Journal of Animal Breeding and Genetics最新文献

{"title":"Single-Step Genomic Predictions for Growth and Carcass Traits in Nordic Charolais and Hereford Cattle.","authors":"Anahit Nazari-Ghadikolaei, Freddy Fikse, Susanne Eriksson","doi":"10.1111/jbg.70018","DOIUrl":"https://doi.org/10.1111/jbg.70018","url":null,"abstract":"<p><p>In order to investigate the applicability and efficiency of genomic selection for growth and carcass traits in Nordic beef cattle, single-step genomic BLUP (ssGBLUP) was applied in 4321 Charolais and 4532 Hereford animals with information on approximately 43,000 SNPs each. Statistics including dispersion value (b1), accuracy ratio and the relative accuracy improvement were estimated for genotyped female animals in the validation set. For estimating dispersion, accuracy ratio and relative accuracy improvement, the Legarra-Reverter linear regression (LR) method was used by truncating the phenotypes after 2018, and the validation set comprised females born from 2019 to 2021. Moreover, for ssGBLUP, different alpha values of 0.95 and 0.70 were utilised as weights on the genomic information when the H matrix was blended for the genomic relationship matrix G and the pedigree relationship matrix A. In general, implementing ssGBLUP led to higher accuracy ratios and improved dispersion values (b1 value closer to the optimum value of one), compared to when using pedigree-based BLUP (PBLUP). Using an alpha value of 0.70 gave a dispersion value closer to one compared with when using an alpha value of 0.95. Additionally, the relative accuracy estimation was improved substantially for several traits by using ssGBLUP instead of PBLUP, with the highest (30%) relative improvement for carcass conformation in Swedish Hereford cattle. In conclusion, ssGBLUP would be beneficial to implement in the future Nordic beef cattle breeding programs.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145208188","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 Analysis of Taurine and Indicine Ancestry in the Montana Tropical Composite Population.","authors":"Camila Alves Dos Santos, El Hamidi Hay, Elisangela Chicaroni de Mattos Oliveira, Rafael Espigolan, José Bento Sterman Ferraz, Tiago do Prado Paim","doi":"10.1111/jbg.70017","DOIUrl":"https://doi.org/10.1111/jbg.70017","url":null,"abstract":"<p><p>The Montana Tropical cattle, a Taurine and Indicine composite, were developed in Brazil since 1994 and were based on crossing four biological types of cattle: zebu (mainly Nelore), tropical adapted taurine (mainly Senepol and Romosinuano), British taurine (mainly Angus) and continental taurine (as Charolais, Simental and Limousin). This study aimed to characterise the genetic ancestry of this composite breed at the genomic level. Principal component analysis revealed the composite in intermediate space between indicine and taurine but closer to the Taurine cluster, which is consistent with its multi-breed origin. The ADMIXTURE analysis indicated the Montana Tropical to be composed of several progenitor breeds without an indication of a dominant breed. Local ancestry analysis showed the Montana animals to have an average of 24% (standard deviation of ±5.41) Zebu ancestry. The total taurine ancestry was 62%, consisting of 19.6% (±6.96) from tropical adapted taurine, 20.1% (±5.99) from British taurine, 21.92% (±7.79) from continental taurine and 14% (±5.26) of the genome was undetermined. Based on the pedigree, these animals would have 20.8% ± 8.5% Zebu, 50.5% ± 14.4% tropical adapted taurine, 21.1% ± 13.5% British taurine and 7.6% ± 5.1% of continental European taurine in their composition. The genomic regions in the composite originating from each biological type highlight the trait complementarity each genetic group contributes. For example, the genomic region of high tropical adapted taurine ancestry was shown to harbour the slick hair locus, and the regions of high indicine ancestry are associated with high length of productive life. This study unravels the complex genetic ancestry of the Montana Tropical composite, highlighting the effective blend of ancestral gene pools that enhance key production and adaptation traits.