Wrong and missing sire information affects genetic gain in the Angeln dairy cattle population

Estimation of Genetic Parameters for Growth and WSSV Resistance Traits in Litopenaeus vannamei

The current study aimed to provide a precise assessment of the genetic parameters associated with growth and white spot syndrome virus (WSSV) resistance traits in Pacific white shrimp (Litopenaeus vannamei). This was achieved through a controlled WSSV challenge assay and the analysis of phenotypic values of five traits: body weight (BW), overall length (OL), body length (BL), tail length (TL), and survival hour post-infection (HPI). The analysis included test data from a total of 1017 individuals belonging to 20 families, of which 293 individuals underwent whole-genome resequencing, resulting in 18,137,179 high-quality SNP loci being obtained. Three methods, including pedigree-based best linear unbiased prediction (pBLUP), genomic best linear unbiased prediction (GBLUP), and single-step genomic BLUP (ssGBLUP) were utilized. Compared to the pBLUP model, the heritability of growth-related traits obtained from GBLUP and ssGBLUP was lower, whereas the heritability of WSSV resistance was higher. Both the GBLUP and ssGBLUP models significantly enhanced prediction accuracy. Specifically, the GBLUP model improved the prediction accuracy of BW, OL, BL, TL, and HPI by 4.77%, 21.93%, 19.73%, 19.34%, and 63.44%, respectively. Similarly, the ssGBLUP model improved prediction accuracy by 10.07%, 25.44%, 25.72%, 19.34%, and 122.58%, respectively. The WSSV resistance trait demonstrated the most substantial enhancement using both genomic prediction models, followed by body size traits (e.g., OL, BL, and TL), with BW showing the least improvement. Furthermore, the choice of models minimally impacted the assessment of genetic and phenotypic correlations. Genetic correlations among growth traits ranged from 0.767 to 0.999 across models, indicating high levels of positive correlations. Genetic correlations between growth and WSSV resistance traits ranged from (-0.198) to (-0.019), indicating low levels of negative correlations. This study assured significant advantages of the GBLUP and ssGBLUP models over the pBLUP model in the genetic parameter estimation of growth and WSSV resistance in L. vannamei, providing a foundation for further breeding programs.

Genetic parameters of sheep growth curve traits reared within rangelands under uncertain paternity

This work aims to improve the selection program of the Timahdit breed through the use of the parameters of the Von Bertalanffy model as selection criteria and the treatment of uncertain paternity found in pastoral systems. A database containing 12,029 animals and a pedigree file integrating the probabilities of the parents with a total of 48,292 animals were used in the analysis. An individual estimation of the parameters of the model studied by the nonlinear regression procedure Proc NLIN of SAS was carried out, followed by the determination of the fixed effects which influence these parameters by means of a general linear model using the GLM procedure of the SAS software. The treatment of uncertain paternity is solved by an R code translating Average Numerator Relationship Matrix Model (ANRM). Then, the variance and (co)variance components were estimated by a Bayesian approach using the BRMS package. The high heritability values obtained, between 0.52 and 0.55 for the parameters studied, suggest good prospects for genetic responses to selection and the maintenance of sustained genetic progress, especially when environmental conditions are unfavorable. The positive correlations between all the parameters studied show that animals with rapid development tend to have lower weight performance. Finally, with optimal selection based on the genetic values associated with these parameters, we can make the desired changes to the growth curve by choosing breeders that achieve high weight performances as quickly as possible, and that would allow improving the feed efficiency for these animals, as well as increasing the profitability of sheep farms.

Animal board invited review: Practical applications of genomic information in livestock

Access to high-dimensional genomic information in many livestock species is accelerating. This has been greatly aided not only by continual reductions in genotyping costs but also an expansion in the services available that leverage genomic information to create a greater return-on-investment. Genomic information on individual animals has many uses including (1) parentage verification and discovery, (2) traceability, (3) karyotyping, (4) sex determination, (5) reporting and monitoring of mutations conferring major effects or congenital defects, (6) better estimating inbreeding of individuals and coancestry among individuals, (7) mating advice, (8) determining breed composition, (9) enabling precision management, and (10) genomic evaluations; genomic evaluations exploit genome-wide genotype information to improve the accuracy of predicting an animal's (and by extension its progeny's) genetic merit. Genomic data also provide a huge resource for research, albeit the outcome from this research, if successful, should eventually be realised through one of the ten applications already mentioned. The process for generating a genotype all the way from sample procurement to identifying erroneous genotypes is described, as are the steps that should be considered when developing a bespoke genotyping panel for practical application.

