Breeding Values Research Articles

Comparison of genomic prediction methods for early growth traits of Inner Mongolia cashmere goats based on multi trait models.

Inner Mongolia cashmere goat is an excellent livestock breed formed through long-term natural selection and artificial breeding, and is currently a world-class dual-purpose breed producing cashmere and meat. Multi trait animal model is considered to significantly improve the accuracy of genetic evaluation in livestock and poultry, enabling indirect selection between traits. In this study, the pedigree, genotype, environment, and phenotypic records of early growth traits of Inner Mongolia cashmere goats were used to build multi trait animal model., Then three methods including ABLUP, GBLUP, and ssGBLUP wereused to estimate the genetic parameters and genomic breeding values of early growth traits (birth weight, weaning weight, average daily weight gain before weaning, and yearling weight). The accuracy and reliability of genomic estimated breeding value are further evaluated using the five fold cross validation method. The results showed that the heritability of birth weight estimated by three methods was 0.13-0.15, the heritability of weaning weight was 0.13-0.20, heritability of daily weight gain before weaning was 0.11-0.14, and the heritability of yearling weight was 0.09-0.14, all of which belonged to moderate to low heritability. There is a strong positive genetic correlation between weaning weight and daily weight gain before weaning, daily weight gain before weaning and yearling weight, with correlation coefficients of 0.77-0.79 and 0.56-0.67, respectively. The same pattern was found in phenotype correlation among traits. The accuracy of the estimated breeding values by ABLUP, GBLUP, and ssGBLUP methods for birth weight is 0.5047, 0.6694, and 0.7156, respectively; the weaning weight is 0.6207, 0.6456, and 0.7254, respectively; the daily weight gain before weaning was 0.6110, 0.6855, and 0.7357 respectively; and the yearling weight was 0.6209, 0.7155, and 0.7756, respectively. In summary, the early growth traits of Inner Mongolia cashmere goats belong to moderate to low heritability, and the speed of genetic improvement is relatively slow. The genetic improvement of other growth traits can be achieved through the selection of weaning weight. The ssGBLUP method has the highest accuracy and reliability in estimating genomic breeding value of early growth traits in Inner Mongolia cashmere goats, and is significantly higher than that from ABLUP method, indicating that it is the best method for genomic breeding of early growth weight in Inner Mongolia cashmere goats.

Implementing multi-trait genomic selection to improve grain milling quality in oats (Avena sativa L.).

Oats (Avena sativa L.) provide unique nutritional benefits and contribute to sustainable agricultural systems. Breeding high-value oat varieties that meet milling industry standards is crucial for satisfying the demand for oat-based food products. Test weight, thins, and groat percentage are primary traits that define oat milling quality and the final price of food-grade oats. Conventional selection for milling quality is costly and burdensome. Multi-trait genomic selection (MTGS) combines information from genome-wide markers and secondary traits genetically correlated with primary traits to predict breeding values of primary traits on candidate breeding lines. MTGS can improve prediction accuracy and significantly accelerate the rate of genetic gain. In this study, we evaluated different MTGS models that used morphometric grain traits to improve prediction accuracy for primary grain quality traits within the constraints of a breeding program. We evaluated 558 breeding lines from the University of Illinois Oat Breeding Program across 2 years for primary milling traits, test weight, thins, and groat percentage, and secondary grain morphometric traits derived from kernel and groat images. Kernel morphometric traits were genetically correlated with test weight and thins percentage but were uncorrelated with groat percentage. For test weight and thins percentage, the MTGS model that included the kernel morphometric traits in both training and candidate sets outperformed single-trait models by 52% and 59%, respectively. In contrast, MTGS models for groat percentage were not significantly better than the single-trait model. We found that incorporating kernel morphometric traits can improve the genomic selection for test weight and thins percentage.

