|
Registro Completo |
|
Biblioteca(s): |
Embrapa Milho e Sorgo. |
|
Data corrente: |
18/09/2020 |
|
Data da última atualização: |
20/12/2020 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Autoria: |
OLIVEIRA, A. A. de; GUIMARAES, L. J. M.; GUIMARÃES, C. T.; GUIMARAES, P. E. de O.; PINTO, M. de O.; PASTINA, M. M.; MARGARIDO, G. R. A. |
|
Afiliação: |
Amanda Avelar de Oliveira, Escola Superior de Agricultura "Luiz de Queiroz"; LAURO JOSE MOREIRA GUIMARAES, CNPMS; CLAUDIA TEIXEIRA GUIMARAES, CNPMS; PAULO EVARISTO DE O GUIMARAES, CNPMS; MARCOS DE OLIVEIRA PINTO, CNPMS; MARIA MARTA PASTINA, CNPMS; Gabriel Rodrigues Alves Margarido, Escola Superior de Agricultura "Luiz de Queiroz". |
|
Título: |
Single nucleotide polymorphism calling and imputation strategies for cost-effective genotyping in a tropical maize breeding program. |
|
Ano de publicação: |
2020 |
|
Fonte/Imprenta: |
Crop Science, v. 60, n. 6, p. 3066-3082, 2020. |
|
DOI: |
10.1002/csc2.20255 |
|
Idioma: |
Inglês |
|
Conteúdo: |
Genotyping-by-sequencing (GBS) datasets typically feature high rates of missingness and heterozygote undercalling, prompting the use of data imputation. We compared the accuracy of four imputation methods?NPUTE, Beagle, knearest neighbors imputation (KNNI), and fast inbreed line library imputation (FILLIN)?using GBS data of maize (Zea mays L.) inbred lines, genotyped using different multiplexing levels. Two strategies for SNP-calling and genotype imputation were evaluated. First, only lines genotyped through 96-plex were used for single nucleotide polymorphism (SNP) discovery, whereas both 96- and 384-plex were simultaneously used in the second strategy. In the first genotype imputation strategy, only the 96-plex lines were imputed, then the remaining lines were appended (96-plex-imputed plus 384-plex) and then imputed. In the second imputation strategy, we jointly imputed both datasets. We also investigated the impacts of including heterozygous genotypes and distinct rates of missing genotypes per locus. The different SNP-calling strategies and percentage of missing data did not substantially affect the imputation accuracy. However, the different imputation strategies showed a substantial effect. Generally, imputations were less accurate for heterozygotes. The scenario 96-plex-imputed plus 384-plex showed accuracies similar to the 96-plex scenario. Beagle and NPUTE produced the highest accuracies. Our results indicate that combining SNP-calling and imputation strategies can enhance genotyping in a cost-effective manner, resulting in higher imputation accuracies. MenosGenotyping-by-sequencing (GBS) datasets typically feature high rates of missingness and heterozygote undercalling, prompting the use of data imputation. We compared the accuracy of four imputation methods?NPUTE, Beagle, knearest neighbors imputation (KNNI), and fast inbreed line library imputation (FILLIN)?using GBS data of maize (Zea mays L.) inbred lines, genotyped using different multiplexing levels. Two strategies for SNP-calling and genotype imputation were evaluated. First, only lines genotyped through 96-plex were used for single nucleotide polymorphism (SNP) discovery, whereas both 96- and 384-plex were simultaneously used in the second strategy. In the first genotype imputation strategy, only the 96-plex lines were imputed, then the remaining lines were appended (96-plex-imputed plus 384-plex) and then imputed. In the second imputation strategy, we jointly imputed both datasets. We also investigated the impacts of including heterozygous genotypes and distinct rates of missing genotypes per locus. The different SNP-calling strategies and percentage of missing data did not substantially affect the imputation accuracy. However, the different imputation strategies showed a substantial effect. Generally, imputations were less accurate for heterozygotes. The scenario 96-plex-imputed plus 384-plex showed accuracies similar to the 96-plex scenario. Beagle and NPUTE produced the highest accuracies. Our results indicate that combining SNP-calling and imputation strategies can... Mostrar Tudo |
|
Palavras-Chave: |
Genotipagem; Imputação. |
|
Thesagro: |
Genética Vegetal; Genótipo; Melhoramento Genético Vegetal; Milho; Polimorfismo; Seleção Genótipa. |
|
Categoria do assunto: |
G Melhoramento Genético |
|
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/217686/1/Single-nucleotide-polymorphism.pdf
|
|
Marc: |
LEADER 02517naa a2200301 a 4500
001 2125019
005 2020-12-20
008 2020 bl uuuu u00u1 u #d
024 7 $a10.1002/csc2.20255$2DOI
100 1 $aOLIVEIRA, A. A. de
245 $aSingle nucleotide polymorphism calling and imputation strategies for cost-effective genotyping in a tropical maize breeding program.$h[electronic resource]
260 $c2020
520 $aGenotyping-by-sequencing (GBS) datasets typically feature high rates of missingness and heterozygote undercalling, prompting the use of data imputation. We compared the accuracy of four imputation methods?NPUTE, Beagle, knearest neighbors imputation (KNNI), and fast inbreed line library imputation (FILLIN)?using GBS data of maize (Zea mays L.) inbred lines, genotyped using different multiplexing levels. Two strategies for SNP-calling and genotype imputation were evaluated. First, only lines genotyped through 96-plex were used for single nucleotide polymorphism (SNP) discovery, whereas both 96- and 384-plex were simultaneously used in the second strategy. In the first genotype imputation strategy, only the 96-plex lines were imputed, then the remaining lines were appended (96-plex-imputed plus 384-plex) and then imputed. In the second imputation strategy, we jointly imputed both datasets. We also investigated the impacts of including heterozygous genotypes and distinct rates of missing genotypes per locus. The different SNP-calling strategies and percentage of missing data did not substantially affect the imputation accuracy. However, the different imputation strategies showed a substantial effect. Generally, imputations were less accurate for heterozygotes. The scenario 96-plex-imputed plus 384-plex showed accuracies similar to the 96-plex scenario. Beagle and NPUTE produced the highest accuracies. Our results indicate that combining SNP-calling and imputation strategies can enhance genotyping in a cost-effective manner, resulting in higher imputation accuracies.
650 $aGenética Vegetal
650 $aGenótipo
650 $aMelhoramento Genético Vegetal
650 $aMilho
650 $aPolimorfismo
650 $aSeleção Genótipa
653 $aGenotipagem
653 $aImputação
700 1 $aGUIMARAES, L. J. M.
700 1 $aGUIMARÃES, C. T.
700 1 $aGUIMARAES, P. E. de O.
700 1 $aPINTO, M. de O.
700 1 $aPASTINA, M. M.
700 1 $aMARGARIDO, G. R. A.
773 $tCrop Science$gv. 60, n. 6, p. 3066-3082, 2020.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Milho e Sorgo (CNPMS) |
|
