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Simple Summary: By analyzing the genome of Hungarian Holstein Friesian cows, we looked for genomic regions which have an effect on the milk, fat, and protein yield. Among the sampled animals and the investigated nucleotides, nine were simultaneously associated with milk, fat, and protein yield. Among the nine variants, two had opposite effects; for example, while increasing the value of milk yield, the other one or two parameters' values decreased. The acquired knowledge can help in the planning of breeding schemes to avoid unwanted interactions among the abovementioned yield parameters. This study aimed to find SNPs that have an effect on the estimated breeding values (EBVs) of milk (MY), fat (FY), and protein yield (PY) of Holstein Friesian cows in Hungary. Holstein Friesian cows (n = 2963) were genotyped on a Eurogenomics (EuroG_MDv4) chip. The EBVs for MY, FY, and PY were obtained from the Association of Hungarian Holstein Breeders (AHHB). The loci associated with the EBVs were identified via three approaches: the calculation of genetic distance of the SNPs (Fst_marker), linear regression, and haplotype association tests. Nine SNPs were significantly associated with MY, FY, and PY located on BTA 2, 5, 28, and X. Among the nine SNPs identified, BTB-00219372 on BTA 5 had a positive β coefficient for MY and a negative β coefficient for FY and PY. In addition, BovineHD3000027615 on BTA X had a positive β coefficient for both MY and PY, as well as a negative β coefficient for FY. The identified SNPs were located near several genes that remain unstudied in cattle, which are potential targets for closer scrutiny in relation to milk properties. The markers associated with two or three EBVs could be used in selection with high efficiency to accelerate genetic development and help AHHB experts achieve their breeding. Most marker effects point in the same direction on EBVs; however, we found that BTB-00219372 and BovineHD3000027615 could be used with caution to increase one EBV while decreasing the other EBV or EBVs. [ABSTRACT FROM AUTHOR]

Pedigrees used in genetic evaluations contain errors. Because of such errors, assumptions regarding the relatedness among individuals in genetic evaluation models are wrong. Consequences of that have been investigated in earlier studies focusing on models that did not account for genomic information yet. The objective of this work was to investigate the effects of pedigree errors on the results from genetic evaluations using the single-step model, and the effect of such effects on results from validation studies with forward prediction. We used a real pedigree (n = 361,980) and real genotypes (n = 25,950) of Fleckvieh cattle, sampled in a way to provide a good consistency between pedigree and genomic relationships. Given the real pedigree and genotypes, true breeding values (TBV) were simulated to have a covariance structure equal to the matrix H assumed in a single-step model. Based on TBV, phenotypes were simulated with a heritability of 0.25. Genetic evaluations were conducted with a conventional animal model (i.e., without genomic information) and a single-step animal model under scenarios using either the correct pedigree or a pedigree containing 5%, 10%, or 20% of wrong records. Wrong records were simulated by randomly assigning wrong sires to nongenotyped females. The increasing rates of pedigree errors led to decreasing correlations between TBV and EBV and lower standard deviations of predictions. Less variation was observed because pedigree errors operate actually as a random exchange of daughters among bulls, making them look more similar to each other than they actually are. This occurs of course only when animals have progeny. Therefore, this decreased variation was more pronounced for progeny tested bulls than for young selection candidates. In a forward prediction validation scenario, the stronger decrease in variation when animals get progeny caused an apparent inflation of early predictions. This phenomenon may contribute to the usually observed problem of inflation of early predictions observed in validation studies. [ABSTRACT FROM AUTHOR]

The objectives of this study were to evaluate the influence of inbreeding on growth traits and body measurements, as well as on the estimation of genetic parameters and genetic trends in Guzerá cattle. Phenotypic records of 4,212 animals selected for postweaning weight from Guzerá Breeding Program of Advanced Beef Cattle Research Center were utilized. The pedigree file contained records from 7,213 animals born from 1928 to 2019. The traits analyzed were: birth weight (BW), weights adjusted to 210, 378 and 550 days of age (W210, W378 and W550, respectively), chest girth at 378 and 550 days of age (CG378 and CG550), scrotal circumference (SC), and hip height at 378 and 550 days of age (HH378 and H550). Linear regression was used to evaluate the effects of inbreeding on traits. Genetic parameters were obtained using models including or not the effect of inbreeding as a covariate. Inbreeding had negative effects (P ≤ 0.01) on BW (-0.09 kg), W378 (-2.86 kg), W550 (-2.95 kg), HH378 (-0.10 cm), and H550 (-0.29 cm). The lowest and highest heritability estimates were obtained for W210 (0.21 ± 0.07) and HH550 (0.57 ± 0.06), respectively. The genetic correlations were strong and positive between all traits, ranging from 0.44 ± 0.08 (SC x HH) to 0.99 ± 0.01 (W378 x W550). Spearman correlations between EBVs obtained with or without inbreeding effect ranged from 0.968 to 0.995 (P < 0.01). The results indicate loss of productive performance in inbred animals. However, the inclusion of inbreeding coefficient in genetic evaluation models did not alter the magnitude of genetic parameters or genetic trends for the traits studied. [ABSTRACT FROM AUTHOR]

A comprehensive study on maize flowering traits, focusing on the regulation of flowering time and the elucidation of molecular mechanisms underlying the genes controlling flowering, holds the potential to significantly enhance our understanding of the associated regulatory gene network. In this study, three tropical maize inbreds, CML384, CML171, and CML444, were used, along with a temperate maize variety, Shen137, as parental lines to cross with Ye107. The resulting F1s underwent seven consecutive generations of self-pollination through the single-seed descent (SSD) method to develop a multiparent population. To investigate the regulation of maize flowering time-related traits and to identify loci and candidate genes, a genome-wide association study (GWAS) was conducted. GWAS analysis identified 556 SNPs and 12 candidate genes that were significantly associated with flowering time-related traits. Additionally, an analysis of the effect of the estimated breeding values of the subpopulations on flowering time was conducted to further validate the findings of the present study. Collectively, this study offers valuable insights into novel candidate genes, contributing to an improved understanding of maize flowering time-related traits. This information holds practical significance for future maize breeding programs aimed at developing high-yielding hybrids. [ABSTRACT FROM AUTHOR]

The aims of this investigation were to compare the accuracy and bias of prediction of Estimated Breeding Values (EBV) for Average Daily Gain (ADG) at 2-4 weeks old by employing pedigree-based BLUP and single-step Genomic BLUP (ssGBLUP) techniques. Additionally, the study aimed to identify the optimal minor allele frequencies (MAF) threshold for pre-selecting SNPs for genetic prediction. The present investigation utilized a total of 488 F2 broiler chickens, which were derived from the crossbreeding of fastgrowing Arian chickens and slow-growing native chickens from Urmia, Iran. These chickens were between 2-4 weeks old at the time of the study. Samples were genotyped using the Illumina 60K chicken Beadchip. In order to examine the impact of MAF on prediction accuracy, a total of 48,379 quality-controlled SNPs were categorized into five subgroups based on their MAF values: 0.05-0.1, 0.1-0.2, 0.2-0.3, 0.3-0.4, and 0.4-0.5. The findings substantiated the dominance of ssGBLUP over conventional BLUP techniques. The average accuracy of GP improved by 1.96, 3.87, and 2.12% using ssGBLUP compared to BLUP method for ADG at 2-4 weeks of age, respectively. Using a specific MAF bin and a subset of SNPs based on age group significantly enhanced the accuracy of genomic prediction for ADG traits. Current results highlighted that the pre-selection of SNPs based on allele frequency may provide a reasonable compromise between accuracy of results, number of independent variables to be considered and computing requirements. [ABSTRACT FROM AUTHOR]

