Aug 2026· PLoS ONE· Vol 21, pp. e0355541· 0 citations· 37 references
Medicine
Abstract
This paper investigates different selection scenarios to reduce the prevalence of a genetic defect in a vulnerable breed, using simulations of selection against gonadal hypoplasia in Swedish Mountain Cattle as a case study. Gonadal hypoplasia (reduced size of ovaries/testes) that leads to reduced fertility has long been a problem in Swedish Mountain cattle (Fjällko). Despite breeding efforts that have reduced the frequency of the defect, it is still present in the breed. There are two translocations involving chromosomes 6 and 29 associated with desired colour phenotypes that segregates in several Swedish local cattle breeds. One of these is associated with gonadal hypoplasia although there is incomplete penetrance. With modern DNA methods it is possible to detect the carriers of this defect and tackle this old problem, but the key issue is to do this without harming genetic diversity. We performed simulations with allele frequencies and penetrance that have been estimated previously in the breed and different scenarios of marker-assisted selection. The simulated scenarios were: genetic testing of potential bulls prior to selection to exclude carriers or homozygotes for the deleterious allele; genetic testing of bulls used for artificial insemination to exclude carriers or homozygotes for the deleterious allele; and genetic testing of bulls used for artificial insemination but where 1 or 5 carrier sires were allowed to be used. Simulations showed that it is possible to reduce the frequency of the allele causing the genetic defect while maintaining the effective population size. This however comes with a cost of requiring many genetic tests. Based on these results, the most promising approach would be to pre-screen bull calves before selection of sires, maintaining the number of bulls that are used. These results suggest that efforts to genotype and phenotype cattle for validation and testing of the marker in Swedish Mountain cattle is warranted.
Effective population size (
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) is a crucial parameter in the fields of evolutionary biology, conservation biology of endangered species, and selective breeding of domestic animals and crops, as it quantifies the magnitude of genetic drift and inbreeding occurring in a population. Because genetic drift is responsible for the loss of genetic variation and adaptive potential of populations, and inbreeding is known to cause the deterioration of fitness (i.e., inbreeding depression),
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is considered one of the key indicators for assessing the genetic status, adaptive potential, and extinction risks of populations. Different methods have been developed to estimate this parameter, with recent advances made possible using genomic markers generated through genotyping and sequencing projects. This review aims to provide an overview of the methods currently employed to estimate contemporary and recent
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from genomic data and to exemplify these methods by analyzing some simulated and empirical datasets.
A. Caballero, E. Santiago, Jinliang Wang· Annual Review of Ecology, Ev...· 0 citations
Inbreeding load is the fraction of the mutation load that is due to recessive action of mutations. This load is only expressed in individual's inbred offspring. As such, inbreeding load contributes to genetic heterogeneity among individuals and can thus be used as a criterion of selection. Future parents could be selected based on their estimated breeding values and their estimated inbreeding load. Here, we evaluated the effectiveness of selection strategies involving inbreeding load in a dairy sheep breeding scheme. We evaluated seven strategies with a stochastic simulation across 15 generations of genetic evaluation and selection. The strategies differed in the criteria of selection (only estimated breeding values, only estimated inbreeding load, both or random) and mate strategies minimising inbreeding load, adjusting estimated breeding values by the expected future inbreeding or random. The strategies were compared in terms of genetic gain, pedigree-based inbreeding coefficients, rate of inbreeding, effective population size, inbreeding depression estimates, and accuracy of selection. Results showed that among the seven strategies, there was no significant difference between the five in which selection was based on estimated breeding values over the 15 years of the simulated dairy sheep breeding scheme. As expected, selection only on the estimated inbreeding load and the random selection and random mating strategy had significantly lower genetic gain than the five strategies in which selection was based on estimated breeding values. To conclude, selecting animals using estimated inbreeding load is feasible. However, the magnitude of inbreeding load effects and its accuracy did not show a clear practical interest. Furthermore, the benefit of using inbreeding load in mate allocation strategies was negligible.
Simona Antonios, J. Obšteter, I. Pocrnić et al.· Journal of animal breeding a...· 0 citations
Dominance is a non-additive genetic effect involving allele interaction at the same locus. In animal breeding, it has often been ignored due to its complexity and the low accuracy of pedigree-based estimates. This study analysed dominance variance components for reproductive traits [age at first foaling (AFF), reproductive efficiency (RE), interval between first and second foaling (I12)] and morphological traits [scapulo-ischial length (SIL), dorsal sternal diameter (DSD), knee circumference (KC)] in Pura Raza Española (PRE) mares. The aim was to assess the magnitude of dominance effects across traits to determine whether alternative models are required for breeding value estimation or if dominance deviation predictions should be reconsidered in strategies such as mating design. Mares with full sisters and at least one foaling were identified and additional records of other females foaling in the same stud and year were also selected. The number of mares with reproductive and morphologic records was 3967 and the pedigree included 11,331 individuals with an average relatedness coefficient of 5%. First, condensed probabilities of identity based on pedigree data were estimated using a recursive algorithm. Next, a linear model in which variance components (dominance, additive and their covariance) were estimated, using the pedigree and phenotypic data. The dominance variance was partitioned into a term linked to relationships between non-inbred individuals and another linked to relationships between inbred individuals, with the latter assumed to be correlated with the additive effect. The broad-sense heritability values oscillated between 0.64 (SIL) and 0.20 (RE) while the narrow-sense heritability ranged between 0.05 (I12) and 0.39 (KC) and estimates of the additive-dominance correlation varied between − 0.43 (RE and I12) and − 0.69 (DSD). The consideration of dominance deviations in mating design would allow a relative increase of 0.05% (DSD) to 3.4% (I12) in the phenotypic performances of newborns foals. Dominance deviations represent a relevant genetic phenomenon in the PRE breeding programme. If ignored, they may bias additive variance estimates and lead to an overestimation of expected selection response. Models that include dominance effects could be valuable for designing mating strategies aimed at maximising the overall genetic value and phenotypic performance of newborn foals.