Analysis of Family Structure and Paternity Test of Tan Sheep in Yanchi Area, China

Tan sheep is a special breed of locally protected sheep in China, one of the best quality meat sheep in the world. Due to the unclear pedigree of the rams on the Ningxia Tan sheep breeding farm, we investigated 74 rams in the field and explored a new method for family division. Genomic DNA was extracted from the blood of breeding rams. Using Plink software, GCTA tools and R language, we analyzed the genetic structure, kinship, and inbreeding coefficient of the breeding sheep, which revealed the genetic relationship between the individuals. The results showed that there was no obvious clustering phenomenon in the PCA, and the genetic background of the samples was similar. The G matrix and IBS distance matrix indicated that most individuals were far away from each other. Paternity testing identified 24 pairs of unknown parent-child pairs, and all the Tan sheep could be divided into 12 families, which provided a reference for sheep breeding. The average inbreeding coefficient based on the ROH of this population was 0.049, so there was a low degree of inbreeding and the rams in the field were able to maintain high genetic diversity. Overall, we explored a more accurate method through paternity and kinship analysis; it provides a scientific basis for pedigree construction, which has an important application value for Tan sheep breeding.

Comparative analysis of inbreeding parameters and runs of homozygosity islands in 2 Italian autochthonous cattle breeds mainly raised in the Parmigiano-Reggiano cheese production region

Reggiana and Modenese are autochthonous cattle breeds, reared in the North of Italy, that can be mainly distinguished for their standard coat color (Reggiana is red, whereas Modenese is white with some pale gray shades). Almost all milk produced by these breeds is transformed into 2 mono-breed branded Parmigiano-Reggiano cheeses, from which farmers receive the economic incomes needed for the sustainable conservation of these animal genetic resources. After the setting up of their herd books in 1960s, these breeds experienced a strong reduction in the population size that was subsequently reverted starting in the 1990s (Reggiana) or more recently (Modenese) reaching at present a total of about 2,800 and 500 registered cows, respectively. Due to the small population size of these breeds, inbreeding is a very important cause of concern for their conservation programs. Inbreeding is traditionally estimated using pedigree data, which are summarized in an inbreeding coefficient calculated at the individual level (F_PED). However, incompleteness of pedigree information and registration errors can affect the effectiveness of conservation strategies. High-throughput SNP genotyping platforms allow investigation of inbreeding using genome information that can overcome the limits of pedigree data. Several approaches have been proposed to estimate genomic inbreeding, with the use of runs of homozygosity (ROH) considered to be the more appropriate. In this study, several pedigree and genomic inbreeding parameters, calculated using the whole herd book populations or considering genotyping information (GeneSeek GGP Bovine 150K) from 1,684 Reggiana cattle and 323 Modenese cattle, were compared. Average inbreeding values per year were used to calculate effective population size. Reggiana breed had generally lower genomic inbreeding values than Modenese breed. The low correlation between pedigree-based and genomic-based parameters (ranging from 0.187 to 0.195 and 0.319 to 0.323 in the Reggiana and Modenese breeds, respectively) reflected the common problems of local populations in which pedigree records are not complete. The high proportion of short ROH over the total number of ROH indicates no major recent inbreeding events in both breeds. ROH islands spread over the genome of the 2 breeds (15 in Reggiana and 14 in Modenese) identified several signatures of selection. Some of these included genes affecting milk production traits, stature, body conformation traits (with a main ROH island in both breeds on BTA6 containing the ABCG2, NCAPG, and LCORL genes) and coat color (on BTA13 in Modenese containing the ASIP gene). In conclusion, this work provides an extensive comparative analysis of pedigree and genomic inbreeding parameters and relevant genomic information that will be useful in the conservation strategies of these 2 iconic local cattle breeds.

Selection and implementation of single nucleotide polymorphism markers for parentage analysis in crossbred cattle population

Crossbreeding is an essential way of improving herd performance. However, frequent parentage record errors appear, which results in the lower accuracy of genetic parameter estimation and genetic evaluation. This study aims to build a single nucleotide polymorphism (SNP) panel with sufficient power for parentage testing in the crossbred population of Simmental and Holstein cattle. The direct sequencing technique in PCR products of pooling DNA along with matrix-assisted laser desorption/ionization time-of-flight MS method for genotyping the individuals was applied. A panel comprising 50 highly informative SNPs for parentage analysis was developed in the crossbred population. The average minor allele frequency for SNPs was 0.43, and the cumulative probability of exclusion for single-parent and both-parent inference met 0.99797 and 0.999999, respectively. The maker-set for parentage verification was then used in a group of 81 trios with aid of the likelihood-based parentage-assignment program of Cervus software. Reconfirmation with on-farm records showed that this 50-SNP system could provide sufficient and reliable information for parentage testing with the parental errors for mother-offspring and sire-offspring being 8.6 and 18.5%, respectively. In conclusion, a set of low-cost and efficient SNPs for the paternity testing in the Simmental and Holstein crossbred population are provided.

