Article

Effect of Misidentification on Genetic Gain and Estimation of Breeding Value in Dairy Cattle Populations

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Abstract

The effect of pedigree errors on estimated breeding value and genetic gain for a sex-limited trait with heritability of 0.25 was evaluated. Ten populations of 100,000 milking cows were simulated with correct paternity identification for all animals, and 10 populations were simulated with 10% incorrect paternal identification. The initial populations consisted of 100,000 unrelated individuals, and simulations were continued for 20 yr. The BLUP genetic evaluations were computed every year by an animal model analysis for each complete population. Estimated breeding values for the populations with 10% incorrect paternity were biased, especially in the later generations. Genetic gains were 4.3% higher with correct paternity identification. Reduction of pedigree errors by paternity confirmation of daughters of test sires by DNA microsatellites may result in considerable economic benefits, depending on the cost of testing in each country.

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... A large body of approaches were developed to explore G Â E at phenotypic level. It includes linear and linear mixed models [5], graphical approaches [138], stability regression [139], genetic covariance functions [140], and multivariate mixed models [141]. ...
... With the advent of GS, several studies investigated the interest of accounting for crossbred performances in CS in addition or instead of purebred performances. Recently, Wientjes et al. [139] explored how to optimize CS in this context using simulations but focused mainly on the crossing design used to generate the crossbred individuals from the purebred and not on the composition of the crossbred CS itself. For allogamous plant species such as maize or sunflower, the breeding objective is to produce single-cross hybrid varieties from two inbred lines, each selected in complementary groups. ...
... Stuber and Cockerham [139] showed that gene substitution effects can be defined within or across populations, and that both approaches are equivalent if all the nonadditive effects are accounted for. Therefore, Christensen et al. [140] proposed an alternative model called the "common genetic" approach, and described the genomic relationship matrix for genotyped and nongenotyped individuals following a single-step rationale [28,29]. ...
Chapter
This chapter provides an overview of the genomic selection progress in long-lived forest tree species. Factors affecting the prediction accuracy in genomic prediction are assessed with examples from empirical studies. Infrastructure and resources required for the implementation of genomic selection are evaluated. Some general guidelines are provided for the successful application of genomic selection in forest tree breeding programs.
... These errors caused heritability to be underestimated (Van Vleck, 1970;Geldermann et al., 1986) and reduced dispersion of EBV (Geldermann et al., 1986). Additionally, pedigree errors favored selection of young bulls instead of proven bulls (Israel and Weller, 2000), creating bias when selecting across generations. Bias also was created when selecting animals across countries, causing selection of domestic instead of foreign bulls (Banos et al., 2001). ...
... Bias also was created when selecting animals across countries, causing selection of domestic instead of foreign bulls (Banos et al., 2001). Pedigree errors decreased genetic gain by 4 to 17% (Geldermann et al., 1986;Israel and Weller, 2000) because of these issues. The lost genetic gain may be recovered by better modeling pedigree accuracy, enabling fair comparisons among animals. ...
... Variation of EBV was similar between models, with slightly more variation with the uncertain parentage model. Previously, pedigree errors reduced the variance of EBV and increased regression coefficients (Israel and Weller, 2000;Banos et al., 2001). Hence, accounting for pedigree accuracy helped compensate for the reduction in dispersion caused by pedigree errors. ...
Article
The objective of this study was to model differences in pedigree accuracy caused by selective genotyping. As genotypes are used to correct pedigree errors, some pedigree relationships are more accurate than others. These accuracy differences can be modeled with uncertain parentage models that distribute the paternal (maternal) contribution across multiple sires (dams). In our case, the parents were the parent on record and an unknown parent group to account for pedigree relationships that were not confirmed through genotypes. Pedigree accuracy was addressed through simulation and through North American Holstein data. Data were simulated to be representative of the dairy industry with heterogeneous pedigree depth, pedigree accuracy, and genotyping. Holstein data were obtained from the official evaluation for milk, fat, and protein. Two models were compared: the traditional approach, assuming accurate pedigrees, and uncertain parentage, assuming variable pedigree accuracy. The uncertain parentage model was used to add pedigree relationships for alternative parents when pedigree relationships were not certain. The uncertain parentage model included 2 possible sires (dams) when the sire (dam) could not be confirmed with genotypes. The 2 sires (dams) were the sire (dam) on record with probability 0.90 (0.95) and the unknown parent group for the birth year of the sire (dam) with probability 0.10 (0.05). An additional set of assumptions was tested in simulation to mimic an extensive dairy production system by using a sire probability of 0.75, a dam probability of 0.85, and the remainder attributed to the unknown parent groups. In the simulation, small bias differences occurred between models based on pedigree accuracy and genotype status. Rank correlations were strong between traditional and uncertain parentage models in simulation (≥0.99) and in Holstein (≥0.99). For Holsteins, the estimated breeding value differences between models were small for most animals. Thus, traditional models can continue to be used for dairy genomic prediction despite using genotypes to improve pedigree accuracy. Those genotypes can also be used to discover maternal parentage, specifically maternal grandsires and great grandsires when the dam is not known. More research is needed to understand how to use discovered maternal pedigrees in genetic prediction.
... Genealogical records in aquatic selective breeding programs have the potential to be more erroneous due to large family sizes and difficulties in retaining pedigree throughout the production cycle, particularly in juvenile stages. Genealogical errors lead to inaccurate estimated breeding values (EBVs), a reduction in genetic gain, and inaccurate estimates of inbreeding within the selective breeding program (Banos et al., 2001;Israel and Weller, 2000). The degree to which these inaccuracies affect genetic gains is correlated with the percentage of errors and the length of the selective breeding program. ...
... In general, as genealogical errors within the population increase, the number of inaccuracies detected are expected to rise (Banos et al., 2001). In order to reduce these errors, accurate molecular data can be used to correct genealogical records, decrease inbreeding occurrences, and improve estimates of EBVs and genetic gains (Israel and Weller, 2000;Munoz et al., 2014;Visscher et al., 2002). ...
... Accurate genealogical records are essential in optimizing the genetic gain obtained within a selective breeding program. Any inaccuracies in pedigree information will erode the accuracy of EBVs and diminish the rate of genetic improvement within the line (Banos et al., 2001;Israel and Weller, 2000). If recorded pedigrees are not available, or in question, molecular based parentage analyses provide a practical and efficient means to identify parent and offspring relationships within a selective breeding program. ...
... Genealogical information is an essential tool for carrying out any genetic breeding program. Its accuracy and completeness influence the reliability of EBV as well as the estimation and control of inbreeding rates (Israel and Weller, 2000;Harder et al., 2005;Heaton et al., 2014) and genetic standard deviation (Banos et al., 2001). ...
... Similar results have been reported for other populations. A stochastic simulation with a 10% paternal error rate and a trait with a heritability of 0.25 showed that genetic gain decreased by 4.3% per year (Israel and Weller, 2000). In a simulation with the same heritability and error rate, genetic variance decreased approximately 8% for progeny-tested bulls and approximately 14% for progeny-test bulls (Harder et al., 2005). ...
... Banos et al. (2001) determined the effect of paternal rate error for US Holstein cows (11%) on genetic evaluation and estimation of genetic parameters and EBV for bulls across countries. Their results showed a higher decrease (approximately 11% for production traits) in national genetic gain than that reported by Israel and Weller (2000) and up to 18% in losses of genetic gain for international evaluations. Additionally, standard deviations of sire transmitting ability decreased by 8 to 9% and estimates of inbreeding coefficients were reduced by approximately 7 to 14% (Banos et al., 2001). ...
Article
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.
