Journal of Animal Breeding and Genetics最新文献

{"title":"Direct Heritability Estimates for Growth, Carcass and Precocity in Snails Cornu aspersum maximum (Synonym Helix aspersa maxima).","authors":"Thamires Aparecida Leôncio, Natalia Costa da Silva, José Teodoro de Paiva, Eula Regina Carrara, Claudiana de Fátima Miranda, Felipe André Oliveira Freitas, Kelvin Rodrigues Kelles, Matheus Aparecido Salviano Lourenço, Fernanda Larissa Cesar Santos, Graziela Tarôco, Aricia Chaves Zanetti Reis, Patrícia Lombardi de Souza, Leila de Genova Gaya","doi":"10.1111/jbg.12915","DOIUrl":"https://doi.org/10.1111/jbg.12915","url":null,"abstract":"<p><p>The aim was to estimate the heritabilities for accumulated weight gain between 60 and 90 days (WG1), 90 and 120 days (WG2) and 120 and 150 days of age (WG3), pre-slaughter body weight (PRE), meat-to-shell ratio (MS), carcass yield (CY) and age at first oviposition (AFO) in a population of snails Cornu aspersum maximum. Single (for heritabilities) and bi-trait (for genetic correlations) analyses were performed using Bayesian inference. The animal model included the random effect of animal and systematic effects of contemporary groups and covariates. The heritability estimates for WG1, WG2 and WG3 were 0.59, 0.60 and 0.32, respectively. Heritabilities for PRE, MS, CY and AFO ranged from 0.22 to 0.51. Environmental factors mostly influenced PRE among the studied traits. However, for carcass traits and age at first oviposition, the 95% HPD intervals of estimates were large. Only the genetic correlations between weight gains reached chain convergence. The correlation between WG1 and WG2 was 0.74, between WG2 and WG3 was 0.57, and between WG1 and WG3 was 0.22 (not statistically significant). In this sense, WG1 appears to be the optimal period for evaluating the body performance of snails. Genetic improvement in WG2 may be obtained by direct selection for WG1 in this population of Cornu aspersum maximum.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142774755","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":"Practical Considerations When Using Mendelian Sampling Variances for Selection Decisions in Genomic Selection Programs.","authors":"Tobias A M Niehoff, Jan Ten Napel, Mario P L Calus","doi":"10.1111/jbg.12913","DOIUrl":"https://doi.org/10.1111/jbg.12913","url":null,"abstract":"<p><p>The purpose of this work was to test the application of selection criteria that consider the genetic variances of future generations. This has not been done previously in numerically large livestock breeding programs based on estimated rather than assumed known marker effects. A generic pure-line pig breeding program was simulated in which 40 males and 400 females were selected every generation. Daily gain was used as an example trait. Three variance-considering criteria as well as different reference population sizes were compared to investigate the effect of differences in genomic prediction accuracy on selection decisions. All variance-considering criteria retained more genetic variance than if selection was based on estimated breeding values (max. 20%). This effect was more pronounced for higher prediction accuracies and criteria assessing the variance more generations ahead. After 20 generations, the criterion with the longest planning horizon combined with the largest reference population resulted in a 2% higher genetic level of boars selected to produce finisher pigs. While the advantage of accounting for future generations diminished with lower accuracy or shorter planning horizons, the variance-considering criteria never performed worse than selection based on genomic estimated breeding values (GEBV) with respect to commercial genetic gain. We are reporting various accuracy metrics to help judge the effectiveness of using one of our tested criteria in real breeding programs. While we did not find large benefits for genetic gain when considering future variances in selection decisions, we also did not find negative side effects, while considerably more genetic variance was maintained. This means that using variance-considering criteria results in either equally good or better performance than truncation selection based on estimated breeding values. Our criteria can be applied to any genomic breeding program as long as phased genotypes, estimated marker effects and a genetic map are available.