Dataset Information

Analytical and statistical consideration on the use of the ISAG-ICAR-SNP bovine panel for parentage control, using the Illumina BeadChip technology: example on the German Holstein population.

ABSTRACT: Parentage control is moving from short tandem repeats- to single nucleotide polymorphism (SNP) systems. For SNP-based parentage control in cattle, the ISAG-ICAR Committee proposes a set of 100/200 SNPs but quality criteria are lacking. Regarding German Holstein-Friesian cattle with only a limited number of evaluated individuals, the exclusion probability is not well-defined. We propose a statistical procedure for excluding single SNPs from parentage control, based on case-by-case evaluation of the GenCall score, to minimize parentage exclusion, based on miscalled genotypes. Exclusion power of the ISAG-ICAR SNPs used for the German Holstein-Friesian population was adjusted based on the results of more than 25,000 individuals.Experimental data were derived from routine genomic selection analyses of the German Holstein-Friesian population using the Illumina BovineSNP50 v2 BeadChip (20,000 individuals) or the EuroG10K variant (7000 individuals). Averages and standard deviations of GenCall scores for the 200 SNPs of the ISAG-ICAR recommended panel were calculated and used to calculate the downward Z-value. Based on minor allelic frequencies in the Holstein-Friesian population, one minus exclusion probability was equal to 1.4×10?¹? and 7.2×10?²?, with one and two parents, respectively. Two monomorphic SNPs from the 100-SNP ISAG-ICAR core-panel did not contribute. Simulation of 10,000 parentage control combinations, using the GenCall score data from both BeadChips, showed that with a Z-value greater than 3.66 only about 2.5% parentages were excluded, based on the ISAG-ICAR recommendations (core-panel: ? 90 SNPs for one, ? 85 SNPs for two parents). When applied to real data from 1750 single parentage assessments, the optimal threshold was determined to be Z = 5.0, with only 34 censored cases and reduction to four (0.2%) doubtful parentages. About 70 parentage exclusions due to weak genotype calls were avoided, whereas true exclusions (n = 34) were unaffected.Using SNPs for parentage evaluation provides a high exclusion power also for parent identification. SNPs with a low GenCall score show a high tendency towards intra-molecular secondary structures and substantially contribute to false exclusion of parentages. We propose a method that controls this error without excluding too many parent combinations from the evaluation.

SUBMITTER: Schutz E

PROVIDER: S-EPMC4318447 | biostudies-other | 2015

REPOSITORIES: biostudies-other

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Analytical and statistical consideration on the use of the ISAG-ICAR-SNP bovine panel for parentage control, using the Illumina BeadChip technology: example on the German Holstein population.

Schütz Ekkehard E Brenig Bertram B

Genetics, selection, evolution : GSE 20150205

<h4>Background</h4>Parentage control is moving from short tandem repeats- to single nucleotide polymorphism (SNP) systems. For SNP-based parentage control in cattle, the ISAG-ICAR Committee proposes a set of 100/200 SNPs but quality criteria are lacking. Regarding German Holstein-Friesian cattle with only a limited number of evaluated individuals, the exclusion probability is not well-defined. We propose a statistical procedure for excluding single SNPs from parentage control, based on case-by-c ...[more]