Accuracy of genomic prediction using multiple Atlantic salmon populations

BackgroundThe accuracy of genomic prediction is partly determined by the size of the reference population. In Atlantic salmon breeding programs, four parallel populations often exist, thus offering the opportunity to increase the size of the reference set by combining these populations. By allowing a reduction in the number of records per population, multi-population prediction can potentially reduce cost and welfare issues related to the recording of traits, particularly for diseases. In this study, we evaluated the accuracy of multi- and across-population prediction of breeding values for resistance to amoebic gill disease (AGD) using all single nucleotide polymorphisms (SNPs) on a 55K chip or a selected subset of SNPs based on the signs of allele substitution effect estimates across populations, using both linear and nonlinear genomic prediction (GP) models in Atlantic salmon populations. In addition, we investigated genetic distance, genetic correlation estimated based on genomic relationships, and persistency of linkage disequilibrium (LD) phase across these populations.ResultsThe genetic distance between populations ranged from 0.03 to 0.07, while the genetic correlation ranged from 0.19 to 0.99. Nonetheless, compared to within-population prediction, there was limited or no impact of combining populations for multi-population prediction across the various models used or when using the selected subset of SNPs. The estimates of across-population prediction accuracy were low and to some extent proportional to the genetic correlation estimates. The persistency of LD phase between adjacent markers across populations using all SNP data ranged from 0.51 to 0.65, indicating that LD is poorly conserved across the studied populations.ConclusionsOur results show that a high genetic correlation and a high genetic relationship between populations do not guarantee a higher prediction accuracy from multi-population genomic prediction in Atlantic salmon.

Residual network improves the prediction accuracy of genomic selection.

Genetic improvement of complex traits in animal and plant breeding depends on the efficient and accurate estimation of breeding values. Deep learning methods have been shown to be not superior over traditional genomic selection (GS) methods, partially due to the degradation problem (i.e. with the increase of the model depth, the performance of the deeper model deteriorates). Since the deep learning method residual network (ResNet) is designed to solve gradient degradation, we examined its performance and factors related to its prediction accuracy in GS. Here we compared the prediction accuracy of conventional genomic best linear unbiased prediction, Bayesian methods (BayesA, BayesB, BayesC, and Bayesian Lasso), and two deep learning methods, convolutional neural network and ResNet, on three datasets (wheat, simulated and real pig data). ResNet outperformed other methods in both Pearson's correlation coefficient (PCC) and mean squared error (MSE) on the wheat and simulated data. For the pig backfat depth trait, ResNet still had the lowest MSE, whereas Bayesian Lasso had the highest PCC. We further clustered the pig data into four groups and, on one separated group, ResNet had the highest prediction accuracy (both PCC and MSE). Transfer learning was adopted and capable of enhancing the performance of both convolutional neural network and ResNet. Taken together, our findings indicate that ResNet could improve GS prediction accuracy, affected potentially by factors such as the genetic architecture of complex traits, data volume, and heterogeneity.

Estimation of the soybean varieties of the world collection according to the trait ‘seed weight per plant’ in the conditions of the central Non-blackearth region

The purpose of the current study was to estimate the potential of soybean varieties of various ecological and geographical groups according to the trait ‘seed weight per plant’ and to identify varieties with high adaptability to the conditions of the Ryazan region. The objects of research were 33 soybean samples from the world collection, which differed in morphological and biological characteristics. The soybean variety ‘Sibiriada’ (Russia), zoned for the Central region, was taken as the standard variety. Field trials were carried out on dark gray forest soil at the Institute of Seed production and Agrotechnologies, branch of the Federal Budgetary Scientific Institution “FRAEC VIM”, located in the Ryazan region in 2021–2023. In order to characterize the adaptability parameters, there have been used such indicators as homeostatic index (Hom), coefficient of variation (CV), stability factor (SF); range of the indicator ‘seed weight per plant’ (d), standard deviation (σ); adaptability coefficient (AC); stability level indicator (SLI) and stress resistance (Ymin–Ymax), calculated using appropriate methods. There has been established that according to the trait ‘seed weight per plant’ the varieties ‘Georgiya’, ‘Snezhana’ and ‘Chera 1’ (Russia) had the lowest value of variation with Cv,%≤20.0. It was found that the varieties ‘Georgiya’ and ‘Snezhana’ (Russia) were the most stable to external environmental changes. This was evidenced by the lowest values of the coefficient of variation (Cv = 12.9 and Cv = 14.0 %, respectively) and high homeostaticity (Hom = 31.3 and Hom =28.9). The greatest variability and low homeostaticity were found in the soybean varieties ‘Vereteyka’ (Hom = 1.69, Cv = 58.4 %) and ‘Elena’ (Hom = 2.17, Cv = 50.3 %), which characterized the low adaptability of these varieties to the conditions of the Ryazan region. As a result of the estimation of the genotypes studied in the trial according to the triat ‘seed weight per plant’, it was established that the varieties ‘Georgia’ (Russia), ‘Snezhana’ (Russia), ‘Chera 1’ (Russia), ‘Garmoniya’ (Russia) were of great breeding value for improving adaptability and stability in the forest-steppe agroclimatic zone of the Ryazan region.