For many years, pig production has focused on maximizing performance by selecting for maximal muscle growth and feeding diets that allow the animals to express their genetic potential. However, it is unclear whether this selection for muscle deposition has affected the capacity of pigs to cope with by-product-based diets, which rely on fat as the primary energy source instead of starches and sugars. Therefore, an experiment was set up to investigate if different types of boars affect how their progeny cope with alternative ingredients in the diet, with a possible need for adapted breeding schemes. Two types of boars within the Piétrain sire line were used based on either a high or low estimated breeding value for daily feed intake (HFI: high feed intake, low feed intake). When their progeny reached 14 weeks of age, two dietary strategies were compared: a control (CON) vs a by-product-based diet high in fat and fiber (HFF). The CON diet was mainly based on cereals (corn, wheat, barley) and soybean meal. The HFF diet was formulated to contain the same net energy, CP and digestible amino acid levels without any cereals or soybean meal. In total 192 animals were included in the experiment (48 animals/type of boar/diet) and performance, digestibility, carcass and meat quality were compared. None of the parameters showed a significant interaction (P

Simple Summary: Progressive ataxia is an autosomal recessive defect that is lethal due to the irreversible changes it causes to the brain and spinal cord. Only homozygous carriers of the mutated KIF1C allele manifest progressing clinical signs, mostly no earlier than 12–24 months of age. The objectives of this field study were to determine the prevalence of the mutated KIF1C allele, uncover its associations with growth and muscle conformation, and build awareness of this lethal condition among beef cattle breeders in Germany. A total of 1315 samples was sent in for mutation testing. Prevalence of the mutated KIF1C allele was 11.75%, resulting from 293 heterozygous and 8 homozygous mutant animals. Homozygous carriers of the mutated KIF1C allele showed a significant superiority in estimated breeding values for daily weight gain and muscle conformation. In order to reduce the frequency of the mutated KIF1C allele, genetic testing should be introduced for Charolais cattle and should be mandatory for all Charolais breeding bulls. It is important to create awareness of this condition among beef cattle breeders, in addition to the possibilities of preventing the number of affected animals. In addition, genetic testing of eight further beef, dual-purpose, or dairy cattle breeds revealed that two German Angus cattle showed heterozygous mutations for the KIF1C A-allele; therefore, we recommend genetic testing of German Angus to prevent the spread of the KIF1C allele. Bovine progressive ataxia in Charolais cattle was first described in the 1970s; then, cases were reported in Charolais worldwide. A homozygous loss-of-function mutation within the KIF1C gene (c.608G>A) was found to be responsible for this neurodegenerative disease. The aim of this study was to determine whether the mutated KIF1C allele segregates in the German Charolais population and whether the estimated breeding values for growth and muscle conformation are associated with the mutated genotypes. Genetic test results of the KIF1C:c.608G>A variant were available for 1315 Charolais cattle from 35 herds located in Germany. In addition, 324 samples from eight other beef cattle breeds were tested for the mutated KIF1C allele. We were able to demonstrate that the KIF1C mutation is common, with a frequency of 11.75% in the German Charolais population. All but two of the eight (2/8 = 25%) homozygous mutated individuals showed clinical signs consistent with progressive ataxia. The estimated breeding values of muscle conformation in 200- and 365-day-old animals indicated a significant superiority for homozygous mutated animals when compared either with heterozygous or homozygous wild-type genotypes; this was also the case for heterozygous genotypes in comparison with homozygous wild-type genotypes. For the estimated breeding values of daily weight gain in 200- and 365-day-old animals, the significant differences between homozygous mutated and heterozygous or wild-type genotypes were in favour of the homozygous mutant animals. There were no differences in the estimated maternal breeding values among all three KIF1C genotypes. For the first time, two German Angus cattle carrying the KIF1C mutation heterozygous were detected. The breeders' survey highlighted that increased awareness would facilitate increased conviction among breeders of the need for genetic testing in order to eliminate the lethal KIF1C allele. [ABSTRACT FROM AUTHOR]

Canine hip dysplasia (CHD) is a progressive and disabling disorder in large dog breeds, such as the German Shepherd dog. Breeding sires and dams free of dysplasia is the only way to reduce its incidence. Several diagnostic methods have been developed based on radiographic examination, on the basis of which dogs are selected for breeding. CHD has a polygenic hereditary basis and environmental influence, with a median to low heritability (ca. 0,20 to 0,40), so the progress in phenotypic selection has been slow. In Argentina, the prevalence of dysplasia in German Shepherd dogs remains high (> 25%) and it is impossible to predict its incidence in the offspring of the breeding stock. Some countries have implemented a selection based on the estimated breeding value, obtaining an important advance. Genome-wide association studies have revealed numerous CHD-associated markers and several candidate genes have been found that point to the possibility of implementing genomic selection in the near future.

Selection for milk production later in lactation (changing the shape of the lactation curve) also may provide an opportunity to increase milk production during a time in an animal's life when energy allocation is possible. Keywords: Genetic Selection; Estimated Breeding Value; Milk Composition EN Genetic Selection Estimated Breeding Value Milk Composition 55 63 9 06/20/23 20230601 NES 230601 Implications Genetic selection to increase milk yield has been very successful. Milk production of domesticated dairy cows can reach 30-50 L per day or 6,000 to 12,000 Lover a lactation compared to 8-10 L per day and <1,000 L over lactation in feral cows ([85]). Milk production in cows follow a dynamic curve starting with an initial rapid increase in milk yield in early lactation (approx. 0-45 days-in-milk, [DIM]), followed by a peak (approx. 46-55 DIM), and then a slow decline in milk yield during late lactation (approx. 56-340 DIM) ([76]). Flow of data between different components of a national milk recording system, including DNA and test-day milk samples collected on farms, milk composition information produced by milk testing laboratories, standardized records computed by dairy records processing centers, and breeding values calculated by the genetic evaluation center. [Extracted from the article]

Growth traits of calves, which are quantitative characteristics determining cattle business profitability, vary according to genetic and environmental factors. In other words, growth traits depend on the genetics of the individual and vary with farm management. The aim of this study was to investigate the effective environmental factors, genetic parameters, and genetic trends for some growth traits and the Kleiber ratio (KR) in Holstein-Friesian calves. For this purpose, the records of 724 calves, progeny of 566 dams and 29 sires, reared between 2017 and 2019 on a private dairy farm in Türkiye, were used. MTDFREML software was utilized to estimate genetic parameters and genetic trends of growth traits and KR. In this study, regarding weight, the mean of birth weight (BW), 60-day weight (W60), and 90-day weight (W90) were 39.76 ± 6.15 kg, 69.23 ± 10.93 kg, and 95.76 ± 16.48 kg, respectively. Concerning weight gain, 1–60 daily weight gain (DWG1-60), 60–90 daily weight gain (DWG60-90), and 1–90 daily weight gain (DWG1-90) were 0.49 ± 0.16 kg, 0.91 ± 0.34 kg, and 0.63 ± 0.17 kg, respectively. With respect to KR, 1–60 daily KR (KR1-60), 60–90 daily KR (KR60-90), and 1–90 daily KR (KR1-90) were 2.03 ± 0.48, 2.93 ± 0.89, and 2.02 ± 0.34, respectively. As a result of the GLM analysis, only the effect of the birth season on all traits was significant (p < 0.05 or p < 0.01). In addition, it was detected that sex had a significant effect on BW and W60 (p < 0.05 or p < 0.01). For all traits, only the effect of parity on KR1-60 was not significant. In REML analysis, direct heritability differed between 0.26 ± 0.16 and 0.81 ± 0.27 obtained at DWG1-90 and DWG1-60, respectively. Also, the highest repeatability (0.100) was obtained in DWG1-60. It was detected that mass selection could be used in all traits for breeding program. In BLUP analysis, the current population had an increasing trend for BW and W90 and a decreasing trend for W60. However, there was no significant change in other weight gain traits and KR over the years. Calves with high breeding values for BW, W60, W90, DWG1-60, DWG60-90, and DWG1-90 should be chosen for selection programs. But for KR1-60, KR60-90, and KR1-90, calves with low breeding values should be selected for efficiency. Also, KR evaluated would contribute to the literature and other research should be studied regarding KR. [ABSTRACT FROM AUTHOR]