... They added that, the proportion of wrong paternity decreased the estimates of genetic para meters. Previous studies by Israel and Weller [10], Christensen et al [11], and Gelderman et al [12] showed the consequences of PE or incorrect sire information in estimation of genetic parameters, for example, decreased value of parent trans mitting ability for a cow and her relatives, reduced EBV, h 2 , and genetic gain for meat and milk traits in cattle popula tions. In addition, biased estimates of EBV and genetic gain for both bulls and cows have been reported [10,1315]. ...
... Previous studies by Israel and Weller [10], Christensen et al [11], and Gelderman et al [12] showed the consequences of PE or incorrect sire information in estimation of genetic parameters, for example, decreased value of parent trans mitting ability for a cow and her relatives, reduced EBV, h 2 , and genetic gain for meat and milk traits in cattle popula tions. In addition, biased estimates of EBV and genetic gain for both bulls and cows have been reported [10,1315]. Al though, the effect of PEs on the accuracy of EBV and genetic estimates might not be available in Korean Hanwoo cattle. As a result, the knowledge of PEs on the accuracy of genetic parameters (EBVs, genetic gain, and h 2 ) would be useful in the Hanwoo beef industry. ...
... Nwogwugwu et al (2020) Asian-Australas J Anim Sci 00: [1][2][3][4][5][6][7][8][9][10][11] of EBV. ...
Article
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Objectives: 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 1298 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 1650 animals from the pedigree data. A REML 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.
... In extensive sheep farming systems, it is difficult to collect accurate relationship information due to the simultaneous presence of more rams in the same group (Hayes & Goddard, 2008). Missing or incomplete pedigree information, especially on the side of the pedigree with larger progeny size, can severely bias-variance components estimation (Israel & Weller, 2000;Visscher, Woolliams, Smith, & Williams, 2002). However, the genomic information may compensate for pedigree problems (Hayes & Goddard, 2008). ...
... Banos, Wiggans, and Powell (2001) showed the paternity misidentification is common in several animal populations; Visscher et al. (2002) estimated 10% overall pedigree error rate in United Kingdom dairy populations; Legarra et al. (2014) reported unknown fatherhood of 50% and 20% for Latxa and Manech/Basco-Béarnaise sheep breeds, respectively. Missing or incomplete pedigree information, especially regarding the sire assignment, is a big problem in variance components estimation (Banos et al., 2001;Israel & Weller, 2000;Visscher et al., 2002). Additionally, in small or autochthonous populations pedigree is not even recorded (Mészáros et al., 2015). ...
Article
We investigated the effects of different strategies for genotyping populations on variance components and heritabilities estimated with an animal model under restricted maximum likelihood (REML), genomic REML (GREML), and single‐step GREML (ssGREML). A population with 10 generations was simulated. Animals from the last one, two or three generations were genotyped with 45,116 SNP evenly distributed on 27 chromosomes. Animals to be genotyped were chosen randomly or based on EBV. Each scenario was replicated five times. A single trait was simulated with three heritability levels (low, moderate, high). Phenotypes were simulated for only females to mimic dairy sheep and also for both sexes to mimic meat sheep. Variance component estimates from genomic data and phenotypes for one or two generations were more biased than from three generations. Estimates in the scenario without selection were the most accurate across heritability levels and methods. When selection was present in the simulations, the best option was to use genotypes of randomly selected animals. For selective genotyping, heritabilities from GREML were more biased compared to those estimated by ssGREML, because ssGREML was less affected by selective or limited genotyping.
... Inaccurate parentage recording is known to contribute to biased variance components (Van Vleck, 1970) and biased genetic evaluations (Israel and Weller, 2000;Banos et al., 2001), both of which subsequently affect genetic gain (Visscher et al., 2002). Unbiased estimates of coancestry among candidate mates require accurate pedigree recording. ...
... The importance of parentage assignment is well established in terms of more precise estimates of genetic parameters (Van Vleck, 1970) and thus the proper partitioning of variances into their causal components, as well as calculated expected responses to selection. Accurate parentage assignment, of course, also impacts the precision of genetic evaluations (Israel and Weller, 2000;Banos et al., 2001), although the impact of the extent of parentage mis-identification is a function of the heritability of the trait in question and also the quantity of available data for a given animal (Visscher et al., 2002). Numerous non-genomic approaches have been proposed as strategies to improve the assignment of parents to offspring. ...
Article
Full-text available
The generally low usage of artificial insemination and single-sire mating in sheep, compounded by mob lambing (and lambing outdoors), implies that parentage assignment in sheep is challenging. The objective here was to develop a low-density panel of single nucleotide polymorphisms (SNPs) for accurate parentage verification and discovery in sheep. Of particular interest was where SNP selection was limited to only a subset of chromosomes, thereby eliminating the ability to accurately impute genome-wide denser marker panels. Data used consisted of 10,933 candidate SNPs on 9,390 purebred sheep. These data consisted of 1,876 validated genotyped sire–offspring pairs and 2,784 validated genotyped dam–offspring pairs. The SNP panels developed consisted of 87 SNPs to 500 SNPs. Parentage verification and discovery were undertaken using 1) exclusion, based on the sharing of at least one allele between candidate parent–offspring pairs, and 2) a likelihood-based approach. Based on exclusion, allowing for one discordant offspring–parent genotype, a minimum of 350 SNPs was required when the goal was to unambiguously identify the true sire or dam from all possible candidates. Results suggest that, if selecting SNPs across the entire genome, a minimum of 250 carefully selected SNPs are required to ensure that the most likely selected parent (based on the likelihood approach) was, in fact, the true parent. If restricting the SNPs to just a subset of chromosomes, the recommendation is to use at least a 300-SNP panel from at least six chromosomes, with approximately an equal number of SNPs per chromosome.
... However, in French sheep populations the rate of known sires can vary widely, from a few percent in hardy breeds reared in high mountain areas up to 100% in specialized meat and dairy breeds. The lack of complete pedigrees and misidentification of sires affect the accuracy of genetic evaluation and consequently the efficiency of breeding programs [2,9,16,29]. By increasing the percentage of known sires, the genetic gain of a breeding scheme is increased [24]. ...
Article
Full-text available
Background The efficiency of breeding programs partly relies on the accuracy of the estimated breeding values which decreases when pedigrees are incomplete. Two reproduction techniques are mainly used by sheep breeders to identify the sires of lambs: animal insemination and natural matings with a single ram per group of ewes. Both methods have major drawbacks, notably time-consuming tasks for breeders, and are thus used at varying levels in breeding programs. As a consequence, the percentage of known sires can be very low in some breeds and results in less accurate estimated breeding values. Results In order to address this issue and offer an alternative strategy for obtaining parentage information, we designed a set of 249 SNPs for parentage assignment in French sheep breeds and tested its efficiency in one breed. The set was derived from the 54 K SNP chip that was used to genotype the thirty main French sheep populations. Only SNPs in Hardy-Weinberg equilibrium, displaying the highest Minor Allele Frequency across all the thirty populations and not associated with Mendelian errors in verified family trios were selected. The panel of 249 SNPs was successfully used in an on-farm test in the BMC breed and resulted in more than 95% of lambs being assigned to a unique sire. Conclusion In this study we developed a SNP panel for assignment that achieved good results in the on-farm testing. We also raised some conditions for optimal use of this panel: at least 180 SNPs should be used and a minute preparation of the list of candidate sires. Our panel also displays high levels of MAF in the SheepHapMap breeds, particularly in the South West European breeds. Electronic supplementary material The online version of this article (doi:10.1186/s12863-017-0518-2) contains supplementary material, which is available to authorized users.
