This study aimed to investigate genetic parameters for sow pelvic organ prolapse in purebred and crossbred herds. Pelvic organ prolapse was recorded as normal or prolapsed on the individual sow level across 32 purebred and 8 crossbred farms. In total, 75,162 purebred Landrace sows from a single maternal line were recorded between 2018 and 2023, while 18,988 commercial two-way crossbred (Landrace x Large White) sows were available between 2020 and 2023. There were 5,122,005 animals included in the pedigree. The prolapse in purebreds and crossbreds was considered two different traits in the model. Pedigrees of the crossbred sows were determined based on genotypes through parentage assignment. The average incidence rates were 1.81% and 3.93% for purebreds and crossbreds, respectively. The bivariate model incorporated fixed effects of parity group and region with random effects of contemporary group (farm and mating year and month at the first parity), additive genetic, and residual. Genetic parameter estimates were obtained using BLUPF90+ with the AIREML option. The estimated additive variance was larger in crossbreds than in purebreds. Estimates of heritability in the observed scale were 0.09 (0.006) for purebreds and 0.11 (0.014) for crossbreds, with a genetic correlation of 0.83 using a linear model. Results suggested that including data from crossbreds with higher incidence rate is beneficial and selection to reduce the prolapse incidence in purebred sow herds would also benefit commercial crossbred sow herds.

Morphological scoring is a common evaluation method for domestic animals. The National Association of Maremmano Breeders (ANAM) has provided a dataset containing the records of 600 horses, four metric measurements (cm) and 24 traits with a continuous evaluation scale, each one with 15 classes. Moreover, a body condition score (BCS) with five classes is included. In this study, factor analysis was conducted to create a small number of informative factors (3) obtained from these traits, and a new BLUP-AM-MT index was established. The New Estimated Breeding Value (NEBV1) of each horse was computed by adding the genetic indexes of the three factors, with each one multiplied using a coefficient indicated by ANAM. The practical feasibility of the NEBV1 was evaluated through Spearman correlations between the rankings of the NEBV1 and the rankings of the BLUP-AM-MT, estimated through the four biometric measures and the morphological score (MS) assigned to each horse by the ANAM judges. The factorial analysis was used to estimate three factors: the \"Trunk Dimension\", \"Legs\" and \"Length\". As the explained variance was only 32%, the model was rotated, and the heritability of the three factors were 0.51, 0.05 and 0.41, respectively. After rotation, the estimated correlations between the new NEBV1 and the biometric measures were improved. These results should encourage breeders to adopt a breeding value index that takes into consideration the factors derived from all the variables observed in the morphological evaluation of the Maremmano. In this way, breeders can use it to select the best animals for breeding.

In this study, six different animal models were fitted, and the constrained maximum likelihood method was used to assess the genetic parameters and genetic trends of early growth traits in Luzhong mutton sheep. The experimental data of this study included the newborn weight (BWT, N = 2464), weaning weight (WWT, N = 2923), weight at 6 months of age (6WT, N = 2428), average daily weight gain from birth to weaning (ADG1, N = 2424), and average daily weight gain from weaning to 6 months of age (ADG2, N = 1836) in Luzhong mutton sheep (2015~2019). The best model for the genetic parameters of the five traits in Luzhong mutton sheep was identified as Model 4 using the Akaike information criterion (AIC) and likelihood ratio test (LRT) methods, in which the estimated values of direct heritability for the BWT, WWT, 6WT, ADG1, and ADG2 were 0.156 ± 0.057, 0.547 ± 0.031, 0.653 ± 0.031, 0.531 ± 0.035, and 0.052 ± 0.046, respectively, and the values for maternal heritability were 0.201 ± 0.100, 0.280 ± 0.047, 0.197 ± 0.053, 0.275 ± 0.052, and 0.081 ± 0.092, respectively. The genetic correlation between the ADG2 and WWT was negative, and the genetic and phenotypic correlations among the remaining traits were positive. In this study, maternal effects had a more significant influence on early growth traits in Luzhong mutton sheep. In conclusion, to effectively improve the accuracy of genetic parameter estimation, maternal effects must be fully considered to ensure more accurate and better breeding planning.

