Genetics Selection Evolution最新文献

{"title":"Selective sweeps for mutations increasing height impede identification of causative mutations for fertility and other correlated traits in cattle","authors":"Mehrnush Forutan, Elizabeth M. Ross, Amanda J. Chamberlain, Geoffry Fordyce, Bailey N. Engle, Loan T. Nguyen, Ben J. Hayes","doi":"10.1186/s12711-025-01004-x","DOIUrl":"https://doi.org/10.1186/s12711-025-01004-x","url":null,"abstract":"Fertility, growth and body composition are key drivers of profitability in beef cattle. With the aim of identifying causative mutations underpinning variation in these traits, we integrated multi-trait genome-wide association analysis (M-GWAS) in a cohort of 28,351 multibreed beef cattle with imputed whole genome sequence (WGS) data, with expression quantitative trait loci (eQTL) summary statistics from 489 indicine cattle using the same WGS variants. An additional aim was to provide insights into the biological basis for the association between growth, metabolism, and reproductive development. First, we conducted M-GWAS for live weight, hip height, body condition score and heifer puberty at approximately 600 days. Subsequently, focusing on a 2 Mb region around the lead GWAS SNP we identified the top eQTL in each region. Through iterative conditional analysis, we successively integrated these variants into individual single trait GWAS and further analysed expression and trait information using conditional and joint GWAS analysis. This iterative process continued until no additional significant SNPs emerged from the M-GWAS. Fifteen candidate genes were identified, including IRAK3, HELB, HMGA2, LAP3, FAM184B, LCORL, PPM1K, ABCG2, MED28, PLAG1, BPNT2, UBXN2B, CTNNA2, SNRPN, and SNURF. When we investigated the number of eQTL in blood associated with these genes, IRAK3, HELB, PPM1K, ABCG2, MED28, BPNT2, and UBXN2B were associated with a single eQTL, while ABCG2 was clearly associated with two eQTLs (Bonferroni corrected P < 1 × 10–10). However, the identification of potential QTLs in these regions was impeded by extensive localised linkage disequilibrium. Analysis of extended haplotype homozygosity in the regions revealed this extended linkage disequilibrium was likely the result of recent strong selection, in most cases for the allele increasing height (Chi-square P = 0.000967). This observation sheds some light on why it has been so difficult to identify mutations affecting fertility, and other traits that are pleiotropic with height, in cattle.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"9 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145235537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coinfection affects the phenotypic but not genetic resistance of cattle to common parasites","authors":"Fabio Luiz Buranelo Toral, Maria Victoria Souza, Mariana Mamedes de Moraes, Valentina Riggio, Gabriela Canabrava Gouveia, Virginia Mara Pereira Ribeiro, Osvaldo Anacleto, Eduardo Penteado Cardoso, Daniel Resende Gonçalves, Andrea Doeschl-Wilson","doi":"10.1186/s12711-025-01003-y","DOIUrl":"https://doi.org/10.1186/s12711-025-01003-y","url":null,"abstract":"Genetic variation in host resistance to individual parasites is well documented in cattle; however, the influence of coinfection on these genetic responses to selection remains poorly characterized. In particular, it is unclear how concurrent exposure to multiple parasite species alters phenotypic expression, heritability estimates, or genetic correlations between resistance traits. To address these gaps, we evaluated the impact of coinfection on the genetic architecture of parasite resistance in yearling Nellore calves naturally challenged with ectoparasites (ticks) and endoparasites (gastrointestinal nematodes and Eimeria spp.). Using longitudinal parasite count data, we estimated genetic parameters and examined how coinfection modifies both individual parasite resistance and the genetic correlations among traits. Our results confirmed that coinfection is a common phenomenon (almost ¾ of samples contained multiple parasites) and that resistance to individual parasites is a heritable trait. Furthermore, coinfection with Eimeria spp. reduced the phenotypic resistance to nematodes, and vice versa. We observed diverse genetic associations for resistance to different parasites, including positive, negative, and nonsignificant correlations. Notably, coinfection had no significant effect on genetic resistance to individual parasites, nor did it alter genetic variances or associations between resistance to different parasites. While coinfection may influence the outcomes of nongenetic parasite control programs, its impact on genetic control strategies appears minimal. In other words, genetic resistance of Nellore cattle to three key parasite species appears to be robust and unaffected by the presence of coinfection.