PMID: 25651826

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Project description:The objective of this study was to compare accuracies of different Bayesian regression models in predicting molecular breeding values for health traits in Holstein cattle. The dataset was composed of 2505 records reporting the occurrence of retained fetal membranes (RFM), metritis (MET), mastitis (MAST), displaced abomasum (DA), lameness (LS), clinical endometritis (CE), respiratory disease (RD), dystocia (DYST) and subclinical ketosis (SCK) in Holstein cows, collected between 2012 and 2014 in 16 dairies located across the US. Cows were genotyped with the Illumina BovineHD (HD, 777K). The quality controls for SNP genotypes were HWE P-value of at least 1 × 10-10 ; MAF greater than 0.01 and call rate greater than 0.95. The FImpute program was used for imputation of missing SNP markers. The effect of each SNP was estimated using the Bayesian Ridge Regression (BRR), Bayes A, Bayes B and Bayes Cπ methods. The prediction quality was assessed by the area under the curve, the prediction mean square error and the correlation between genomic breeding value and the observed phenotype, using a leave-one-out cross-validation technique that avoids iterative cross-validation. The highest accuracies of predictions achieved were: RFM [Bayes B (0.34)], MET [BRR (0.36)], MAST [Bayes B (0.55), DA [Bayes Cπ (0.26)], LS [Bayes A (0.12)], CE [Bayes A (0.32)], RD [Bayes Cπ (0.23)], DYST [Bayes A (0.35)] and SCK [Bayes Cπ (0.38)] models. Except for DA, LS and RD, the predictive abilities were similar between the methods. A strong relationship between the predictive ability and the heritability of the trait was observed, where traits with higher heritability achieved higher accuracy and lower bias when compared with those with low heritability. Overall, it has been shown that a high-density SNP panel can be used successfully to predict genomic breeding values of health traits in Holstein cattle and that the model of choice will depend mostly on the genetic architecture of the trait.

Project description:BackgroundThe extent of linkage disequilibrium (LD) within a population determines the number of markers that will be required for successful association mapping and marker-assisted selection. Most studies on LD in cattle reported to date are based on microsatellite markers or small numbers of single nucleotide polymorphisms (SNPs) covering one or only a few chromosomes. This is the first comprehensive study on the extent of LD in cattle by analyzing data on 1,546 Holstein-Friesian bulls genotyped for 15,036 SNP markers covering all regions of all autosomes. Furthermore, most studies in cattle have used relatively small sample sizes and, consequently, may have had biased estimates of measures commonly used to describe LD. We examine minimum sample sizes required to estimate LD without bias and loss in accuracy. Finally, relatively little information is available on comparative LD structures including other mammalian species such as human and mouse, and we compare LD structure in cattle with public-domain data from both human and mouse.ResultsWe computed three LD estimates, D', Dvol and r2, for 1,566,890 syntenic SNP pairs and a sample of 365,400 non-syntenic pairs. Mean D' is 0.189 among syntenic SNPs, and 0.105 among non-syntenic SNPs; mean r2 is 0.024 among syntenic SNPs and 0.0032 among non-syntenic SNPs. All three measures of LD for syntenic pairs decline with distance; the decline is much steeper for r2 than for D' and Dvol. The value of D' and Dvol are quite similar. Significant LD in cattle extends to 40 kb (when estimated as r2) and 8.2 Mb (when estimated as D'). The mean values for LD at large physical distances are close to those for non-syntenic SNPs. Minor allelic frequency threshold affects the distribution and extent of LD. For unbiased and accurate estimates of LD across marker intervals spanning < 1 kb to > 50 Mb, minimum sample sizes of 400 (for D') and 75 (for r2) are required. The bias due to small samples sizes increases with inter-marker interval. LD in cattle is much less extensive than in a mouse population created from crossing inbred lines, and more extensive than in humans.ConclusionFor association mapping in Holstein-Friesian cattle, for a given design, at least one SNP is required for each 40 kb, giving a total requirement of at least 75,000 SNPs for a low power whole-genome scan (median r2 > 0.19) and up to 300,000 markers at 10 kb intervals for a high power genome scan (median r2 > 0.62). For estimation of LD by D' and Dvol with sufficient precision, a sample size of at least 400 is required, whereas for r2 a minimum sample of 75 is adequate.

Dataset Information

Analytical and statistical consideration on the use of the ISAG-ICAR-SNP bovine panel for parentage control, using the Illumina BeadChip technology: example on the German Holstein population.

Publications

Analytical and statistical consideration on the use of the ISAG-ICAR-SNP bovine panel for parentage control, using the Illumina BeadChip technology: example on the German Holstein population.

Similar Datasets

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