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142774889","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 Diversity of U.S. Katahdin Hair Sheep.","authors":"Sara M Nilson, Joan M Burke, Gabrielle M Becker, Brenda M Murdoch, Jessica L Petersen, Ronald M Lewis","doi":"10.1111/jbg.12914","DOIUrl":"https://doi.org/10.1111/jbg.12914","url":null,"abstract":"<p><p>In the late 1950s, Katahdin hair sheep were developed as a composite breed of medium size and moderate prolificacy, with potential to express resistance to gastrointestinal nematodes. With increasing popularity and the recent adoption of genomic prediction in their genetic evaluation, there is a risk of decreasing variation with selection based on genomically enhanced estimated breeding values. While Katahdin pedigrees are readily available for monitoring diversity, they may not capture the entirety of genetic relationships. We aimed to characterise the genomic population structure and diversity present in the breed, and how these impact the size of a reference population necessary to achieve accurate genomic predictions. Genotypes of Katahdin sheep from 81 member flocks in the National Sheep Improvement Program (NSIP) were used. After quality control, there were 9704 animals and 31,984 autosomal single nucleotide polymorphisms analysed. Population structure was minimal as a single ancestral population explained 99.9% of the genetic variation among animals. The current N_e was estimated to be 150, and despite differences in trait heritabilities, the effect of N_e on the accuracy of genomic predictions suggested the breed should aim for a reference population size of 15,000 individuals. The average degree of inbreeding estimated from runs of homozygosity (ROH) was 16.6% ± 4.7. Four genomic regions of interest, previously associated with production traits, contained ROH shared among > 50% of the breed. Based on four additional methods, average genomic inbreeding coefficients ranged from 0.011 to 0.012. The current population structure and diversity of the breed reflects genetic connectedness across flocks due to the sharing of animals. Shared regions of ROH should be further explored for incorporation of functional effects into genomic predictions to increase selection gains. Negative impacts on genetic diversity due to genomic selection are not of immediate concern for Katahdin sheep engaged in NSIP.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142734822","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":"The Effect of Preselection on the Level of Bias and Accuracy in a Broiler Breeder Population, a Simulation Study.","authors":"Charlie A de Hollander, Thinh T Chu, Danye Marois, Vivian B Felipe, Fernando B Lopes, Mario P L Calus","doi":"10.1111/jbg.12908","DOIUrl":"https://doi.org/10.1111/jbg.12908","url":null,"abstract":"<p><p>Many breeding programmes have to perform preselection, as genotyping and phenotyping all potential breeder candidates is often not a feasible option. There is need to understand how preselection affects the quality of the genomic estimated breeding values (EBVs) at final selection and thereby can affect genetic progress. This simulation study evaluated nine different preselection strategies in a broiler breeder programme and their effect on the quality of the (genomic) EBVs and genetic progress for three different traits: body weight (Body Weight), residual feed intake (RFI) and body weight gain (Gain). All birds have Body Weight recorded at preselection, but only the preselected birds were phenotyped for RFI and Gain and genotyped. The following criteria and intensities were studied: preselection based on phenotypic Body Weight (P), on a BLUP index (B) or on an ssGBLUP Index (G). Additionally, all criteria were studied with three different selection intensities, 10% of the males and 30% of the females (P10, B10, G10), 15% of the males and 45% of the females (P15, B15, G15) and 20% of the males and 60% of the females (P20, B20, G20). The accuracy at preselection with G10 was more accurate than B10 for both RFI and Gain (0.71 vs. 0.58 and 0.65 vs. 0.55 respectively), and also G15 was more accurate than B15 for both RFI and Gain (0.72 vs. 0.63 and 0.67 vs. 0.64 respectively); thus, the difference in accuracy reduces with an increasing number of birds being preselected. Differences in accuracy at final selection were mostly notable in the RFI trait between P10, B10 and G10, where G10 showed the highest accuracy (0.82 vs. 0.84 vs. 0.86 respectively). This difference in accuracy for RFI disappeared when more animals were preselected. For Body Weight and Gain, the BLUP preselection resulted in the highest accuracy at final selection when selection intensity decreased. The dispersion bias of EBVs at final selection was most pronounced in the P10 and P15 for Body Weight (0.81 and 0.92) but disappeared at P20 (0.97). The dispersion bias for all other criteria and traits was relatively small. Genetic progress was mostly affected when P10 or P15 was used at preselection, where the progress in Body Weight was noticeably higher, but prominently lower for RFI and Gain. The BLUP and ssGBLUP preselection had very similar genetic progress across traits and showed comparable improvements in the selection index. In conclusion, with high preselection intensity, the use of ssGBLUP at preselection might be favoured as there is an improvement in genetic progress across traits in all scenarios, which is due to the increased preselection accuracy. When preselection intensity decreases, the benefit of using ssGBLUP over BLUP at preselection disappears.