Mammalian Genome最新文献

{"title":"Utilising genomic association data for causal inference in anorexia nervosa.","authors":"Danielle M Adams, Murray J Cairns","doi":"10.1007/s00335-025-10150-y","DOIUrl":"https://doi.org/10.1007/s00335-025-10150-y","url":null,"abstract":"<p><p>Anorexia nervosa (AN) is a prevalent psychiatric disorder with high rates of mortality and limited treatment options. AN is a complex disorder, for which common variation contributes to disorder risk. To dissect the genetic architecture of AN, a variety of statistical methods can be applied. Many of these utilise genome-wide association study (GWAS) datasets to investigate biological mechanisms within disease progression in addition to broader associations between complex traits. GWAS for AN have revealed important biological insights, however, these have not translated into new pharmacotherapies. Here, we review the application of statistical methods that use GWAS, to investigate the relationship between genetic variation, biochemical compounds and complex traits to identify potential relationships which could advance our understanding of disease biology. We discuss genetic variant association data for AN, the application of gene-based and complex trait level correlation methods and approaches for establishing evidence of causality between complex traits and AN. These methods all contribute to the growing literature regarding the genetic influences of AN risk and demonstrate that statistical analysis utilising genetic data is a valuable tool to progress our understanding of this disease.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144608731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrative multiomics elucidate crotonylation-associated GCDH in Parkinson's disease pathogenesis via metabolome remodeling.","authors":"Jia Fu, Jing Zhao, Na Mi, Chao Zhang, Yali Zhang, Lifen Yao","doi":"10.1007/s00335-025-10151-x","DOIUrl":"https://doi.org/10.1007/s00335-025-10151-x","url":null,"abstract":"<p><p>The pathophysiological significance of crotonylation and its metabolomic regulatory circuitry in Parkinson's disease (PD) remains elusive. We utilized Mendelian randomization (MR) frameworks combined with mediation analysis to establish causal links between crotonylation-associated genes and PD, while systematically delineating metabolite-mediated mechanisms. In this study, crotonylation-related genes were selected from the eQTLGen dataset, and their causal relationship with PD was assessed using two-sample MR analysis. Subsequently, we investigated metabolites associated with PD risk. Additionally, two-step MR and MR mediation analyses were applied to explore the mediating effects of crotonylation-related genes, metabolites, and PD. To further interpret cellular heterogeneity, publicly available GEO single-cell transcriptome data were integrated to analyze PD brain tissue dynamics and the regulatory mechanisms of key crotonylation-related genes. We identified 16 crotonylation-associated genes harboring cis-eQTLs, notably SIRT1, GCDH, and HDAC7, which demonstrated significant inverse associations with PD risk (p < 0.05). Through MR analysis, 74 PD-associated metabolites were identified. Mediation analysis further delineated GCDH-mediated PD risk reduction (β_all = -0.054) through downregulation of X-21,471 and tetradecanedioate (C14-DC). Furthermore, single-cell transcriptomic analysis revealed that GCDH is predominantly and specifically highly expressed in astrocytes within PD brain tissues, and its dynamic regulatory pattern is closely linked to cell differentiation processes, suggesting a potential role in regulating PD pathogenesis via the NRG3-ERBB4 signaling axis. Our findings indicate that GCDH and its mediated metabolome critically contribute to PD pathogenesis, with astrocytes emerging as a central regulatory cell type. This study not only elucidates novel molecular landscapes underlying PD pathology but also highlights astrocytes as promising targets for therapeutic intervention.