional random variable. To this end, we developed a set of statistical models and methods by extending the canonical model selection problem in Gaussian concentration, and directed acyclic graph models. Our frequentist formulations combined existing methods with the EM algorithm and were termed Glasso-EM, Concord-EM and CSCS-EM, whereas our Bayesian formulations corresponded to hierarchical models termed Bayes G-Sel and Bayes DAG-Sel. We implemented our methods in a real bull fertility dataset and then carried out gene annotation of seven markers having the highest degrees in the estimated PCN. Our findings brought biological evidence supporting the usefulness of identifying genomic regions that are highly connected in the inferred PCN. Moreover, a simulation study showed that some of our methods can accurately recover the PCN (accuracy up to 0.98 using Concord-EM), estimate the precision matrix (Concord-EM yielded the best results) and predict breeding values (the best reliability was 0.85 for a trait with heritability of 0.5 using Glasso-EM).</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016713","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":"Analysis of Social Genetic Effects on Pigs Fed With Automatic Feeders Using a Visit-Based Approach.","authors":"P Nuñez, C Casto-Rebollo, S Negro, S Gol, J Reixach, L Varona, J Casellas, N Ibáñez-Escriche","doi":"10.1111/jbg.12924","DOIUrl":"https://doi.org/10.1111/jbg.12924","url":null,"abstract":"<p><p>Social behaviour traits and their impact on feed efficiency are of particular interest in pig farming. The integration of automatic feeders enables the collection of multiple phenotypes for breeding purposes. The additive genetic and social genetic effect can be estimated considering all the visits to the feeder by modelling each visit independently in a 'visit-based approach'. This study aimed to determine the impact of the social genetic effect on individual feed intake and duration per visit in Pietrain pigs and Iberian pigs separately. The dataset comprised 883,906 visits from 1608 Pietrain pigs and 775,054 visits from 856 Iberian pigs. In the Pietrain population, the social genetic effects did not explain a substantial percentage of the phenotypic variance (~1%). In contrast, the Iberian population exhibited more substantial contributions, with social genetic effects accounting for 6.2% of the variance in duration per visit and 5.5% in feed intake per visit. The correlations between additive direct genetic and additive social genetic effects were slightly positive for feed intake across all analyses, and around zero for duration per visit with most of them including the zero in the highest posterior density interval (HPD95%). These weak correlations suggest that both effects could be selected independently. The visit-based approach successfully identified social genetic effects in the studied populations. Models incorporating social genetic effects demonstrated lower residual variance, enhancing the accuracy of additive values and, consequently, the potential for an improved response to selection.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016712","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}