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142683712","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 Using Imputed Whole-Genome Sequence Data in Australian Angus Cattle.","authors":"Nantapong Kamprasert, Hassan Aliloo, Julius H J van der Werf, Christian J Duff, Samuel A Clark","doi":"10.1111/jbg.12912","DOIUrl":"https://doi.org/10.1111/jbg.12912","url":null,"abstract":"<p><p>Whole-genome sequence (WGS) data was used to estimate genomic breeding values for growth and carcass traits in Australian Angus cattle. The study aimed to compare the accuracy and bias of genomic predictions with three marker densities, including 50K, high-density (HD) and WGS. The dataset used in this study consisted of animals born between 2013 and 2022. Body weight traits included birthweight, weight at 400 days and weight at 600 days of age. The carcass traits were carcass weight, carcass intramuscular fat and carcass marbling score. The accuracy and bias of prediction were assessed using the cross-validation. Further, for the growth traits, animals in the validation group were subdivided into two subgroups, which were moderately or highly related to the reference. Genomic best linear unbiased prediction (GBLUP) was used to compare genomic predictions with the three marker densities. The prediction accuracies were generally similar across the marker densities, ranging between 0.61 and 0.68 for the body weight traits and between 0.40 and 0.52 for the carcass traits. However, the accuracies marginally decreased as the marker density increased for all the traits studied. A similar lack of difference was found when considering the accuracy by the relatedness subgroups. The results indicated that no meaningful difference in prediction accuracy was estimated when comparing the three marker densities due to the population structure. In conclusion, there was no substantial improvement in genomic prediction when using the WGS in this study.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142640305","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 Characterisation of Feeding Patterns in Lactating Holstein Cows and Their Association With Feed Efficiency Traits.","authors":"Ligia Cavani, Kristen L Parker Gaddis, Ransom L Baldwin, José E P Santos, James E Koltes, Robert J Tempelman, Michael J VandeHaar, Heather M White, Francisco Peñagaricano, Kent A Weigel","doi":"10.1111/jbg.12911","DOIUrl":"https://doi.org/10.1111/jbg.12911","url":null,"abstract":"<p><p>Feeding behaviour traits, such as number, duration or intake per feeder visit, have been associated with feed efficiency in dairy cattle. Those traits, however, do not fully capture cows' feeding patterns throughout the day. The goal of this study was to propose a new phenotype for characterising within-day feeding patterns and estimate its heritability and genetic correlations with dry matter intake (DMI), secreted milk energy, metabolic body weight and residual feed intake. Feeding patterns were evaluated using 4.8 million bunk visits from 1684 midlactation Holstein cows collected from 2009 to 2023 with an Insentec system. Feed efficiency traits were available from 6099 lactating Holstein cows at six research stations across the United States. Daily bunk visits were ordered, with Time 0 designated as the time of first feed delivery. Intake proportions were calculated by visit for each cow by dividing feed intake per visit by the total intake of the cow for that day. Feeding patterns were characterised by the area under the curve of cumulative feed intake proportions for each cow throughout the day. The feeding pattern phenotype per cow was defined as the average of areas under the curve across days, whereas consistency of feeding pattern was calculated as the natural logarithm of variance of daily area under the curve values. Estimates of heritability and genetic correlations were performed using Bayesian inference with an animal model, considering lactation, days in milk and cohort (trial-treatment) as fixed effects and animal as a random effect. Heritability estimates for average area under the curve and variance of daily area under the curve were 0.35 ± 0.05 and 0.16 ± 0.05, respectively. The genetic correlation between average area under the curve and secreted milk energy was -0.30 ± 0.14. Genetic correlations between average area under the curve and DMI, metabolic body weight and residual feed intake were not statistically significant. Variance of daily area under the curve was genetically correlated with DMI (0.47 ± 0.15), secreted milk energy (0.40 ± 0.17) and metabolic body weight (0.28 ± 0.13). The genetic correlation between variance of daily area under the curve and residual feed intake was not significant. Overall, we provided a reliable method to truly characterise feeding patterns in midlactation dairy cows. Feeding pattern and its consistency were heritable, indicating that a significant proportion of phenotypic variation is explained by additive genetic effects. Genetic correlation estimates indicate that cows with more consistent daily feeding patterns have lower DMI, lower secreted milk energy and lower metabolic body weight.