Sexual dimorphism in the environmental sensitivity of weaning weight in beef cattle

This study investigates the environmental sensitivity and sexual dimorphism in the genetic parameters of weaning weight (WW) in Nelore beef cattle. Five reaction norms models were employed to analyze the 148,131 WW records, considering different definitions of the environmental descriptor (ED). (Co)variance components and genetic parameters were separately estimated for males and females. Results reveal substantial sexual dimorphism in various parameters. Significant divergence across sexes was observed for environmental sensitivity, with males showing an increased response to favorable environments while females genetically responded better to more challenging environments. Including sex in defining the ED can inflate the estimated breeding values of sires with a higher number of male progeny records, highlighting the importance of choosing a reliable ED in analyses of traits influenced by sexual dimorphism and genotype-by-environment interaction (G × E). The observed sexual dimorphism and environmental sensitivity underscore the complexity of genetic evaluation of WW in beef cattle populations, with implications for selection strategies. The findings suggest that a sex-separated trait analysis considering G × E effects is most appropriate for genetic evaluations of WW. However, a simpler single-trait model excluding sex from the ED definition yielded a higher coincidence of selected sires with the sex-separated analysis. In conclusion, understanding sexual dimorphism and environmental sensitivity is crucial for genetic evaluations and selection decisions in beef cattle breeding programs, emphasizing the need for careful model selection and ED definition.

Эффективность определения племенной ценности быков-производителей в зависимости от метода оценки

The purpose of the study is to determine the effectiveness of various methods for assessing the bree-ding value of bulls in the dairy cattle population of the Omsk Region. Objectives: to compare the effectiveness of assessing the breeding value of stud bulls using the “assessment by quality of offspring” and BLUP methods; to determine the correlation between the breeding value of bulls and the level of productivity of offspring. The object of the study was 67 bulls who were the fathers of 926 cows that completed their first lactation. The breeding value assessment using the Daughters-Peers method was carried out for 15 stud bulls. Of the bulls assessed using the Daughters-Peers method, 9 bulls were improvers, which is 60 % of all animals tested using this method. Using the BLUP method, from all bulls, positive breeding value was identified in 12 bulls, which is 17.9 % of the total number of bulls. When assessed by the Daughters-Peers method, the maximum number of bulls (33.33 %) have a breeding value for milk yield of 301–450 kg. The results of the BLUP assessment showed that 4 bulls, or 33.33 %, had a breeding value of less than 150 kg. The share of bulls with a breeding value of more than 451 kg is 25 %. The probability of error when selecting bulls with the best breeding value in terms of milk production is higher when it is determined by the Daughters-Peers method by 34 % compared to the BLUP method. When selecting bulls based on milk fat content, the assessment of breeding value using the BLUP method is more effective. The accuracy of the method is 47.7 % higher than when assessing breeding value using the Daughters-Peers method. Assessment using the BLUP method objectively and relatively accurately makes it possible to determine the genetic potential of animal productivity and optimally use them in breeding work.

Plateau-linear reaction norm model analysis of number born alive in purebred Landrace pigs using meteorological data in Japan.

We performed a plateau-linear reaction norm model (RNM) analysis of number born alive (NBA) in purebred Landrace pigs, where breeding value changes according to maximum temperature at mating day, using public meteorological observation data in Japan. We analysed 52,668 NBA records obtained from 10,320 Landrace sows. Pedigree data contained 99,201 animals. Off-farm daily temperature data at the nearest weather station from each of the farms were downloaded from the Japan Meteorological Agency website. A plateau-linear RNM analysis based on daily maximum temperature on mating day (threshold temperature of 16.6°C) was performed. The percentage of the records with daily maximum temperatures at mating days of ≤16.6, ≥25.0, ≥30.0 and ≥35.0°C were 34.3%, 33.6%, 14.0% and 0.8%, respectively. The value of Akaike's information criterion for the plateau-linear RNM was lower than that for a simple repeatability model (RM). With the plateau-linear RNM, estimated value of heritability ranged from 0.14 to 0.15, while that from the RM analysis was 0.15. Additive genetic correlation between intercept and slope terms was estimated to be -0.52 from the plateau-linear RNM analysis. Estimated additive genetic correlations were >0.9 between NBA at different temperatures ranging from 16.6 to 37.6°C. For the 10,320 sows, average values of prediction reliability of the intercept and slope terms for breeding values in the plateau-linear RNM were 0.47 and 0.16, respectively. Increasing weight for slope term in linear selection index could bring positive genetic gain in the slope part, but prediction accuracy would decrease. Our results imply that genetically improving heat tolerance in sows reared in Japan focusing on NBA using RNM is possible, while RNM is more complex to implement and interpret. Therefore, further study should be encouraged to make genetic improvement for heat tolerance in sows more efficient.

