Cargando…
Accuracy of genotype imputation in Nelore cattle
BACKGROUND: Genotype imputation from low-density (LD) to high-density single nucleotide polymorphism (SNP) chips is an important step before applying genomic selection, since denser chips tend to provide more reliable genomic predictions. Imputation methods rely partially on linkage disequilibrium b...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4192291/ https://www.ncbi.nlm.nih.gov/pubmed/25927950 http://dx.doi.org/10.1186/s12711-014-0069-1 |
_version_ | 1782338751291195392 |
---|---|
author | Carvalheiro, Roberto Boison, Solomon A Neves, Haroldo H R Sargolzaei, Mehdi Schenkel, Flavio S Utsunomiya, Yuri T O’Brien, Ana Maria Pérez Sölkner, Johann McEwan, John C Van Tassell, Curtis P Sonstegard, Tad S Garcia, José Fernando |
author_facet | Carvalheiro, Roberto Boison, Solomon A Neves, Haroldo H R Sargolzaei, Mehdi Schenkel, Flavio S Utsunomiya, Yuri T O’Brien, Ana Maria Pérez Sölkner, Johann McEwan, John C Van Tassell, Curtis P Sonstegard, Tad S Garcia, José Fernando |
author_sort | Carvalheiro, Roberto |
collection | PubMed |
description | BACKGROUND: Genotype imputation from low-density (LD) to high-density single nucleotide polymorphism (SNP) chips is an important step before applying genomic selection, since denser chips tend to provide more reliable genomic predictions. Imputation methods rely partially on linkage disequilibrium between markers to infer unobserved genotypes. Bos indicus cattle (e.g. Nelore breed) are characterized, in general, by lower levels of linkage disequilibrium between genetic markers at short distances, compared to taurine breeds. Thus, it is important to evaluate the accuracy of imputation to better define which imputation method and chip are most appropriate for genomic applications in indicine breeds. METHODS: Accuracy of genotype imputation in Nelore cattle was evaluated using different LD chips, imputation software and sets of animals. Twelve commercial and customized LD chips with densities ranging from 7 K to 75 K were tested. Customized LD chips were virtually designed taking into account minor allele frequency, linkage disequilibrium and distance between markers. Software programs FImpute and BEAGLE were applied to impute genotypes. From 995 bulls and 1247 cows that were genotyped with the Illumina® BovineHD chip (HD), 793 sires composed the reference set, and the remaining 202 younger sires and all the cows composed two separate validation sets for which genotypes were masked except for the SNPs of the LD chip that were to be tested. RESULTS: Imputation accuracy increased with the SNP density of the LD chip. However, the gain in accuracy with LD chips with more than 15 K SNPs was relatively small because accuracy was already high at this density. Commercial and customized LD chips with equivalent densities presented similar results. FImpute outperformed BEAGLE for all LD chips and validation sets. Regardless of the imputation software used, accuracy tended to increase as the relatedness between imputed and reference animals increased, especially for the 7 K chip. CONCLUSIONS: If the Illumina® BovineHD is considered as the target chip for genomic applications in the Nelore breed, cost-effectiveness can be improved by genotyping part of the animals with a chip containing around 15 K useful SNPs and imputing their high-density missing genotypes with FImpute. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12711-014-0069-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4192291 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41922912014-10-11 Accuracy of genotype imputation in Nelore cattle Carvalheiro, Roberto Boison, Solomon A Neves, Haroldo H R Sargolzaei, Mehdi Schenkel, Flavio S Utsunomiya, Yuri T O’Brien, Ana Maria Pérez Sölkner, Johann McEwan, John C Van Tassell, Curtis P Sonstegard, Tad S Garcia, José Fernando Genet Sel Evol Research BACKGROUND: Genotype imputation from low-density (LD) to high-density single nucleotide polymorphism (SNP) chips is an important step before applying genomic selection, since