Evaluation of the International Society for Animal Genetics bovine single nucleotide polymorphism parentage panel in South African Bonsmara and Drakensberger cattle

A panel of 200 single nucleotide polymorphisms (SNPs) have been recommended by the International Society for Animal Genetics (ISAG) for use in parentage verification of cattle. While the SNPs included on the ISAG panel are segregating in European Bos taurus and Bos indicus breeds, their applicability in South African (SA) Sanga cattle has never been evaluated. This study, therefore, assessed the usefulness of the ISAG panel in SA Bonsmara (BON) and Drakensberger (DRB) cattle. Genotypes of 185 ISAG SNPs from 64 BON and 97 DRB sire-offspring pairs were available, all of which were validated with 119,375 SNPs. Of the 185 ISAG SNPs, 14 and 18 in the BON and DRB, respectively (9 in common to both breeds), were either monomorphic, exhibited at least one discordance between validated sire-offspring pairs, or had poor call rate or clustering issue. The mean minor allele frequency of the 185 ISAG SNPs was 0.331 in the BON and 0.359 in the DRB. The combined probability of parentage exclusion (P_E) was the same (99.46%) for both breeds, while the probability of identity varied from 1.61 × 10^-48 (BON) to 1.11 × 10^-54 (DRB). Fifteen (23.4%) and 32 (33%) of the already validated sire-offspring pairs for the BON and DRB, respectively, were determined by the ISAG panel to be false-negatives based on a threshold of having at least two discordant SNPs. In comparison to sire discovery using the 119,375 SNPs, sire discovery using only the ISAG panel identified correctly 44 (out of 64 identified using the 119,375 SNPs) unique sire-offspring BON pairs and 62 (out of 97 identified using the 119,375 SNPs) unique sire-offspring DRB when all sires were masked. Five BON and three DRB offspring had > 1 sire nominated. This study demonstrated that the use of the ISAG panel may result in incorrect exclusions and multiple candidate sires for a given animal. Selection of more informative SNPs is, therefore, necessary in the pursuit of a low-cost and effective SNP panel for indigenous cattle breeds in SA.

Coat Color Roan Shows Association with KIT Variants and No Evidence of Lethality in Icelandic Horses

Roan (Rn) horses show a typical seasonal change of color. Their body is covered with colored and white hair. We performed a descriptive statistical analysis of breeding records of Icelandic horses to challenge the hypothesis of roan being lethal in utero under homozygous condition. The roan to non-roan ratio of foals from roan × roan matings revealed homozygous roan Icelandic horses to be viable. Even though roan is known to be inherited in a dominant mode and epistatic to other coat colors, the causative mutation is still unknown. Nevertheless, an association between roan phenotype and the KIT gene was shown for different horse breeds. In the present study, we identified KIT variants by Sanger sequencing, and show that KIT is also associated with roan in the Icelandic horse breed.

Genetic Parameters for Growth and Kid Survival of Indigenous Goat under Smallholding System of Burundi

The goal of this study was to estimate genetic parameters for the growth, conformation, and survival of goat kids raised in smallholder farming systems in Burundi. To do this, measurements were taken on live weight, thoracic perimeter, length, and height at birth (n = 1538 animals), at 3 months (n = 1270 animals), at 6 months (n = 992 animals), at 9 months (n = 787 animals), and at 12 months (n = 705 animals). Kids were born between 2016 and 2019, from 645 dams and 106 bucks. Three bivariate animal models were used to estimate genetic parameters of body weight and conformation measurements as potential indicators of this weight. According to the measure, heritability was estimated between 15 and 17% and genetic correlations between 65 and 79%. An accelerated failure time animal model was used to estimate the heritability of survival for kids under one year, adjusted for birth weight. Goat survival was significantly prolonged by 0.64 days per kilogram of birth weight. The estimated heritability for this trait was 2%. Overall, these results suggest that a selection program could be implemented to improve animal growth, either directly on weight or indirectly on conformational traits. At the same time, efforts need to be made to improve rearing conditions to increase the survival of kids.