... Studies indicated that using SE in the context of multiclonal forestry can result in genetic gains of as much as 45% for some traits in white spruce (Park, 2002). A simulation study showed that pedigree errors corresponding to a pollen contamination of 10% could decrease the genetic gain expected by about 4% (Israel and Weller, 2000). However, this reduction could be more drastic considering the specific second-generation selection strategy currently planned and being implemented for white spruce in Quebec. ...
Article
Full-text available
Biological material is at the forefront of research programs, as well as application fields such as breeding, aquaculture, and reforestation. While sophisticated techniques are used to produce this material, all too often, there is no strict monitoring during the “production” process to ensure that the specific varieties are the expected ones. Confidence rather than evidence is often applied when the time comes to start a new experiment or to deploy selected varieties in the field. During the last decade, genomics research has led to the development of important resources, which have created opportunities for easily developing tools to assess the conformity of the material along the production chains. In this study, we present a simple methodology that enables the development of a traceability system which, is in fact a by-product of previous genomic projects. The plant production system in white spruce (Picea glauca) is used to illustrate our purpose. In Quebec, one of the favored strategies to produce elite varieties is to use somatic embryogenesis (SE). In order to detect human errors both upstream and downstream of the white spruce production process, this project had two main objectives: (i) to develop methods that make it possible to trace the origin of plants produced, and (ii) to generate a unique genetic fingerprint that could be used to differentiate each embryogenic cell line and ensure its genetic monitoring. Such a system had to rely on a minimum number of low-cost DNA markers and be easy to use by non-specialists. An efficient marker selection process was operationalized by testing different classification methods on simulated datasets. These datasets were generated using in-house bioinformatics tools that simulated crosses involved in the breeding program for which genotypes from hundreds of SNP markers were already available. The rate of misidentification was estimated and various sources of mishandling or contamination were identified. The method can easily be applied to other production systems for which genomic resources are already available.
... While the initial cost and availability of each new technology has hindered their adaption, their increasing ability to reduce pedigree errors cannot be ignored. A 10% pedigree error rate can have a 6-13% effect on the inbreeding coefficient, 11-18% reduction on breeding value trends, 2-3% loss in selection response (Banos et al., 2001;Visscher et al., 2002), and a downward basis on heritability estimates (Israel and Weller, 2000). While sire error rates have been estimated at >7% in national herds, dam errors and missing parental information can be substantial, especially in commercial herds (Harder et al., 2005;Sanders et al., 2006) and their effects are additive (Sanders et al., 2006). ...
Article
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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.
... e.g., family F18. Therefore, breeding value scores were more accurate and stable for selection while conducting Qi value with the breeding value concerned (Israel C et al., 2000;Pan XQ, 2014). Selected families could be utilized as excellent subjects for the establishment of improved seed orchards, and it could also provide the theoretical basis for excellent family selection and evaluation of L. kaempferi. ...
Article
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Tree height and diameter at breast height of 30 half-sib Larix kaempferi families were analyzed at different ages. Analysis of variance revealed a significant difference in growth among dif­ferent families. Phenotypic variation coefficients of the traits tree height and diameter at breast height among families of different ages ranged from 11.04 % to 31.74 % and 19.01 % to 19.83 %, respectively. Average heritability of tree height and diameter at breast height ranged from 0.87 to 0.96 and 0.93 to 0.96, respectively. Significant positive correlations were obser­ved among all traits at different ages. By the method of multip­le-traits comprehensive, six families (L18, L12, L8, L3, L25 and L20) were selected as being elite using a 20 % selection ratio at 12 years of age. Average values of these elite families were 11.15 % and 16.83 % higher than the total average for height and diameter at breast height, and genetic gains were 10.53 % and 15.79 %, respectively. Forty five elite individual plants were selected using a 5 % selection ratio which were 23.47 % and 24.90 % higher than the overall average for height and diame­ter at breast height, respectively.
... Incorrect paternity assignment in cattle can significantly affect the rates of genetic gain. A 10% error rate in paternity determination reduces genetic gain by 4.3% per year and cumulative genetic gain by 3.5% after 20 years (Israel and Weller, 2000). Misidentification should thus be controlled to < 8% to ensure > 1% genetic gain each year (Banos et al., 2001). ...
Article
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.
... To our knowledge, no previous sheep study has investigated the impact of mis-recording of phenotypic data on genetic evaluations for lambing traits. The impact of pedigree errors on genetic evaluations has, however, been studied extensively in dairy cattle and results suggest that parentage misidentification will result in downward biased heritability estimates (Van Vleck, 1970;Parlato and Van Vleck, 2012) and reduced rates of genetic gain (Israel and Weller, 2000;Banos et al., 2001). In contrast, the direct and maternal heritability estimates reported in the current study did not differ between the Accurate and Inaccurate Scenario (Table 3) but the proportion of data manipulated in the Inaccurate Scenarios was low (~0.02). ...
Article
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The objective of the present study was to quantify the impact of the systematic environmental effects of both birth and rearing type on pre-weaning lamb live weight, and to evaluate the repercussions of inaccurate recording of birth and rearing type on subsequent genetic evaluations. A total of 32,548 birth weight records, 35,770 forty-day weight records and 32,548 records for average daily gain (ADG) between birth and 40-day weight from the Irish national sheep database were used. For each lamb, a new variable, birth-rearing type, reflecting both the birth and rearing type of a lamb was generated by concatenating both parameters. The association between birth-rearing type and birth weight, 40-day weight, and ADG was estimated using linear mixed models. The repercussions of inaccurate recording of birth type were determined by quantifying the impact on sire estimated breeding value (EBV; with an accuracy of ≥ 35%), where one of the lambs born in a selection of twin litter births was assumed to have died at birth but the farmer recorded the birth and rearing type as a singleton. The heaviest mean birth weight was associated with lambs born and subsequently reared as singles (5.47 kg); the lightest mean birth weight was associated with lambs born and reared as triplets (4.10 kg). The association between birth-rearing type and 40-day weight differed by dam parity (P < 0.001). Lambs reared by first parity dams as singles, irrespective of birth type were, on average, heavier at 40-day weighing than lambs reared as multiples, but as parity number increased, single-born lambs reared as twins outperformed triplet-born lambs reared as singles. Irrespective of the trait evaluated, the correlation between sire EBV estimated from the accurately recorded data and sire EBV estimated from the data with recording errors was strong ranging from 0.93 (birth weight) to 0.97 (ADG). The EBV for sires with progeny data manipulated were 0.14 kg, 0.34 kg and 5.56 g/d less for birth weight, 40-day weight and ADG, respectively, compared to their equivalent EBV calculated using accurately recorded data. Results from this study highlight the importance of precise recording of birth-rearing type by producers for the generation of accurate genetic evaluations.
... Visscher et al., (2002) for UK dairy cows estimated an overall pedigree error rate of 10% and predicted this would result in a loss of selection response of 2 to 3%. For the same pedigree error rate, Israel and Weller, (2000) predicted a 4.3% loss in genetic response. Banos et al., (2001) showed that with 11% pedigree errors there was a reduction in the Estimated Breeding Values (EBVs) genetic trends of 11 to 18%. ...
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The aim of this study was to investigate the effects of animal trait, breed combination, and climate on the expressed levels of heterosis in crossbreeding schemes using tropical cattle. A meta-analysis of 42 studies was carried out with 518 heterosis estimates. In total, 62.5% of estimates were found to be significantly different from zero, the majority of which (89.8%) were beneficial for the studied trait. Trait and breed combination were shown to have a significant effect on the size of heterosis (P < 0.001 and P = 0.044, respectively). However, climate did not have a significant effect. Health, longevity, and milk production traits showed the highest heterosis (31.84 ± 10.73%, 35.13 ± 14.35%, and 35.15 ± 3.29%, respectively), whereas fertility, growth, and maternal traits showed moderate heterosis (12.02 ± 4.10%, 12.25 ± 2.69%, and 15.69 ± 3.26%, respectively). Crosses between breeds from different types showed moderate to high heterosis ranging from 9.95 ± 4.53% to 19.53 ± 3.62%, whereas crosses between breeds from the same type did not express heterosis that was significantly different from zero. These results show that heterosis has significant and favorable impact on productivity of cattle farming in tropical production systems, particularly in terms of fitness but also milk production traits.