denser chips tend to provide more reliable genomic predictions. Imputation methods rely partially on linkage disequilibrium between markers to infer unobserved genotypes. Bos indicus cattle (e.g. Nelore breed) are characterized, in general, by lower levels of linkage disequilibrium between genetic markers at short distances, compared to taurine breeds. Thus, it is important to evaluate the accuracy of imputation to better define which imputation method and chip are most appropriate for genomic applications in indicine breeds. METHODS: Accuracy of genotype imputation in Nelore cattle was evaluated using different LD chips, imputation software and sets of animals. Twelve commercial and customized LD chips with densities ranging from 7 K to 75 K were tested. Customized LD chips were virtually designed taking into account minor allele frequency, linkage disequilibrium and distance between markers. Software programs FImpute and BEAGLE were applied to impute genotypes. From 995 bulls and 1247 cows that were genotyped with the Illumina® BovineHD chip (HD), 793 sires composed the reference set, and the remaining 202 younger sires and all the cows composed two separate validation sets for which genotypes were masked except for the SNPs of the LD chip that were to be tested. RESULTS: Imputation accuracy increased with the SNP density of the LD chip. However, the gain in accuracy with LD chips with more than 15 K SNPs was relatively small because accuracy was already high at this density. Commercial and customized LD chips with equivalent densities presented similar results. FImpute outperformed BEAGLE for all LD chips and validation sets. Regardless of the imputation software used, accuracy tended to increase as the relatedness between imputed and reference animals increased, especially for the 7 K chip. CONCLUSIONS: If the Illumina® BovineHD is considered as the target chip for genomic applications in the Nelore breed, cost-effectiveness can be improved by genotyping part of the animals with a chip containing around 15 K useful SNPs and imputing their high-density missing genotypes with FImpute. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12711-014-0069-1) contains supplementary material, which is available to authorized users. BioMed Central 2014-10-10 /pmc/articles/PMC4192291/ /pubmed/25927950 http://dx.doi.org/10.1186/s12711-014-0069-1 Text en © Carvalheiro et al.; licensee BioMed Central Ltd. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Carvalheiro, Roberto Boison, Solomon A Neves, Haroldo H R Sargolzaei, Mehdi Schenkel, Flavio S Utsunomiya, Yuri T O’Brien, Ana Maria Pérez Sölkner, Johann McEwan, John C Van Tassell, Curtis P Sonstegard, Tad S Garcia, José Fernando Accuracy of genotype imputation in Nelore cattle |
title | Accuracy of genotype imputation in Nelore cattle |
title_full | Accuracy of genotype imputation in Nelore cattle |
title_fullStr | Accuracy of genotype imputation in Nelore cattle |
title_full_unstemmed | Accuracy of genotype imputation in Nelore cattle |
title_short | Accuracy of genotype imputation in Nelore cattle |
title_sort | accuracy of genotype imputation in nelore cattle |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4192291/ https://www.ncbi.nlm.nih.gov/pubmed/25927950 http://dx.doi.org/10.1186/s12711-014-0069-1 |
work_keys_str_mv | AT carvalheiroroberto accuracyofgenotypeimputationinnelorecattle AT boisonsolomona accuracyofgenotypeimputationinnelorecattle AT nevesharoldohr accuracyofgenotypeimputationinnelorecattle AT sargolzaeimehdi accuracyofgenotypeimputationinnelorecattle AT schenkelflavios accuracyofgenotypeimputationinnelorecattle AT utsunomiyayurit accuracyofgenotypeimputationinnelorecattle AT obrienanamariaperez accuracyofgenotypeimputationinnelorecattle AT solknerjohann accuracyofgenotypeimputationinnelorecattle AT mcewanjohnc accuracyofgenotypeimputationinnelorecattle AT vantassellcurtisp accuracyofgenotypeimputationinnelorecattle AT sonstegardtads accuracyofgenotypeimputationinnelorecattle AT garciajosefernando accuracyofgenotypeimputationinnelorecattle |