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144608730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiple omics-based machine learning reveals peripheral blood immune cell landscape during acute rejection of kidney transplantation and constructs a precise non-invasive diagnostic strategy.","authors":"Jiyue Wu, Lijian Gan, Xihao Shen, Feilong Zhang, Zhen Li, Huawei Cao, Hao Wang, Zejia Sun, Le Qi, Wei Wang","doi":"10.1007/s00335-025-10149-5","DOIUrl":"https://doi.org/10.1007/s00335-025-10149-5","url":null,"abstract":"<p><p>Kidney transplantation is the optimal treatment for end-stage renal disease (ESRD), but acute rejection (AR) remains a major factor affecting graft survival and patient prognosis. Currently, renal biopsy is the gold standard for diagnosing AR, but its invasiveness limits the application of dynamic monitoring. This study aims to analyze changes of immune cell and gene expression in the peripheral blood of AR recipients and construct a non-invasive AR diagnosis strategy. All datasets were downloaded from the GEO database. Single cells were annotated based on the expression profiles of surface proteins and changes of immune cell in the peripheral blood of AR and stable transplant (STA) recipients were compared. The high-dimensional weighted gene co-expression network analysis (hdWGCNA) algorithm was used to analyze gene modules related to AR and to screen out hub genes by integrating bulk RNA-Seq. Based on hub genes, consensus clustering stratified recipients into two sub-clusters and a non-invasive AR diagnostic model was constructed using Convolutional Neural Networks (CNNs). Additionally, we also constructed a predictive model for long-term graft survival through combinations of 111 machine learning algorithms and validated the expression of hub genes in the rat AR model. AR recipients had higher abundance of memory B cells, effector memory T cells, terminally differentiated effector memory T cells (TEMRA), and NK T cells but lower Tregs in the peripheral blood compared to STA recipients. Through hdWGCNA analysis, we identified gene modules associated with these immune cells and screened out four hub immune-related genes (TBX21, CX3CR1, STAT1, and NKG7) after integrating bulk RNA-Seq. Based on these hub genes, recipients can be stratified into two sub-clusters with distinct clinical outcomes and biological characteristics. We also innovatively constructed a non-invasive AR diagnostic model using CNNs, which can effectively address the issues caused by batch effects and demonstrate a high diagnostic accuracy. Besides, the predictive model for long-term graft survival constructed using the RSF algorithm can divided recipients into high- and low-risk groups, with significantly higher rates of AR and long-term graft failed in the high-risk group. This study successfully identified immune cell subsets and hub genes related to AR. Based on hub genes, we successfully identified two distinct molecular sub-clusters of kidney transplant recipients, and constructed a non-invasive diagnostic model for AR and a predictive model for long-term graft survival. These models offer new tools for precise diagnosis and prognosis in kidney transplantation and may advance precision medicine.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144584299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low-coverage whole-genome sequencing facilitates accurate and cost-effective haplotype reconstruction in complex mouse crosses.","authors":"Samuel J Widmayer, Lydia K Wooldridge, Emily Swanzey, Mary Barter, Chrystal Snow, Michael Saul, Qingchang Meng, Beth Dumont, Laura Reinholdt, Daniel M Gatti","doi":"10.1007/s00335-025-10148-6","DOIUrl":"https://doi.org/10.1007/s00335-025-10148-6","url":null,"abstract":"<p><p>The search for the underlying genetic contributions to complex traits and diseases relies on accurate genetic data from populations of interest. Outbred populations, like the Diversity Outbred (DO), are commonly genotyped using commercial SNP arrays, such as the Giga Mouse Universal Genotyping Array (GigaMUGA). However, array genotypes are expensive to collect, subject to significant ascertainment bias, and too sparse to capture the genetic structure of highly recombined mouse crosses. We investigated the efficacy of sequencing-based genotyping by comparing genotyping results between the GigaMUGA, double-digest restriction-site associated DNA sequencing (ddRADseq), and low-coverage whole-genome sequencing (lcWGS). We aligned reads at ~ 1× coverage and imputed segregating SNPs from the eight DO founder strains onto 48 DO genomes and reconstructed their