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145187491","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":"Microbial and Genomic Information Synergistically Contribute to Predicting Swine Performance Across Production Systems.","authors":"Christian Maltecca, Enrico Mancin, Jicai Jiang, Maria Chiara Fabbri, Riccardo Bozzi, Clint Schwab, Francesco Tiezzi","doi":"10.1111/jbg.70014","DOIUrl":"https://doi.org/10.1111/jbg.70014","url":null,"abstract":"<p><p>Microbiota composition represents a promising tool in precision farming, simultaneously serving as a benchmark of environmental challenge, a predictor of animal physiological status, and a direct target for host selection. In this paper, we compared the ability of microbiota composition and genomic information to predict swine performance in two production settings, namely a purebred nucleus (NU) and a terminal cross commercial population (TE). Microbiota consistently predicted all traits in both scenarios (NU-TE: training on NU to predict TE; TE-NU: training on TE to predict NU) and at two time points: mid-test and off-test. The highest correlation (i.e., prediction accuracy) was achieved for back fat, with values of 0.08 and 0.04, and 0.30 and 0.23 for mid and off-tests, predicting from nucleus to terminal, and vice versa. Similarly, daily gains correlations were 0.05 and 0.04, and 0.18 and 0.15 for the same time points and scenario combinations. Including genomic information yielded correlations ranging from low for loin area to moderate for back fat (0.19 nucleus to terminal, 0.16 for the opposite). Microbiota had higher prediction accuracies than genomic for back fat both from nucleus to terminal and vice versa (+0.11, +0.07) and daily gain (+0.08, +0.02) at off-test. Lower accuracies were obtained for the IMF. Including genomic and microbial information produced higher accuracies than microbiota or genomic alone for back fat (0.37 and 0.29 for nucleus to terminal and opposite) and daily gain (0.19 and 0.21 for nucleus to terminal and opposite). Results for other traits differed for different scenarios. Results show that microbiota composition effectively predicted most growth and carcass traits, particularly growth and fat deposition, across production systems, prediction scenarios (NU-TE and TE-NU), and time points (mid-test and off-test). These findings highlight the potential of microbiota profiles to predict phenotypes across production systems and support their use as a tool for selecting animals in environments they have not been exposed to.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145132707","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 Prediction Ability for Novel Profitability Traits Using Different Models in Nelore Cattle.","authors":"Letícia Silva Pereira, Cláudio Ulhôa Magnabosco, Guilherme Rosa, Nedenia Bonvino Stafuzza, Tiago Zanett Albertini, Minos Carvalho, Raysildo Barbosa Lobo, Elisa Peripolli, Eduardo da Costa Eifert, Fernando Baldi","doi":"10.1111/jbg.70016","DOIUrl":"https://doi.org/10.1111/jbg.70016","url":null,"abstract":"<p><p>The aim of this study was to assess the accuracy, bias and dispersion of genomic predictions for accumulated profitability (APF) and profit per kilogram of liveweight gain (PFT) in Nelore cattle using different prediction approaches. The dataset consisted of 3969 phenotypic records for each trait. The pedigree harboured information from 38,930 animals born between 1998 and 2016, including 2691 sires and 19,884 dams. A total of 2449 animals were genotyped using the Clarifide Nelore 3.0 SNP panel. Nine models for genomic prediction were evaluated: a linear animal model was applied to estimate genetic parameters and perform the genomic single-trait best linear unbiased prediction (ST_ss-default). Additionally, a two-trait (ssGBLUP TT_W450 and TT_DMI), three-trait (TTT_CAR) and multi-trait ssGBLUP (MT_ss) were tested. Finally, two models employing the weighted linear (ST_sswl1 and ST_sswl2) and non-linear (ST_sswnl1 and ST_sswnl2) single-step genomic approach (WssGBLUP) were used to predict genomic breeding values (GEBV). The ability to predict future performance was assessed by calculating the correlation between GEBV and adjusted phenotypes. The average prediction accuracy of the GEBV models ranged from 0.345 to 0.665 for PFT and from 0.425 to 0.603 for APF. The predictive capability of the MT_ss model (0.665) was significantly higher than that of the other models for PFT, except for the TTT_CAR model (0.604), which also showed an improvement in predictive performance. For APF, the MT_ss (0.561) and TT_W450 (0.556) models demonstrated improved genomic prediction accuracy compared to the other models. In