... Previous studies indicated that 4.3% of annual losses with regard to genetic gain during dairy breeding were caused by pedigree errors (10%), compared to simulation analysis of accurate paternity determination data (Israel & Weller, 2000). In fact, the pedigree error rate in yaks was high due to incorrect paternity as yaks feed primarily by grazing, thwarting parentage attribution. ...
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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.
... Furthermore, the differences of genetic gains in the different traits between cows and bulls might be due to the differences of sexes and also the effects of differences in selection intensity. The genetic gains can be differed by the animal model parameters, selection intensities and with the differences of sexes were mentioned by other researchers (Israel and Weller [27], Ntombizakhe Mpotu et al. [28]). ...
Article
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The study was undertaken to investigate the use of several economic indices including QTL assisted selection for the improvement of production and health trait of dairy cattle under Bangladesh conditions. Five traits (lactation milk, fat, protein yield, somatic cell score (SCS) and direct mastitis) were simulated over 14 generations, considering three selection objectives (selection for direct mastitis; milk SCS; and the combination of direct mastitis and SCS). In addition the selection objective for SCS was simulated incorporating marker/QTL information. Genetic gains per generation for different traits were calculated by plotting the average true breeding values (TBVs) and estimated breeding values (EBVs) over generation. Selection of replacement bulls and cows were based on total merit. The genetic gains based on TBVs and EBVs of cows for milk, fat and protein yield in three selection objectives with no QTL information were similar, but gains were higher with QTL- assisted selection implemented for SCS. Genetic gains of cows for different traits based on TBVs were higher than bulls, but reverse results were obtained for bulls. The genetic trends for all traits in cows were similar in all selection objectives. However, for bulls distinct differences were observed between the QTL and no QTL-assisted selection schemes and also between SCS and the combination of SCS and direct mastitis selection objectives. Higher correlations between TBVs and EBVs for lactation milk and fat yield for both cows and bulls were found under QTL-assisted selection compared to the no QTL-assisted selection schemes. The QTL-assisted selection scheme showed higher rates of genetic gain for lactation milk, fat and protein yields than no QTL-assisted selection. However, it does not affect SCS and index values from any of the selection objectives or selection schemes. The QTL-assisted selection scheme has a positive effect on milk production and mastitis control.
... France, the sire misidentification rate for meat sheep breeds reached 7.7% in 2011 (Raoul, 2011). Although most of the studies did not quantify these effects on the genetic gain, Israel and Weller (2000) reported a loss of genetic gain of 4.3% with 10% of incorrect paternity for a trait with a heritability of 0.25. In a similar manner, Harder et al. (2005) predicted a decrease of the response to selection for proven sires (8.6%) and males being progeny tested (12.6%) for a trait with a heritability of 0.25 when 40% of the sire information was missing. ...
Article
In sheep and goat breeding programs, the proportion of females for which the sire is known (known paternity rate [KPR]) can be very low. In this context, paternity assignment using SNP is an attractive tool. The annual genetic gain (AGG) is impacted by the accuracy of the EBV. In populations with a low KPR, the number of known relatives for a given individual is low, and the EBV that are based on this information are imprecise. However, the impact of partially known paternal filiations, in terms of potential genetic and economic losses, has never been quantitatively evaluated in situations where natural mating is the main reproductive mode. A deterministic model was developed to assess, for a panel of real breeding programs, the influence of the female KPR on the AGG and economic benefit. First, males were divided into categories according to their status (natural mating or AI sire) and breeding cycle and females according to parity, sire status (including unknown sire), and breeding cycle of the sire. Second, a demographic model described, for each category, the accumulation of known records for individuals and their close relatives. The output from this model was used to compute the average accuracy of the EBV per category. Then, a genetic model based on the gene flow between categories over time was described. Using the average accuracy of EBV per category, it provided the asymptotic AGG of the nucleus given its KPR. In the economic studies, changes to the mean genetic values in the nucleus and the commercial population after an increase in KPR and various gain:cost ratios (monetary gain due to an extra genetic SD of the selected trait divided by the cost of 1 assignment) were considered. Relative profit and payback periods were computed. We showed that SNP-based parentage assignment aimed at increasing the female KPR was not always profitable and that the type of breeding program and the size of the commercial population should be taken into consideration. Notably, achieving a profit was largely dependent on obtaining a favorable gain:cost ratio. The maximum supplementary AGG (16.9%) was obtained for breeding programs using only natural mating. In such programs without AI, a gain:cost ratio of 5 was needed to make assignment profitable at the nucleus level whereas a gain:cost ratio of 2 was sufficient if the nucleus represented a third of the total population.
... DNA testing has been widely used in the breeding of high-value animals (such as horses) to monitor the accuracy of pedigree records. Pedigree verification is an important aspect of the use of molecular markers in several breeding programs [10] lead to substantial opportunities for increasing accuracy of estimated breeding values (EBV) and genetic gain [11] ...
... As livestock improvement is enhanced by using information on relatives, a requirement for such programmes has been parentage recording. However, incorrect parentage assignment may be up to 15% on commercial sheep farms , which will result in a lower genetic gain than either possible or predicted (Israel and Weller, 2000). Molecular information can be used to provide information about parentage. ...
Article
Molecular information is finding increasing use in sheep and goat breeding programs, as systems become available to make use of this information and the cost of obtaining the information declines. Genetic markers have been used for parentage verification or determination, for product tracing or brand protection, and for assisting selection decisions for production or breeding stock. The predominant uses of markers in selection have been in selecting for scrapie resistance, high prolificacy and for increased size of higher value muscles. Most of these applications of selection have placed preferential emphasis on the favourable gene variant, and quantitative information is used to select within genotype. The sophisticated use of molecular and quantitative information on an industry-wide scale will require robust systems that can cope with imperfect data as well as development of selection indices to take full advantage of the information. The prospect for further increases in the use of molecular information looks bright.
... The presence of such errors can lead to incorrect estimates of the additive variance, causing a decrease in the BLUP-BV prediction accuracy (Ericsson, 1999;Banos et al., 2001;Sanders et al., 2006). In traditional BLUP-based selection, it has been reported that decreased BV accuracy reduces genetic gains by 4.3 to 17% (Geldermann et al., 1986;Israel and Weller, 2000). ...
Article
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Quantitative genetic analyses aim to estimate genetic parameters and breeding values to select superior parents, families, and individuals. For these estimates a relationship matrix derived from the pedigree typically is used in a mixed model framework. However, breeding is a complex, multistep process and errors in the pedigree are common. Because errors reduce the accuracy of genetic parameter estimates and affect genetic gain, it is important to correct these errors. Here we show that a realized relationship matrix (RRM) derived from single nucleotide polymorphism markers based on the normality of the relationship coefficients can be used to correct pedigree errors. For a loblolly pine (Pinus taeda L.) breeding population, errors in the pedigree were detected and corrected with the RRM. With the corrected pedigree, best linear unbiased predictor (BLUP) models fit the data significantly better for 14 out of 15 traits evaluated, and the predictive ability of the genomic selection models using ridge regression BLUP increased for 13 traits. The corrected pedigree based on the normality of the relationship coefficients improves accuracy of traditional estimations of heritability and breeding values as well as genomic selection predictions. As more breeding programs begin to use genomic selection, we recommend first using the dense panel of markers to correct pedigree errors and then using the improved information to develop genomic selection prediction models.