haplotypes using R/qtl2. Haplotype reconstructions derived from all three methods were highly concordant. However, lcWGS more faithfully recapitulated crossover counts and identified more small (< 1 Mb) haplotype blocks at as low as 0.1× coverage. Over 90% of local expression quantitative trait loci identified in a set of 183 DO-derived embryoid bodies using the GigaMUGA were recalled by lcWGS at coverages as low as 0.1×. We recommend that lcWGS be adopted as the primary method of genotyping complex crosses, and cell-based resources derived from them because they are as accurate as array-based reconstructions, robust to ultra-low sequencing depths, may more accurately model haplotypes of the mouse genome that are difficult to resolve with dense reference data, and cost-effective.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144540764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploration of shared diagnostic genes and mechanisms between crohn's disease and ischemic stroke by integrated comprehensive bioinformatics analysis and machine learning.","authors":"Chunlin Ren, Xinmin Li, Fangjie Yang, Jing Wang, Pengxue Guo, Zhenfei Duan, Yuting Kong, Mengyao Bi, Yongqi Yuan, Tian Tian, Yasu Zhang","doi":"10.1007/s00335-025-10145-9","DOIUrl":"https://doi.org/10.1007/s00335-025-10145-9","url":null,"abstract":"<p><p>Investigating comorbidities of ischemic stroke (IS) enhances understanding of its intricate mechanisms. Crohn's disease (CD) is associated with an increased risk of IS, but the underlying mechanisms remain unclear. This study aims to identify shared diagnostic genes and explore the mechanisms underlying CD-IS comorbidity using bioinformatics and machine learning approaches. Gene expression data for CD and IS were obtained from the Gene Expression Omnibus. Shared genes were identified through differential expression and weighted gene co-expression network analyses (WGCNA). Functional enrichment analyses highlighted key biological pathways. Core genes were screened via machine learning algorithms and protein-protein interaction networks. Diagnostic nomograms were constructed, and single-cell RNA sequencing was used to characterize expression patterns of core genes. Immune cell infiltration was quantified using CIBERSORT, and a competing endogenous RNA network was built based on TarBase and SpongeScan databases. Mendelian randomization was performed to assess causal associations between core genes and disease risk. Candidate drugs were predicted using the Drug-Gene Interaction Database and validated through molecular docking. Twenty shared genes were identified through differential expression analysis and WGCNA. The toll-like receptor (TLR) signaling pathway was identified as a key pathway in CD-IS comorbidity. TLR2 and TLR8 were identified as core genes, with strong diagnostic performance (AUC > 0.80). The polymorphism of rs73221365 was associated with both CD and IS. Resveratrol hexanoic acid was a potential therapeutic candidate for CD-IS comorbidity. This study highlights the critical role of TLR-mediated inflammatory responses in CD-IS comorbidity. TLR2 and TLR8 may serve as promising diagnostic biomarkers. These findings advance understanding of the shared pathophysiology in CD-IS comorbidity and provide a foundation for developing precise diagnostics and targeted therapies.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144528637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Elucidation of novel diagnostic biomarkers and therapeutic targets in colorectal carcinoma: an integrative approach leveraging multi-omics, computational biology, and single-cell sequencing technologies.","authors":"Tingyang Li, Yuhua Tian, Yinchuan Wang, Jianle Yang, Ziyu Chen, Yiliang Li","doi":"10.1007/s00335-025-10141-z","DOIUrl":"https://doi.org/10.1007/s00335-025-10141-z","url":null,"abstract":"<p><p>This study employs a comprehensive, multi-layered analytical approach to comprehensively investigate the pathogenesis, diagnostic methodologies, and potential therapeutic targets of colorectal cancer. Integrating data from the Global Burden of Disease (GBD) database, transcriptomics, proteomics, and single-cell sequencing technologies, this study elucidates both the epidemiological characteristics and molecular mechanisms of colorectal cancer. Our findings