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"56 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145235538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 correlations of environmental sensitivity based on daily feed intake perturbations with economically important traits in a male pig line","authors":"Tomasi Tusingwiire, Carolina Garcia-Baccino, Bruno Ligonesche, Catherine Larzul, Zulma G. Vitezica","doi":"10.1186/s12711-025-01000-1","DOIUrl":"https://doi.org/10.1186/s12711-025-01000-1","url":null,"abstract":"Pigs in intensive production systems encounter various stressors that negatively impact their productivity and welfare. The primary aim of this study was to estimate the genetic correlations of the slope (indicator of sensitivity of the animals to environmental challenges) of the daily feed intake (DFI) across different environmental gradients (probability of the occurrence of a challenge on a given day) with growth, feed efficiency, carcass, and meat quality traits using a single-step reaction norm animal model (RNAM) in Piétrain pigs. In addition, genetic correlations of DFI (its total breeding value) with the same traits were also estimated. The probabilities of the occurrence of an unrecorded environmental challenge, inferred via a Gaussian mixture model, were taken as a reference and used in the genetic analysis as an environmental descriptor. Variance components were estimated via restricted maximum likelihood using the single-step genomic best linear unbiased prediction method, using a series of multivariate RNAM with two phenotypes (DFI and each of the traits of economic importance), with the probability of an unrecorded challenge on a given day included as an environmental descriptor for DFI only, because DFI is recorded daily but the other traits are not. Genetic correlations of the slope of DFI were 0.15 with age at 100 kg, 0.04 with backfat thickness, − 0.29 with loin muscle thickness, 0.05 with feed conversion ratio, − 0.07 with lean meat percentage, − 0.13 with pH of the ham at 24 h postmortem, 0.06 with drip loss percentage, and 0.15 with boneless ham weight. Complementary results showed that genetic correlations of DFI with other economic traits varied across the environmental gradients. Estimates of genetic correlations of DFI with other traits of economic importance varied across the environmental gradients, especially for growth rate, which suggests the presence of genotype-by-environment interactions. The slope of DFI is an indicator of sensitivity of the animals to environmental challenges. Most traits of economic importance exhibited weak genetic correlations with the slope of DFI, indicating that selection for resilience based on the environmental sensitivity (slope of DFI) can be performed without adversely affecting these other traits. Our results demonstrate the feasibility of improving resilience through genetic selection.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"60 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145203220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of genomic regions affecting thermotolerance traits in growing pigs during acute and chronic heat stress","authors":"Hélène Gilbert, Yann Labrune, Katia Fève, David Renaudeau, Roseline Rosé, Mario Giorgi, Yvon Billon, Jean-Luc Gourdine, Juliette Riquet","doi":"10.1186/s12711-025-00995-x","DOIUrl":"https://doi.org/10.1186/s12711-025-00995-x","url":null,"abstract":"This study aimed to identify genomic regions involved in animal responses to chronic and acute Heat challenges in 1149 pigs tested in three climatic environments (temperate, tropical, and temperate Heated to 30 °C for 3 weeks). Production (growth rate, feed intake and efficiency, backfat thicknesses) and thermoregulation (rectal and cutaneous temperatures) traits were recorded in a backcross between Large White and Créole pigs. Genome-wide association studies were applied to the full population assuming SNP effects to be the same in both environments or to depend on the environment (GxE), and to the population in each environment separately. The genetic models used linkage disequilibrium in all chromosomes (LD) or only in Large White chromosomes (LW), or breed-of-origin of F1 alleles through linkage analyses (LA). Fifty-two regions distributed on 16 autosomes were detected. Most were identified with the LW or LD analyses, indicating both a large variability of effects in Large