Genomic regions, candidate genes, and pleiotropic variants associated with physiological and anatomical indicators of heat stress response in lactating sows

BackgroundHeat stress (HS) poses significant threats to the sustainability of livestock production. Genetically improving heat tolerance could enhance animal welfare and minimize production losses during HS events. Measuring phenotypic indicators of HS response and understanding their genetic background are crucial steps to optimize breeding schemes for improved climatic resilience. The identification of genomic regions and candidate genes influencing the traits of interest, including variants with pleiotropic effects, enables the refinement of genotyping panels used to perform genomic prediction of breeding values and contributes to unraveling the biological mechanisms influencing heat stress response. Therefore, the main objectives of this study were to identify genomic regions, candidate genes, and potential pleiotropic variants significantly associated with indicators of HS response in lactating sows using imputed whole-genome sequence (WGS) data. Phenotypic records for 18 traits and genomic information from 1,645 lactating sows were available for the study. The genotypes from the PorcineSNP50K panel containing 50,703 single nucleotide polymorphisms (SNPs) were imputed to WGS and after quality control, 1,622 animals and 7,065,922 SNPs were included in the analyses.ResultsA total of 1,388 unique SNPs located on sixteen chromosomes were found to be associated with 11 traits. Twenty gene ontology terms and 11 biological pathways were shown to be associated with variability in ear skin temperature, shoulder skin temperature, rump skin temperature, tail skin temperature, respiration rate, panting score, vaginal temperature automatically measured every 10 min, vaginal temperature measured at 0800 h, hair density score, body condition score, and ear area. Seven, five, six, two, seven, 15, and 14 genes with potential pleiotropic effects were identified for indicators of skin temperature, vaginal temperature, animal temperature, respiration rate, thermoregulatory traits, anatomical traits, and all traits, respectively.ConclusionsPhysiological and anatomical indicators of HS response in lactating sows are heritable but highly polygenic. The candidate genes found are associated with important gene ontology terms and biological pathways related to heat shock protein activities, immune response, and cellular oxidative stress. Many of the candidate genes with pleiotropic effects are involved in catalytic activities to reduce cell damage from oxidative stress and cellular mechanisms related to immune response.

Assessing selection potential for Pacific oyster (Crassostrea gigas) to a North American OsHV-1 μvar: Comparing two experimental assay methods

Ostreid Herpesvirus - 1 is a global threat to Pacific oyster aquaculture as catastrophic farm losses have occurred where OsHV-1 microvariants (μvars) become endemic. Genetic selection has proven effective for increasing survival to OsHV-1 exposure in multiple Pacific oyster breeding programs, but a novel μvar detected in San Diego Bay California has the potential to severely impact commercial aquaculture along the North American Pacific coast as no OsHV-1 μvar selected population is available commercially. Using a Molluscan Broodstock Program population descending from imports originating in the Miyagi prefecture (Japan), we evaluated the potential for genetic selection to improve survival against the San Diego Bay OsHV-1 μvar using a laboratory trial. Two experimental methods were evaluated, a common garden method where all 15 full-sibling families were pooled, and a petri dish method, where each family was confounded within replicate. No striking differences were found between experimental methods, and both experiments displayed high heritability (0.69 and 0.64) of the tested trait, a broad range of estimated breeding values, and a moderate prediction accuracy for the survival trait. A significant genotype-by-environment interaction occurred, highlighting variability in laboratory-based disease challenges, but the two experiments yielded similar results with minor to moderate re-ranking of mean family survival. Overall, the Miyagi population of Pacific oysters curated by the Molluscan Broodstock Program is a promising population to use for artificial selection to increase survival against San Diego Bay OsHV-1 μvar in attempts to obviate farm losses if the virus expands its currently isolated range.

Genomic prediction model optimization for growth traits of olive flounder (Paralichthys olivaceus)

