4 results
Imputation of non-genotyped sheep from the genotypes of their mates and resulting progeny
- D. P. Berry, N. McHugh, S. Randles, E. Wall, K. McDermott, M. Sargolzaei, A. C. O’Brien
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Accurate genomic analyses are predicated on access to a large quantity of accurately genotyped and phenotyped animals. Because the cost of genotyping is often less than the cost of phenotyping, interest is increasing in generating genotypes for phenotyped animals. In some instances this may imply the requirement to genotype older animals with greater phenotypic information content. Biological material for these older informative animals may, however, no longer exist. The objective of the present study was to quantify the ability to impute 11 129 single nucleotide polymorphism (SNP) genotypes of non-genotyped animals (in this instance sires) from the genotypes of their progeny with or without including the genotypes of the progenys’ dams (i.e. mates of the sire to be imputed). The impact on the accuracy of genotype imputation by including more progeny (and their dams’) genotypes in the imputation reference population was also quantified. When genotypes of the dams were not available, genotypes of 41 sires with at least 15 genotyped progeny were used for the imputation; when genotypes of the dams were available, genotypes of 21 sires with at least 10 genotyped progeny were used for the imputation. Imputation was undertaken exploiting family and population level information. The mean and variability in the proportion of genotypes per individual that could not be imputed reduced as the number of progeny genotypes used per individual increased. Little improvement in the proportion of genotypes that could not be imputed was achieved once genotypes of seven progeny and their dams were used or genotypes of 11 progeny without their respective dam’s genotypes were used. Mean imputation accuracy per individual (depicted by both concordance rates and correlation between true and imputed) increased with increasing progeny group size. Moreover, the range in mean imputation accuracy per individual reduced as more progeny genotypes were used in the imputation. If the genotype of the mate of the sire was also used, high accuracy of imputation (mean genotype concordance rate per individual of 0.988), with little additional benefit thereafter, was achieved with seven genotyped progeny. In the absence of genotypes on the dam, similar imputation accuracy could not be achieved even using genotypes on up to 15 progeny. Results therefore suggest, at least for the SNP density used in the present study, that it is possible to accurately impute the genotypes of a non-genotyped parent from the genotypes of its progeny and there is a benefit of also including the genotype of the sire’s mate (i.e. dam of the progeny).
Imputation of ungenotyped parental genotypes in dairy and beef cattle from progeny genotypes
- D. P. Berry, S. McParland, J. F. Kearney, M. Sargolzaei, M. P. Mullen
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The objective of this study was to quantify the accuracy of imputing the genotype of parents using information on the genotype of their progeny and a family-based and population-based imputation algorithm. Two separate data sets were used, one containing both dairy and beef animals (n=3122) with high-density genotypes (735 151 single nucleotide polymorphisms (SNPs)) and the other containing just dairy animals (n=5489) with medium-density genotypes (51 602 SNPs). Imputation accuracy of three different genotype density panels were evaluated representing low (i.e. 6501 SNPs), medium and high density. The full genotypes of sires with genotyped half-sib progeny were masked and subsequently imputed. Genotyped half-sib progeny group sizes were altered from 4 up to 12 and the impact on imputation accuracy was quantified. Up to 157 and 258 sires were used to test the accuracy of imputation in the dairy plus beef data set and the dairy-only data set, respectively. The efficiency and accuracy of imputation was quantified as the proportion of genotypes that could not be imputed, and as both the genotype concordance rate and allele concordance rate. The median proportion of genotypes per animal that could not be imputed in the imputation process decreased as the number of genotyped half-sib progeny increased; values for the medium-density panel ranged from a median of 0.015 with a half-sib progeny group size of 4 to a median of 0.0014 to 0.0015 with a half-sib progeny group size of 8. The accuracy of imputation across different paternal half-sib progeny group sizes was similar in both data sets. Concordance rates increased considerably as the number of genotyped half-sib progeny increased from four (mean animal allele concordance rate of 0.94 in both data sets for the medium-density genotype panel) to five (mean animal allele concordance rate of 0.96 in both data sets for the medium-density genotype panel) after which it was relatively stable up to a half-sib progeny group size of eight. In the data set with dairy-only animals, sufficient sires with paternal half-sib progeny groups up to 12 were available and the within-animal mean genotype concordance rates continued to increase up to this group size. The accuracy of imputation was worst for the low-density genotypes, especially with smaller half-sib progeny group sizes but the difference in imputation accuracy between density panels diminished as progeny group size increased; the difference between high and medium-density genotype panels was relatively small across all half-sib progeny group sizes. Where biological material or genotypes are not available on individual animals, at least five progeny can be genotyped (on either a medium or high-density genotyping platform) and the parental alleles imputed with, on average, ⩾96% accuracy.
Genetic diversity of Guernsey population using pedigree data and gene-dropping simulations
- M. G. Melka, M. Sargolzaei, F. Miglior, F. Schenkel
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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.
Genome scan to detect quantitative trait loci for economically important traits in Holstein cattle using a dense SNP map
- H.D. Daetwyler, F.S. Schenkel, M. Sargolzaei, J.A.B. Robinson
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- Journal:
- Proceedings of the British Society of Animal Science / Volume 2007 / April 2007
- Published online by Cambridge University Press:
- 22 November 2017, p. 6
- Print publication:
- April 2007
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Quantitative trait loci (QTL) are chromosome regions which are significantly associated with the expression of a phenotypic trait in a particular population. Detection of a QTL is carried out using association with a genetic marker, such as a single nucleotide polymorphism (SNP), which is in linkage disequilibrium (LD) with the QTL. The two main categories of association studies are linkage analyses (LA), which consider LD within families and linkage disequilibrium methods, which make use of LD across an entire population. The recent reduction in genotyping costs has allowed for testing individuals for a large number of SNP. This substantial increase in genotypic data has lead to denser marker distributions on the bovine genome thus potentially increasing the power of QTL detection studies. The objective of this study was to scan the bovine genome to detect QTL for 305 day lactation milk yield (MY), 305 day lactation fat yield (FY), 305 day lactation protein yield (PY), herd life (HL), somatic cell score (SCS), interval from calving to first service in cows (CTFS) and age at first service in heifers (AFS). HL is a measure of longevity measured in the number of lactations a cow stays in the herd. SCS refers to the amount of somatic cells a cow has in her milk and is an important indicator trait for mastitis. CTFS is the period from parturition to first insemination in days and AFS is the age in days at which a heifer was artificially inseminated for the first time. Fertility traits, such as CTFS and AFS, are indicators of reproductive efficiency.