Initial findings on genomic selection (GS) indicated substantial improvement for major traits, such as performance, and even successful selection for antagonistic traits. However, recent unofficial reports indicate an increased frequency of deterioration of secondary traits. This phenomenon may arise due to the mismatch between the accelerated selection process and resource allocation. Traits explicitly or implicitly accounted for by a selection index move toward the desired direction, whereas neglected traits change according to the genetic correlations with selected traits. Historically, the first stage of commercial genetic selection focused on production traits. After long-term selection, production traits improved, whereas fitness traits deteriorated, although this deterioration was partially compensated for by constantly improving management. Adding these fitness traits to the breeding objective and the used selection index also helped offset their decline while promoting long-term gains. Subsequently, the trend in observed fitness traits was a combination of a negative response due to genetic antagonism, positive response from inclusion in the selection index, and a positive effect of improving management. Under GS, the genetic trends accelerate, especially for well-recorded higher heritability traits, magnifying the negatively correlated responses for fitness traits. Then, the observed trend for fitness traits can become negative, especially because management modifications do not accelerate under GS. Additional deterioration can occur due to the rapid turnover of GS, as heritabilities for production traits can decline and the genetic antagonism between production and fitness traits can intensify. If the genetic parameters are not updated, the selection index will be inaccurate, and the intended gains will not occur. While the deterioration can accelerate for unrecorded or sparsely recorded fitness traits, GS can lead to an improvement for widely recorded fitness traits. In the context of GS, it is crucial to look for unexpected changes in relevant traits and take rapid steps to prevent further declines, especially in secondary traits. Changes can be anticipated by investigating the temporal dynamics of genetic parameters, especially genetic correlations. However, new methods are needed to estimate genetic parameters for the last generation with large amounts of genomic data.
Initial findings on genomic selection indicated substantial improvement for major traits such as growth or milk yield and even successful selection for secondary traits such as fertility or survival. However, recent unofficial reports indicate an increased frequency of problems in several secondary traits. This study looks at potential sources of those problems and mitigation strategies. Under selection initially carried out for production traits, production improved, but fertility (i.e., a secondary trait) declined, with the decline partially compensated for by improving management. Later, also because the observed deteriorations were becoming too strong, these traits became part of the breeding objectives, and used selection indexes were modified to include secondary traits, halting the deterioration. Under genomic selection, genetic gains accelerate, especially for higher heritability production traits, potentially magnifying the negative responses for secondary traits, and management modifications may not be fast enough to alleviate the decline. The responses can especially decline for unrecorded or sparsely recorded fitness traits. While the decline may be slow and hard to see, it may be serious in the long term and hard to reverse. Changes under genomic selection may be monitored by recalculating genetic parameters every generation. Secondary traits that become more antagonistic with production traits will likely deteriorate more and will need special attention.

Korean native pigs (KNPs) have been one of the traditional livestock primarily raised in rural areas of Korea for centuries. KNPs have adapted to the climate and geography of the Korean Peninsula for a long time, exhibiting excellent adaptability even in challenging environments. For these reasons, the preservation and purification of KNPs are crucial in securing unique genetic resources. Therefore, this review covers the characteristics, production status, commercial value and potential breeding directions of KNPs. Unfortunately, there is still a long way to go for the improvement of KNPs. It is crucial to acknowledge the current challenges, identify the issues, and dedicate efforts to the breed\'s improvement. Each section of this comprehensive review will play an important role in integrating related research and data into the overall findings. In-depth discussions on the genetic diversity, productivity, genetic conservation, ecological roles, and sustainability of KNPs will be crucial components in the future of KNP business.