Genomic prediction (GP) has emerged an effective tool for addressing the many shortcomings of traditional selective breeding, thereby enhancing the selection process. In this study, we optimized GP methods using 5-fold cross-validation to estimate genome-estimated breeding values for the weight traits of olive flounder (Paralichthys olivaceus). To accomplish our goal, we determined the parentage of the target broodstock and the ability of 11 prediction models to predict the weight traits of 1.8-year-old olive flounders, which were genotyped using a 70 K single nucleotide polymorphism (SNP) array. Moreover, our optimization efforts toward the predictive ability of genomic best linear unbiased prediction (GBLUP), Bayesian B (BB), and random forest (RF) methods encompassed changes in various aspects such as fixed effects, SNP quantity, population size, and phenotypic data collected at different fish ages. Additionally, we assessed the predictive ability for the total length and body depth of fish using GBLUP, BB, and RF. Among the 11 prediction methods used in this study, the BB (0.675), Elastic Net (0.679), and RF (0.698) methods exhibited the highest predictive abilities, whereas the GBLUP (0.637) method demonstrated the lowest. Incorporating information regarding fish sex as a fixed effect substantially improved the predictive ability of GBLUP and BB. For mean models, utilizing 3000–5000 random SNP markers resulted in a higher predictive ability, similar to that obtained using 50,000 SNPs. Increasing the population size reduced the standard deviation of the predictive ability. Notably, phenotypic records from 1.8-year-old fish exhibited a significantly higher predictive ability than those from the other age groups. Furthermore, GBLUP, BB, and RF provided higher predictive abilities for length (0.655–0.852) and body depth (0.665–0.861). These findings may significantly shape future olive flounder genomic selection programs and offer valuable insights into GP in aquaculture.

Validation of genomic tools to improve production efficiency, health resilience and the carbon footprint of beef production

Genomic tools and accuracy of molecular breeding values (MBVs) for economically important traits continue to improve and are being applied in commercial crossbred beef cattle. Ge­nomic breed composition and retained heterozygosity of an individual animal can be used to further improve female fertil­ity, stayability, lifetime productivity and calf health resilience. But this is just the first step. Within specific crossbred popula­tions, researchers at Livestock Gentec have used large numbers of cattle phenotypes and genotypes, combined with advanced statistical genomic analyses to generate MBVs for 18 traits with moderate to moderately-high accuracy (0.35 to 0.60). This accu­racy is equivalent to 10 to 20 progeny records. These MBVs are economically balanced into multi-trait profit indices such as the Replacement Heifer Profit Index Score and the Feeder Profit In­dex. The use of these genomic tools will improve the sustainabil­ity of beef production by improving profitability, lowering the carbon footprint, and improving an animal’s ability to adapt to changing environments. The following paper outlines the valida­tion of these genomic tools and their potential benefits.

Ontogeny of immunity and natural viral infection in Apis mellifera drones and workers

The most common viral diseases affecting honey bees (Apis mellifera) in Israel include deformed wing viruses (DWV-A and DWV-B) and acute paralysis viruses (ABPV and IAPV). These viruses are transmitted within and between colonies, both horizontally and vertically. All members of the colony contribute to this transmission, on the other hand individual and social immunity, particularly hygienic behaviour, may affect the outcome of the process. In this study, we evaluated the ontogeny of natural infections of DWV-A, DWV-B, ABPV and IAPV, their prevalence and loads, in workers and drones from high (H) and low (L) hygienic colonies. In parallel, we evaluated the expression of two immune genes: peptidoglycan recognition protein S2(PGRP-S2) and hymenoptaecin. The prevalence of DWV-B and IAPV increased with age and was higher in workers than in drones. ABPV was not detected in drones. The expression of both immune genes was significantly affected by age and sex. Drones from H colonies had higher expression of these genes. The increased expression of immune genes with drones’ age, particularly in hygienic colonies, suggest additional value of honey bee breeding for hygienic behaviour for sustainable beekeeping.

Stacked mutations in wheat homologues of rice SEMI-DWARF1 confer a novel semi-dwarf phenotype

BackgroundSemi-dwarfing alleles are used widely in cereals to confer improved lodging resistance and assimilate partitioning. The most widely deployed semi-dwarfing alleles in rice and barley encode the gibberellin (GA)-biosynthetic enzyme GA 20-OXIDASE2 (GA20OX2). The hexaploid wheat genome carries three homoeologous copies of GA20OX2, and because of functional redundancy, loss-of-function alleles of a single homoeologue would not be selected in wheat breeding programmes.Instead, approximately 70% of wheat cultivars carry gain-of-function mutations in REDUCED HEIGHT 1 (RHT1) genes that encode negative growth regulators and are degraded in response to GA. Semi-dwarf Rht-B1b or Rht-D1b alleles encode proteins that are insensitive to GA-mediated degradation. However, because RHT1 is expressed ubiquitously these alleles have pleiotropic effects that confer undesirable traits in some environments.ResultsWe have applied reverse genetics to combine loss-of-function alleles in all three homoeologues of wheat GA20OX2 and its paralogue GA20OX1 and evaluated their performance in three years of field trials. ga20ox1 mutants exhibited a mild height reduction (approximately 3%) suggesting GA20OX1 plays a minor role in stem elongation in wheat. ga20ox2 mutants have reduced GA1 content and are 12–32% shorter than their wild-type segregants, comparable to the effect of the Rht-D1b ‘Green Revolution’ allele. The ga20ox2 mutants showed no significant negative effects on yield components in the spring wheat variety ‘Cadenza’.ConclusionsOur study demonstrates that chemical mutagenesis can expand genetic variation in polyploid crops to uncover novel alleles despite the difficulty in identifying appropriate mutations for some target genes and the negative effects of background mutations. Field experiments demonstrate that mutations in GA20OX2 reduce height in wheat, but it will be necessary to evaluate the effect of these alleles in different genetic backgrounds and environments to determine their value in wheat breeding as alternative semi-dwarfing alleles.

