Pedigree analysis by computer simulation

MacCluer, Jean W.; VandeBerg, John L.; Read, Bruce; Ryder, Oliver A.

doi:10.1002/zoo.1430050209

Cited by 272 publications

(215 citation statements)

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“…Thus, we simulated 38 independent founders and their descendants according to the known pedigree structure. A gene-dropping method (Maccluer et al 1986) was used to simulate Mendelian inheritance of marker alleles from parents to offspring while Haldane's mapping function (Haldane 1919), was used to transform linkage distances into recombination fractions. The genetic linkage map differed from the real data set as markers were placed equidistantly along the genome.…”

Section: Simulated Datamentioning

confidence: 99%

Comparison of marker-based pairwise relatedness estimators on a pedigreed plant population

et al. 2008

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Several estimators have been proposed that use molecular marker data to infer the degree of relatedness for pairs of individuals. The objective of this study was to evaluate the performance of seven estimators when applied to marker data of a set of 33 key individuals from a large complex apple pedigree. The evaluation considered different scenarios of allele frequencies and different numbers of marker loci. The method of moments estimators were Similarity, Queller-Goodknight, Lynch-Ritland and Wang. The maximum likelihood estimators were Thompson, Anderson-Weir and Jacquard. The pedigree-based coancestry coefficients were taken as the point of reference in calculating correlations and root mean square error (RMSE). The marker data comprised 86 multi-allelic SSR markers on 17 linkage groups, covering 11 Morgans. Additionally, we simulated 10 datasets conditional on the real pedigree to support the results on the real dataset. None of the estimators outperformed the others. Knowledge of allele frequencies appeared to be the most influential, i.e., the highest correlations and lowest RMSE were found when frequencies from the founder population were available. When equal allele frequencies were used, all estimators resulted in very similar, but on average lower, correlations. The use of allele frequencies estimated from the set of 33 individuals gave, on average, the poorest results. The maximum likelihood estimators and the Lynch-Ritland estimator were the most sensitive to allele frequencies. The results from the simulation study fully supported the trends in results of the real dataset. This study indicated that high correlations (up to 0.90) and small RMSE (below 0.03), may be obtained when population allelic frequencies are available. In this scenario, the performances of the various estimators were similar, but seemed to favor the maximum likelihood estimators. In the absence of reliable allele frequencies the method of moments estimators were shown to be more robust. The number of marker loci influenced the average performance of the estimators; however, the ranking was not affected. Correlations up to 0.80 were obtained when two markers per chromosome and appropriate allele frequencies were available. Adding more markers to the current dataset may lead to marginal improvements.

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Section: Simulated Datamentioning

confidence: 99%

Comparison of marker-based pairwise relatedness estimators on a pedigreed plant population

et al. 2008

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“…In each generation, the number of male and female parents are equal, and their alleles were inherited to descendents based on Mendelian segregation using the gene dropping method [11]. Unique numbers were assigned as mutant alleles to QTL in a given generation (depending on mutation age).…”

Section: Simulation Studymentioning

confidence: 99%

“…Meuwissen and Goddard [13] used the gene dropping method [11] to estimate IBD probabilities between unrelated animals based on similarity of marker haplotypes. Using the IBD probabilities between the unrelated animals, IBD probabilities between animals in the following generations can be recursively estimated from pedigree and observed marker genotypes.…”

Section: Building a Genotype Relationship Matrix (Grm)mentioning

confidence: 99%

The efficiency of designs for fine-mapping of quantitative trait loci using combined linkage disequilibrium and linkage

Lee

Werf

2004

Genet. Sel. Evol.