Effect of errors in pedigree on the accuracy of estimated breeding value for carcass traits in Korean Hanwoo cattle

OBJECTIVE

This study evaluated the effect of pedigree errors (PEs) on the accuracy of estimated breeding value (EBV) and genetic gain for carcass traits in Korean Hanwoo cattle.

METHODS

The raw data set was based on the pedigree records of Korean Hanwoo cattle. The animals' information was obtained using Hanwoo registration records from Korean animal improvement association database. The record comprised of 46,704 animals, where the number of the sires used was 1,298 and the dams were 38,366 animals. The traits considered were carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT), and marbling score (MS). Errors were introduced in the pedigree dataset through randomly assigning sires to all progenies. The error rates substituted were 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, and 80%, respectively. A simulation was performed to produce a population of 1,650 animals from the pedigree data. A restricted maximum likelihood based animal model was applied to estimate the EBV, accuracy of the EBV, expected genetic gain, variance components, and heritability (h2) estimates for carcass traits. Correlation of the simulated data under PEs was also estimated using Pearson's method.

RESULTS

The results showed that the carcass traits per slaughter year were not consistent. The average CWT, EMA, BFT, and MS were 342.60 kg, 78.76 cm2, 8.63 mm, and 3.31, respectively. When errors were introduced in the pedigree, the accuracy of EBV, genetic gain and h2 of carcass traits was reduced in this study. In addition, the correlation of the simulation was slightly affected under PEs.

CONCLUSION

This study reveals the effect of PEs on the accuracy of EBV and genetic parameters for carcass traits, which provides valuable information for further study in Korean Hanwoo cattle.

Pedigree verification and parentage assignment using genomic information in the Mexican Holstein population

Genealogical information is an essential tool for carrying out any genetic improvement program. The objective of this study was to determine the accuracy of pedigree information in the Mexican registered Holstein population using genomic data available in Mexico and for the US Holstein population. The study included 7,508 animals (158 sires and 7,350 cows) that were born from 2002 through 2014, registered with Holstein de México, and genotyped with single nucleotide polymorphism arrays of different densities. Parentage could not be validated for 17% of sires of cows and 12% of sires of bulls. Most (79%) of the dams of cows and the dams of bulls had no genotype available and could not be validated. A parentage test was possible for only 6,104 sires of cows, 139 sires of bulls, 1,519 dams of cows, and 33 dams of bulls. Of the animals with a parentage test, parent assignment was confirmed for 89% of sires of cows, 92% of dams of cows, 95% of sires of bulls, and 97% of dams of bulls. Parent discovery was possible for some animals without confirmed parents: 17% for sires of cows, 2.5% for dams of cows, 43% for sires of bulls, and 0% for dams of bulls. Of the 7,795 progeny tests, 777 had parent conflicts, which is an error rate of 9.97% for parental recording in the population, a rate that is similar to those recently reported for other populations. True parents for some progeny conflicts (15%) were discovered for the Mexican population, and the remaining parents were assigned as unknown. Expected effects of misidentification on rate of genetic gain could be decreased by half if genealogical errors were decreased to 5%. This study indicates that genotyping and genealogy recovery may help in increasing rates of genetic improvement in the Mexican registered Holstein population.

Evaluation of 17 microsatellite markers for parentage testing and individual identification of domestic yak (Bos grunniens)

BACKGROUND

Yak (Bos grunniens) is the most important domestic animal for people living at high altitudes. Yak ordinarily feed by grazing, and this behavior impacts the accuracy of the pedigree record because it is difficult to control mating in grazing yak. This study aimed to evaluate the pedigree system and individual identification in polled yak.

METHODS

A total of 71 microsatellite loci were selected from the literature, mostly from the studies on cattle. A total of 35 microsatellite loci generated excellent PCR results and were evaluated for the parentage testing and individual identification of 236 unrelated polled yaks. A total of 17 of these 35 microsatellite loci had polymorphic information content (PIC) values greater than 0.5, and these loci were in Hardy-Weinberg equilibrium without linkage disequilibrium.

RESULTS

Using multiplex PCR, capillary electrophoresis, and genotyping, very high exclusion probabilities were obtained for the combined core set of 17 loci. The exclusion probability (PE) for one candidate parent when the genotype of the other parent is not known was 0.99718116. PE for one candidate parent when the genotype of the other parent is known was 0.99997381. PE for a known candidate parent pair was 0.99999998. The combined PEI (PE for identity of two unrelated individuals) and PESI (PE for identity of two siblings) were >0.99999999 and 0.99999899, respectively. These findings indicated that the combination of 17 microsatellite markers could be useful for efficient and reliable parentage testing and individual identification in polled yak.