Radiological measurements of the feet of normal Straight Egyptian Arabian horses in Qatar

The Arabian horse has been identified as carrying a risk locus for equine metabolic syndrome, predisposing this breed to development of laminitis. Radigraphy of the equine foot is widely considered the main diagnostic imaging technique for evaluation of the laminitic horse. Knowledge of ‘normal’ breed values allows assessment of the degree and severity of radiological changes associated with laminitis. The objective of this study was to investigate the normal values for radiological measurements of the feet of the Straight Egyptian Arabian horse in Qatar. The design was a clinical prospective study. Radiographs of the fore and hind feet of 10 clinically normal adult Straight Egyptian Arabian horses were taken. On the lateromedial views, 17 measurements were taken (13 distances and four angles). On the horizontal dorsopalmar/plantar views, two measurements were taken. On the dorsal 45 degree, proximo-palmarodistal oblique projections, four measurements were taken. Normal reference ranges were reported for radiological measurements of the feet of the Straight Egyptian Arabian horse. Several variables showed significant differences between fore and hind feet, including hoof angle, distal wall thickness, and two proximal inner layer measurements (p < 0.05). In addition, the Straight Egyptian Arabian horse was found to have a number of measurements which varied from previously published reports. The results reported within provide a useful reference for normal radiographic measurements of the Straight Egyptian Arabian horse with relevance for laminitis.

30 Effects of using different dietary standardized ileal digestible lysine plans on growth performance and carcass characteristics of grow-finish pigs from high or low breeding value boars

Abstract The present study aimed to evaluate the impact of using different dietary standardized ileal digestible (SID) lysine (Lys) plans on growth performance and carcass characteristics of grow-finish pigs coming from high or low breeding value boars. A total of 2,080 pigs (PIC 800 × PIC Camborough) were housed in 20 mixed sex pens (26 pigs/pen), blocked by body weight (BW), and randomly allotted in a 2 × 2 factorial arrangement with boar breeding value (high or low) and nutrition Lys plan (current SID Lys curve recommendation for PIC 800 as % of PIC 337 SID Lys curve or alternative SID Lys curve). Pigs were weaned at 21 d of age (6.1 ± 0.05 kg BW) and followed during the wean-to-finish period until reach the market slaughter weight. Pigs were fed either the current recommendation or an alternative SID Lys curve for PIC 800, in a 6 phase feeding program: phase 1 (6-11 kg; 100 vs 100%, respectively); phase 2 (11-23 kg; 97 vs 100%, respectively); phase 3 (23-45 kg; 97 vs 100%, respectively); phase 4 (45-73 kg; 97 vs 95%, respectively); phase 5 (73-102 kg; 97 vs 95%, respectively); and phase 6 (102-132 kg; 97 vs 90%, respectively). Pigs were fed isoenergetic diets. Performance and carcass traits, and removals and mortality were recorded. Data were analyzed using mixed models in R, and considering pen as the experimental unit for performance traits and individual carcasses for carcass traits. There was no evidence of interaction between boar breeding value and nutrition plan factors. Overall, high breeding value pigs had greater average daily gain (ADG; 0.84 ± 0.005 g/d) compared with low breeding value pigs (0.82 ± 0.005 kg/d; P &amp;lt; 0.01), which was driven by increased average daily feed intake (ADFI; 1.92 ± 0.011 and 1.89 ± 0.011 kg/d, respectively; P &amp;lt; 0.05; Table 1). Moreover, high breeding value pigs had greater hot carcass weight (HCW; 97.8 ± 1.09 kg), carcass yield (74.1 ± 0.23%), backfat thickness (16.3 ± 0.29 mm) and lower lean meat % (57.0 ± 0.21%) compared with low breeding value pigs (96.0 ± 1.09 kg; 73.7 ± 0.23 %; 15.4 ± 0.28; 57.5 ± 0.21%, respectively; P &amp;lt; 0.05; Table 1). Regarding nutrition plan, no significant differences were observed for overall performance traits between pigs fed the current or alternative SID Lys curve (P &amp;gt; 0.05; Table 1). Nevertheless, pigs fed the alternative SID Lys curve had heavier HCW (97.3 ± 1.09 kg) compared with pigs fed the current SID Lys curve (96.6±1.09 kg; P &amp;lt; 0.05; Table 1). No significant differences were observed for overall removals and mortality by breeding value or nutrition Lys plan (P &amp;gt; 0.05). In summary, grow finish pigs from high breeding value boars have an improved productive performance. PIC 800 pigs may achieve the same productive performance with lower lysine levels at the end of the grow-finish period.