D. Perdomo-González, Mercedes Valera, Antonio Molina et al.· Genetics Selection Evolution· 0 citations
Modern breeding of agricultural animals has transitioned from phenotype-based selection to high-precision genomic prediction based on hundreds of thousands of DNA markers. This has not only accelerated the development of breeds with target traits but also enhanced their adaptability and stress resistance through the design of balanced selection programs. In this context, the present work involved the selection and validation of various DNA markers associated with adaptation potential in rabbits (Oryctolagus cuniculus) and fur-bearing animals (using the sable Martes zibellina as an example). Studies were conducted using PCR and real-time PCR. In the population-genetic study of female sables (n=9, yearlings born in 2023; n=5, two-year-olds born in 2022; n=7, born before 2022), highly polymorphic markers ((ACC)6G, LTR-BERV-K1) were identified, demonstrating high discriminatory power in analyzing differences between animal generations. In the study of feed additive effectiveness in rabbits (n=12, Rodnik cross), reduced expression of metabolic genes g6pd and slc15a1 was observed when using a vitamin-mineral premix during the fattening period. The micronucleus test revealed the potential genome-destabilizing effect of the premix on blood cells, despite the absence of a statistically significant effect on body weight gain. In the behavior genetics study (n=8, rabbits of the Soviet Chinchilla and White Giant breeds), breed and sex differences in the expression of glutamatergic system genes grik3 and gria2 were discovered, opening prospects for selection aimed at reducing aggression in captive animal populations. The proposed approaches create new opportunities for fur farming and rabbit breeding through targeted selection of DNA markers to control genetic variability across generations and the functional activity of key metabolic network components.
A.V. Leonov, T. Glazko, O. Skobel et al.· №4 (2018)· 0 citations
Abstract Cattle breeds exhibit phenotypic and genomic differences shaped by artificial and natural selection. Runs of homozygosity (ROH) analyses detect contiguous homozygous regions on chromosomes that arise as genomic diversity decreases over time. These regions may reflect shared ancestry within a population, selection pressures, or demographic processes. This study aimed to identify ROH profiles, common ROH islands, and their associated genes affected by them in twelve Australian beef cattle breeds (Alexandria, Angus, Brahman, Brangus, Charolais, Droughtmaster, Hereford, Kynuna, Limousin, Santa Gertrudis, Shorthorn, and Speckle Park). The dataset included 463,877 animals from the BREEDPLAN evaluation system, with marker densities ranging from 33K to 100K across breeds. An inverse relationship was observed between effective population size (Ne) and genome-wide ROH profiles, with populations exhibiting smaller Ne values generally accumulating more and longer ROH segments. The Speckle Park showed the highest amount of ROH and small Ne (121), while the Droughtmaster showed the lowest amount of ROH and high Ne (300), indicating their evolutionary backgrounds during the breeding program. Common ROH islands were identified on chromosomes 1, 3, 5, 6, 7, 8, 13, 14, 24, and 26. Common ROH islands on chromosomes 3, 8, and 13 primarily reflected founder contributions from Angus, Brahman, and Shorthorn to their admixed populations. In contrast, common ROH islands on chromosomes 1, 5, 6, 7, 14, 24, and 26 among breeds suggest convergent selection. Identified candidate genes within common ROH islands were enriched in biological processes related to adaptability, reproductive, and production traits, suggesting the effects of artificial and natural selection on economically important traits in Australian beef breeds. These results emphasize the importance of demographic history and selection pressures when interpreting ROH patterns and highlight specific genomic regions that can inform targeted breeding programs, monitor genetic diversity at the genomic segment level, and optimize genotyping array design.
Z. Manzari, N. Connors, J. V. D. van der Werf et al.· Journal of Animal Science· 0 citations
Genomic selection (GS) has transformed modern animal breeding by enabling the prediction of genetic merit using dense genome-wide molecular markers rather than relying solely on pedigree and phenotypic information. Since its conceptual introduction in 2001, GS has become a cornerstone of genetic improvement programs in livestock species, particularly dairy cattle, and has subsequently expanded to beef cattle, sheep, goats, swine, poultry, and aquaculture. The integration of high-density single nucleotide polymorphism (SNP) genotyping with advanced statistical prediction models has substantially increased the accuracy of breeding value estimation, shortened generation intervals, and accelerated rates of genetic gain. Compared with conventional best linear unbiased prediction (BLUP) and marker-assisted selection (MAS), genomic selection captures the combined effects of thousands of loci distributed throughout the genome, making it highly effective for complex quantitative traits governed by many genes of small effect. Recent advances, including single-step genomic BLUP, Bayesian prediction methods, whole-genome sequence analysis, functional genomics, multi-omics integration, artificial intelligence, and precision livestock farming technologies, have further enhanced the scope and efficiency of genomic prediction. These innovations are facilitating simultaneous improvement in productivity, fertility, feed efficiency, disease resistance, animal welfare, and environmental sustainability. Moreover, genomic information is increasingly being integrated with genome editing technologies such as CRISPR to support precision breeding strategies. This review summarizes the historical evolution, fundamental principles, methodological developments, and practical applications of genomic selection in livestock breeding while highlighting emerging innovations and future research directions that are expected to shape next-generation animal improvement programs.
S. Pathak, Amit Kumar, Vaishali Sah· International Journal of Env...· 0 citations