Litter size is a reproductive trait of economic importance in small ruminants. This study was carried out to investigate litter size (LS) as a selection criterion in Merino rams using Estimated Breeding Value (EBV). Hence, the heritability (h2) value was estimated with paternal halfshib correlation model through analysis of variance (ANOVA) method. A total of 650 records of LS were used in this study, representing in the progeny of fourteen (14) rams collected from year 1999 to 2004 at Cimanglid Research Park, Bogor, Indonesia. This study showed that the average of LS in sheep samples was 1.34±0.51 with h2 value of 0.04±0.06 (low). However, six Merino rams (43%) had positive of EBV value. Moreover, the data records of LS from each observed ram were sufficient for evaluation and signed by a moderate relative accuracy (RA) value ranged from 0.27 to 0.71. It can be concluded that selection of Merino rams can be performed based on LS using EBV. [ABSTRACT FROM AUTHOR]

A comprehensive study on maize flowering traits, focusing on the regulation of flowering time and the elucidation of molecular mechanisms underlying the genes controlling flowering, holds the potential to significantly enhance our understanding of the associated regulatory gene network. In this study, three tropical maize inbreds, CML384, CML171, and CML444, were used, along with a temperate maize variety, Shen137, as parental lines to cross with Ye107. The resulting F1s underwent seven consecutive generations of self-pollination through the single-seed descent (SSD) method to develop a multiparent population. To investigate the regulation of maize flowering time-related traits and to identify loci and candidate genes, a genome-wide association study (GWAS) was conducted. GWAS analysis identified 556 SNPs and 12 candidate genes that were significantly associated with flowering time-related traits. Additionally, an analysis of the effect of the estimated breeding values of the subpopulations on flowering time was conducted to further validate the findings of the present study. Collectively, this study offers valuable insights into novel candidate genes, contributing to an improved understanding of maize flowering time-related traits. This information holds practical significance for future maize breeding programs aimed at developing high-yielding hybrids.

【Objective】Four genetic parameters including days to 100 kg (DAYS_100), average daily gain (ADG_100), loin muscle area (LMA_100) and average back fat thickness (BFT_100) at 100 kg body weight in a Landrace pig population were estimated, and the correlations between traits as well as genetic and phenotypic progress of the four traits were analyzed, which could provide a basis for the genetic improvement of the target population.【Method】Records of growth traits of Landrace pigs were collected in a core breeding pig farm in Guangxi from 2002 to 2020. A fixed effect analysis on the factors affecting the growth traits of Landrace pigs was conducted by R software. In addition, the genetic parameters of the four traits were estimated with DMU software and a multi-trait animal model. Furthermore, the genetic correlations and phenotypic correlations between these traits, genetic progress and phenotypic progress were evaluated.【Result】The estimated heritability for the four growth traits of Landrace pigs, including DAYS_100, ADG_100, LMA_100 and BFT_100 were 0.399, 0.391, 0.433 and 0.421, respectively, and all of them had medium to high heritability. Both genetic correlation and phenotypic correlation between DAYS_100 and ADG_100 were significantly negative, with correlation coefficient -0.997 and -0.992, respectively. In general, the phenotypic trend of DAYS_100 was rising while the phenotypic trends of ADG_100, LMA_100 and BFT_100 were declining; the genetic trends of ADG_100 and BFT_100 showed an overall upward trend while the trends of DAYS_100 and LMA_100 were generally downward.【Conclusion】The four growth traits of Landrace pigs are medium-high heritability traits, therefore, their genetic progress can be accelerated through direct selection. There is a strong correlation between DAYS_100 and ADG_100. The management of phenotypic measurement of pig farms and the selection of target traits for pig population breeding have an important impact on the performance of growth traits. In addition, the improvements in farm production management and changes in breed structure may influence genetic progress.

Accuracy of predicted breeding values (PBV) for low heritability traits may be increased in early generations by exploiting the information available in correlated traits. We compared the accuracy of PBV for 10 correlated traits with low to medium narrow-sense heritability ( h 2) in a genetically diverse field pea (Pisum sativum L.) population after univariate or multivariate linear mixed model (MLMM) analysis with pedigree information. In the contra-season, we crossed and selfed S1 parent plants, and in the main season we evaluated spaced plants of S0 cross progeny and S2+ (S2 or higher) self progeny of parent plants for the 10 traits. Stem strength traits included stem buckling (SB) ( h 2 = 0.05), compressed stem thickness (CST) ( h 2 = 0.12), internode length (IL) ( h 2 = 0.61) and angle of the main stem above horizontal at first flower (EAngle) ( h 2 = 0.46). Significant genetic correlations of the additive effects occurred between SB and CST (0.61), IL and EAngle (−0.90) and IL and CST (−0.36). The average accuracy of PBVs in S0 progeny increased from 0.799 to 0.841 and in S2+ progeny increased from 0.835 to 0.875 in univariate vs MLMM, respectively. An optimized mating design was constructed with optimal contribution selection based on an index of PBV for the 10 traits, and predicted genetic gain in the next cycle ranged from 1.4% (SB), 5.0% (CST), 10.5% (EAngle) and −10.5% (IL), with low achieved parental coancestry of 0.12. MLMM improved the potential genetic gain in annual cycles of early generation selection in field pea by increasing the accuracy of PBV. [ABSTRACT FROM AUTHOR]

This study aims to estimate variance components, heritability, and repeatability of lactation yield (270 day), as well as estimated breeding value for 879 water buffalo lactation records for 615 animals belonging to the water buffalo breeding project using BUGA software. The model was constructed by using all available the pedigree information. Herd, season and year were used as fixed effects while lactation length and age were used as covariate. Random environment variance, genotypic variance and permanent environment variance values were estimated as 48388.61±0.0003 kg2, 12003.08±0.0003 kg2 and 9567.92±0.0003 kg2 while heritability (h2) and repeatability (r) of lactation yield were estimated as 0.17 ±0.162 and 0.30, respectively. The study concluded that the heritability of milk yield was low and in order to achieve more effective genetic improvement, the project should be organized in a way that allows for the identification of sire records for the animals involved. In addition, the environmental conditions in which buffalos are raised must be brought closer to the conditions required by the animals. [ABSTRACT FROM AUTHOR]

Simple Summary: Native chickens are vitally important livestock at the community level and represent food security and a source of savings, especially in developing countries where they are considered a valuable genetic resource for use in the development of high-yielding breeds. However, due to the constraints of their slow growth rate, there is an inadequate supply to meet consumer demand. Therefore, genetic improvement for growth traits is one sustainable way to solve these problems. In this study, a multiple trait animal model and selection index are developed as a solution for this problem to improve growth performance in smallholder farms. To ensure that any new technology developed within an experimental station is appropriate to the community's needs and compatible with the existing systems, on-site farm research is an important component in examining the effectiveness of agricultural research. The present study examined the growth performance and genetics of Thai native chickens under conditions typically experienced by farmers on smallholder farms (on-site farms) compared with at an experimental unit (on-station). There were 1694 Thai native chickens (Pradu Hang dum) used in this experiment, and they were divided into 613 chickens for the on-station and 1081 chickens for the on-site farm experiments. The individual chicken data included the birth weight (BW0) and body weight at 4, 8, 12, and 16 weeks of age (BW4, BW8, BW12, and BW16, respectively), ADG from 0–4, 4–8, 8–12, 12–16 weeks of age (ADG0–4, ADG4–8, ADG8–12, ADG12–16, respectively), and breast circumference at 8, 12, and 16 weeks of age (BrC8, BrC12, BrC16, respectively). A multiple traits animal model and a selection index were used to estimate the variance components, genetic parameters, and breeding values of growth traits. The results showed that the body weight, average daily gain, and breast circumference at 8, 12, and 16 weeks of age of Thai native chickens raised on-station were higher than those raised on-site at the farm among mixed-sex and sex-segregated chickens, while the birth weight and body weight at four weeks of age (BW0 and BW4) and ADG from 0–4 weeks of age (ADG0–4) were not significantly different (p > 0.05). The heritability estimates of body weight, average daily gain, and breast circumference in the chickens raised at the on-site farm and on-station were moderate to high, with on-station values slightly higher than on-site farm values. The heritability estimates of body weight were 0.236 to 0.499 for the on-site farm, and 0.291 to 0.499 for on-station. For average daily gain, the heritability estimates were 0.274 to 0.283 for the on-site farm and 0.298 to 0.313 for on-station; meanwhile, and for breast circumference, the heritability estimates were 0.204 to 0.268 for the on-site farm and 0.278 to 0.296 for on-station. Both phenotypic and genetic correlations among and between growth traits were positive and ranged from low to high values. The top 20% of the estimated breeding values and selection indices in the on-site farm and on-station experiments showed that the body weight at eight weeks of age (BW8), ADG from 4–8 weeks of age (ADG4–8), and breast circumference at eight weeks of age (BrC8) should be used as selection criteria for Thai native chicken breeding programs. In conclusion, the genetic parameters and breeding values in on-station experiments showed that the breeding program by selection index for improving growth performance is valid. Therefore, to implement such a breeding program in an on-site farm, an intensive or semi-intensive farm system should be considered to minimize the effect of genotype-environment interaction. [ABSTRACT FROM AUTHOR]