98 Adding parasite resistance to the breeding objective in hair sheep

Abstract Economic selection indexes provide the best method to achieve genetic gain for multiple traits simultaneously. Hair sheep enterprises, particularly in environments with substantial gastrointestinal nematode challenge, may benefit from incorporating parasite resistance in a selection index. However, obtaining the relative economic value (REV) for parasite resistance is challenging; information on its impact on productivity is incomplete, as are the costs of treatment given anthelmintic resistance. The National Sheep Improvement Program (NSIP) currently provides producers with an index designed to increase total weight of lamb weaned per ewe lambing (TW). Our objective was to assess the effects of including fecal egg count, an indicator of parasite resistance, as an additional goal trait. Including the benchmark scenario with TW as its sole objective, 10 indexes were constructed using standard index theory. Post-weaning fecal egg count (PFEC) was added to this breeding objective with a REV of -1 and the REV for TW was varied from +1 to +5 at +0.5 increments. Weaning weight, number of lambs born and weaned, and PFEC were the selection criteria, modelled as either phenotypes or estimated breeding values (EBV). Phenotypes and EBV were simulated for 1,000 lambs by Cholesky decomposition and used to generate index scores. Ten replicates were run and the top 3% of males and 26% of females were retained on index scores. Annual responses in the goal traits were estimated. Responses in PFEC were expressed as a percentage, assuming a mean PFEC of 2,089 eggs/g as in NSIP. Concordances with those selected in the benchmark scenario were determined. Using EBV as selection criteria, TW increased by 1.7 kg/yr in the benchmark scenario (Table 1). However, unfavorably, PFEC increased by 2.3%/yr. When phenotypic criteria were used, TW increased by 0.5 kg/yr, and PFEC by 0.3%/yr. Once added to the breeding objective, PFEC decreased regardless of the REV of TW. However, response in TW also reduced, although less so as its REV increased. With EBV as the criteria, the REV of +3 for TW appeared preferable: PFEC reduced by 7.1%/yr with 98% of the response in TW retained. With phenotypic selection criteria, PFEC reduced by 5.2%/yr with 94% of the response in TW retained. With +3 REV for TW and EBV as the selection criteria, on average 65% and 82% of males and females, respectively, were chosen in common with the benchmark. When phenotypic criteria were used, those percentages were 60% and 80%, respectively. Implementing a more holistic index with REV of +3 for TW and -1 for PFEC would result in reasonable responses in both traits. However, producers will need to decide if reduced gains in TW is acceptable to improve parasite resistance in a hair sheep breeding program.