general, the single trait ssGBLUP (ST_ss-default) models and the non-linear weighting approach did not enhance prediction accuracy for either trait. For the phenotypic prediction ability of PFT, the linear WssGBLUP models ST_sswl1 (0.65) and ST_sswl2 (0.70), TT_W450 (0.64) and ssGBLUP-M (0.66) demonstrated the highest prediction accuracies. Similar results were observed for the phenotypic prediction ability of APF for both models. However, the linear WssGBLUP models ST_sswl1 (0.84) and ST_sswl2 (0.94) provided higher prediction performance compared to the two-, three- and multi-trait models. The results indicate that the multi-trait model achieved better predictive ability for the novel traits PFT and APF. Multi-trait genomic selection may yield greater genetic gains than other models for these forthcoming economically important traits in breeding programmes.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145114961","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 Prediction of Meat Tenderness in Nellore Cattle: Multi-Trait and Weighted Single-Step Genomic Best Linear Unbiased Prediction Approaches.","authors":"Byanka Bueno Soares, Ludmilla Costa Brunes, Eduardo da Costa Eifert, Marcos Fernando Oliveira E Costa, Roberto Daniel Sainz, Ana Christina Sanches, Fernando Baldi, Cláudio Ulhoa Magnabosco","doi":"10.1111/jbg.70015","DOIUrl":"https://doi.org/10.1111/jbg.70015","url":null,"abstract":"<p><p>This study aimed to evaluate the impact of different genomic prediction approaches on the predictive ability for meat tenderness in Nellore cattle. Phenotypic (n = 73,286), pedigree (n = 4,141,892) and genomic (n = 15,300) data from animals belonging to the genetic improvement program of the National Association of Breeders and Researchers (ANCP) were used. Six models were tested: (1) standard ssGBLUP (Single-step Genomic Best Linear Unbiased Prediction), considering direct additive genetic and residual effects as random, contemporary group (CG) as a fixed effect, and slaughter age as a linear and quadratic covariate; (2) Model 1 + ssGBLUP weighted with SNP effects from the first WssGWAS iteration; (3) Model 1 + ssGBLUP weighted with SNP effects from the second WssGWAS iteration; (4) Model 1 + body weight as a covariate; (5) Model 1 as a bi-trait model with body weight at 450 days (W450); (6) Model 1 as a multi-trait model with carcass traits: ribeye area (REA), backfat thickness (BFT) and rump fat thickness (RFT). Predictive ability was evaluated using linear regression, in which the dataset was divided into a complete and a partial subset (n = 374) dataset. Accuracy ranged from 0.04 (Models 2 and 3) to 0.37 (Model 6). Bias was low for all models, with Models 2 and 3 showing the least bias (-0.001). Model 6 showed the best performance in terms of accuracy and correlation (0.897), suggesting it was more effective in capturing genetic variability of meat tenderness, while reducing bias and increasing the precision of the estimates. Multi-trait models may offer more robust genomic predictions by leveraging trait correlations to increase prediction accuracy.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145076635","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":"Properties of Runs of Homozygosity as a Measure of Identity by Descent.","authors":"Oda B Wæge, Tom Druet, Peer Berg, Theo Meuwissen","doi":"10.1111/jbg.70013","DOIUrl":"https://doi.org/10.1111/jbg.70013","url":null,"abstract":"<p><p>Runs of Homozygosity (ROH) are commonly used to quantify autozygosity/identity-by-descent (IBD) in an individual or population. However, the method's accuracy at the segment level in livestock populations has only been evaluated in a few studies. Thus, the aim of this study was to determine to what extent ROH are truly IBD and estimate the proportion of IBD segments that go undetected in a simulated livestock population. We simulated a population of randomly mating animals for 100 generations. The genome consisted of a single chromosome with a SNP density of either 46 or 92 SNPs per mega base (Mb). In addition, a set of founder markers tracing IBD was recorded. ROH were detected using four different parameter combinations. Using the two sets of markers, we calculated the true positive rate, power, and overall correlation between true (F_IBD) and estimated inbreeding (F_ROH). Additionally, a new measure for within-ROH inbreeding (F|ROH) was introduced and calculated the level of