Simple Summary: In the Republic of Serbia, pig selection in recent decades has been based on genetic improvement of growth and carcass quality traits. Genetic improvement of reproductive traits of pigs was based on the so-called phenotypic selection. The introduction of modern information systems and the availability larger dataset have opened the possibility to perform genetic estimation of reproductive traits within the main breeding programme of the Republic of Serbia. Using the methods of gene flow and connectedness evaluation, our study investigated the possibility of improving the reliability of estimating the breeding value of reproductive traits in highly productive sows. We believe that these methods could lead to a systematic improvement of the genetic value of reproductive traits in sows. Thus far, none of the methods for estimating the degree of connectedness between herds in pigs has been used in the preparation of the National Breeding Programme of the Republic of Serbia. This study investigated the influence of the degree of connectedness on the reliability of the estimated breeding values (EBVs). The focal trait in the study was the number of piglets born alive (NBA) from sows of the highly prolific Large White and Landrace sows. An analysis included total of 58,043 farrowing's during the 2008–2020 period. BLUP procedure was used to estimate the breeding values for NBA for the three herds separately and after merging all three herds into one herd. The model for EBV estimation included the following fixed factors: parity, genotype, seasons, litter sire, herds, sow age at farrowing, weaning-conception interval, length of previous lactation, and the following random effects: common litter environment, permanent litter environment, and direct additive genetic effect of animal. Heritability values for NBA ranged from 0.048 to 0.097, depending on the data included in the analysis. The connectedness between herds was analysed using the connectedness rating (CR) and the gene flow (GF) methods. CR among the observed herds ranged from 0.245 to 0.994%, depending on the data included. The exchange of genetic material between all three herds was determined using GF method. The high degree of connectedness determined by the CR and GF method had a strong effect on EBV reliability. The average EBV reliability ranged from 0.520 to 0.867, depending on the data included. The increase in average reliability was observed in both cases when the data were added, both in the analysis of average reliability for purebred animals and when crossbreeds were added, where an increase in this value was also observed. The increase in average EBV reliability is a consequence of the greater amount of information included in the joint evaluation. In conclusion, we believe that our research will improve EBV reliability and help in further selection work in the Republic of Serbia. [ABSTRACT FROM AUTHOR]

Objective This study was conducted to estimate effect of single nucleotide polymorphisms (SNP) on the estimated breeding value of Hungarian Grey (HG) bulls and to find markers associated with horn colour. Methods Genotypes 136 HG animals were determined on Geneseek high-density Bovine SNP 150K BeadChip. A multi-locus mixed-model was applied for statistical analyses. Results Six SNPs were identified to be associated (−log10P>10) with green and white horn. These loci are located on chromosome 1, 3, 9, 18, and 25. Seven loci (on chromosome 1, 3, 6, 9, 10, 28) showed considerable association (−log10P>10) with the estimated breeding value. Conclusion Analysis provides markers for further research of horn colour and supplies markers to achieve more effective selection work regarding estimated breeding value of HG.

This study was conducted to construct basic data for the selection of elite cows by analyzing the estimated breeding value (EBV) and accuracy using the pedigree of Hanwoo cows in Gyeongnam. The phenotype trait used in the analysis are the carcass weight (CWT), eye muscle area (EMA), backfat thickness (BFT) and marbling score (MS). The pedigree of the test group and reference group was collected to build a pedigree structure and a numeric relationship matrix (NRM). The EBV, genetic parameters and accuracy were estimated by applying NRM to the best linear unbiased prediction (BLUP) multiple-trait animal model of the BLUPF90 program. Looking at the pedigree structure of the test group, there were a total of 2,371 cows born between 2003 to 2009, of these 603 cows had basic registration (25%), 562 cows had pedigree registration (24%) and 1,206 cows had advanced registration (51%). The proportion of pedigree registered cows was relatively low but it gradually increased and reached a point of 20,847 cows (68%) between 2010 to 2017. Looking at the change in the EBV, the CWT improved from 4.992 kg to 9.885 kg, the EMA from 0.970 cm2 to 2.466 cm2, the BFT from −0.186 mm to −0.357 mm, and the MS from 0.328 to 0.559 points. As a result of genetic parameter estimation, the heritability of CWT, EMA, BFT, and MS were 0.587, 0.416, 0.476, and 0.571, respectively, and the accuracy of those were estimated to be 0.559, 0.551, 0.554, and 0.558, respectively. Selection of superior genetic breed and efficient improvement could be possible if cow ability verification is implemented by using the accurate pedigree of each individual in the farms.

Genetic evaluations in beef cattle have evolved over the past 50 years relative to the hardware or software used, the statistical methodology underpinning them, and the traits evaluated. However, the underlying premise has remained the same; to generate predictions of genetic merit such that selection decisions can be made that materialize as phenotypic changes in commercial animals. The wide-spread availability and adoption of genomic technology has enabled more accurate genetic predictions of young animals albeit with the requirement of continual collection and reporting of phenotypic data., Competing Interests: Disclosure The authors have no conflict of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

To ensure that any new technology developed within an experimental station is appropriate to the community’s needs and compatible with the existing systems, on-site farm research is an important component in examining the effectiveness of agricultural research. The present study examined the growth performance and genetics of Thai native chickens under conditions typically experienced by farmers on smallholder farms (on-site farms) compared with at an experimental unit (on-station). There were 1694 Thai native chickens (Pradu Hang dum) used in this experiment, and they were divided into 613 chickens for the on-station and 1081 chickens for the on-site farm experiments. The individual chicken data included the birth weight (BW0) and body weight at 4, 8, 12, and 16 weeks of age (BW4, BW8, BW12, and BW16, respectively), ADG from 0–4, 4–8, 8–12, 12–16 weeks of age (ADG0–4, ADG4–8, ADG8–12, ADG12–16, respectively), and breast circumference at 8, 12, and 16 weeks of age (BrC8, BrC12, BrC16, respectively). A multiple traits animal model and a selection index were used to estimate the variance components, genetic parameters, and breeding values of growth traits. The results showed that the body weight, average daily gain, and breast circumference at 8, 12, and 16 weeks of age of Thai native chickens raised on-station were higher than those raised on-site at the farm among mixed-sex and sex-segregated chickens, while the birth weight and body weight at four weeks of age (BW0 and BW4) and ADG from 0–4 weeks of age (ADG0–4) were not significantly different (p > 0.05). The heritability estimates of body weight, average daily gain, and breast circumference in the chickens raised at the on-site farm and on-station were moderate to high, with on-station values slightly higher than on-site farm values. The heritability estimates of body weight were 0.236 to 0.499 for the on-site farm, and 0.291 to 0.499 for on-station. For average daily gain, the heritability estimates were 0.274 to 0.283 for the on-site farm and 0.298 to 0.313 for on-station; meanwhile, and for breast circumference, the heritability estimates were 0.204 to 0.268 for the on-site farm and 0.278 to 0.296 for on-station. Both phenotypic and genetic correlations among and between growth traits were positive and ranged from low to high values. The top 20% of the estimated breeding values and selection indices in the on-site farm and on-station experiments showed that the body weight at eight weeks of age (BW8), ADG from 4–8 weeks of age (ADG4–8), and breast circumference at eight weeks of age (BrC8) should be used as selection criteria for Thai native chicken breeding programs. In conclusion, the genetic parameters and breeding values in on-station experiments showed that the breeding program by selection index for improving growth performance is valid. Therefore, to implement such a breeding program in an on-site farm, an intensive or semi-intensive farm system should be considered to minimize the effect of genotype-environment interaction.