indicate that VEGFA, ICAM1, and IL6R play prominent roles in cancer progression. Proteomics analysis has identified multiple potential drug targets, and molecular docking and dynamic simulations have provided a theoretical foundation for developing drugs targeting VEGFA. Multi-omics studies have revealed that colorectal cancer progression involves intricate microbiome-host interactions, metabolic regulation, and immune response mechanisms, with factors such as Clostridia, 4E-BP1, AIFM1, and CXCL5 exhibiting dual roles. These discoveries not only deepen our understanding of colorectal cancer pathogenesis but also offer novel insights for optimizing diagnostic and therapeutic strategies, thereby laying the groundwork for developing personalized treatment regimens. Future research should focus on further validating these findings and exploring their potential clinical applications.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144484956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review on the mechanism and potential diagnostic application of CRISPR/Cas13a system.","authors":"Abdul Basit, Anjing Liu, Wanglong Zheng, Jianzhong Zhu","doi":"10.1007/s00335-025-10143-x","DOIUrl":"https://doi.org/10.1007/s00335-025-10143-x","url":null,"abstract":"<p><p>Clustered regularly Interspaced short palindromic repeats (CRISPRs) and CRISPR-associated (Cas) proteins form a natural immune defense system in prokaryotic species, with approximately 90% of archaea and 40% of bacteria possessing these systems, highlighting their widespread role in microbial immunity. Among these, the CRISPR/Cas13a system, guided by a single-stranded RNA (crRNA), selectively targets RNA sequences and has shown immense potential in developing sensitive diagnostic tools. Recent advancements have combined Cas13a with amplification methods and lateral flow detection (CRISPR/Cas13a-LFD), improving its application for rapid and accurate RNA detection. In this review, we explore the history, structure, and functional mechanism of the CRISPR/Cas13a system, focusing on its diagnostic capabilities. We compare CRISPR/Cas13a to conventional diagnostic approaches, highlighting their advantages in sensitivity, specificity, speed, and flexibility for point-of-care application. Given the rapid development of CRISPR-based diagnostics in recent years, the Cas13a system shows great potential as a next-generation platform for accurate, portable, and cost-effective detection of viral and bacterial diseases. Furthermore, we address the existing challenges, including reliance upon amplification and off-target effects, and highlight the need for ongoing research to develop amplification-free systems suitable for clinical application.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144484955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FOXP2 mediates ZSCAN18 transcriptional activation to inhibit oral squamous cell carcinoma progression by blocking Hedgehog signaling.","authors":"Ling Niu, Guangyao Hu","doi":"10.1007/s00335-025-10147-7","DOIUrl":"https://doi.org/10.1007/s00335-025-10147-7","url":null,"abstract":"<p><p>Zinc finger and SCAN domain-containing (ZSCAN) family members have been implicated in cancer progression. This paper was to assess the role of ZSCAN18 in oral squamous cell carcinoma (OSCC). The OSCC datasets were obtained from the GEO database, and the differentially expressed gene ZSCAN18 was screened for the next analysis. ZSCAN18 protein levels in OSCC tissues and cell lines were investigated. ZSCAN18 was manually overexpressed in OSCC cells to analyze cell proliferation, invasion, migration, and stemness. The protein level of GLI1, a marker protein of the Hedgehog pathway, was detected to determine the effect of ZSCAN18 on this signaling pathway. A mouse xenograft tumor model was constructed to observe tumor growth. Rescue experiments were designed to validate the impact of the FOXP2/ZSCAN18 axis on OSCC. ZSCAN18 was lowly expressed in OSCC and predicted poor prognoses. ZSCAN18 overexpression inhibited OSCC progression, tumor cell stemness, and the Hedgehog pathway. FOXP2, an upstream transcription factor of ZSCAN18, transcriptionally activated ZSCAN18. Rescue experiments further confirmed that FOXP2 transcriptionally activated ZSCAN18 and thus inhibited stemness and tumor growth. Collectively, FOXP2 mediates ZSCAN18 transcriptional activation to inhibit OSCC by blocking Hedgehog signaling.