homozygosity within a ROH compared to the general expectation in the genome. The results indicate that ROH longer than 2 Mb are a reliable indicator of IBD, with the F|ROH being over 0.9 for all ROH lengths and parameter combinations. True positive rates only exceeded 0.9 consistently for ROH over 9 Mb, indicating that many of the identified ROH may be associated with common ancestors more ancient than the base population. The power was mainly controlled by the parameter stringency, that is, allowing for shorter ROH increased the power. The ROH-based individual measure of inbreeding F_ROH was highly correlated to F_IBD while also having regression coefficients close to 1 (i.e., a 1% variation in F_ROH corresponded to a 1% variation in F_IBD). Using stringent ROH parameters resulted in underestimation of the rate of inbreeding in the population. Increasing marker density improved predictions, including a higher true positive rate, power, higher correlations, and less underestimation of inbreeding rates.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144979609","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":"Unravelling Twin Births in German Holstein Cows: Phenotypic Associations, Genetic Analysis and Potential Underlying Genes and Hormones.","authors":"Laura Hüneke, Hatem Alkhoder, Dierck Segelke, Georg Thaller, Christin Schmidtmann","doi":"10.1111/jbg.70012","DOIUrl":"https://doi.org/10.1111/jbg.70012","url":null,"abstract":"<p><p>Twin births in dairy cattle are rare but present significant challenges for animal welfare, as both the health of the cow and the calves are affected. This causes economic losses, which prompts breeders to select against twin births and identify associated risk factors. This study examines the phenotypic relationship between milk yield, fertility traits and twin births in German Holstein cattle using a large, population-wide dataset. GEBV correlations for twin births, milk production and fertility traits were estimated. Genome-wide association studies (GWAS) were conducted for calving numbers 1-3 in order to explore the genetic background in more detail. The twin birth rate showed a strong phenotypic association with milk production and a moderate phenotypic association with the timing of successful insemination. However, GEBV correlations were low: 0.04 with milk yield and -0.10 to 0.01 with fertility traits. GWAS revealed two potential candidate genes on BTA11: LHCGR and FSHR, which encode receptors for LH and FSH, two hormones crucial to estrus. In contrast to the first calving, significantly associated regions on BTA5 and BTA25 were found in calving numbers 2 and 3. This study demonstrates the interaction between genotype and environment, concluding that a genetic predisposition for twin births, in combination with a favourable endocrine state (environment), increases the likelihood of twin births.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144979552","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":"Random Regression Models on Genetic Parameters of Meat-Type Quails Raised With Different Threonine Levels.","authors":"Daniel Dantas Pereira, João Vitor Santana Prates, Yara Cardoso Braga, Roberta Maira Gomes de Jesus, Ronaldo Francesco Zevallos Contreras, Cristina Maria Lima Sá Fortes, Fabiana Ferreira, Felipe Gomes da Silva","doi":"10.1111/jbg.70011","DOIUrl":"https://doi.org/10.1111/jbg.70011","url":null,"abstract":"<p><p>We aimed to evaluate the inclusion of fixed effects and residual variance classes in random regression models in the estimation of genetic parameters for ICA1 and ICA2 meat-type quails at 21 and 35 days of age raised with five levels of threonine (1.14%, 1.24%, 1.34%, 1.44%, and 1.54%). We used 920 body weight records from three incubations and a pedigree comprising 5407 animals from five generations. The effects of sex, incubation, sex by incubation interaction, and birth weight were tested using a multivariate analysis of variance. We compared five models considering residual variance classes according to threonine levels: homogeneous, with a single class (1.14%-1.54%), and heterogeneous models with two classes (1.14%-1.34% and 1.44%-1.54%), three classes (1.14%-1.24%, 1.34%, and 1.44%-1.54%), four classes (1.14%, 1.24%, 1.34%, and 1.44%-1.54%), and five classes (1.14%, 1.24%, 1.34%, 1.44%, and 1.54%). The effects of sex, incubation, and linear birth weight were significant. There was no significant difference in Log(L) among any of the models according to the likelihood ratio test (LRT). The homogeneous model provided the best fit for ICA1 and ICA2 according to the Bayesian Information Criterion (BIC).