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-In a simulation study, different designs were compared for efficiency of finemapping of QTL. The variance component method for fine-mapping of QTL was used to estimate QTL position and variance components. The design of many families with small size gave a higher mapping resolution than a design with few families of large size. However, the difference is small in half sib designs. The proportion of replicates with the QTL positioned within 3 cM of the true position is 0.71 in the best design, and 0.68 in the worst design applied to 128 animals with a phenotypic record and a QTL explaining 25% of the phenotypic variance. The design of two half sib families each of size 64 was further investigated for a hypothetical population with effective size of 1000 simulated for 6000 generations with a marker density of 0.25 cM and with marker mutation rate 4 × 10 −4 per generation. In mapping using bi-allelic markers, 42∼55% of replicated simulations could position QTL within 0.75 cM of the true position whereas this was higher for multi allelic markers (48∼76%). The accuracy was lowest (48%) when mutation age was 100 generations and increased to 68% and 76% for mutation ages of 200 and 500 generations, respectively, after which it was about 70% for mutation ages of 1000 generations and older. When effective size was linearly decreasing in the last 50 generations, the accuracy was decreased (56 to 70%). We show that half sib designs that have often been used for linkage mapping can have sufficient information for fine-mapping of QTL. It is suggested that the same design with the same animals for linkage mapping should be used for fine-mapping so gene mapping can be cost effective in livestock populations.quantitative trait loci / fine-mapping / restricted maximum likelihood / simulation / designs

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“…However, the probabilities of allele extinction of founders can be only obtained using simulation. Therefore, gene-dropping simulation, as proposed by MacCluer et al (1986), was applied to the reference populations (animals born from 2002 to 2007). Accordingly, unique alleles were assigned to founders and the genotypes of all descendants were generated along the actual pedigree through Monte Carlo simulation following Mendelian segregation.…”

Section: Characterization Of the Pedigree Informationmentioning

confidence: 99%

“…Gene-dropping simulation, as proposed by MacCluer et al (1986), may also be used in order to compute the proportions of founder alleles lost and the probability of founder alleles being at high risk of extinction, which would be useful in monitoring the effect of bottlenecks on the genetic diversity of Guernsey populations. The objectives of this study were, therefore, to examine the trend of within-breed genetic diversity, and identify major causes of loss of genetic diversity in Canada (GCN), GSA and GUS based on pedigree records.…”

Section: Introductionmentioning

confidence: 99%

Genetic diversity of Guernsey population using pedigree data and gene-dropping simulations

Melka

Sargolzaei

Miglior

et al. 2013

Animal

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The objectives of this study were to analyze the trend of within-breed genetic diversity and identify major causes leading to loss of genetic diversity in Guernsey breed in three countries. Pedigree files of Canadian (GCN), South African (GSA) and American (GUS) Guernsey populations containing 130 927, 18 593 and 1 851 624 records, respectively, were analyzed. Several parameters derived from the in-depth pedigree analyses were used to measure trends and current levels of genetic diversity. Pedigree completeness index of GCN, GSA and GUS populations, in the most recent year (2007), was 97%, 74% and 79%, respectively, considering four generations back in the analysis. The rate of inbreeding in each population was 0.19%, 0.16% and 0.17% between 2002 and 2007, respectively. For the same period, the estimated effective population size for GCN, GSA and GUS was 46, 57 and 46, respectively. The estimated percentage of genetic diversity lost within each population over the last four decades was 8%, 3% and 5%, respectively. The relative proportion of genetic diversity lost due to random genetic drift in the three populations was 93%, 91% and 86%, respectively. In conclusion, the results suggested that GCN and GUS have lost more genetic diversity than GSA over the past four decades, and this loss is gaining momentum due to increasing rates of inbreeding. Therefore, strategies such as optimum contribution selection and migration of genetic material are advised to increase effective population size, particularly in GCN and GUS.

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Pedigree analysis by computer simulation

Cited by 272 publications

References 10 publications

Comparison of marker-based pairwise relatedness estimators on a pedigreed plant population

Comparison of marker-based pairwise relatedness estimators on a pedigreed plant population

The efficiency of designs for fine-mapping of quantitative trait loci using combined linkage disequilibrium and linkage

Genetic diversity of Guernsey population using pedigree data and gene-dropping simulations

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