Parentage identification using single nucleotide polymorphism genotypes: Application to product tracing1

Hill, William G.; Salisbury, Benjamin A.; Webb, Anne

doi:10.2527/jas.2007-0276

Cited by 25 publications

(23 citation statements)

References 15 publications

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“…In addition to the quantity, the quality of marker data has a large impact on the performance of parentage (Marshall et al 1998;Kalinowski et al 2007;Hill et al 2008) and sibship (Wang 2004) assignment methods. To avoid false exclusions of sibship and parentage, various models of genotyping errors have been proposed and applied.…”

Section: Discussionmentioning

confidence: 99%

Parentage and Sibship Inference From Multilocus Genotype Data Under Polygamy

2009

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Likelihood methods have been developed to partition individuals in a sample into sibling clusters using genetic marker data without parental information. Most of these methods assume either both sexes are monogamous to infer full sibships only or only one sex is polygamous to infer full sibships and paternal or maternal (but not both) half sibships. We extend our previous method to the more general case of both sexes being polygamous to infer full sibships, paternal half sibships, and maternal half sibships and to the case of a two-generation sample of individuals to infer parentage jointly with sibships. The extension not only expands enormously the scope of application of the method, but also increases its statistical power. The method is implemented for both diploid and haplodiploid species and for codominant and dominant markers, with mutations and genotyping errors accommodated. The performance and robustness of the method are evaluated by analyzing both simulated and empirical data sets. Our method is shown to be much more powerful than pairwise methods in both parentage and sibship assignments because of the more efficient use of marker information. It is little affected by inbreeding in parents and is moderately robust to nonrandom mating and linkage of markers. We also show that individually much less informative markers, such as SNPs or AFLPs, can reach the same power for parentage and sibship inferences as the highly informative marker simple sequence repeats (SSRs), as long as a sufficient number of loci are employed in the analysis.

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Section: Discussionmentioning

confidence: 99%

Parentage and Sibship Inference From Multilocus Genotype Data Under Polygamy

2009

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“…According to Marshall et al (1998), a positivo LOD score means that the candidate parent is more likely to be the true parent than not the true parent. Hill et al (2008) suggested that an observed LOD score greater than 5 was strong evidence that the sire had been identified, whereas a negative LOD score gave strong evidence that the sire had not been found. In the current study, working with 80 or more SNP, all the offspring were assigned to the true father for scenarios 1 and 2.…”

Section: Thresholds For Parameters For Paternal Identificationmentioning

confidence: 93%

“…Several stndies have been carried out to evaluate the power of DNA markers for parental identification and traceability in livestock (Hayes et al, 2005;Gomez-Raya et al, 2008). The concept of parental identification was extended by Hill et al (2008) for application in product tracing, particularly in pigs. They calculated, based on simulation, that 100 to 150 SNP with minor alíele frequencies (MAF) >0.3 would be sufficient to trace a piece of meat back to the parents and to the farm of origin.…”

Section: Introductionmentioning

confidence: 99%

A single nucleotide polymorphism set for paternal identification to reduce the costs of trait recording in commercial pig breeding1,2

Harlizius¹,

Lopes

Duijvesteijn³

et al. 2011

Journal of Animal Science

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In animal breeding, recording of correct pedigrees is essential to achieve genetic progress. Markers on DNA are useful to verify the on-farm pedigree records (parental verification) but can also be used to assign parents retrospectively (parental identification). This approach could reduce the costs of recording for traits with low incidence, such as those related to diseases or mortality. In this study, SNP were used to assign the true sires of 368 purebred animals from a Duroc-based sire line and 140 crossbred offspring from a commercial pig population. Some of the sires were closely related. There were 3 full sibs and 17 half sibs among the true fathers and 4 full sibs and 35 half sibs among all putative fathers. To define the number of SNP necessary, 5 SNP panels (40, 60, 80, 100, and 120 SNP) were assembled from the Illumina PorcineSNP60 Beadchip (Illumina, San Diego, CA) based on minor allele frequency (>0.3), high genotyping call rate (≥90%), and equal spacing across the genome. For paternal identification considering only the 66 true sires in the data set, 60 SNP resulted in 100% correct assignment of the sire. By including additional putative sires (n = 304), 80 SNP were sufficient for 100% correct assignment of the sire. The following criteria were derived to identify the correct sire for the current data set: the logarithm of odds (LOD) score for assigning the correct sire was ≥5, the number of mismatches was ≤1, and the difference in the LOD score between the first and the second most likely sire was >5. If the correct sire was not present among all putative sires, the mean LOD for the most likely sire was close to zero or negative when using 100 SNP. More SNP would be needed for paternal identification if the number of putative sires increased and the degree of relatedness was greater than in the data set used here. The threshold for the number of mismatches can be adjusted according to the practical situation to account for the trade-off between false negatives and false positives. The latter can be avoided efficiently, ensuring that the correct father is being sampled. Nevertheless, a restriction on the number of putative sires is advisable to reduce the risk of assigning close relatives.