</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144979612","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":"Genome-Wide Association Study and Genomic Prediction of Sperm Quality Traits in Pietrain Pigs.","authors":"Bauer Martin, Sölkner Johann, Kahsa Tadel Gebre, Pfeiffer Christina","doi":"10.1111/jbg.70010","DOIUrl":"https://doi.org/10.1111/jbg.70010","url":null,"abstract":"<p><p>In the present study, a genome-wide association study (GWAS), estimation of genetic parameters, and prediction of breeding values for semen quality and quantity traits in Pietrain pigs were performed. The traits inferred were total number of sperm, motility, volume, and density. Traits were recorded from 2012 to 2021 using a CASA system (computer aided sperm analysis) and provided data from 96,815 ejaculates from 1647 Pietrain boars. The animals were kept in three Austrian artificial insemination (AI) stations. Genomic data were analysed using Illumina 60 and 80 k SNP arrays and yielded 43,430 markers from 909 individuals after quality control. Genome-wide association was based on a mixed linear association model with phenotypic pre-correction. GWAS revealed three possible associations for total number of sperm on chromosome 8, 16, and 17, including two genes from the cadherin family (PCDH15, CDH12). Genetic parameters and breeding values were estimated using a single-step GBLUP (ssGBLUP) procedure for total number of sperm and motility. Estimated heritabilities for total number of sperm and motility were 25.9% and 11.5%, respectively. Genetic correlation was -0.321 between motility and sperm density, and 0.419 between motility and ejaculate volume. Breeding value estimation provided proof of the advantage of ssGBLUP compared to pedigree-based BLUP in this study, as reliabilities (r²) were significantly higher for young boars without phenotypes (0.346 vs. 0.196 for total number of sperm and 0.276 vs. 0.190 for motility). This indicates positive response to selection if included in routine genetic evaluation.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144859956","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":"Genome-Wide Detection of Copy Number Variation and Association Studies With Physiological and Anatomical Indicators of Heat Stress Response in Lactating Sows.","authors":"Letícia Fernanda de Oliveira, Renata Veroneze, Lorena Ferreira Benfica, André Campelo Araujo, Yijian Huang, Jay S Johnson, Luiz F Brito","doi":"10.1111/jbg.70009","DOIUrl":"https://doi.org/10.1111/jbg.70009","url":null,"abstract":"<p><p>Indicators of heat stress response are heritable complex traits with polygenic inheritance. Copy number variations (CNV) are important genomic structural variations that may be linked to climatic adaptation by influencing the phenotypic variability of traits related to thermal stress and disease resistance in animals. Therefore, the primary objectives of this study were to detect CNV and CNV regions (CNVR) in pigs and explore their associations with physiological and anatomical indicators of HS response in lactating sows. A total of 4184 autosomal genome CNV (4012 deletions and 172 duplications) were detected in 969 animals. CNVR were identified by merging CNV with at least 1-bp overlap, which enabled the identification of 236 autosomal CNVR. The association analyses led to the identification of three CNVR significantly associated with ear skin temperature and one CNVR significantly associated with vaginal temperature considering all records, vaginal temperature measured at 8:00 h, and hair density. Eleven genes harboured the CNVR with significant associations. In summary, various CNV and CNVR were identified in crossbred maternal-line pigs, including CNVR significantly associated with physiological and anatomical heat stress response indicators in lactating sows. Candidate genes involved in immune and stress responses overlapped with the significant CNVR, suggesting that they may contribute to climatic resilience in pigs. The findings of this study contribute to better understanding the genetic background of heat stress response in lactating sows.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144823262","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}