DISCUSSION

Many microsatellite loci have been investigated for cattle paternity testing. Nevertheless, these loci cannot be directly applied to yak identification because the two bovid species have different genomic sequences and organization. A total of 17 loci were selected from 71 microsatellite loci based on efficient amplification, unambiguous genotyping, and high PIC values for polled yaks, and were suitable for parentage analysis in polled yak populations.

Selection and effectiveness of informative SNPs for paternity in Chinese Simmental cattle based on a high-density SNP array

Incorrect paternity assignment in cattle can significantly influence the accuracy of genetic evaluation. Recent advances in high-throughput technology have facilitated the identification of single nucleotide polymorphism (SNP) markers and their applications for filiation and individual identification. We genotyped 1074 bulls from a reference population of Chinese Simmental cattle for genomic selection using a BovineSNP770K BeadChip. Among them, a total of 136 bulls were randomly selected to design a suitable low-density SNP panel for paternity testing in Simmental cattle. Our results showed that 50 SNPs were determined to be the most informative markers in parental testing, with an accuracy of 99.89% for CPE (cumulative probability of exclusion) in the unknown female parent case. The 50 highly informative SNP markers were distributed across 25 chromosomes, and the mean intermarker distance per chromosome was 26.72 Mb. The average minor allele frequency (MAF), expected heterozygosity (HE), and polymorphic information content (PIC) values were 0.3748, 0.4998, and 0.4818, respectively. Finally, the 50 identified SNPs were used to estimate paternity for the remaining 938 of 1074 bulls from 23 farms. Our results revealed that 76.75% of the 938 bulls were assigned parentage to the pedigree sires with 95% confidence, and the rate of pedigree record mistakes ranged from 9.52%-39.29% in different herds. Our study is the first attempt to provide valuable insights into the extraction of informative markers through the application of high-density SNP chips for paternity testing in Chinese Simmental cattle.

SNP Data Quality Control in a National Beef and Dairy Cattle System and Highly Accurate SNP Based Parentage Verification and Identification

A major use of genetic data is parentage verification and identification as inaccurate pedigrees negatively affect genetic gain. Since 2012 the international standard for single nucleotide polymorphism (SNP) verification in Bos taurus cattle has been the ISAG SNP panels. While these ISAG panels provide an increased level of parentage accuracy over microsatellite markers (MS), they can validate the wrong parent at ≤1% misconcordance rate levels, indicating that more SNP are needed if a more accurate pedigree is required. With rapidly increasing numbers of cattle being genotyped in Ireland that represent 61 B. taurus breeds from a wide range of farm types: beef/dairy, AI/pedigree/commercial, purebred/crossbred, and large to small herd size the Irish Cattle Breeding Federation (ICBF) analyzed different SNP densities to determine that at a minimum ≥500 SNP are needed to consistently predict only one set of parents at a ≤1% misconcordance rate. For parentage validation and prediction ICBF uses 800 SNP (ICBF800) selected based on SNP clustering quality, ISAG200 inclusion, call rate (CR), and minor allele frequency (MAF) in the Irish cattle population. Large datasets require sample and SNP quality control (QC). Most publications only deal with SNP QC via CR, MAF, parent-progeny conflicts, and Hardy-Weinberg deviation, but not sample QC. We report here parentage, SNP QC, and a genomic sample QC pipelines to deal with the unique challenges of >1 million genotypes from a national herd such as SNP genotype errors from mis-tagging of animals, lab errors, farm errors, and multiple other issues that can arise. We divide the pipeline into two parts: a Genotype QC and an Animal QC pipeline. The Genotype QC identifies samples with low call rate, missing or mixed genotype classes (no BB genotype or ABTG alleles present), and low genotype frequencies. The Animal QC handles situations where the genotype might not belong to the listed individual by identifying: >1 non-matching genotypes per animal, SNP duplicates, sex and breed prediction mismatches, parentage and progeny validation results, and other situations. The Animal QC pipeline make use of ICBF800 SNP set where appropriate to identify errors in a computationally efficient yet still highly accurate method.