... Progeny test based on halfsib records and genetic markers can greatly enhance the accuracy of selection (Spelman et al. 1999). The use of genetic markers also reduce errors in parentage determination (Israel and Weller 2000). Meuwissen and van Arendonk (1992) reported that inclusion of marker information increases the accuracy of sire evaluations and increases the rate of genetic gain by 5% when the markers explained 25% of the genetic variance. ...
Article
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A reference family consisting of 12 half sib sire families were created for the identification of QTLs for milk yield in buffaloes. Daughters were recorded for monthly test day milk yield. The number of daughters per sire varied from 50 to 335 daughters per sire. Seventy nine polymorphic microsatellite markers located on 8 chromosomes were genotyped for 2281 daughters of the 12 sires. Whole chromosome scanning was done using single marker analysis and interval mapping using three different algorithms. The analysis was carried out sire family wise. QTLs (63) were identified in single marker analysis and 32 QTLs were identified using interval mapping. The significance of LOD score was tested using permutation tests. The metaQTL analysis was carried out to find out the consensus chromosomal regions associated with milk yield in buffaloes. Five models were utilised and the best was selected on the basis of Akaike Information content. Total 23 chromosomal regions were identified for milk yield in buffaloes. 2 metaQTL chromosomal regions were identified on buffalo chromosome BBU2q; 3 metaQTLs each on buffalo chromosomes BBU8, BBU10 and BBU15 and 4 metaQTL regions each on BBU1q, BBU6, BBU9.
... In order to avoid such situation genetic parameters used in constructing a selection index and thus estimating genetic gain was assumed ahead based on same breed and most phenotypically as well as geographically related. This procedure was performed by many researchers 36,37 . In order to overcome such a problem, another simulated scenario were performed assuming changes in the heritabilities values of studied criteria under investigation, keeping the genetic variance, repeatabilities and the genetic and phenotypic correlations constant. ...
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This simulation study aimed to predict potential breeding program of increasing milk and meat production of Hejaz goat in subtropical areas. Computer ZPLAN + software was used to simulated breeding program of five-year duration. ZPLAN + was provided by a wide range of performance, phenotypic and genetic parameters of studied selection criteria and breeding objectives; milk and meat production. Furthermore, a close breeding scheme was assumed of ten selection groups where nucleus buck's genetic material was disseminated into multiplier and commercial unites. The result of simulated scenario was increasing milk and meat productivity by 0.199 and 0.107 kg, respectively, under assumed subtropical conditions where Hejaz goats habitat. Therefore, such breeding program was found sustainable in short term in which genetic gain showed reasonable increment regardless the trait's genetic makeup or heritability values. On the other hand, it has been found that genetic gain was sensitive to changes in heritability values. The change of heritability values varied from 0.10 to 0.40 for total milk and meat production. The changes in the magnitudes of the genetic gain stress the importance of using more reliable estimates of these traits in the breeding program. Further work on application of long-term breeding program is needed and updated estimates of genetic and economic values for Hejaz goat breed is also needed.
... Most of these studies used microsatellite markers, but in recent years the focus has shifted towards the use of single nucleotide polymorphisms (SNPs) (see Weinman et al. 2015 for a comparison). Identifying incorrect pedigrees are of importance in livestock populations as it adversely influences genetic gains (Israel and Weller 2000). Although lovebird species are not under directional selection for increased genetic gain, incorrect pedigrees will still negatively affect the populations' general fitness. ...
Article
The genus Agapornis consists of nine small African parrot species that are globally well known as pets, but are also found in their native habitat. Illegal trapping, poaching and habitat destruction are the main threats these birds face in the wild. In aviculture, Agapornis breeding is highly popular all across the globe. Birds are mainly selected based on their plumage colour variations but very little molecular research has been conducted on this topic. There are 30 known colour variations amongst the nine species and most of these are inherited as Mendelian traits. However, to date none of the genes or polymorphisms linked to these variations have been identified or verified. Due to unethical breeding practices, the need for the development of molecular tests such as identification verification tests or species identity tests is growing. Future research is paramount to ensure the conservation of wild populations as well as aiding breeders in improving breeding strategies.
... While the initial cost and availability of each new technology has hindered their adaption, their increasing ability to reduce pedigree errors cannot be ignored. A 10% pedigree error rate can have a 6-13% effect on the inbreeding coefficient, 11-18% reduction on breeding value trends, 2-3% loss in selection response (Visscher et al., 2002a, Banos et al., 2001, and a downward basis on heritability estimates (Israel and Weller, 2000). While sire error rates have been estimated at >7% in national herds, dam errors and missing parental information can be substantial, especially in commercial herds (Sanders et al., 2006, Harder et al., 2005 and their effects are additive (Sanders et al., 2006). ...
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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) based verification in Bos taurus cattle has been the ISAG 100 and 200 SNP panels. While these SNP sets have provided an increased level of parentage accuracy over microsatellite markers (MS), they can validate the wrong parent for an animal 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 Bos 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) analysed 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 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 a genomic sample QC pipeline to deal with the unique challenges of >1,000,000 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.
... Pedigree errors can have a significant impact on the accuracy and capacity for breeding value estimation, response to selection and can result in incorrect estimations of family diversity on farm. Studies investigating the effects of pedigree errors circa 10 % have reported losses in genetic gain of 2-4 % (Israel and Weller, 2000;Visscher et al., 2002). In such cases, the value of DNA parentage analysis to accurately construct pedigrees, such as the analysis presented in this study, is highlighted. ...
Article
To enable cumulative increases in aquaculture productivity, structured and efficient selective breeding programs are required. These are contingent on the management of genetic resources within the breeding population though the attainment of accurate pedigree information which can be provided by DNA-based parentage analysis. This study developed a SNP panel for greenlip abalone, Haliotis laevigata, from DArTSeq data produced from a genetic audit of greenlip abalone (n = 336) from five farms. The initial dataset consisted of 15,320 SNPs. Strict filtering on SNP quality control metrics was conducted to select the most informative 1,004 SNPs for the design of a DArTag™ genotyping panel for greenlip abalone. Sixteen broodstock and 1035 hatchery produced progeny were genotyped using the 1,004 SNP DArTag™ panel. The resulting genotypes were filtered, to produce 705 high performing SNPs. In silico parentage analysis using subsets of these SNPs (highest ranked by polymorphic information content) revealed that the inclusion of < 50 SNPs were satisfactory to resolve parentage for 10,000 simulated progeny to up to 200 candidate parents. The resolving power of the panel was also assessed under high levels of inbreeding (0–50 %) and relatedness (0–50 %) between candidate parents, and conditions of missing parental genotypes (10–50 %) in silico. Under all levels of inbreeding, relatedness and missing parental genotypes simulated, the panel was able to accurately assign parental pairs to the offspring. To validate these in silico results, parentage analysis of the hatchery produced progeny of the 16 candidate broodstock was conducted using both CERVUS and APIS. Complete parentage was assigned to all experimental progeny, with 100 % consensus between the two methods used. This study indicates this panel will serve as an efficient and cost-effective tool for accurate pedigree establishment for greenlip abalone.
... However, the success of genetic evaluations systems is directly affected by the accuracy of pedigrees. Complete pedigree information is a prerequisite to get accurate EBVs, correctly rank parents and offspring and maximize the genetic gain (Israel & Weller, 2000;Raoul et al., 2016). In this sense, the proportion of known sires is very low in Spanish meat sheep populations because the management (extensive or semi-extensive farming) relies very little on artificial insemination (AI) or natural mating with a single ram per group of ewes. ...