Infection by gastrointestinal nematodes (GIN), particularly Haemonchus contortus , can be detrimental to sheep health and performance. Genetic susceptibility to GIN varies between breeds, with those lacking high levels of natural resistance often requiring frequent anthelmintic treatment when facing parasitic challenge. Genetic technology can serve as a tool to decrease GIN susceptibility via selection for sheep with reduced fecal egg count (FEC) estimated breeding values (EBVs). However, the physiological changes that result from implementation of this strategy are not well described. Additionally, there is a need for comparison of animals from recent selective breeding against breeds with inherent GIN resistance. In this study we administered a challenge of H. contortus to Dorper x White Dorper (DWD; n = 92) lambs that have been genetically selected for either low (DWD-) or high (DWD+) FEC EBVs and Barbados Blackbelly x Mouflon (BBM; n = 19) lambs from a genetically resistant breed backgrounds. Lamb FEC, packed-cell volume (PCV) and serum IgG were measured at intermittent levels over 5 weeks. At day 21 and day 35, the selectively bred DWD- had a lower mean FEC compared to DWD+, but were higher than BBM. Reductions in both PCV and serum IgG from initial day 0 levels were observed in DWD lambs, but not in BBM. Furthermore, from a subset of lambs (n = 24) harvested at day 21, DWD- only tended (p = 0.056) to have lower mean worm counts than DWD+, with BBM having the lowest mean worm count. Differentially expressed genes (DEGs) identified via RNA-sequencing of abomasal tissue at day 21 indicate a more pronounced Th2 immune response and more rapid worm expulsion occurred in iBBM than iDWD- and iDWD+ lambs. However, gene expression in DWD- suggests an association between reduced FEC EBV and gastric acid secretion and the ability to limit worm fecundity. Ultimately, selection of Dorper sheep for low FEC EBV can reduce susceptibility to GIN, but it will likely require multiple generations with this trait as a breeding priority before presenting a similar resistance level to Caribbean breeds. • Reducing FEC EBV results in lower FECs following a Haemonchus contortus challenge. • Barbados Blackbelly lambs prevented the establishment of Haemonchus contortus larvae. • Dorper lambs with a lower FEC EBV upregulate genes involved in immunity. [ABSTRACT FROM AUTHOR]

Fish egg quality is strongly related with the ability of the egg to be fertilized and develop a normal embryo with good survival and a lack of abnormalities. Large variations in the spawning quantity or quality impact directly in the competitiveness and sustainability of hatcheries, which create an overly large broodstock in order to satisfy the on-growing companies’ demand for undeformed fry. The present study reports, for the first time in relation to gilthead seabream, the effect of the genetic background of breeders for presence or absence of deformity on their spawning quality and the importance of considering this when creating broodstock. The spawning quality of crosses of breeders with genetic background for presence or absence of deformity (EBVdef), were evaluated during a whole spawning season, through study of the following traits: oocyte yield, fertilization rate, viability rate, hatching rate, larval survival rate, fertilized eggs, viable eggs, hatched eggs, and number of alive larvae. Breeders with a genetic background for deformity and a normal phenotype had shorter spawning periods, lower oocyte yield and, consequently, produced a lower number of alive larvae. In these two traits, the genetic background of breeders was of greater importance during intermediate spawning periods, when spawning is generally considered optimal for the industry, while environmental factors were more important at the beginning and end of the spawning season. In conclusion, these results demonstrate the importance of controlling the breeders’ genetics when creating broodstock.

Body condition score (BCS) is a known risk factor for cow health and well-being. Many different BCS scales and systems for assessment exist;while the scales used for assessing BCS vary, differences in how BCS is assessed (i.e., visual versus visual plus tactile) and the extent of training and experience of the assessor (i.e., professional linear classifiers versus producers) also contributes to the underlying variability. Registered dairy cows globally are routinely assessed for linear type traits which describe biological extremes in the morphological attributes; BCS and a correlated trait angularity are within this suite of traits assessed. These linear-type data are used to generate estimates of genetic merit (predicted transmitting ability), but how these estimates manifest themselves as phenotypic differences when assessed by producers on commercial multiparous cows has never been quantified. To evaluate this, 58440 phenotypic BCS records from 48823 lactations in 38608 cows were used. Associations were undertaken using linear mixed models relating phenotypic BCS to genetic merit after accounting for nuisance factors. Differences in genetic merit for either BCS or angularity (assessed visually by professionals on a 1 to 9 scale just once during lactation in primiparous registered cows) translated to phenotypic difference in BCS (assessed by producers using both tactile and visual assessment on a 1 to 5 scale across lactation in commercial dairy cows). The partial correlation between test phenotypic BCS and genetic merit for either BCS or angularity was 0.13 and 0.10, respectively. Based on the model coefficients estimated in the present study, the mean expected difference in phenotypic BCS on a 1 to 5 scale between the top and bottom 10% on genetic merit for BCS or angularity was 0.28 and 0.31 units, respectively. Results from the present study clearly provide confidence that genetic merit for BCS or angularity based on a single visual assessment in primiparous cows is useful to breed for cows of better body condition, irrespective of stage of lactation or parity.

Objective: This study was conducted to estimate effect of single nucleotide polymorphisms (SNP) on the estimated breeding value of Hungarian Grey (HG) bulls and to find markers associated with horn colour. Methods: Genotypes 136 HG animals were determined on Geneseek high-density Bovine SNP 150K BeadChip. A multi-locus mixed-model was applied for statistical analyses. Results: Six SNPs were identified to be associated (-log10P>10) with green and white horn. These loci are located on chromosome 1, 3, 9, 18, and 25. Seven loci (on chromosome 1, 3, 6, 9, 10, 28) showed considerable association (-log10P>10) with the estimated breeding value. Conclusion: Analysis provides markers for further research of horn colour and supplies markers to achieve more effective selection work regarding estimated breeding value of HG. [ABSTRACT FROM AUTHOR]

The BVA/KC (British Veterinary Association/Kennel Club) and FCI (Fédération Cynologique Internationale) are the main screening schemes used to evaluate the status of canine hip dysplasia (HD) in Europe. Jointly utilizing HD records from both BVA/KC and FCI schemes could improve the reliability of genetic evaluation within and across countries. In this study, HD scores for German shepherd dogs (GSDs) in the UK (using the BVA/KC scheme) and Sweden (using the FCI scheme) were used to investigate how to better operate joint genetic evaluations across the two schemes. It was shown that under a bivariate model, which regarded BVA/KC and FCI scores as different traits, the estimated genetic correlations between the UK and Swedish GSD populations were the same when using BVA/KC total or worse hip scores and for single-country or joint analysis of both the UK and Swedish populations. Under a univariate model that converted BVA/KC scores into FCI scores, the predictability of estimated breeding values was slightly improved by performing a joint analysis.