White in response to Heat stress, and high variability among the 10 Créole genomes segregating in the design. However, for thermoregulation traits, the majority of QTLs were detected with the LW model, suggesting interesting segregation of susceptibility and resistance alleles within the Large White breed. Ten regions were detected with the GxE model, mainly corresponding to significant effects in the temperate environment and no effect in the tropical situation, except for two regions on chromosome 2, which affected backfat thickness and growth rate, respectively. Twenty-four regions were detected for thermoregulation traits, but none were significant for both rectal and cutaneous temperatures. Of the 13 QTL regions detected for traits recorded during acute stress, four were also detected for similar traits during chronic stress, suggesting some consistency of responses during both stresses, although nine QTL regions were only detected during acute heat stress. Measuring direct indicators of responses to heat stress, such as thermoregulatory responses, is essential to detect QTL and propose candidate genes involved in these responses. Multiple QTL for thermoregulatory responses segregate in the Large White breed were detected, paving the way for opportunities to select for heat stress resilience in European pig breeds.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"30 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145133581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Principal components-based selection criteria for genetic improvement of growth in sheep breeding programs","authors":"Ajoy Mandal, Indrajit Gayari, Sylvia Lalhmingmawii, David R. Notter, Hasan Baneh","doi":"10.1186/s12711-025-00992-0","DOIUrl":"https://doi.org/10.1186/s12711-025-00992-0","url":null,"abstract":"The objective of this study was to investigate the use of principal components (PC) as potential selection criteria to improve growth in sheep. The PC were derived from body weights of 2223 Muzaffarnagari lambs at birth, 90, 180, 270 and 360 days of age. Univariate animal models including various combinations of direct and maternal effects were fitted to the PC. Genetic correlations among PC and with body weights and estimated growth curve parameters for the Brody and Richards functions were estimated using bivariate animal models. The first three PC explained 94% of multivariate variation in body weights. PC1 contrasted lambs with larger versus smaller body weights at all postnatal ages. PC2 contrasted lambs with heavier versus lighter birth weights, with little emphasis on postnatal weights. PC3 placed positive emphasis on weights at birth and after 6 months of age but negative emphasis on weight at 3 through 9 months of age. Direct heritabilities for PC1, PC2, and PC3 were 0.19, 0.12 and 0.08, respectively. Maternal genetic and permanent environmental effects affected PC1 (0.04 and 0.08, respectively). PC2 was influenced by maternal genetic effects (0.10). Direct genetic correlations of PC1 with PC2 and PC3 were 0.48 and 0.72. The maternal genetic correlation between PC1 and PC2 was 0.97. Genetic relationships of PC1 with yearling weight and with estimates of final body weight from both growth functions exceeded 0.65. PC2 was genetically correlated with birth weight (≥ 0.64) and degree of maturity for body weight at birth (u0; ≥ 0.83). PC3 had negative genetic correlations with measures of maturing rate (~ -0.86) and with u0 ( -0.52 and -0.49), but positive correlations with final body weight (0.85 and 0.90) and time required to reach 50% of mature weight (0.83). Maternal genetic correlations of PC1 and PC2 with birth weight and u0 exceeded 0.83. We conclude that PC could be used as selection criteria in genetic improvement programs in sheep. Also, selection on PC1 and PC2 would likely be adequate to describe and improve direct and maternal genetic potentials for postnatal growth and birth weight, respectively, in Muzaffarnagari lambs.