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142632975","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":"Methods of Calculating Prediction Error Variance and Prediction Accuracy for Restricted Best Linear Unbiased Prediction of Breeding Values.","authors":"Masahiro Satoh","doi":"10.1111/jbg.12910","DOIUrl":"https://doi.org/10.1111/jbg.12910","url":null,"abstract":"<p><p>Prediction error variance (PEV) and prediction accuracy (PA) of breeding values (BVs) are essential for formulating breeding plans and predicting response to selection. However, restricted best linear unbiased prediction method (RBLUP method) carries many unknowns: in particular, the formulas for calculating PEV and PA are not clear. New findings were obtained using the RBLUP method. The uniqueness of RBLUP of BVs was proven. The formulas of PEV and PA for the RBLUP of BVs were derived from restricted mixed model equations. A method was also devised for easily calculating the PEV and PA for the RBLUP of BVs. Finally, the relationship between the RBLUP and ordinary BLUP of BVs was derived. It has become easier to calculate the PEV and PA for the RBLUP of BVs. This method is particularly effective for calculating the PEV and PA when applying the RBLUP method to achieve relative desired changes in all traits. This has also made it possible to predict the response to selection using the RBLUP method.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142584486","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 Evaluation of Growth Rates and Kleiber's Ratios in Harnali Sheep: Dissecting Maternal and Additive Genetic Contributions.","authors":"Spandan Shashwat Dash, Yogesh C Bangar, Ankit Magotra, C S Patil","doi":"10.1111/jbg.12909","DOIUrl":"https://doi.org/10.1111/jbg.12909","url":null,"abstract":"<p><p>Understanding the genetic basis of growth and metabolic traits in sheep is crucial for improving production efficiency and sustainability. The current study aimed to estimate the genetic influences, both direct and maternal, on growth rate and Kleiber's ratio traits in Harnali sheep using pedigree data under Bayesian inference. The data pertained to 2404 animals spanned over 24 years (1998-2021). Fixed factors such as birth period, lamb sex and dam's weight at lambing were considered. The traits studied included average daily gains (ADGs) categorised into ADG1 (birth to weaning age), ADG2 (weaning to 6 months of age) and ADG3 (6-12 months of age), as well as corresponding Kleiber's ratios (KR1, KR2 and KR3). Six single-trait animal models were employed to estimate covariance components and heritabilities, integrating direct additive and maternal effects alongside significant fixed factors using THRGIBBS1F90 and POSTGIBBSF90 programmes. Direct heritability estimates were obtained for ADG1 (0.11 ± 0.05), ADG2 (0.06 ± 0.03), ADG3 (0.03 ± 0.03), KR1 (0.07 ± 0.03), KR2 (0.06 ± 0.03) and KR3 (0.05 ± 0.03). Maternal genetic effects have contributed significant particularly to pre-weaning traits. The study identified an antagonistic relationship between direct additive and maternal genetic effects. Positive genetic and phenotypic correlations emphasised the intricate relationship between growth and metabolic efficiency in Harnali sheep. The current study offers critical insights into the genetic basis of growth and metabolic traits in Harnali sheep, ultimately contributing to more efficient and sustainable sheep production systems.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142559506","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":"Are SNPs Linked to Somatic Cell Score Suitable Markers for the Susceptibility to Specific Mastitis Pathogens in Holstein Cows?","authors":"U Müller, E M Strucken, J Gao, S Rahmatalla, P Korkuć, M Reissmann, G A Brockmann","doi":"10.1111/jbg.12904","DOIUrl":"https://doi.org/10.1111/jbg.12904","url":null,"abstract":"<p><p>Mastitis in cattle is often caused by microorganism infections in the udder. The three most common pathogens are esculin-positive streptococci (SC+), coagulase-negative staphylococci (CNS), and Escherichia coli (E. coli). In a previous study, 10 SNPs were associated with somatic cell score and mastitis in diverse Holstein populations. We tested these SNPs for their effects on individual pathogen presence. Milk and pathogen samples of 3076 Holstein cows were collected from four farms. Samples were excluded if multiple pathogens were present at the same time. Records of the same pathogen within 14 days of each other were counted as one infection. This resulted in 1129 pathogen-positive samples. Cases and controls were in ratios of 20:80 for SC+, 8:92 for CNS, and 11:89 for E. coli. The lasso, backward, and forward methods were used to narrow down SNPs associated with pathogen presence. The suitability of the SNPs to separate the samples into cases or controls for