Mastitis is one of the most common diseases in dairy cattle, causing severe economic losses to dairy farmers. Mastitis usually occurs due to intramammary infection (IMI) caused by a variety of pathogenic bacteria. Although good progress has been made in understanding genetics of pathogen-specific clinical mastitis, studies involving genetic analysis of pathogen-specific IMI are scarce. The overall objective of this study was, therefore, to assess genetic variation of overall and pathogen-specific IMI in nonclinical primiparous and multiparous cows using bacterial culture. Data and milk samples were collected over a 2-yr interval as part of the Canadian Bovine Mastitis Research Network. The final data set contained records of 46,900 quarter milk samples from 3,382 clinically healthy primiparous and multiparous Holstein cows from 84 dairy herds. For the genetic analysis, we considered the following 7 traits: overall IMI, non- aureus staphylococci (NAS) IMI, contagious pathogen IMI, environmental pathogen IMI, major pathogen IMI, minor pathogen IMI and somatic cell score (SCS). Data were analyzed at the quarter level using a threshold-probit model via Gibbs sampling in BLUPF90. Prevalence of IMI traits at the quarter level in multiparous cow from 0 to 400 DIM ranged from 6.8 to 45.5%. Posterior mean of quarter heritability estimates (on the underlying scale, posterior SD in brackets) of overall IMI and pathogen-specific IMI traits ranged from 0.017 to 0.073 (±0.009 to 0.030). Weak to strong genetic correlations [ranging from 0.18 to 0.97 (±0.01 to 0.29)] among pathogen-specific IMI traits and with overall IMI indicated that not all of these traits were genetically similar. Weak to moderate Spearman rank correlations between estimated breeding values for overall IMI and pathogen-specific IMI traits (from 0.31 to 0.87) indicated possible substantial reranking of sires. The percentage of daughters with IMI caused by various pathogen groups ranged from 13 to 80% and from 38 to 94% for the best (10% decile) and worst sires (90% decile) according to their IMI trait-specific estimated breeding values, respectively. Pathogen-specific IMI traits and overall IMI had weak to moderate positive genetic correlations [ranging from 0.11 to 0.81 (±0.11 to 0.22)] with SCS. Therefore, selection for lower SCS will improve resistance to IMI. However, based on the observed weak to moderate rank correlations (0.04 to 0.47) between pathogen-specific IMI traits and SCS, selection for lower SCC will not improve resistance to IMI from every pathogen-specific IMI group in the same manner. Therefore, despite low heritability estimates, there was sizeable genetic variation for pathogen-specific IMI traits, indicating that long-term direct genetic selection for pathogen-specific IMI can improve pathogen-specific IMI resistance. [ABSTRACT FROM AUTHOR]

This study evaluated carcass attributes, meat and belly qualities in finisher boars (n = 79) selected for feed efficiency (low, intermediate and high) based on estimated breeding value for feed conversion ratio within a Large White dam and sire genetic lines. The sire line had lower trimmed fat proportions and higher lean than the dam line (P < 0.01). Genetic lines expressed slight colour changes and drip losses (P < 0.05), with no differences in pH, marbling and cooking traits (P > 0.05). High-efficient animals presented the highest lean yield (P < 0.01), the lowest trimmed fat proportion (P < 0.01) and no effect on meat and belly quality attributes (P > 0.05) compared with other efficient groups. Interaction between efficiency group and genetic line was only detected for belly weight and thickness (P < 0.01). High-efficient animals offer a greater leanness level, with minimal impact on meat and belly quality traits. [ABSTRACT FROM AUTHOR]

• Do different types of boars cope differently with alternative ingredients? • No significant interaction between the type of boar and diet. • Type of boar did affect performance, carcass quality and intramuscular fat content. • Type of diet did affect performance, carcass quality and digestibility. • Feeding sustainable diets does not appear to require any change in breeding goals. For many years, pig production has focused on maximizing performance by selecting for maximal muscle growth and feeding diets that allow the animals to express their genetic potential. However, it is unclear whether this selection for muscle deposition has affected the capacity of pigs to cope with by-product-based diets, which rely on fat as the primary energy source instead of starches and sugars. Therefore, an experiment was set up to investigate if different types of boars affect how their progeny cope with alternative ingredients in the diet, with a possible need for adapted breeding schemes. Two types of boars within the Piétrain sire line were used based on either a high or low estimated breeding value for daily feed intake (HFI : high feed intake, low feed intake). When their progeny reached 14 weeks of age, two dietary strategies were compared: a control (CON) vs a by-product-based diet high in fat and fiber (HFF). The CON diet was mainly based on cereals (corn, wheat, barley) and soybean meal. The HFF diet was formulated to contain the same net energy, CP and digestible amino acid levels without any cereals or soybean meal. In total 192 animals were included in the experiment (48 animals/type of boar/diet) and performance, digestibility, carcass and meat quality were compared. None of the parameters showed a significant interaction (P < 0.05) between the type of boar and diet, suggesting that shifting to diets that are less prone to feed-food competition is equally feasible in different types of pigs. Type of boar did affect performance, carcass quality and intramuscular fat content. HFI pigs showed higher daily feed intake (DFI) and daily gain (P < 0.001), with no significant difference in feed conversion ratio (P = 0.205), lower carcass quality (P < 0.001) and higher intramuscular fat content (P = 0.030). For both boar types, pigs fed the CON diet performed better, with a higher daily gain (P = 0.028), DFI (P = 0.011) and dressing yield (P = 0.009) and better digestibility (P < 0.001), but without differences in feed conversion ratio or meat quality. In conclusion, there was no indication that pigs differing in feed intake capacity cope differently with a high-fat, high-fiber diet based on by-products. Different types of pigs may cope well with diets that are less prone to feed-food competition. [ABSTRACT FROM AUTHOR]

In single-step analyses, missing genotypes are explicitly or implicitly imputed, and this requires centering the observed genotypes using the means of the unselected founders. If genotypes are only available for selected individuals, centering on the unselected founder mean is not straightforward. Here, computer simulation is used to study an alternative analysis that does not require centering genotypes but fits the mean μg of unselected individuals as a fixed effect. Starting with observed diplotypes from 721 cattle, a five-generation population was simulated with sire selection to produce 40,000 individuals with phenotypes, of which the 1000 sires had genotypes. The next generation of 8000 genotyped individuals was used for validation. Evaluations were undertaken with (J) or without (N) μg when marker covariates were not centered; and with (JC) or without (C) μg when all observed and imputed marker covariates were centered. Centering did not influence accuracy of genomic prediction, but fitting μg did. Accuracies were improved when the panel comprised only quantitative trait loci (QTL); models JC and J had accuracies of 99.4%, whereas models C and N had accuracies of 90.2%. When only markers were in the panel, the 4 models had accuracies of 80.4%. In panels that included QTL, fitting μg in the model improved accuracy, but had little impact when the panel contained only markers. In populations undergoing selection, fitting μg in the model is recommended to avoid bias and reduction in prediction accuracy due to selection.

• Stochastic simulation demonstrated the benefits of importing sires for improvement of canine hip dysplasia (HD). • Importing sires with high genetic merits may improve genetic progress and genetic variability. • When countries used different scales to estimate HD breeding values, high genetic correlation was required. • Greater international consensus in HD screening protocols is recommended. Breeding against canine hip dysplasia (HD) may benefit from the importation of foreign sires. When foreign sires are evaluated on a different HD scale, this may diminish the efficacy. Using stochastic simulations, we evaluated genetic change and inbreeding levels for different scenarios of importing sires with high genetic merit for HD. Population size and genetic parameters (e.g. heritability, accuracy of selection, genetic correlation) were based on actual data for HD in Golden retrievers and Labrador retrievers in the UK and Sweden. For countries with different HD scales and an estimated breeding value (EBV) evaluation in place, the importation was useful if imported sires had EBV rankings in the top 50% and if genetic correlations between EBV systems were above 0.85. When importing sires with EBV rankings in the top 10%, moderate accuracies of EBVs (>0.40) and moderately strong genetic correlations (>0.70) were needed. Selection against HD without the importation of sires may increase inbreeding levels, while the importation of sires can decrease inbreeding levels. For national genetic evaluation and selection programmes, importing sires with high genetic merit can be an effective breeding strategy, but care is needed to estimate reliable EBVs. [ABSTRACT FROM AUTHOR]

Replacement pigs’ genomic prediction for reproduction (total number and born alive piglets in the first parity), meat, fatness and growth traits (muscle depth, days to 100 kg and backfat thickness over 6–7 rib) was tested using single-step genomic best linear unbiased prediction ssGBLUP methodology. These traits were selected as the most economically significant and different in terms of heritability. The heritability for meat, fatness and growth traits varied from 0.17 to 0.39 and for reproduction traits from 0.12 to 0.14. We confirm from our data that ssGBLUP is the most appropriate method of genomic evaluation. The validation of genomic predictions was performed by calculating the correlation between preliminary GEBV (based on pedigree and genomic data only) with high reliable conventional estimates (EBV) (based on pedigree, own phenotype and offspring records) of validating animals. Validation datasets include 151 and 110 individuals for reproduction, meat and fattening traits, respectively. The level of correlation (r) between EBV and GEBV scores varied from +0.44 to +0.55 for meat and fatness traits, and from +0.75 to +0.77 for reproduction traits. Average breeding value (EBV) of group selected on genomic evaluation basis exceeded the group selected on parental average estimates by 22, 24 and 66% for muscle depth, days to 100 kg and backfat thickness over 6–7 rib, respectively. Prediction based on SNP markers data and parental estimates showed a significant increase in the reliability of low heritable reproduction traits (about 40%), which is equivalent to including information about 10 additional descendants for sows and 20 additional descendants for boars in the evaluation dataset.