225 Genomic diversity of Katahdin sheep and impacts on genomic prediction

Abstract In the late 1950s, Katahdin hair sheep were developed as a composite breed of medium size and moderate prolificacy, with potential to express resistance to gastrointestinal nematodes. With its increasing popularity and the recent adoption of genomic prediction in the Katahdin breeding program, evaluating the genetic diversity in this breed is necessary. Prediction accuracies rely on the strength of genetic relationships. That strength often increases with selection using genomically-enhanced estimated breeding values; however, it carries the risk of decreasing diversity. We aim to characterize the genetic diversity present in the breed and the subsequent impact on the accuracies of genomic predictions. Genotypes on Katahdin sheep from member flocks in the National Sheep Improvement Program were used. Data from two medium density 50k bead chips and one high density 600k bead chip were merged and limited to shared autosomal single nucleotide polymorphisms (SNP). After quality control, there were 9,705 animals and 31,984 SNP remaining. Only for analyses of inbreeding and heterozygosity, linkage disequilibrium (LD) pruning was performed; variants with an LD score exceeding 0.8 were removed with 29,904 SNP remaining. To determine the extent of population structure, principal component (PC) analysis was conducted with PC one and PC two explaining 4.9% and 3.8% of the variation in the population, respectively. When examining subpopulations, a single ancestral population explained 99.9% of the genetic variation among animals. When clustered by identity-by-state, all animals were placed in a single cluster. Inbreeding coefficients were estimated with four methods: method of moments, variance-standardized relationship minus one, excess homozygosity, and correlation between uniting gametes. Across methods, average inbreeding coefficients ranged from 1.14% to 1.20% with Pearson and Spearman correlations ranging from -0.51 to 0.91 (Table 1). Historical effective population sizes (Ne) were estimated for earlier generations, and a linear regression fit to predict more recent Ne. At the founding of the breed, historical Ne was estimated to be 310, and the current Ne was estimated to be 150. Effects of Ne on the accuracy of genomic predictions were examined for reference population sizes ranging from 1k to 25k for traits of low (0.1), moderate (0.3), and high (0.5) heritabilities. The corresponding number of effective chromosomal segments were 2NeL, where L was the length of the genome in morgans (26M). Accuracies of genomic predictions increased as the reference population size grew, with only marginal gains once the population exceeded 15k. Overall, there were no detectable genetic subpopulations in the Katahdin breed. Current levels of inbreeding were low. With a small Ne the breed can achieve high accuracy for genomic predictions by aiming for a reference population of 15k animals. Negative impacts on genetic diversity due to genomic selection are not of immediate concern.

Breeding value of potato hybrid clones from the VIR collection revealed in the environments of Kamchatka Territory

Background. Potato breeding involves planned artificial hybridization between previously selected parental lines. A way to make potato breeding more efficient is to use the diversity of the germplasm and broaden the gene pool of parental lines. Interspecific potato hybrids originated on the elite potato germplasm display a set of valuable traits. The current challenge is to assess the performance of potato hybrids under specific soil and climate conditions to clarify their breeding value.The objective of the study was to evaluate potato hybrids in the environments of Kamchatka Territory according to a set of traits, identify the best parental lines, develop new hybrid combinations, and select promising breeding material.Materials and methods. Eleven potato hybrids from VIR were studied over three years (2020–2022) in the fields of Kamchatka Research Institute of Agriculture. The hybrids were benchmarked against two reference potato cultivars, ‘Fresco’ and ‘Vulkan’, belonging to the early and mid-early maturity groups, respectively. Crosses between the hybrids and 28 potato cultivars were carried out in the greenhouse. The new hybrid material was tested in a preliminary trial nursery for yield and earliness.Results. Hybrid 117-2 was better in yield (899 g/plant) than cvs. ‘Vulkan’ and ‘Fresco’ (700–739 g/plant). Hybrids 94-5, 99-10- 1, 8-1-2004, 8-3-2004, 8-5-2004, 135-3-2005, 135-5-2005, 99-6-6, and 134-2-2006 in most traits matched the potato cultivars, manifesting good berry formation and seed setting when crossed. Out of 140 crosses between 11 hybrids and 28 cultivars, 35 crosses between 10 hybrids and 13 cultivars were successful. Most hybrids were effectively used in crossings as maternal forms.Conclusion. VIR’s hybrids 94-5, 8-1-2004, and 8-5-2004 proved the most promising as source material for the development of new early potatoes under the conditions of Kamchatka Territory.

Accounting for nuclear and mito genome in dairy cattle breeding - a simulation study

Mitochondria play a significant role in numerous cellular processes through proteins encoded by both the nuclear genome (nDNA) and mito genome (mDNA), and increasing evidence shows that traits of interest might be affected by mito-nuclear interactions. While the variation in nDNA is influenced by mutations and recombination of parental genomes, the variation in mDNA is solely driven by mutations. In addition, mDNA is inherited in a haploid form, from the dam. Cattle populations show significant variation in mDNA between and within breeds. Past research suggests that variation in mDNA accounts for 1–5% of the phenotypic variation in dairy traits. Here we simulated a dairy cattle breeding program to assess the impact of accounting for mDNA variation in pedigree-based and genome-based genetic evaluations on the accuracy of estimated breeding values for mDNA and nDNA components. We also examined the impact of alternative definitions of breeding values on genetic gain, including nDNA and mDNA components that both impact phenotype expression, but mDNA is inherited only maternally. We found that accounting for mDNA variation increased accuracy between +0.01 and +0.03 for different categories of animals, especially for young bulls (+0.03) and females without genotype data (between +0.01 and +0.03). Different scenarios of modeling and breeding value definition impacted genetic gain. The standard approach of ignoring mDNA variation achieved competitive genetic gain. Modeling, but not selecting on mDNA expectedly reduced genetic gain, while optimal use of mDNA variation recovered the genetic gain.