Limb-conformation defects significantly influence equine performance and welfare, necessitating thorough investigation for effective management. This study examines the prevalence and genetic parameters of 14 limb-conformation defects in Menorca Purebred horses using data from 1120 records (509 animals with an average age of 101.87 ± 1.74 months) collected between 2015 and 2023. Defects were evaluated using a three-class scale by three appraisers, and a Bayesian approach via Gibbs sampling was employed to estimate genetic parameters including gender, birth period, stud selection criteria, evaluation age and appraiser as fixed effects. Splay-footed forelimb and closed hocks were the most prevalent defects (67.20% and 62.53%, respectively). Horses with any of the defects analyzed have been observed to obtain significantly lower scores for both walk and trot. Heritability estimates range from 0.12 (s.d.: 0.025) for closed hock to 0.30 (s.d.: 0.054) for base narrow, confirming the genetic influences on the expression of limb conformation defects. The divergent defect in hind limbs showed the highest genetic correlations with forelimb defects (camped under, -0.69; s.d: 0.32 and camped out, 0.70; s.d: 0.27). The significant genetic correlations between defects highlight the complexity of the relationships, which requires careful consideration.

Qianhua Mutton Merino is a dual-purpose (meat and wool) breed of sheep that has been newly developed in China. In this study, we assessed the growth and development of the Qianhua Mutton Merino sheep breed under house feeding conditions by measuring the body weight and chest circumference of 2300 rams and ewes of this breed aged 0-24 months. Based on the fitting results of three nonlinear growth models, namely Logistic, Gompertz, and von Bertalanffy, in Qianhua Mutton Merino, we selected the von Bertalanffy model because of its highest fitting degree among all models (R2 > 0.977). The significant analysis of the combined fixation of each sheep body\'s weight and bust took place (A: mature body weight, B: adjustment parameter, K: instant relative growth rate). The results revealed that parameters A, B, and K of body weight and chest circumference have high heritability and thus could be used as target traits for genetic improvement. Moreover, the correlation strength among A, B, and K suggested that these parameters can be used as a reference to adjust the genetic parameters in the growth model to genetically improve the body size of Qianhua Mutton Merino during breeding.

Beef × dairy crossbred cattle (n = 615) were used to evaluate the effect of preharvest indicator traits and genotypes on the accuracy of estimated breeding values (EBVs) of seedstock candidates for selection. Genotypes for 100,000 single nucleotide polymorphisms were provided by the American Simmental Association of purebred and crossbred seedstock animals (n = 2,632). Five hundred and ninety-five of the 615 beef × dairy cattle had carcass camera and ultrasound data. Phenotypes were not used for any of the seedstock animals even though some may have had performance and ultrasound data. We estimated the genomic relationship matrix among 3,247 animals including both phenotyped and unphenotyped animals. We computed genetic parameters among 37 traits using 666 bivariate restricted maximum likelihood analyses. The accuracy of EBV depends on heritability. For the sake of brevity, we report accuracy for marbling as a proxy for other traits with similar heritability. We focus on accuracy for marbling because marbling is the primary determinant of carcass value. We computed EBV for all 3,247 animals for marbling based on camera data postharvest using best linear unbiased prediction. We report evidence of overlap in causative genes among postharvest carcass traits; marbling, ribeye area, yield grade, fat thickness, and hot carcass weight (HCW) based on genetic correlations. Genetic correlations range from -0.73 to 0.89. Several live animal traits (frame size, body weight and ultrasound fat thickness and ribeye area) were genetically correlated with postharvest traits; including HCW, ribeye area, yield grade, fat thickness, and marbling. Genetic correlations between pre- and postharvest traits ranged from -0.53 to 0.95. Accuracy for marbling ranged from 0.64 to 0.80 for animals with marbling recorded, and from 0.09 to 0.60 for animals without marbling recorded. The accuracy of animals without phenotypes was related to the genomic relationship between animals with phenotype and those without. Live animal traits were useful for predicting economically important carcass traits based on genetic correlations. The accuracy of EBV for seedstock animals that were not phenotyped was low, but this is consistent with theory, and accuracy is expected to increase with the addition of genotypes and carcass data from beef × dairy animals.
Low-cost genotyping platforms and sexed-semen have enabled the production of high breeding value dairy replacement heifers from a fraction of the herd representing the most elite cows. The remainder of the cow herd can be bred to beef bulls using male-sexed-semen. Camera carcass data postharvest and ultrasound carcass estimates preharvest (live animals) on beef × dairy animals combined with genotypes and ultrasound on seedstock animals may provide an efficient scheme for selecting beef bulls to mate to dairy cows in the future to maximize carcass value of the progeny. Genotypes are needed to link carcass data from previously harvested to seedstock bull selection candidates because pedigree is typically not available for beef × dairy cattle. We report that live animal ultrasound carcass estimates are predictive of postharvest economically important carcass traits. The accuracy of genetic evaluation of selection candidates without recorded carcass traits was low but is expected to increase with more genotypes and phenotypes on beef × dairy cattle. Genotypes, ultrasound estimates, and camera carcass data on thousands of beef × dairy cattle could enable increased accuracy of selection with periodic infusion of new phenotypes from future generations.