Agronomic and quality traits in alfalfa are very important to forage industry. Genomic prediction (GP) based on genotyping-by-sequencing (GBS) data could shorten the breeding cycles and accelerate the genetic gains of these complex traits, if they display moderate to high prediction accuracies. The aim of this study was to investigate the predictive potentials of these traits in alfalfa. A total of 322 genotypes from 75 alfalfa accessions were used for GP of the agronomic and quality traits, which were related to yield and nutrition value, respectively, using BayesA, BayesB, and BayesCπ methods. Ten-fold cross validation was used to evaluate the accuracy of GP represented by the correlation between genomic estimated breeding value (GEBV) and estimated breeding value (EBV). The accuracies ranged from 0.0021 to 0.6485 for different traits. For each trait, three GP methods displayed similar prediction accuracies. Among 15 quality traits, mineral element Ca had a moderate and the highest prediction accuracy (0.34). NDF digestibility after 48 h (NDFD 48 h) and 30 h (NDFD 30 h) and mineral element Mg had prediction accuracies varying from 0.20 to 0.25. Other traits, for example, fat and crude protein, showed low prediction accuracies (0.05 to 0.19). Among 10 agronomic traits, however, some displayed relatively high prediction accuracies. Plant height (PH) in fall (FH) had the highest prediction accuracy (0.65), followed by flowering date (FD) and plant regrowth (PR) with accuracies at 0.52 and 0.51, respectively. Leaf to stem ratio (LS), plant branch (PB), and biomass yield (BY) reached to moderate prediction accuracies ranging from 0.25 to 0.32. Our results revealed that a few agronomic traits, such as FH, FD, and PR, had relatively high prediction accuracies, therefore it is feasible to apply genomic selection (GS) for these traits in alfalfa breeding programs. Because of the limitations of population size and density of SNP markers, several traits displayed low accuracies which could be improved by a bigger reference population, higher density of SNP markers, and more powerful statistic tools.

Thoroughbred, a relatively recent horse breed, is best known for its use in horse racing. Although myostatin (MSTN) variants have been reported to be highly associated with horse racing performance, the trait is more likely to be polygenic in nature. The purpose of this study was to identify genetic variants strongly associated with racing performance by using estimated breeding value (EBV) for race time as a phenotype. We conducted a two-stage genome-wide association study to search for genetic variants associated with the EBV. In the first stage of genome-wide association study, a relatively large number of markers (~54,000 single-nucleotide polymorphisms, SNPs) were evaluated in a small number of samples (240 horses). In the second stage, a relatively small number of markers identified to have large effects (170 SNPs) were evaluated in a much larger number of samples (1,156 horses). We also validated the SNPs related to MSTN known to have large effects on racing performance and found significant associations in the stage two analysis, but not in stage one. We identified 28 significant SNPs related to 17 genes. Among these, six genes have a function related to myogenesis and five genes are involved in muscle maintenance. To our knowledge, these genes are newly reported for the genetic association with racing performance of Thoroughbreds. It complements a recent horse genome-wide association studies of racing performance that identified other SNPs and genes as the most significant variants. These results will help to expand our knowledge of the polygenic nature of racing performance in Thoroughbreds.

The aim of this study was to estimate breeding values of fertility traits, using univariate and bivariate models in Holstein and Jersey cattle, in Antioquia, Colombia. The information was obtained from 92 dairy herds, located in 18 municipalities of Antioquia. The fertility traits evaluated were: calving interval (IEP), days open (DO), number of services per conception (NSC) and conception rate (TC). The estimated breeding values (EBV) for fertility traits were calculated using two types of univariate animal model (univariate model UV and univariate model with repeatability UVR) and two types of animal bivariate models (bivariate model BV and BVR bivariate model with repeatability). The traits used as correlated in bivariate models were: milk production (PL), protein percentage (PRO) and fat percentage (GRA). The solutions of the equations of the linear mixed models were obtained through the maximum likelihood derivative free restricted method. In this investigation, was determined that the bivariate models (BV and BVR), improve the accuracy of EBVs in all reproductive traits by 3 and 2 percentage points in Holstein and Jersey respectively compared with univariate models (UV and UVR). The results obtained in this study show that the genetic evaluations performed through bivariate analysis, increase the accuracy of EBVs in fertility traits (IEP, DA, NSC and TC), when production traits (PL, PRO and GRA) were used as correlated. [ABSTRACT FROM AUTHOR]

Agronomic and quality traits in alfalfa are very important to forage industry. Genomic prediction (GP) based on genotyping-by-sequencing (GBS) data could shorten the breeding cycles and accelerate the genetic gains of these complex traits, if they display moderate to high prediction accuracies. The aim of this study was to investigate the predictive potentials of these traits in alfalfa. A total of 322 genotypes from 75 alfalfa accessions were used for GP of the agronomic and quality traits, which were related to yield and nutrition value, respectively, using BayesA, BayesB, and BayesCπ methods. Ten-fold cross validation was used to evaluate the accuracy of GP represented by the correlation between genomic estimated breeding value (GEBV) and estimated breeding value (EBV). The accuracies ranged from 0.0021 to 0.6485 for different traits. For each trait, three GP methods displayed similar prediction accuracies. Among 15 quality traits, mineral element Ca had a moderate and the highest prediction accuracy (0.34). NDF digestibility after 48 h (NDFD 48 h) and 30 h (NDFD 30 h) and mineral element Mg had prediction accuracies varying from 0.20 to 0.25. Other traits, for example, fat and crude protein, showed low prediction accuracies (0.05 to 0.19). Among 10 agronomic traits, however, some displayed relatively high prediction accuracies. Plant height (PH) in fall (FH) had the highest prediction accuracy (0.65), followed by flowering date (FD) and plant regrowth (PR) with accuracies at 0.52 and 0.51, respectively. Leaf to stem ratio (LS), plant branch (PB), and biomass yield (BY) reached to moderate prediction accuracies ranging from 0.25 to 0.32. Our results revealed that a few agronomic traits, such as FH, FD, and PR, had relatively high prediction accuracies, therefore it is feasible to apply genomic selection (GS) for these traits in alfalfa breeding programs. Because of the limitations of population size and density of SNP markers, several traits displayed low accuracies which could be improved by a bigger reference population, higher density of SNP markers, and more powerful statistic tools. [ABSTRACT FROM AUTHOR]

Summary: We aimed to investigate the performance of three deregression methods (VanRaden, VR; Wiggans, WG; and Garrick, GR) of cows’ and bulls’ breeding values to be used as pseudophenotypes in the genomic evaluation of test‐day dairy production traits. Three scenarios were considered within each deregression method: (i) including only animals with reliability of estimated breeding value (RELEBV ) higher than the average of parent reliability (RELPA ) in the training and validation populations; (ii) including only animals with RELEBV higher than 0.50 in the training and RELEBV higher than RELPA in the validation population; and (iii) including only animals with RELEBV higher than 0.50 in both training and validation populations. Individual random regression coefficients of lactation curves were predicted using the genomic best linear unbiased prediction (GBLUP), considering either unweighted or weighted residual variances based on effective records contributions. In summary, VR and WG deregression methods seemed more appropriate for genomic prediction of test‐day traits without need for weighting in the genomic analysis, unless large differences in RELEBV between training population animals exist. [ABSTRACT FROM AUTHOR]