Article
Aim of study: To validate two existing single nucleotide polymorphism (SNP) panels for parentage assignment in sheep, and develop a cost effective genotyping system to use in some North-Eastern Spanish meat sheep populations for accurate pedigree assignment.Area of study: SpainMaterial and methods: Nine sheep breeds were sampled: Rasa Aragonesa (n=38), Navarra (n=39), Ansotana (n=41), Xisqueta (n=41), Churra Tensina (n=38), Maellana (39), Roya Bilbilitana (n=24), Ojinegra (n=36) and Cartera (n=39), and these animals were genotyped with the Illumina OvineSNP50 BeadChip array. Genotypes were extracted from the sets of 249 SNPs and 163 SNPs for parentage assignment designed in France and North America, respectively. Validation of a selected cost-effective genotyping panel of 158 SNPs from the French panel were performed by Kompetitive allele specific PCR (KASP). Additionally, some functional SNPs (n=15) were also genotyped.Main results: The set of 249 SNPs for parentage assignment showed better diversity, probability of identity, and exclusion probabilities than the set of 163 SNPs. The average minor allele frequency for the set of 249, 163 and 158 SNPs were 0.41 + 0.01, 0.39 + 0.01 and 0.42 + 0.01, respectively. The parentage assignment rate was highly dependent to the percentage of putative sires genotyped.Research highlights: The described method is a cost-effective genotyping system combining the genotyping of SNPs for the parentage assignment with some functional SNPs, which was successfully used in some Spanish meat sheep breeds.
... Pedigree errors resulted in incorrect estimates of variance components and heritabilities and decreased breeding value accuracies. The genetic gains of breeding populations could be reduced by 4.3-17% when using incorrect pedigree information [37,42,43]. In the current study, the SNP-corrected pedigree considerably increased the accuracy of genomic selection, similar to that reported by Muñoz et al. [44]. ...
Article
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Background: Non-key traits (NKTs) in radiata pine (Pinus radiata D. Don) refer to traits other than growth, wood density and stiffness, but still of interest to breeders. Branch-cluster frequency, stem straightness, external resin bleeding and internal checking are examples of such traits and are targeted for improvement in radiata pine research programmes. Genomic selection can be conducted before the performance of selection candidates is available so that generation intervals can be reduced. Radiata pine is a species with a long generation interval, which if reduced could significantly increase genetic gain per unit of time. The aim of this study was to evaluate the accuracy and predictive ability of genomic selection and its efficiency over traditional forward selection in radiata pine for the following NKTs: branch-cluster frequency, stem straightness, internal checking, and external resin bleeding. Results: Nine hundred and eighty-eight individuals were genotyped using exome capture genotyping by sequencing (GBS) and 67,168 single nucleotide polymorphisms (SNPs) used to develop genomic estimated breeding values (GEBVs) with genomic best linear unbiased prediction (GBLUP). The documented pedigree was corrected using a subset of 704 SNPs. The percentage of trio parentage confirmed was about 49% and about 50% of parents were re-assigned. The accuracy of GEBVs was 0.55-0.75 when using the documented pedigree and 0.61-0.80 when using the SNP-corrected pedigree. A higher percentage of additive genetic variance was explained and a higher predictive ability was observed when using the SNP-corrected pedigree than using the documented pedigree. With the documented pedigree, genomic selection was similar to traditional forward selection when assuming a generation interval of 17 years, but worse than traditional forward selection when assuming a generation interval of 14 years. After the pedigree was corrected, genomic selection led to 37-115% and 13-77% additional genetic gain over traditional forward selection when generation intervals of 17 years and 14 years were assumed, respectively. Conclusion: It was concluded that genomic selection with a pedigree corrected by SNP information was an efficient way of improving non-key traits in radiata pine breeding.
... The negative impacts of wrong and missing parentage information on the reliability of estimated breeding values and genetic gain had been estimated in several studies (Sanders et al., 2006), especially sires with small offspring size and traits with low heritability. An error rate by 10% in paternity determination would decline by 4.3% genetic gain per year (Israel and Weller, 2000). Therefore, parentage testing as an essential tool for revising pedigree errors has become an important tool in both breeding practices and investigative studies. ...
Article
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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.
... Banos et al. (2001) indicated that an 11% paternal error rate in genetic evaluations reduced genetic gain by 11 to 15%. Other studies have predicted that a 10% parentage error, with a heritability of 0.25, would contribute to a 3% (Visscher et al. 2002) to 4.3% (Israel and Weller 2000) reduction in genetic gain. For the same pedigree error and a heritability of 10%, a 7% reduction in genetic gain was observed (García-Ruiz et al. 2019). ...
Article
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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.
... Several authors have also reported the effect of pedigree errors (missing information about the parents) and wrong parentage on the accuracy of EBV and genetic parameters (Christensen et al., 1982;Gelderman et al., 1986;Israel and Weller, 2000). For example, reduction in the value of a parent transmitting ability (PTA) for a cow and her relatives; reduced EBV, heritability (h 2 ), and genetic gain for meat and milk traits in cattle. ...
Article
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Hanwoo cattle (HC) being an indigenous breed are greatly adapted to Korean hot-humid climate. They can survive and thrive in harsh environmental conditions. This makes the HC a valuable genetic resource, given the challenges of climate adjustment and varying demands of the livestock sector. Respects to these genetic attributes of HC, breeding initiatives were designed for genetic improvements, such as the Hanwoo-Gaeryang-Danji (HGD) and Hanwoo-Gaeryang-Nongga (HGN), respectively. These initiatives have resulted in tremendous success in the meat industry. The genetic improvement of HC is somehow fulfilling the breeding objectives of increasing the growth performance traits, enhancing meat quality, improving fertility and maintaining adaptability. The breeding and production systems have also contributed towards achieving the breeding goal. The HC production system comprised of 3-tier, the seed stock, multiplier and feedlot sector. The production system provides a link that enables genetic material from the nucleus herd down to various sectors. The results from various studies on the evaluation of genetic improvement and parameters in Korean HC have revealed the degree of genetic progress. Furthermore, the implementation and the used of pedigree and performance records have been helpful using best linear unbiased prediction (BLUP) to estimate breeding values. In addition, the EBV and accuracy of estimated breeding values (EBVs) are an important tool for selecting superior animals to replace the next generation. However, several factors can influence the accuracy of EBVs, such as selection accuracy, selection intensity, pedigree errors and the generation interval (GI). Applying genomic selection (GS) is a potential method to improve prediction accuracy and genetic gains in economically important traits in dairy and beef cattle. Therefore, this study reviews the genetic improvement and application of genomic selection in Korean Hanwoo cattle.
... Several authors have reported the effect of PEs on the EBV, the accuracy of the EBV and the genetic gain in livestock spe cies [10,39]. Their findings indicate that PEs greatly reduce the accuracy of the EBV in beef and dairy cattle. ...
