scholarly journals Genotype imputation strategies for Portuguese Holstein cattle using different SNP panels

2019 ◽  
Vol 64 (No. 9) ◽  
pp. 377-386
Author(s):  
Alessandra Silva ◽  
Fabyano Silva ◽  
Delvan Silva ◽  
Hugo Silva ◽  
Cláudio Costa ◽  
...  
Keyword(s):  
Imputation Accuracy ◽  
Genotype Imputation ◽  
Holstein Cattle ◽  
Small Populations ◽  
Nucleotide Polymorphism ◽  
Genomic Evaluation ◽  
Single Nucleotide ◽  
Factors Affecting ◽  
Validation Population ◽  
Snp Panels

Although several studies have investigated the factors affecting imputation accuracy, most of these studies involved a large number of genotyped animals. Thus, results from these studies cannot be directly applied to small populations, since the population structure affects imputation accuracy. In addition, factors affecting imputation accuracy may also be intensified in small populations. Therefore, we aimed to compare different imputation strategies for the Portuguese Holstein cattle population considering several commercially available single nucleotide polymorphism (SNP) panels in a relatively small number of genotyped animals. Data from 1359 genotyped animals were used to evaluate imputation in 7 different scenarios. In the S1 to S6 scenarios, imputations were performed from LDv1, 50Kv1, 57K, 77K, HDv3 and Ax58K panels to 50Kv2 panel. In these scenarios, the bulls in 50Kv2 were divided into reference (352) and validation (101) populations based on the year of birth. In the S7 scenario, the validation population consisted of 566 cows genotyped with the Ax58K panel with their genotypes masked to LDv1. In general, all sample imputation accuracies were high with correlations ranging from 0.94 to 0.99 and concordance rate ranging from 92.59 to 98.18%. SNP-specific accuracy was consistent with that of sample imputation. S4 (40.32% of SNPs imputed) had higher accuracy than S2 and S3, both with less than 7.59% of SNPs imputed. Most probably, this was due to the high number of imputed SNPs with minor allele frequency (MAF) < 0.05 in S2 and S3 (by 18.43% and 16.06% higher than in S4, respectively). Therefore, for these two scenarios, MAF was more relevant than the panel density. These results suggest that genotype imputation using several commercially available SNP panels is feasible for the Portuguese national genomic evaluation.

Assessing single nucleotide polymorphism selection methods for the development of a low-density panel optimized for imputation in South African Drakensberger beef cattle

2021 ◽  
Author(s):  
Simon F Lashmar ◽  
Donagh P Berry ◽  
Rian Pierneef ◽  
Farai C Muchadeyi ◽  
Carina Visser
Keyword(s):  
South African ◽  
Clustering Algorithm ◽  
Imputation Accuracy ◽  
Developed Countries ◽  
Genotype Imputation ◽  
Selection Strategy ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Single Nucleotide Polymorphism Selection ◽  
The Mean

Abstract A major obstacle in applying genomic selection (GS) to uniquely adapted local breeds in less-developed countries has been the cost of genotyping at high densities of single nucleotide polymorphisms (SNP). Cost reduction can be achieved by imputing genotypes from lower to higher densities. Locally adapted breeds tend to be admixed and exhibit a high degree of genomic heterogeneity thus necessitating the optimization of SNP selection for downstream imputation. The aim of this study was to quantify the achievable imputation accuracy for a sample of 1,135 South African (SA) Drakensberger using several custom-derived lower-density panels varying in both SNP density and how the SNP were selected. From a pool of 120,608 genotyped SNP, subsets of SNP were chosen 1) at random, 2) with even genomic dispersion, 3) by maximizing the mean minor allele frequency (MAF), 4) using a combined score of MAF and linkage disequilibrium (LD), 5) using a partitioning-around-medoids (PAM) algorithm, and finally 6) using a hierarchical LD-based clustering algorithm. Imputation accuracy to higher density improved as SNP density increased; animal-wise imputation accuracy defined as the within-animal correlation between the imputed and actual alleles ranged from 0.625 to 0.990 when 2,500 randomly selected SNP were chosen versus a range of 0.918 to 0.999 when 50,000 randomly selected SNP were used. At a panel density of 10,000 SNP, the mean (standard deviation) animal-wise allele concordance rate was 0.976 (0.018) versus 0.982 (0.014) when the worst (i.e., random) as opposed to the best (i.e., combination of MAF and LD) SNP selection strategy was employed. A difference of 0.071 units was observed between the mean correlation-based accuracy of imputed SNP categorized as low (0.01<MAF≤0.1) versus high MAF (0.4<MAF≤0.5). Greater mean imputation accuracy was achieved for SNP located on autosomal extremes when these regions were populated with more SNP. The presented results suggested that genotype imputation can be a practical cost-saving strategy for indigenous breeds such as the South African Drakensberger. Based on the results, a genotyping panel consisting of approximately 10,000 SNP selected based on a combination of MAF and LD would suffice in achieving a less than 3% imputation error rate for a breed characterized by genomic admixture on the condition that these SNP are selected based on breed-specific selection criteria.

HLA-DRB1*1501 tagging rs3135388 polymorphism is not associated with neuromyelitis optica

2010 ◽  
Vol 16 (8) ◽  
pp. 981-984 ◽  
Author(s):  
Marcelo Matiello ◽  
Janet Schaefer-Klein ◽  
Doralina G Brum ◽  
Elizabeth J Atkinson ◽  
Orhun H Kantarci ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Single Nucleotide Polymorphism ◽  
Association Study ◽  
Neuromyelitis Optica ◽  
Genetic Association Study ◽  
Case Control ◽  
Small Populations ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Nuclease Assay

Background: Association of the HLA-DRB1*1501 allele with multiple sclerosis is well established, but its association with neuromyelitis optica has only been evaluated in small populations. Methods: We performed a case-control genetic association study to evaluate the association of HLA-DRB1*1501 with neuromyelitis optica. The single nucleotide polymorphism rs3135388, which tags HLA-DRB1*1501, was genotyped in 164 patients with neuromyelitis optica, 220 patients with multiple sclerosis and 959 controls matched for age, gender and ethnicity. Genotyping for rs3135388 was performed by Taqman-based 5' nuclease assay. Results: Rs3135388*A was positively associated with multiple sclerosis (OR = 3.93; 95% CI = 2.58—5.97, p = 1.18 × 10-09) but negatively associated with NMO (OR = 0.57; 95% CI = 0.36—0.91, p = 0.01). Conclusions: Multiple sclerosis and neuromyelitis optica differ in their associations with DRB1*1501.

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