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"17 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145133585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of using preselected markers from imputed whole-genome sequence for genomic prediction in Angus cattle","authors":"Nantapong Kamprasert, Hassan Aliloo, Julius H. J. van der Werf, Christian J. Duff, Samuel A. Clark","doi":"10.1186/s12711-025-00999-7","DOIUrl":"https://doi.org/10.1186/s12711-025-00999-7","url":null,"abstract":"The advent of next-generation sequencing enables the opportunity to use denser marker tools, up to whole-genome sequences (WGS), for genomic prediction in livestock. Improvement in genomic prediction (GP) accuracy from using WGS has been observed in simulation studies. In contrast, such advantage has found to be inconsistent once implemented in practice. The benefit of WGS appears to be from markers that are significant for the trait of interest. Thus, the main objective of this study was to investigate the predictive ability of adding preselected markers to the standard-industry 50k genotype for GP of economically important traits in Angus cattle, namely, birth weight (BW), scrotal circumference (SC), carcass weight (CWT) and carcass intramuscular fat (CIMF). Animals were genotyped with either commercial or customised SNP-genotyping arrays; then, the genotypes were imputed to WGS. The 50k genotype was used as the control group. Informative markers associated with the desired traits were extracted from WGS, then were added to the 50k genotype. Several methods were chosen to select different sets of informative markers, including LD-based pruning, top SNP from a genome-wide association study (GWAS), functional annotation based on Gene Ontology, cattle QTL database, and sequence annotation. In total, eight different sets of genotypes were investigated. We applied different statistical models to predict genomic breeding values, including GBLUP, BayesR, and BayesRC, and two-GRM GBLUP constructed separately from the 50k and the preselected genotype set. Heritability (h2) estimates were similarly calculated using different sets of genotypes and statistical methods across all traits. The log-likelihood ratio values revealed that two-GRM GBLUP was more suitable than the single-GRM GBLUP. There was no significant difference in accuracy and bias among the different sets of genotypes compared to the control group or the statistical methods, except for BW. For BW, the Bayesian models slightly outperformed GBLUP. The findings suggest that potential improvements may be achieved by using preselected SNPs from the GWAS, a method that has proven within the population. The performance of preselected markers on GP influenced by several factors, including population structure, method used to select significant markers, and genetic architecture of traits.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"40 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145133582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-density genome-wide association study points out major candidate genes for resistance to infectious pancreatic necrosis in rainbow trout","authors":"Jonathan D’Ambrosio, Yoannah François, Thierry Morin, Sébastien Courant, Alexandre Desgranges, Pierrick Haffray, Bertrand Collet, Pierre Boudinot, Florence Phocas","doi":"10.1186/s12711-025-00996-w","DOIUrl":"https://doi.org/10.1186/s12711-025-00996-w","url":null,"abstract":"This study focuses on genetic resistance to infectious pancreatic necrosis (IPN), a highly contagious disease caused by an aquatic birnavirus (IPNV) which especially affects salmonids worldwide. The objectives were to estimate the heritability of IPN resistance and to fine map quantitative trait loci (QTL) using a Bayesian Sparse Linear Mixed Model to identify candidate genes possibly linked to IPN resistance in two successive generations from a French commercial strain of rainbow trout. For each generation, 2000 fish were experimentally exposed by bath to IPNV and mortalities were monitored daily during 5 weeks. All fish were genotyped using a medium-density 57 K single nucleotide polymorphism (SNP) chip and imputed to high-density genotypes (665 K SNPs). The mean survival rate was 70% after 37 days, with a higher survival rate in the second generation compared to the first one (78% versus 61%). Heritability was moderate (~ 0.20). Approximately 74% of the genetic variance of IPN resistance was explained by several tens of SNPs. In total, 25 QTL were mapped on 10 chromosomes, of which 7 were detected with very strong evidence, on chromosomes 1, 14, 16 and 28. The most interesting QTL were associated to top SNPs with mean survival rate differences over 20% between the beneficial and detrimental homozygous genotypes. Those SNPs were all located within promising functional candidate genes on chromosome 1 (uts2d, rc3h1, ga45b) and chromosome 16 (irf2bp, eif2ak2), which were all associated with regulation of inflammatory pathways. A key factor for the genetic differences in susceptibility to IPNV among fish is the dsRNA-dependent serine/threonine-protein kinase (PKR) encoded by the eif2ak2 gene. All genes associated with the most significant QTL on chromosomes 1 and 16 are involved in the regulation of inflammatory pathways, strongly suggesting a central role of inflammation in IPN resistance in rainbow trout. These findings offer the possibility of marker-assisted selection for rapid dissemination of genetic improvement for IPN resistance.