Article
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This study assessed genomic prediction accuracies based on different selection methods, evaluation procedures, training population (TP) sizes, heritability (h2) levels, marker densities and pedigree error (PE) rates in a simulated Korean beef cattle population. A simulation was performed using two different selection methods, phenotypic and EBV, with an h2 of 0.1, 0.3 or 0.5 and marker densities of 10, 50 or 777K. A total of 275 males and 2,475 females were randomly selected from the last generation in order to simulate ten recent generations. The simulation of the pedigree error dataset was modified using only the EBV method of selection with a marker density of 50K and a heritability of 0.3. The proportions of errors substituted were 10, 20, 30 and 40%, respectively. Genetic evaluations were performed using genomic best linear unbiased prediction (GBLUP) and single-step best linear unbiased prediction (SSGBLUP) with different weighted values. The accuracies of the predictions were determined. Compared with phenotypic selection, the results revealed that the prediction accuracies obtained using GBLUP and SSGBLUP increased across heritability levels and TP sizes during EBV selection. However, an increase in the marker density did not yield higher accuracy in either method except when the h2 was 0.3 under the EBV selection method. Based on EBV selection with a heritability of 0.1 and a marker density of 10K, GBLUP and SSGBLUP_0.95 prediction accuracy was higher than that obtained by phenotypic selection. The prediction accuracies from SSGBLUP_0.95 outperformed those from the GBLUP method across all scenarios. When errors were introduced into the pedigree dataset, the prediction accuracies were only minimally influenced across all scenarios. Our study suggests that the use of SSGBLUP_0.95, EBV selection, and low marker density could help improve genetic gains in beef cattle. Keywords: Heritability; Marker Density; Prediction Accuracy; Simulation; Selection Method
... Secondly, accuracy of EBVs, which is a function of the reliability of pedigree/performance records as well as the methods of estimating breeding values (Waldmann and Ericsson, 2006;Furlotte et al., 2014), has a significant impact on the effectiveness of selection activities. Israel and Weller (2000) estimated a loss of 4.6% in selection response due to misidentification of sires. ...
Article
A major challenge in improving genetic merits of smallholder farmers’ flocks in developing livestock systems is the absence of pedigree and performance recording for reliable selection decisions. In this study, we evaluated the reliability of pedigree recording in a community-based Menz sheep village breeding program in Ethiopia, with the purpose of introducing genetic evaluation in the selection program. A total of 3577 six-month weight (SW) and 3876 weaning weight (WW) records collected from 2009 to 2017 were analysed fitting three mixed effects animal models. RP model: considering the sires recorded by farmers as certain, HM model: uncertain paternity with candidate sires in a breeding season assigned posterior paternity probabilities according to phenotypic information, and model AR: uncertain paternity with sires assigned equal priori probabilities and using the average numerator relationship matrix to estimate the genetic effects. The model selection criteria Deviance Information Criteria and Conditional Predictive Ordinate for the three models were comparable, indicating all the three models fitted the data equally. Heritability (Monte Carlo Error in parenthesis) of SW estimated by HM, AR, and RP models were 0.306 (0.00067), 0.374 (0.00061), and 0.418 (0.00048), respectively. EBV and ranks of rams estimated by RP were highly correlated (r = 0.82-0.94) with those of HM and AR models. Up to 82% of the top 30% rams ranked by RP were also ranked by HM and AR models, but accuracy of EBVs was higher for HM model than for AR and RP models. The accuracy of parameter estimates from RP and their correlations with the reference models (HM and AR) is a compelling evidence towards the reliability of farmers pedigree records. It can be fairly recommended to introduce genetic evaluation in community-based breeding programs, estimating EBVs using farmers’ pedigree records directly or with complementary evaluations using methods for uncertain paternity situations. If farmers’ records are to be used directly, expert support in data collection is required to improve the accuracy of EBV above the estimated 70% in this study.
... However, due to the potential high cost, sometimes it is impossible to genotype all breeding animals, meaning that not all pedigrees can be fully verified. Incomplete or incorrect pedigrees affect the rate of genetic response, genetic gain, as well as the accuracy of genetic predictions (Israel and Weller, 2000;Long, 1990;Nwogwugwu et al., 2020). Using key genomic information from a proportion of the population in tandem with complete or incomplete pedigree data could be beneficial in reducing errors, enhancing accuracy and accelerating genetic gain (Berry et al., 2014). ...
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Genomic variants such as Single Nucleotide Polymorphisms and animal pedigree are now used widely in routine genetic evaluations of livestock in many countries. The use of genomic information not only can be used to enhance the accuracy of prediction but also to verify pedigrees for animals that are extensively managed using natural mating and enabling multiple-sire mating groups to be used. By so doing, the rate of genetic gain is enhanced, and any bias associated with incorrect pedigrees is removed. This study used a set of 8 764 sheep genotypes to verify the pedigree based on both the conventional opposing homozygote method as well as a novel method when combined with the inclusion of the genomic relationship matrix (GRM). The genomic relationship coefficients between verified pairs of animals showed on average a relationship of 0.50 with parent, 0.25 with grandparent, 0.13 with great grandparent, 0.50 with full-sibling and 0.27 with half-sibling. Minimum obtained values from these verified pairs were then used as thresholds to determine the pedigree for unverified pairs of animals, to detect potential errors in the pedigree. Using a case study from a population partially genotyped UK sheep, the results from this study illustrate a powerful way to resolve parentage inconsistencies, when combining the conventional ‘opposing homozygote’ method using genomic information together with GRM for pedigree checking. In this way, previously undetected pedigree errors can be resolved.
... Ces difficultés et aléas d'identification des clones au sein des programmes d'amélioration ont été relevés par plusieurs auteurs (Adams et al. 1988 ;Doerksen et Herbinger 2008 ;Kumar et Richardson 2005 ;Zhao et al. 2013). Les erreurs de pedigree et/ou d'identification diminuent la précision de l'estimation des valeurs génétiques et ont un impact sur le gain génétique (Banos et al. 2001 ;Israel et Weller 2000 ;Munoz et al. 2014 ;Sanders et al. 2006). L'utilisation des marqueurs moléculaires permet de vérifier les identités et de corriger les bases de données sur lesquelles reposent les analyses génétiques. ...
Thesis
Le pin maritime (Pinus pinaster Ait.) est l’une des principales espèces forestières en France, fournissant près d’un quart de la production nationale de bois. Un programme d’amélioration, mis en place dans les années 1960, propose des variétés génétiquement améliorées pour la croissance et la rectitude du tronc.Cette thèse explore la possibilité d’introduire les marqueurs moléculaires dans les stratégies d’amélioration génétique du pin maritime en Aquitaine. Les marqueurs sont utilisés afin de reconstituer a posteriori les pedigrees au sein d’un test de descendance « polycross », pour d’une part vérifier les hypothèses sur lesquelles repose la sélection backward, et d’autre part, pour proposer une stratégie de sélection innovante. Tout d’abord, la reconstitution du pedigree de 984 individus à l’aide de 63 marqueurs SNPs permet de valider les hypothèses de la sélection backward, et montre que les estimations des paramètres génétiques et des valeurs génétiques maternelles, basées sur l’information d’un pedigree partiel ou complet, diffèrent peu. Puis, les meilleurs descendants du test polycross sont présélectionnés et génotypés pour évaluer la faisabilité d’une stratégie de sélection forward. Enfin, des vergers à graines sont simulés selon différentes stratégies de sélection (backward, forward, mixte) afin de comparer les gains génétiques des variétés améliorées ainsi obtenues.Une stratégie de sélection forward chez le pin maritime permettrait d’accélérer les cycles de sélection et d’augmenter la fréquence des sorties variétales. De plus, le jeu de marqueurs SNPs développé dans cette étude est en cours de valorisation dans différentes étapes du programme d’amélioration.
... genetic gain per year [3]. Therefore, parentage testing, an essential tool for revising pedigree errors, has become an important element in both breeding practices and research. ...
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... Sanders et al. [2] had estimated the enormous influence of wrong and missing sire information on the reliability of estimated breeding values and genetic gain, especially those sires with small progeny size and traits with low heritability. An error rate by 10% in paternity determination would decline by 4.3% genetic gain per year [3]. Therefore, parentage testing, an essential tool for revising pedigree errors, has become an important element in both breeding practices and research. ...
