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PubMed2026

Transition from Conventional to Genomic Selection (ssGBLUP) led to improve in accuracy gains and selection decisions in Sahiwal Cattle.

By using genome-wide markers to predict an individual's genetic potential, the introduction of Genomic Selection (GS) has transformed animal breeding. This greatly accelerated selection for complex traits by lowering reliance on drawn-out field trials, allowing for faster genetic gains in livestock. However, there is little research on the effects of genomic selection on Sahiwal cattle in India, and comparing it to the current culling or selection process is even more uncommon, particularly in nations with fewer genotyped animals. This study is an initial effort to address the aforementioned gaps in knowledge. Genomic selection was implemented in Sahiwal cattle for the 305 days milk yield using univariate animal model and the single-step Genomic Best Linear Unbiased Prediction (ssGBLUP) method. The Effective Population size (Ne) of the Sahiwal herd was calculated using genomic data and was reported for the previous generation to be 71.927. The heritability of 305 days milk yield was estimated as 0.177 ± 0.068. Genomic estimated breeding values (GEBVs) were predicted for each individual using ssGBLUP, yielding a mean prediction accuracy of 43.11%, compared with 40.88% obtained using conventional pedigree-based BLUP. Cross-validation further demonstrated superior predictive performance of ssGBLUP, with accuracies of 76.82% and 70.50% for ssGBLUP and PBLUP, respectively. To further check the effectiveness of the genomic selection methodology, we also compared the GEBVs obtained and compared it with the Expected Progeny Difference (EPD) which is being applied in our farm for culling decisions. It was seen that GEBVs obtained from ssGBLUP methodology were also in line with the conventionally used method of EPD. The use of genomic selection enables genetic studies with limited pedigree information. Additionally, the ssGBLUP methodology allows to check for pedigree errors, where family relationships are incorrectly recorded. The EPD and GEBVs were consistent with one another, indicating that genomic selection may also be utilised to support culling and selection decisions in a farm. Thus, in a conventional animal breeding program with constraint resources and an incomplete pedigree, we recommend employing the ssGBLUP model for regular genomic assessment and identification of suitable candidates to effectively carry out a genomic selection program.

Animals↗

PubMed2025

Genomic prediction and genome-wide association study for liver abscesses in crossbred beef cattle.

Liver abscesses are a concern in feedlot cattle, and little is known about the role of genetics in their development. This study aimed to estimate genetic parameters and to identify single-nucleotide polymorphisms (SNPs) associated with liver abscesses. Crossbred cattle representing 18 breeds in the U.S. Meat Animal Research Center Germplasm Evaluation Program were phenotyped for liver abscesses at slaughter (n = 9,044). Seventeen percent of cattle had liver abscesses. These cattle had genotypes that were imputed to sequence variant genotypes. After filtering and quality control, 340,723 SNPs were used in the analysis. Liver abscess prevalence was modeled with a single-step genomic best linear unbiased prediction (ssGBLUP) threshold model using a Bayesian framework. The model included contemporary group (sex, treatment group, and slaughter date), additive genomic, and residual effects. Genomic heritability was 0.039 (95% highest posterior density = 0.005, 0.081), which was very small. To assess prediction quality, a 5-fold random cross-validation structure was used. Method Linear Regression was used to assess accuracy, bias, and dispersion by comparing estimated breeding values (EBV) from full and reduced analyses. Cross-validation metrics showed EBV based on genotypes had 0.05 reliability (SD < 0.01) with no bias relative to EBV based on genotypes and phenotypes. For the genome-wide association study, SNP effects were back calculated from the EBV solutions from ssGBLUP. No SNPs were associated with liver abscesses at a Benjamini-Hochberg adjusted 0.05 significance level. Although a large dataset was used, this result was because of the low genomic heritability and imprecise EBV used to calculate SNP effects. Based on these results, environmental factors contribute to most of the variation in liver abscesses. Genetic selection to reduce liver abscesses would be slow because of the low genomic heritability, measurement late in life, and inability to measure breeding animals. A faster approach would be finding additional environmental interventions that maintain animal performance.

Animals↗

PubMed2024

Genomic prediction and genome-wide association studies of morphological traits and distraction index in Korean Sapsaree dogs.