The present study was aimed at evaluating the genetic variation and population structure in a collection of 22 rice genotypes. Twenty-two rice genotypes were assessed using quantitative traits and SSR molecular markers for genetic variability and genetic diversity. As for genetic diversity, the genotypes were clarified based on twelve quantitative traits. Clustering produced two large groups: the IR70423-169-2-2 variety was in a branch alone due to its long duration, while, the second group included all rest of genotypes and was split up into two sub-groups. The first sub-group included IR67418-131-2-3-3-3, IR67420-206-3-1-3-3, Giza181, Giza182, Sakha104, and P1044-86-5-3-3-2M. However, pedigree played in divided clustering with Giza181 and Giza182, which were belonging to the Indica type and produced from the same parents. SSR markers produced 87 alleles, with a mean of 4.3 alleles per locus, which were detected in 22 rice genotypes. A higher number of alleles were found with primers RM262, RM244, RM3843, RM212, and RM3330. With an overall mean of 0.837, the polymorphic information content values were high for all SSR markers, ranging from a low of 0.397 for M254 to a high of 0.837 for RM244. The dendogram was divided into six groups according to the types of genotypes, with the pedigree playing a major role for the genetic distance. In order to help breeders choose parents and create suitable hybrids to achieve genetic improvement in crops, particularly rice, SSR is a useful technique for analysing genotype diversity and aiding in the genetic fingerprinting of each variety.

BACKGROUND: Early selection in tree breeding could be achieved by addressing the longevity of tree improvement activities. Genetic parameter changes and age-age correlations are essential for determining the optimal timing of early selection. Practical tracking of genetic parameters of Pinus koraiensis, a major timber species with economic and ecological value, has become feasible as its progeny testing has entered the mid-term age in Korea. However, research on the age-age correlation of P. koraiensis as progeny trials approach rotation age is limited. This study aimed to investigate genetic parameter trends and age-age correlations in P. koraiensis progeny. P. koraiensis progeny were assessed at two sites using a linear mixed-effects model with two-dimensional spatial autoregressive structure. Height, diameter, and volume growth were measured in 11 assessments over 40 years.
RESULTS: Genetic parameters, such as height and diameter, showed different patterns of change. The heritability ranged for the three growth traits in 0.083-0.710, 0.288-0.781, and 0.299-0.755 across the sites and age. Height heritability and its coefficient of variance decreased, whereas the diameter and volume estimates remained relatively constant. Correlations with Age 40 for phenotypic, genetic, and rank of breeding values ranged between 0.16 and 0.92, 0.594 and 0.988, and 0.412 and 0.965, respectively. These correlations generally increased as the age approached Age 40, with particularly high levels observed at Age 26 and Age 30.
CONCLUSIONS: The observed genetic trends in P. koraiensis progeny testing offer valuable insights for early and precise selection. Notably, selecting superior genotypes at Ages 26-30 is supported by discernible genetic gains and robust correlations. Future research should integrate unbalanced data for selecting mother trees or families and conduct a comprehensive economic analysis of early selection to validate its practical benefits.