Justification for setting the individual animal genotype call rate threshold at eighty-five percent

Data quality of SNP arrays impacts the accuracy and precision of downstream data analyses. One such quality control measure often imposed is a threshold on individual animal call rate. Different call rate thresholds have been applied across studies; little is known, however, about the impact of these thresholds on the quality of the genotype data. The objective of the present study was to investigate the effect of different call rate thresholds on the integrity of the genotypes but also to quantify the contribution of different factors to the variability in animal call rate. Data included 142,342 samples genotyped on a custom Illumina genotype panel from 141,591 dairy and beef cattle; the number of Illumina SNP on the panel was 14,371. The mean animal call rate across all samples was 99.09%; 487 animals had both a low call rate (<99%) and a subsequent high call rate (≥99%) after resampling and regenotyping. Several factors were associated ( < 0.001) with individual call rate including animal sex, the sampling herd, the date of genotyping, the genotyping plate, and the plate well. The genotype and allele concordance between the genotypes of the 487 low- and high-call rate individuals improved at a diminishing rate as mean animal call rate increased. Mean genotype and allele concordance rates of 0.987 and 0.997, respectively, existed when animal call rate was between 85 and 90%, increasing to 0.998 and 0.999, respectively, when animal call rate was between 95 and <99%. The mean within-animal allele concordance rate of rare variants (i.e., minor allele frequency < 0.05) between low and high genotype call rate animals increased when animal call rate improved; an allele concordance rate of 1.00 was achieved when animal call rate was between 85 and <99%. The accuracy of imputation of the nonobserved genotypes in the low-call rate animals improved as animal call rate increased; the mean genotype concordance rate of the imputed nonobserved SNP was 0.41 when animal call rate was <40% but increased to 0.95 when animal call rate was between 95 and <99%. Parentage validation, determined by the count of opposing homozygotes in a parent-progeny pair, was unreliable when animal call rate was <85%. Therefore, to ensure the provision of high-quality genotypes while also considering the cost and inconvenience of resampling and regenotyping, we suggest a minimum animal call rate threshold of 85%.

Analysis of population structure and genetic variability in Iranian buffaloes (Bubalus bubalis) using pedigree information

The objective of this study was to use pedigree analysis to evaluate the population structure, genetic variability and inbreeding in Iranian buffaloes. The analysis was based on the pedigree information of 42 285 buffaloes born from 549 sires and 6376 dams within 1697 herds. Pedigree information used in this study was collected during 1976 to 2012 by the Animal Breeding Centre of Iran. The CFC program was applied to calculate pedigree statistics and genetic structure analysis of the Iranian buffaloes. Also, the INBUPGF90 program was used for calculating regular inbreeding coefficients for individuals in the pedigree. The analysis of pedigree indicated that inbreeding coefficient ranged from 0% to 31% with an average of 3.42% and the trend of inbreeding was significantly positive over the years (P < 0.0001). Average coancestry was increased in recent years and overall generation interval was 6.62 years in Iranian buffaloes. Founder genome equivalent, founder equivalent, effective number of founders and effective number of non-founders were increased from 1976 to 2002, but their values decreased from 2002 onwards. A designed mating system to avoid inbreeding may be applied to this population of buffalo to maintain genetic diversity.

A high throughput single nucleotide polymorphism multiplex assay for parentage assignment in New Zealand sheep

Accurate pedigree information is critical to animal breeding systems to ensure the highest rate of genetic gain and management of inbreeding. The abundance of available genomic data, together with development of high throughput genotyping platforms, means that single nucleotide polymorphisms (SNPs) are now the DNA marker of choice for genomic selection studies. Furthermore the superior qualities of SNPs compared to microsatellite markers allows for standardization between laboratories; a property that is crucial for developing an international set of markers for traceability studies. The objective of this study was to develop a high throughput SNP assay for use in the New Zealand sheep industry that gives accurate pedigree assignment and will allow a reduction in breeder input over lambing. This required two phases of development- firstly, a method of extracting quality DNA from ear-punch tissue performed in a high throughput cost efficient manner and secondly a SNP assay that has the ability to assign paternity to progeny resulting from mob mating. A likelihood based approach to infer paternity was used where sires with the highest LOD score (log of the ratio of the likelihood given parentage to likelihood given non-parentage) are assigned. An 84 “parentage SNP panel” was developed that assigned, on average, 99% of progeny to a sire in a problem where there were 3,000 progeny from 120 mob mated sires that included numerous half sib sires. In only 6% of those cases was there another sire with at least a 0.02 probability of paternity. Furthermore dam information (either recorded, or by genotyping possible dams) was absent, highlighting the SNP test’s suitability for paternity testing. Utilization of this parentage SNP assay will allow implementation of progeny testing into large commercial farms where the improved accuracy of sire assignment and genetic evaluations will increase genetic gain in the sheep industry.