The Korean Sapsaree dog is a native breed known for its distinctive appearance and historical significance in Korean culture. The accurate estimation of breeding values is essential for the genetic improvement and conservation of such indigenous breeds. This study aimed to evaluate the accuracy of breeding values for body height, body length, chest width, hair length, and distraction index (DI) traits in Korean Sapsaree dogs. Additionally, a genome-wide association study (GWAS) was conducted to identify the genomic regions and nearby candidate genes influencing these traits. Phenotypic data were collected from 378 Korean Sapsaree dogs, and of these, 234 individuals were genotyped using the 170k Illumina CanineHD BeadChip. The accuracy of genomic predictions was evaluated using the traditional BLUP method with phenotypes only on genotyped animals (PBLUP-G), another traditional BLUP method using a pedigree-based relationship matrix (PBLUP) for all individuals, a GBLUP method based on a genomic relationship matrix, and a single-step GBLUP (ssGBLUP) method. Heritability estimates for body height, body length, chest width, hair length, and DI were 0.45, 0.39, 0.32, 0.55, and 0.50, respectively. Accuracy values varied across methods, with ranges of 0.22 to 0.31 for PBLUP-G, 0.30 to 0.57 for PBLUP, 0.31 to 0.54 for GBLUP, and 0.39 to 0.67 for ssGBLUP. Through GWAS, 194 genome-wide significant SNPs associated with studied Sapsaree traits were identified. The selection of the most promising candidate genes was based on gene ontology (GO) terms and functions previously identified to influence traits. Notable genes included CCKAR and DCAF16 for body height, PDZRN3 and CNTN1 for body length, TRIM63, KDELR2, and SUPT3H for chest width, RSPO2, EIF3E, PKHD1L1, TRPS1, and EXT1 for hair length, and DDHD1, BMP4, SEMA3C, and FOXP1 for the DI. These findings suggest that significant QTL, combined with functional candidate genes, can be leveraged to improve the genetic quality of the Sapsaree population. This study provides a foundation for more effective breeding strategies aimed at preserving and enhancing the unique traits of this Korean dog breed.

Animals↗

PubMed2026

Integrated GWAS and methylation analysis identify DNMT3A as an important regulator of growth in rabbits.

The parameters of individual growth curve can serve as pseudo-phenotype for genetic evaluation in livestock. In this study, we compared five nonlinear growth models using post-weaning body weights of 706 New Zealand White rabbits. Under the best-fitting model, two parameters of mature weight and maturity rate were subjected to GWAS through single-step genomic BLUP framework that integrated phenotypic records from non-genotyped animals with 41,359 SNPs genotyped in 198 individuals. Association analysis identified 147 relevant genomic regions, and also highlighted DNMT3A as a promising candidate gene for further functional investigation. siRNA-mediated knockdown of DNMT3A significantly impaired myoblast proliferation. Whole-genome bisulfite sequencing of DNMT3A-knockdown myoblasts identified 69,480 differentially methylated regions (DMRs). Integrative analyses revealed substantial overlap between DMR-associated genes and GWAS candidate genes, with significant enrichment in vitamin B6 and tyrosine metabolism pathways. These findings suggest that DNMT3A may regulate rabbit growth via mediating DNA methylation of downstream genes.

Animals↗

PubMed2026

Genomic background of gestation length and calving-related traits in Holstein cattle.

The reproductive success of cows directly influences the profitability of dairy farms. Reproductive traits, particularly calving-related traits, generally have low heritability but sufficient additive genetic variance to enable genetic progress through genomic selection. Thus, the primary objectives of this study were to estimate genetic parameters and perform single-step genome-wide association studies (ssGWAS) for calf size, calving ease, gestation length, and stillbirth in Holstein cattle. Variance components were estimated based on animal models and Bayesian inference using a data set containing 226,717 animals with phenotypic records, 15,761 animals genotyped with 45,101 SNP markers, and 461,819 animals in the pedigree. SNP effects were estimated using the single-step GBLUP method. For direct and maternal genetic effects, heritability estimates (posterior standard deviation) ranged from 0.001 (0.002) for gestation length in heifers to 0.16 (0.001) for gestation length in cows. Genetic correlations ranged from -0.57 (0.01) between calving ease and stillbirth in heifers to 0.74 (0.01) between gestation length evaluated in heifers and cows. The ssGWAS results supported a highly polygenic architecture for calving-related traits, with most genomic signals not reaching genome-wide significance. A genome-wide significant association was detected for calving ease in cows on BTA23, highlighting FARS2 as a positional candidate gene. The strongest GWAS signals for each trait harbored additional biologically important candidate genes, including NPPA, NPPB, BCHE, EPHA4, DLD, and GTF2I. Given the generally low heritability estimates and the predominantly polygenic architecture observed for these traits, genomic selection may contribute to the genetic improvement of calving-related traits in Holstein cattle, with potential benefits for cow welfare, calf survival, and overall dairy production efficiency.

dairy cattle↗