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"35 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145133584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 genetic relationship between immune competence traits and micro-genetic environmental sensitivity of weight, fat, and muscle traits in Australian Angus cattle","authors":"Mette D. Madsen, Julius H. J. van der Werf, Aaron Ingham, Brad Hine, Antonio Reverter, Sam A. Clark","doi":"10.1186/s12711-025-00998-8","DOIUrl":"https://doi.org/10.1186/s12711-025-00998-8","url":null,"abstract":"Improving immune competence (IC) in livestock could reduce the incidence of disease and reliance on the use of antibiotics. In Australian Angus cattle, IC is a measure of an animal’s combined ability to mount antibody and cell-mediated immune responses (AMIR and CMIR). Immune competence may affect traits such as growth and related phenotypes as well as the variability of such phenotypes. However, the genetic relationship between IC and genetic sensitivity to individual environments, measured as micro-genetic environmental sensitivity (GES), is yet to be reported. In this study the genetic parameters of, and correlations between, AMIR or CMIR and micro-GES of live weaning weight (WW) and ultrasound scan records of rib (RIB) and rump (RUMP) fat depth and eye muscle area (EMA) measured between 501 and 900 days of age were estimated. This was accomplished by fitting eight multivariate models with AMIR or CMIR and a double hierarchical generalised linear model on a production trait. The heritabilities were 0.35 and 0.36 for AMIR and CMIR, respectively, and 0.25–0.70 for the production traits. The heritabilities and the genetic coefficient of variation of micro-GES of the production traits ranged from 0.01–0.04 and 18–82%, respectively, and were higher in RIB and RUMP than WW and EMA. The genetic correlations between AMIR and WW, RIB, RUMP, or EMA were -0.35 (SE 0.11), 0.11 (0.12), 0.06 (0.12) and -0.13 (0.12), respectively, while the genetic correlations between CMIR and WW, RIB, RUMP, or EMA were -0.26 (0.12), 0.15 (0.13), 0.16 (0.12) and 0.04 (0.13), respectively. The genetic correlations between IC and micro-GES of WW, RIB, RUMP or EMA were moderately negative to lowly positive and had large SEs rendering them non-significant. The unfavourable genetic correlation between the IC traits and WW supports the hypothesis that mounting an effective immune response can direct resources away from growth when resources are limited. Based on the heritabilities and genetic coefficient of variation of micro-GES, selection to increase uniformity is possible for WW, RIB, RUMP and EMA. The standard errors of the genetic correlations between IC and micro-GES of the production traits were too large to draw any definite conclusions about their relationships. Standard errors are expected to reduce as more IC records are collected.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"1 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145133608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating gene expression data via weighted multiple kernel ridge regression improved accuracy of genomic prediction","authors":"Xue Wang, Jingfang Si, Yachun Wang, Lingzhao Fang, Zhe Zhang, Yi Zhang","doi":"10.1186/s12711-025-00997-9","DOIUrl":"https://doi.org/10.1186/s12711-025-00997-9","url":null,"abstract":"Gene expression profiles hold potentially valuable information for the prediction of breeding values and phenotypes. However, in practical breeding programs, most reference population individuals typically have only genomic data, lacking transcriptomic data. Predicting gene expression based on genetic markers and integrating the genetically predicted gene expression data into genomic prediction may offer a potential solution. This study extends kernel ridge regression (KRR) to weighted multiple kernel ridge regression (WMKRR), which integrates genomic data and transcriptomic data predicted from genetic markers through a multiple kernel learning (MKL) approach. We evaluated the predictive ability of WMKRR compared to traditional genomic best linear unbiased prediction (GBLUP) and a combined genomic and transcriptomic best linear unbiased prediction (GTBLUP) in both genotype feature selection and non-feature selection scenarios in two datasets: (i) 3305 simulated data based on the Cattle Genotype-Tissue Expression (CattleGTEx) dataset, (ii) 5515 real dairy cattle data. Our