Assessing the impact of natural service bulls and genotype by environment interactions on genetic gain and inbreeding in organic dairy cattle genomic breeding programs

The objective of the present study was to compare genetic gain and inbreeding coefficients of dairy cattle in organic breeding program designs by applying stochastic simulations. Evaluated breeding strategies were: (i) selecting bulls from conventional breeding programs, and taking into account genotype by environment (G×E) interactions, (ii) selecting genotyped bulls within the organic environment for artificial insemination (AI) programs and (iii) selecting genotyped natural service bulls within organic herds. The simulated conventional population comprised 148 800 cows from 2976 herds with an average herd size of 50 cows per herd, and 1200 cows were assigned to 60 organic herds. In a young bull program, selection criteria of young bulls in both production systems (conventional and organic) were either 'conventional' estimated breeding values (EBV) or genomic estimated breeding values (GEBV) for two traits with low (h 2=0.05) and moderate heritability (h 2=0.30). GEBV were calculated for different accuracies (r mg), and G×E interactions were considered by modifying originally simulated true breeding values in the range from r g=0.5 to 1.0. For both traits (h 2=0.05 and 0.30) and r mg⩾0.8, genomic selection of bulls directly in the organic population and using selected bulls via AI revealed higher genetic gain than selecting young bulls in the larger conventional population based on EBV; also without the existence of G×E interactions. Only for pronounced G×E interactions (r g=0.5), and for highly accurate GEBV for natural service bulls (r mg>0.9), results suggests the use of genotyped organic natural service bulls instead of implementing an AI program. Inbreeding coefficients of selected bulls and their offspring were generally lower when basing selection decisions for young bulls on GEBV compared with selection strategies based on pedigree indices.

Estimation of inbreeding and effective population size of full-blood Wagyu cattle registered with the American Wagyu Cattle Association

The objective of this research was to examine the population structure of full-blood (100%) Wagyu cattle registered in the United States with the American Wagyu Association, with the aim of estimating and comparing the levels of inbreeding from both pedigree and genotypic data. A total of 4132 full-blood Wagyu cattle pedigrees were assessed and used to compute the inbreeding coefficients (FIT and FST ) and the effective population size (Ne ) from pedigree data for the period 1994 to 2011. In addition to pedigree analysis, 47 full-blood Wagyu cattle representing eight prominent sire lines in the American Wagyu cattle population were genotyped using the Illumina BovineSNP50 BeadChip. Genotypic data were then used to estimate genomic inbreeding coefficients (FROH ) by calculating runs of homozygosity. The mean inbreeding coefficient based on the pedigree data was estimated at 4.80%. The effective population size averaged 17 between the years 1994 and 2011 with an increase of 42.9 in 2000 and a drop of 1.8 in 2011. Examination of the runs of homozygosity revealed that the 47 Wagyu cattle from the eight prominent sire lines had a mean genomic inbreeding coefficient (FROH ) estimated at 9.08% compared to a mean inbreeding coefficient based on pedigree data of 4.8%. These data suggest that the mean genotype inbreeding coefficient of full-blood Wagyu cattle exceeds the inbreeding coefficient identified by pedigree. Inbreeding has increased slowly at a rate of 0.03% per year over the past 17 years. Wagyu breeders should continue to utilize many sires from divergent lines and consider outcrossing to other breeds to enhance genetic diversity and minimize the adverse effects of inbreeding in Wagyu.

Higher precision level at individual laying performance tests in noncage housing systems

With the Weihenstephan funnel nest box, 12 laying hen flocks were tested for their individual laying performance, egg quality, and nesting behavior in a noncage environment. During the whole observation period of 8 yr, a transponder-based data recording system was continuously improved and resulted in a recording accuracy of 97%. At peak production, heritabilities for the number of eggs laid are in some flocks higher than expected. With improved data accuracy, heritability estimates on individual egg weights are more stable. Heritabilities for nesting behavior traits range between a low to moderate level, providing very useful information for laying hen selection to help improve traits that cannot be recorded in cages. Over the years, the benefits of the Weihenstephan funnel nest box for laying hen breeders have grown. This is due to higher data recording accuracies and extended testing capacities, which result in more reliable genetic parameters.