Despite Japanese flounder ( Paralichthys olivaceus ) is of importance in aquaculture of Northeast Asia, selective breeding programs for growth performance traits remain limited. The aim of this study was to estimate parameters of growth performance traits in this species. The heritabilities, genetic and phenotypic correlations, and breeding values were estimated for body weight (BW), total length (TL), condition factor (K), and average daily gain (ADG). The genetic analyses were performed on a total number of 186 full-sib families (108 sires and 146dams, 16,807 individuals with integrated pedigree information) from 4 year-classes based on three mixed animal models with tank and year-class as fixed effects, mean family trait values at tagging as a covariate, and additive genetic effect as a random effect using the restricted maximum likelihood method. For all growth traits the maternal and sir-dam interaction effects in proportion to phenotypic variance were very low (0.00–0.05). The heritability estimates for growth traits ranged from 0.12 to 0.39, which is in a low to moderate level. These results indicated that there is a considerable additive genetic variation in growth traits, and the ongoing selective breeding project will produce considerable genetic improvement in growth traits of Japanese flounder. The genetic and phenotypic correlations among BW, TL and ADG were high and positive (0.87–0.94, P < .001). However, the correlations between K and other three traits were low to moderate (−0.10–0.58, P < .001). These data indicate that these traits (except K) could be selected and enhanced simultaneously and also imply that direct selection of TL, which is an easily measurable trait, will be more favorable than selection on BW and ADG. The estimated breeding values of parents and individuals and the average family breeding values for 4 traits were obtained. In summary, all the findings in this study will be of significance to optimize the flounder selective breeding program. Statement of relevance This paper offers guidelines to select breeding strategy in Japanese flounder. [ABSTRACT FROM AUTHOR]

In beef cattle, horn management is practiced to physically or surgically remove horns for the safety of animals and workers. However, invasive practices of dehorning and disbudding are a great threat to animal welfare, health, production and human safety, as well as labour intensive and costly. The most effective way to limit the impacts and costs of horns is to prevent their occurrences by breeding naturally polled (hornless) herds. Horn development is complex, although two mutually exclusive genetic variants (Celtic and Friesian) have been found prevalent on each copy of chromosome 1 in most polled cattle. Predicting genotypes in an animal is challenging. Available genetic testing assays were often limited in tropically adapted beef cattle. In this study we present a new optimized poll testing (OPT) assay, which has been bundled with SNP genotyping arrays being used for genomic evaluation in cattle. Breeding schemes can profile future parents for pure-polled stock based on the OPT results. We also evaluated the factors causing complexity in horn conditions. Thus, we coupled OPT predictions with head-status and sex distributions, by modelling genetic and non-genetic impacts, revealing that genetics, sex and sex hormones control horn ontology. Finally, concerns of polledness adversely affecting production and reproduction were investigated by using estimated breeding values of several beef traits. We found no detrimental effects of polledness on production or reproduction. Overall, this research concludes that genetically polled cattle will minimize issues about animal welfare and management costs without reducing production potentials in the tropically adapted beef cattle.

The objective of the present study was to investigate the phenotypic inter- and intra-relationships within and among alternative feed efficiency metrics across different stages of lactation and parities; the expected effect of genetic selection for feed efficiency on the resulting phenotypic lactation profiles was also quantified. A total of 8,199 net energy intake (NEI) test-day records from 2,505 lactations on 1,290 cows were used. Derived efficiency traits were either ratio based or residual based; the latter were derived from least squares regression models. Residual energy intake (REI) was defined as NEI minus predicted energy requirements based on lactation performance; residual energy production (REP) was defined as net energy for lactation minus predicted energy requirements based on lactation performance. Energy conversion efficiency was defined as net energy for lactation divided by NEI. Pearson phenotypic correlations among traits were computed across lactation stages and parities, and the significance of the differences was determined using the Fisher r-to-z transformation. Sources of variation in the feed efficiency metrics were investigated using linear mixed models, which included the fixed effects of contemporary group, breed, parity, stage of lactation, and the 2-way interaction of parity by stage of lactation. With the exception of REI, parity was associated with all efficiency and production traits. Stage of lactation, as well as the 2-way interaction of parity by stage of lactation, were associated with all efficiency and production traits. Phenotypic correlations among the efficiency and production traits differed not only by stage of lactation but also by parity. For example, the strong phenotypic correlation between REI and energy balance (EB; 0.89) for cows in parity 3 or greater and early lactation was weaker (P < 0.05) for parity 1 cows at the same lactation stage (0.81), suggesting primiparous cows use the ingested energy for both milk production and growth. Nonetheless, these strong phenotypic correlations between REI and EB suggested negative REI animals (i.e., more efficient) are also in more negative EB. These correlations were further supported when assessing the effect on phenotypic performance of animals genetically divergent for feed intake and efficiency based on parental average. Animals genetically selected to have lower REI resulted in cows who consumed less NEI but were also in negative EB throughout the entire lactation. Nonetheless, such repercussions of negative EB do not imply that selection for negative REI (as defined here) should not be practiced, but instead should be undertaken within the framework of a balanced breeding objective, which includes traits such as reproduction and health. [ABSTRACT FROM AUTHOR]

The use of molecular genetic information in the evaluation of livestock has become more common. This study looks at the efficacy of using such information to improve the genetic evaluation of a rare breed of dual-purpose cattle. Data were available in the form of pedigree information on the Gloucester cattle breed in the United Kingdom and recorded milk and beef performance on a small number of animals. In addition, molecular genetic information in the form of multi-marker, multiple regression results converted to a 1 to 10 score (Igenity scores) and 123 single nucleotide polymorphism (SNP) genotypes for 199 non-recorded animals were available. Appropriate mixed-animal models were explored for the recorded traits and these were used to calculate estimated breeding values (EBV), and their accuracies, for 6527 animals in the breed’s pedigree file. Various ways to improve the accuracy of these EBV were explored. This involved using multivariate BLUP analyses, genomic estimated breeding values (GEBV) and combining Igenity scores with recorded traits in a series of bivariate genetic analyses. Using the milk recording traits as an example, the accuracy of a number of traits could be improved using multivariate analyses by up to 14%, depending on the combination of traits used. The level of increase in accuracy largely corresponded to the absolute difference between the genetic and residual correlations between two traits, but this was not always symmetrical. The use of GEBV did not increase the accuracy of milk trait EBV owing to the low proportion of variance explained by the 101 SNPs used. Using Igenity scores in bivariate analyses with the recorded data was more successful in increasing EBV accuracy. The largest increases were found in genotyped animals with no recorded performance (e.g. a 58% increase in fat weight in milk); however, the size of the increase depended on the level of the genetic correlation between the recorded trait and the Igenity score for that trait. Lower levels of improvements in accuracy were seen in animals that were recoded but not genotyped, and ancestors which were neither genotyped nor recorded. This study demonstrated that it was possible to improve the accuracy of EBV estimation by including Igenity score information in genetic analyses but it also concluded that increasing the level of performance recording in the breed would be beneficial.

Genomic Selection (GS) is a method in plant breeding to predict the genetic value of untested lines based on genome-wide marker data. The method has been widely explored with simulated data and also in real plant breeding programs. However, the optimal strategy and stage for implementation of GS in a plant-breeding program is still uncertain. The accuracy of GS has proven to be affected by the data used in the GS model, including size of the training population, relationships between individuals, marker density, and use of pedigree information. GS is commonly used to predict the additive genetic value of a line, whereas non-additive genetics are often disregarded. In this review, we provide a background knowledge on genomic prediction models used for GS and a view on important considerations concerning data used in these models. We compare within- and across-breeding cycle strategies for implementation of GS in cereal breeding and possibilities for using GS to select untested lines as parents. We further discuss the difference of estimating additive and non-additive genetic values and its usefulness to either select new parents, or new candidate varieties.

A high quality of stallion semen is of particular importance for maximum reproductive efficiency. In the present study, we estimated the relationships among estimated breeding values (EBVs) of semen traits and EBVs for the paternal component of the pregnancy rate per estrus cycle (EBV-PAT) for 100 German Warmblood stallions using correlation and general linear model analyses. The most highly correlated sperm quality trait was total number of progressively motile sperm ( r = 0.36). EBV-PAT was considered in three classes with stallions 1 SD below (<80), around (80–120), and above (>120) the population mean of 100. The general linear model analysis showed significant effects for EBVs of all semen traits. EBVs of sperm quality traits greater than 100 to 110 were indicative for EBV-PAT greater than 120. Recommendations for breeding soundness examinations on the basis of the assessments of sperm quality traits and estimation of breeding values seem to be an option to support breeders to improve stallion fertility in the present and future stallion generation. [ABSTRACT FROM AUTHOR]