Preprint
Full-text available
Combining direct sequencing method in polymerase chain reaction (PCR) products of deoxyribonucleic acid (DNA) pooling and matrix-assisted laser desorption/ionisation time of flight mass spectrometry (MALDI-TOF MS) genotyping method in individuals, a panel consisting of 50 highly informative single nucleotide polymorphisms (SNPs) for parentage analysis was developed in a crossbred Chinese cattle population. The average minor allele frequency (MAF) was 0.43 and the cumulative exclusion probability for single-parent and both-parent inference met 0.99797 and 0.999999, respectively. The maker-set was then used for parentage verification in a group of 81 trios with the likelihood-based parentage-assignment program of Cervus software. Compared with on-farm records, the results showed that this 50-SNP system could provide sufficient and reliable information for parentage testing with the parental mistakes for mother-offspring and sire-offspring being 8.6% and 18.5%, respectively. Knowledge of these results, we provided one low-cost and efficient method of SNP assays for running paternity testing in crossbred cattle population of Simmental and Holstein in China.
... Also, it has been suggested that before carrying out the breeding programs the paternity test can help correctly identify the superior sires with the required genetic information for the breeding program. Israel and Weller, (2000) reported that annually there is a 4.3% loss of genetic gain and the misidentification of animal for breeding cause a loss of 10% in dairy production. Fernandez et al. (2009) used 116 single nucleotide polymorphism (SNP) and 18 microsatellites (STR) to detect the polymorphism between 36 closely related Angus cattle and found that the information provided by SNPs were more helpful in distinguishing between the 36 closely related Angus cattle. ...
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Thesis
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Chapter
Genomic prediction can be a powerful tool to achieve greater rates of genetic gain for quantitative traits if thoroughly integrated into a breeding strategy. In rice as in other crops, the interest in genomic prediction is very strong with a number of studies addressing multiple aspects of its use, ranging from the more conceptual to the more practical. In this chapter, we review the literature on rice ( Oryza sativa ) and summarize important considerations for the integration of genomic prediction in breeding programs. The irrigated breeding program at the International Rice Research Institute is used as a concrete example on which we provide data and R scripts to reproduce the analysis but also to highlight practical challenges regarding the use of predictions. The adage “ To someone with a hammer, everything looks like a nail ” describes a common psychological pitfall that sometimes plagues the integration and application of new technologies to a discipline. We have designed this chapter to help rice breeders avoid that pitfall and appreciate the benefits and limitations of applying genomic prediction, as it is not always the best approach nor the first step to increasing the rate of genetic gain in every context.
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A population of individuals was simu- lated to study convergence rate of an iterative method, a mix of Gauss-Seidel and second-order Jacobi, for solving mixed model equations for an animal model. The solutions drifted for many iterations and their accuracy for con- verged solutions was far from that sug- gested by criteria such as the difference between right-hand and left-hand sides or a modified difference between consecu- tive solutions. The drift in later rounds of iteration closely followed a geometric progression, and formulas were derived for estimating: 1) the true solutions via exponential extrapolation, 2) relation- ships between various convergence cri- teria, and 3) number of rounds needed to increase the accuracy of solutions by an arbitrarily specified factor. A range of relaxation factors was studied. The accu- racy of solutions was very sensitive to the value of this factor in the absence of extrapolation. The optimal relaxation factor was lower when solutions were extrapolated, but its value was not as critical in this case.
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Three methods of analysis: 1) multiparity analysis with the first three parities analyzed as correlated traits, 2) multiparity analysis with all lactations analyzed as a single trait, and 3) first parity only analysis were compared on simulated data. A selection index was used to compute multiparity evaluations from the separate parity evaluations of the multitrait analyses. Twenty simulated populations, each of 8,500 cows, were generated by an algorithm that approximated the multitrait model. Populations were simulated with both random and yield-based culling of cows after first and second parity. Populations simulated with yield-based culling were analyzed both with the first parity records of all cows included and with an arbitrary one-third of first parity records deleted. First parity records of all cows were included in the analyses of the randomly culled populations. Accuracy of evaluation, estimated by correlations between true effects and evaluations and prediction error variances, was highest by the multitrait analysis and lowest by the first parity only analysis. Evaluations obtained by the two multilactation methods were nearly identical with random culling. Regression of effect on evaluation was close to unity for the multitrait evaluation; was only .94 and .90 for the all lactation single trait evaluation with random and yield culling, respectively; and was .80 for the index of sire effects on the first parity only analysis. Single-trait multilactation method may be preferred, as it is nearly as accurate as the multitrait method and easier computationally.
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Estimated breeding value (EBV) was calculated based on either individual phenotype (SP), an index of individual phenotype and full- and half-sib family averages (SI) or Best Linear Unbiased Prediction (BLUP). Calculations were done with correct data or data with 5, 10, 15 or 20% of the records per generation containing pedigree errors. Traits considered were litter size (LS), backfat (BF) and average daily gain (ADG). When data were correct, BLUP resulted in an advantage in expected genetic gain over SP of 22, 7.2 or 30.8% for LS, BF and ADG, respectively, and over SI of 9.6, 3.8 or 21.4%. When sire and dam pedigrees were incorrect for 20% of the pigs each generation, genetic gain using SI was reduced by 7, 2.5 or 6.5% and genetic gain using BLUP was reduced by 9.3, 3.2 or 12.4% for LS, BF and ADG, respectively. With 20% of the pedigrees in error, the advantages in genetic gain of using BLUP over SP, the method unaffected by errors in pedigree, were 10.5, 3.8 and 14.6% for LS, BF and ADG, respectively. These results suggest that, although BLUP is affected to a greater degree by pedigree errors than SP or SI, selection of swine using BLUP still would improve response to selection over the use of SP or SI.
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For daughter groups of 15 test bulls, controls of paternity were performed by using blood group factors and biochemical polymorphisms. Data of incorrectly assigned daughters influenced the estimation of breeding values, heritabilities and correlations for milk performance traits. Formulae are given that show the effects of variable misidentification rates on estimation of breeding values, selection intensities, heritabilities, and genetic gains. For example, for milk fat yield, the genetic gains drop at a misidentification rate of 15% between 8.7% (for h2 = .5) and 16.9% (for h2 = .2) below values attained without misidentifications. Consequently, decreasing misidentification rates in progeny of test bulls can be used to diminish the progeny size per test bull for constant genetic gain, to achieve more precise ranking of all or distinct test bulls according to their "true" breeding values and(or) to increase the number of test bulls by using the same amount of test inseminations and the same precision of ranking. Actions to reduce misidentification rates in cattle populations are discussed.
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The DNA microsatellites can be efficiently used to determine incorrect paternity attribution of cattle without genotyping of dams. Allelic frequencies of the population were determined for 12 microsatellites using the maternal alleles of 102 AI sires. The frequency of the most common microsatellite allele ranged from 0.27 to 0.58. Most loci had at least one allele that was present in only a single individual. Paternity of 9 of 173 cows (5.2%) and 3 of 102 bulls (2.9%) was excluded because putative paternal alleles were not present in progeny for at least one locus. For 4 of the 9 cows and all 3 bulls, exclusion was based on at least two loci. Mean probability of exclusion was 0.85 for cows and 0.99 for bulls. With an assumed cost of US $5 per genotype, a misidentification rate of 5%, and a discount rate of 0.05, additional profit for the Israeli-Holstein breeding program from genotyping 100 test daughters of each young sire becomes positive within 10 yr and reaches nearly US $2.4 million after 20 yr.
Effect of pedigree errors in the animal genetic evaluation
  • P L Souza-Carneiro
The influence of incorrect sire-identification on the estimates of genetic parameters and breeding values
  • Christensen