Controlling inbreeding and maximizing genetic gain using semi-definite programming with pedigree-based and genomic relationships

Because of the relatively high levels of genetic relationships among potential bull sires and bull dams, innovative selection tools should consider both genetic gain and genetic relationships in a long-term perspective. Optimum genetic contribution theory using official estimated breeding values for a moderately heritable trait (production index, Index-PROD), and a lowly heritable functional trait (index for somatic cell score, Index-SCS) was applied to find optimal allocations of bull dams and bull sires. In contrast to previous practical applications using optimizations based on Lagrange multipliers, we focused on semi-definite programming (SDP). The SDP methodology was combined with either pedigree (a(ij)) or genomic relationships (f(ij)) among selection candidates. Selection candidates were 484 genotyped bulls, and 499 preselected genotyped bull dams completing a central test on station. In different scenarios separately for PROD and SCS, constraints on the average pedigree relationships among future progeny were varied from a(ij)=0.08 to a(ij)=0.20 in increments of 0.01. Corresponding constraints for single nucleotide polymorphism-based kinship coefficients were derived from regression analysis. Applying the coefficient of 0.52 with an intercept of 0.14 estimated for the regression pedigree relationship on genomic relationship, the corresponding range to alter genomic relationships varied from f(ij) = 0.18 to f(ij) = 0.24. Despite differences for some bulls in genomic and pedigree relationships, the same trends were observed for constraints on pedigree and corresponding genomic relationships regarding results in genetic gain and achieved coefficients of relationships. Generally, allowing higher values for relationships resulted in an increase of genetic gain for Index-PROD and Index-SCS and in a reduction in the number of selected sires. Interestingly, more sires were selected for all scenarios when restricting genomic relationships compared with restricting pedigree relationships. For example, at constraint of f(ij)=0.185 and selection on Index-PROD, the number of selected sires was 35. In contrast, only 21 sires were selected at the comparable constraint on additive genetic relationship of a(ij)=0.09. A further reduction in relationships is possible when using SDP output (i.e., suggested genetic contributions of selected parents) and applying a simulated annealing algorithm to define specific mating plans. However, the advantage of this strategy is limited to a short-term perspective and probably not successful in the period of genomic selection allowing a substantial reduction of generation intervals.

Effects of pedigree errors on the efficiency of conservation decisions

Conservation schemes often aim at increasing genetic diversity by minimizing kinship, and the best method to achieve this goal, when pedigree data is available, is to apply optimal contributions. Optimal contributions calculate contributions per animal so that the weighted average mean kinship among candidate parents is minimized. This approach assumes that pedigree data is correct and complete. However, in practice, pedigrees often contain errors: parents are recorded incorrectly or even missing. We used simulations to investigate the effect of these two types of errors on minimizing kinship. Our findings show that a low percentage of wrong parent information reduces the effect of optimal contributions. When the percentage of wrong parent information is above 15%, the population structure and type of errors, should be taken into account before applying optimal contributions. Optimal contributions based on pedigrees with missing parent information hampers conservation of genetic diversity; however, missing parent information can be corrected. It is crucial to know which animals are founders. We strongly recommend that pedigree registration include whether missing parents are either true founders or non-founders.

Technical note: a note on the differential impact of wrong and missing sire information on reliability and gain

This note analytically derives the impact that wrong and missing sire information (WSI and MSI, respectively) has on the reliability of predicting merit and gain compared with perfect information. In particular, for small WSI and MSI, WSI was shown to have twice the impact of MSI for both reliability and gain, and the impact of both WSI and MSI increased as the reliability of predicting merit with perfect information decreased. The overall impact on the efficiency of gain for small WSI and MSI was half the overall impact on reliability.

Characterization of the DGAT1 Mutations and the CSN1S1 Promoter in the German Angeln Dairy Cattle Population

The identification of quantitative trait loci (QTL) and genes with influence on milk production traits has been the objective of various mapping studies in the last decade. In the centromeric region of Bos taurus autosome (BTA) 14, the acyl-CoA:diacylglycerol acyltransferase1 gene (DGAT1) has been identified as the most likely causative gene underlying a QTL for milk fat yield and content. Recently, a second polymorphism in the promoter of DGAT1 emerged as an additional source of variation. In this study, the frequencies and the effects of alleles at the DGAT1 K232A and at the DGAT1 promoter variable number of tandem repeat (VNTR) locus on BTA14, and of alleles at the CSN1S1 (alpha(S1)-casein-encoding gene) promoter on BTA6 in the German Angeln dairy cattle population were investigated. Analyzed traits were milk, fat, protein, lactose, and milk energy yield, fat, protein, lactose, and milk energy content and somatic cell score. The lysine variant of the DGAT1 K232A mutation showed significant effects for most of the milk production traits. A specific allele of the DGAT1 promoter VNTR showed significant effects on the traits lactose yield and content, milk energy content, and SCS compared with the other alleles. Additionally, a regulation mechanism between the DGAT1 K232A mutation and the DGAT1 promoter VNTR was found for fat yield and content, which could be caused by an upper physiological bound for the effects of the DGAT1 gene. At the CSN1S1 promoter, 2 of 4 alleles showed significant allele substitution effects on the milk yield traits.