results show that WMKRR yielded higher predictive abilities than GBLUP And GTBLUP in both simulated And real dairy cattle data. For the simulated data based on CattleGTEx, WMKRR achieved an average improvement in predictive ability of 1.12% And 1.13% over GBLUP And GTBLUP, respectively, under the non-feature selection scenario, And 3.17% And 3.23%, respectively, under the feature selection scenario. For the real dairy cattle data, in cross-validation, WMKRR improved over GBLUP And GTBLUP by An average of 5.56% And 7.23%, respectively, without feature selection, And by 5.66% And 6.40%, respectively, with feature selection. In forward validation, WMKRR improved over GBLUP And GTBLUP by An average of 5.68% And 8.41%, respectively, without feature selection, And by 4.66% And 7.06%, respectively, with feature selection. Our result demonstrates that the WMKRR model, which integrates genomic and genetically predicted transcriptomic data, achieves better prediction performance compared to traditional genomic prediction models. This study showed the potential of enhanced genomic breeding application using omics data with no further omics sequencing cost.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"13 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145133607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring skeletal disorders in cattle and sheep: a WGS-based framework for diagnosis and classification","authors":"Joana Jacinto, Anna Letko, Arcangelo Gentile, Arthur Otter, Tobias Floyd, Rachael Collins, Moyna Richey, Helen Carty, Sandra Scholes, Alwyn Jones, Harriet Fuller, Irene M. Häfliger, Ben Strugnell, Eveline Studer, Cinzia Benazzi, Marilena Bolcato, Jože Starič, Alessia Diana, Jim Weber, Markus Freick, Gesine Lühken, Imke Tammen, David C. E. Kraft, Celina M. Lindgren, Marlene Sickinger, Sara Soto, Brendon A. O’Rourke, Jørgen S. Agerholm, Cord Drögemüller","doi":"10.1186/s12711-025-01002-z","DOIUrl":"https://doi.org/10.1186/s12711-025-01002-z","url":null,"abstract":"Genetic skeletal disorders are a heterogeneous group of syndromic or non-syndromic diseases characterized by abnormal bone, joint or cartilage development. These disorders generally occur sporadically in ruminants. Although a genetic etiology is often suspected, only a limited number of causal variants have been identified and no comprehensive genetic analyses of a cohort of bovine and ovine skeletal developmental defects have been published. The aims of our study were (1) to propose a nosology of genetic skeletal disorders in cattle and sheep and (2) to contribute to the nosology with a number of novel genomically characterized cases. Based on a literature review, the proposed nosology of skeletal disorders in cattle and sheep with a confirmed molecular cause was found to comprise 43 different disorders associated with 45 different genes. In addition, horn traits were also included. The disorders were grouped into 21 categories based on the human medical nosology. Thirty novel bovine and nine ovine cases of congenital skeletal disorders were investigated. These represented 19 different disorders, which were grouped into 9 categories. Whole-genome sequencing (WGS) data were generated based on sample availability for either complete trios, affected paternal halfsiblings or isolated single cases. We identified 21 SNVs or small indels for 12 skeletal disorders. Of these, 17 were considered candidate variants affecting 16 different genes, including 11 that were classified as pathogenic and six as likely pathogenic. Additionally, the remaining 4 SNVs were of uncertain significance. Two aneuploidies (trisomy and partial monosomy) were the cause of two different disorders. For eight cases affected by six disorders no variant could be identified. Different modes of inheritance were detected, including spontaneous dominant de novo mutations, autosomal recessive alleles, an X-linked dominant allele, as well as aneuploidies. The overall molecular genetic diagnostic rate was 64%. Genomic analysis revealed considerable heterogeneity of the described phenotypes in terms of mode of inheritance, affected genes, and variant type. We propose, for the first time in veterinary medicine, a nosology of genetic skeletal disorders in ruminants that may be useful for more precise differential clinicopathological diagnosis. We emphasize the potential of WGS to enhance genetic disease diagnosis and the importance of adopting a nosology for disease categorization.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"57 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145133583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}