each pathogen was indicated using ROC curves. The Cochran-Armitage (CAT) and the Jonckheere-Terpstra (JTT) tests evaluated the influence of the SNPs on pathogen presence. Finally, a generalised linear mixed model (GLMM) including fixed environmental effects and a random sire effect was fitted to the binary trait of pathogen presence to test for association. In total, six out of the 10 investigated SNPs showed associations with pathogen presence based on the forward method: Two SNPs each for SC+ (rs41588957, rs41257403) and CNS (rs109934030, rs109441194), and three for E. coli (rs109934030, rs41634110, rs41636878). The CAT and GTT tests linked four SNPs (rs41588957, rs41634110, rs109441194, rs41636878) to pathogen presence, two of which were confirmed with the GLMM (rs41634110, rs109441194), with effects on CNS and E. coli. The SNPs linked to CNS and those linked to E. coli explained 13.2% and 13.8% of the variance, compared to 19% and 18.4%, respectively, of the full model with all 10 SNPs. Half of the SNP genotypes previously linked to lower SCS also decreased the probability for pathogen presence and might therefore be targets not just for lower SCS but for a better pathogen resistance. Trial Registration: Not applicable, no new data were collected for this study.</p>","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142559505","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":"Effects of the Prenatal Maternal Health Status on Calf Disease Prevalences and Respective Genetic Parameter Estimates in German Holstein Cattle.","authors":"Laura Aufmhof, Tong Yin, Katharina May, Sven König","doi":"10.1111/jbg.12906","DOIUrl":"https://doi.org/10.1111/jbg.12906","url":null,"abstract":"&lt;p&gt;&lt;p&gt;The aim of the present study was to infer phenotypic responses and genetic parameters of the F1 calf diseases diarrhoea (DIAR) and pneumonia (PNEU) in dependency of the prenatal maternal health status (PMHS) of the dam and of the herd-calving year. The PMHS considered diagnoses for the cow disease mastitis (MAST) and claw disorders (CD) during gestation of F0 dams. Furthermore, 305-d milk production traits of F1 offspring from either healthy or diseased dam groups were compared. The study comprised 20,045 female calves (F1 = generation 1) and their corresponding dams (F0 = parental generation 0), kept in 41 large-scale herds. All F1 calves were from their dams' 2nd parity, implying that all dam (maternal) diseases were recorded during the first lactation and dry period of the dams. The F1 calves were phenotyped for DIAR up to 30 days post-partum, and for PNEU up to 180 days of age. At least one entry for the respective disease implied a score = 1 = sick, otherwise, a score = 0 = healthy, was assigned. Production records of the 10,129 F1 cows comprised 305-d records in first lactation for milk yield (MY), protein yield (PY) and fat yield (FY). Linear and generalised linear mixed models were applied to infer phenotypic responses of F1 traits in dependency of the PMHS for CD and MAST. A diagnosis for MAST or CD in F0 cows during gestation was significantly (p ≤ 0.05) associated with an increased prevalence for DIAR and PNEU, with pairwise differences of least-squares-means between calves from healthy and diseased cow groups up to 3.61%. The effects of PMHS on 305-d production traits in offspring were non-significant (p &gt; 0.05). In bivariate genetic analyses, DIAR and PNEU were defined as different traits according to the PMHS, i.e., DIAR-MAST&lt;sub&gt;healthy&lt;/sub&gt; and DIAR-MAST&lt;sub&gt;diseased&lt;/sub&gt;, DIAR-CD&lt;sub&gt;healthy&lt;/sub&gt; and DIAR-CD&lt;sub&gt;diseased&lt;/sub&gt;, PNEU-MAST&lt;sub&gt;healthy&lt;/sub&gt; and PNEU-MAST&lt;sub&gt;diseased&lt;/sub&gt;, and PNEU-CD&lt;sub&gt;healthy&lt;/sub&gt; and PNEU-CD&lt;sub&gt;diseased&lt;/sub&gt;. The direct heritabilities for DIAR and PNEU were quite similar in the healthy and respective diseased dam group. Slightly larger direct heritabilities in the diseased dam groups were due to increased genetic variances. Maternal heritabilities were quite stable and smaller than the direct heritabilities. In random regression models, genetic parameters for DIAR and PNEU were estimated along the continuous herd-calving-year prevalence scale, considering a prevalence for MAST and CD (based on the 20,045 dam records plus 16,193 herd contemporary records) in the range from 0% to 30%. Direct heritabilities for PNEU were quite stable along the herd-calving-year gradient for MAST and CD. For DIAR, we observed stronger estimate fluctuations, especially increasing direct heritabilities in dependency of the herd-calving-year prevalence for MAST from 0.13 (at a MAST prevalence of 0%) to 0.30 (at a MAST prevalence of 30%). Consequently, obvious genotype x herd-calving-year PMHS interaction","PeriodicalId":54885,"journal":{"name":"Journal of Animal Breeding and Genetics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142513235","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}