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144484957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomic signatures of selection in drug metabolizing genes across cattle populations.","authors":"Sonali Sonejita Nayak, Manjit Panigrahi, Ayushi Vaidhya, G Ravi Prakash, Subhashree Parida, Triveni Dutt","doi":"10.1007/s00335-025-10139-7","DOIUrl":"https://doi.org/10.1007/s00335-025-10139-7","url":null,"abstract":"<p><p>Cattle are integral to agriculture and rural livelihoods in India, where diverse indigenous breeds have adapted to varied environments. The diversity of Indian breeds has shaped genetic traits linked to toxin processing, disease resistance, and metabolic efficiency. The genomic study of cattle reveals significant insights into the evolutionary pressures shaping drug-metabolizing genes (DMGs) across breeds. This study analyzed genome-wide selection signatures in seven cattle breeds, including Indigenous such as Red Sindhi (n = 96), Tharparkar (n = 72), Gir (n = 96), crossbred such as Frieswal (n = 14), Vrindavani (n = 72), and exotic cattle populations such as Holstein Friesian (n = 63), Jersey (n = 28). We utilized 50K and ddRAD SNP genotyping data to perform intra-population analyses (iHS, CLR, ROH) and inter-population analyses (F_ST, XP-EHH) for detecting genomic regions under selection. Key findings include the identification of cytochrome P450 genes (e.g., CYP7A1, CYP4A11, CYP19A1) and other DMGs exhibiting selection signatures linked to metabolic and biosynthetic processes. Red Sindhi cattle exhibited selection in genes like CYP7A1 and CYP2W1, which were involved in steroid biosynthesis and chemical stimulus response. Tharparkar cattle demonstrated positive selection in CYP4A11 and related genes involved in the functionalization of compounds. Crossbreeds of Vrindavani and Frieswal displayed intermediate signatures, reflecting mixed genetic contributions. Our research shows that Indigenous purebred cattle possess a superior selection signature of drug-metabolizing ability, enhanced disease resistance, and greater adaptability than crossbred and exotic breeds. This research contributes to understanding breed-specific adaptations, informing pharmacological interventions and conservation efforts.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144317360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of genomic breeding values and accuracy for carcass traits in Korean Hanwoo cows using whole-genome SNP chip panels.","authors":"Ji-Hee Jang, Han-Deul Lee, Jong-Joo Kim, Md Azizul Haque","doi":"10.1007/s00335-025-10142-y","DOIUrl":"https://doi.org/10.1007/s00335-025-10142-y","url":null,"abstract":"<p><p>Enhancing the quality and yield of Korean beef relies on improving carcass traits, including carcass weight (CWT), eye muscle area (EMA), backfat thickness (BF), and marbling score (MS). This study aimed to evaluate the accuracy of genomic EBVs for these traits using the genomic BLUP method. Phenotypic data were collected from 19,153 Hanwoo steers and 6,200 Hanwoo cows, with all animals genotyped using the Illumina Bovine 50K SNP chip. The population was divided into three groups to evaluate prediction accuracy. For CWT, theoretical accuracy reached 0.76, 0.75, and 0.78 for Groups 1, 2, and 3, respectively, with realized accuracy ranging from 0.70 to 0.74, indicating a strong correlation between predicted and actual performance. For EMA, theoretical accuracy ranged from 0.74 to 0.76, while realized accuracy was lower (0.64, 0.68, 0.69), suggesting the need for improved prediction models or larger, more diverse reference populations. BF showed theoretical accuracies of 0.75, 0.75, and 0.77, with realized accuracies of 0.59, 0.62, and 0.65. MS demonstrated the highest performance, with theoretical accuracies between 0.78 and 0.81, and realized accuracies between 0.73 and 0.78, reflecting a strong genetic component in marbling traits. This study underscores the importance of building a larger, cow-specific reference population to enhance GEBV prediction accuracy and maximize genetic gains in Hanwoo cow breeding programs.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144317359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}