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“…Alternative methods, including statistical likelihood-based procedures, are also able to qualify parentage but were not explored in these data. Likelihood procedures offer an alternative methodology to this problem but still require extensive calibration for allele and genotype frequencies as well as population structure and the number of possible sires (Dodds et al 2005;Hill et al 2008). Further, principal component analysis of the SNP data can be used to identify half-sib or full-sib groups even in the absence of parental information.…”

Section: Discussionmentioning

confidence: 99%

Analysis of validated and population-specific single nucleotide polymorphism parentage panels in pedigreed and commercial beef cattle populations

Buchanan

Woronuk²,

Marquess³

et al. 2016

Can. J. Anim. Sci.

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A pedigreed population containing 71 calves and 8 sires was used to compare sire qualification using three genotyping platforms [14 microsatellite, real-time quantitative PCR, and 100, 200, 500, and 1000 single nucleotide polymorphism (SNP) arrays]. Parentage was also qualified in an unknown-pedigree population containing 8480 calves with 460 sires using SNP arrays. The three platforms qualified the true sire in the known-pedigree population with zero mismatches. The 100 and 200 SNP arrays yielded specificities of 0.92 and 0.99 with a 1% mismatch rate in the knownpedigree population, respectively. In the larger population, SNP panels of the 500 and 1000 highest minor allele frequency SNPs were also evaluated. The 1000 SNP panel qualified paternity to a single sire for 82.1% of calves with 1% or 2% mismatches. Not all commercial sires were genotyped, which accounts for missing paternity for some calves. In this larger population, the 100 SNP array qualified multiple sires to 0.42% of calves and single sires to 80.84% of calves without mismatches. The 200 SNP array assigned unique paternity, and 79.8% of calves were qualified to a sire without mismatches. With a 2% mismatch rate, sire qualifications agreed with the 1000 SNP array. This study highlights the interplay among population size, genotyping error rates, and the specificity and sensitivity of parentage platforms.Key words: SNP parentage panel, sensitivity (parentage), specificity (parentage), Charolais, cattle (beef).Résumé : Une population à pedigree contenant 71 veaux et 8 géniteurs mâles a été utilisée pour comparer la qualification des géniteurs mâles au moyen de trois plateformes de génotypage (14 microsatellites, PCR quantitative en temps réel, ainsi que des réseaux de 100, 200, 500, et 1000 SNPs). La parenté a aussi été qualifiée dans une population de pedigree inconnu contenant 8480 veaux et 460 géniteurs mâles au moyen des réseaux de SNPs. Les trois plateformes ont qualifié le véritable géniteur dans la population à pedigree connu avec aucun écart. Les réseaux à 100 et 200 SNPs ont rendu des spécificités de 0,92 et 0,99 avec un taux d'écart de 1 % dans la population à pedigree connu, respectivement. Dans la plus grande population, les panels de SNPs de 500 et 1000 SNPs de fréquence d'allèles mineurs les plus élevés ont aussi été évalués. Le panel de 1000 SNPs a qualifié la paternité à un seul géniteur pour 82,1 % des veaux avec seulement 1 % à 2 % d'écarts. Tous les géniteurs mâles commerciaux n'ont pas été génotypés ce qui explique la paternité manquante pour certains veaux. Dans cette population plus grande, le réseau à 100 SNPs a qualifié de multiples géniteurs à 0,42 % des veaux et un seul géniteur à 80,84 % des veaux sans écarts. Le réseau à 200 SNPs a assigné une paternité unique et 79,8 % des veaux ont été qualifiés à un géniteur sans écart. Avec un taux d'écart de 2 %, la qualification des géniteurs était en accord avec le réseau de 1000 SNPs. Cette étude souligne l'interdépendance entre la taille de la population, les taux d'éca...

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Parentage identification using single nucleotide polymorphism genotypes: Application to product tracing1

Cited by 25 publications

References 15 publications

Parentage and Sibship Inference From Multilocus Genotype Data Under Polygamy

Parentage and Sibship Inference From Multilocus Genotype Data Under Polygamy

A single nucleotide polymorphism set for paternal identification to reduce the costs of trait recording in commercial pig breeding1,2

Analysis of validated and population-specific single nucleotide polymorphism parentage panels in pedigreed and commercial beef cattle populations

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