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Registro Completo |
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Biblioteca(s): |
Embrapa Pecuária Sudeste. |
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Data corrente: |
26/11/2015 |
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Data da última atualização: |
15/03/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
CHUD, T. C. S.; VENTURA, R. V.; SCHENKEL, F. S.; CARVALHEIRO, R.; BUZANSKAS, M. E.; ROSA, J. O.; MUDADU, M. de A.; SILVA, M. V. G. B.; MOKRY, F. B.; MARCONDES, C. R.; REGITANO, L. C. de A.; MUNARI, D. P. |
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Afiliação: |
TATIANE C. S. CHUD, UNESP; RICARDO V. VENTURA, UNESP; FLAVIO S. SCHENKEL, University of Guelph; ROBERTO CARVALHEIRO, UNESP; MARCOS E. BUZANSKAS, UNESP; JAQUELINE O. ROSA, UNESP; MAURICIO DE ALVARENGA MUDADU, CPPSE; MARCOS VINICIUS GUALBERTO B SILVA, CNPGL; FABIANA B. MOKRY, Federal University of São Carlos; CINTIA RIGHETTI MARCONDES, CPPSE; LUCIANA CORREIA DE ALMEIDA REGITANO, CPPSE; DANÍSIO P. MUNARI, UNESP. |
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Título: |
Strategies for genotype imputation in composite beef cattle. |
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Ano de publicação: |
2015 |
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Fonte/Imprenta: |
BMC Genomics, v. 16, n. 99, 2015. |
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Páginas: |
10 p. |
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DOI: |
10.1186/s12863-015-0251-7 |
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Idioma: |
Inglês |
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Conteúdo: |
Genotype imputation has been used to increase genomic information, allow more animals in genome-wide analyses, and reduce genotyping costs. In Brazilian beef cattle production, many animals are resulting from crossbreeding and such an event may alter linkage disequilibrium patterns. Thus, the challenge is to obtain accurately imputed genotypes in crossbred animals. The objective of this study was to evaluate the best fitting and most accurate imputation strategy on the MA genetic group (the progeny of a Charolais sire mated with crossbred Canchim X Zebu cows) and Canchim cattle. The data set contained 400 animals (born between 1999 and 2005) genotyped with the Illumina BovineHD panel. Imputation accuracy of genotypes from the Illumina-Bovine3K (3K), Illumina-BovineLD (6K), GeneSeek-Genomic-Profiler (GGP) BeefLD (GGP9K), GGP-IndicusLD (GGP20Ki), Illumina-BovineSNP50 (50K), GGP-IndicusHD (GGP75Ki), and GGP-BeefHD (GGP80K) to Illumina-BovineHD (HD) SNP panels were investigated. Seven scenarios for reference and target populations were tested; the animals were grouped according with birth year (S1), genetic groups (S2 and S3), genetic groups and birth year (S4 and S5), gender (S6), and gender and birth year (S7). Analyses were performed using FImpute and BEAGLE software and computation run-time was recorded. Genotype imputation accuracy was measured by concordance rate (CR) and allelic R square (R2). |
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Palavras-Chave: |
Canchim breed; Crossbred cattle; Genomic data; Low density panel. |
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Thesaurus Nal: |
single nucleotide polymorphism. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/134135/1/regitano4.pdf
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Marc: |
LEADER 02356naa a2200337 a 4500
001 2029694
005 2023-03-15
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024 7 $a10.1186/s12863-015-0251-7$2DOI
100 1 $aCHUD, T. C. S.
245 $aStrategies for genotype imputation in composite beef cattle.$h[electronic resource]
260 $c2015
300 $a10 p.
520 $aGenotype imputation has been used to increase genomic information, allow more animals in genome-wide analyses, and reduce genotyping costs. In Brazilian beef cattle production, many animals are resulting from crossbreeding and such an event may alter linkage disequilibrium patterns. Thus, the challenge is to obtain accurately imputed genotypes in crossbred animals. The objective of this study was to evaluate the best fitting and most accurate imputation strategy on the MA genetic group (the progeny of a Charolais sire mated with crossbred Canchim X Zebu cows) and Canchim cattle. The data set contained 400 animals (born between 1999 and 2005) genotyped with the Illumina BovineHD panel. Imputation accuracy of genotypes from the Illumina-Bovine3K (3K), Illumina-BovineLD (6K), GeneSeek-Genomic-Profiler (GGP) BeefLD (GGP9K), GGP-IndicusLD (GGP20Ki), Illumina-BovineSNP50 (50K), GGP-IndicusHD (GGP75Ki), and GGP-BeefHD (GGP80K) to Illumina-BovineHD (HD) SNP panels were investigated. Seven scenarios for reference and target populations were tested; the animals were grouped according with birth year (S1), genetic groups (S2 and S3), genetic groups and birth year (S4 and S5), gender (S6), and gender and birth year (S7). Analyses were performed using FImpute and BEAGLE software and computation run-time was recorded. Genotype imputation accuracy was measured by concordance rate (CR) and allelic R square (R2).
650 $asingle nucleotide polymorphism
653 $aCanchim breed
653 $aCrossbred cattle
653 $aGenomic data
653 $aLow density panel
700 1 $aVENTURA, R. V.
700 1 $aSCHENKEL, F. S.
700 1 $aCARVALHEIRO, R.
700 1 $aBUZANSKAS, M. E.
700 1 $aROSA, J. O.
700 1 $aMUDADU, M. de A.
700 1 $aSILVA, M. V. G. B.
700 1 $aMOKRY, F. B.
700 1 $aMARCONDES, C. R.
700 1 $aREGITANO, L. C. de A.
700 1 $aMUNARI, D. P.
773 $tBMC Genomics$gv. 16, n. 99, 2015.
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Registro original: |
Embrapa Pecuária Sudeste (CPPSE) |
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| 1. |  | CHUD, T. C. S.; VENTURA, R. V.; SCHENKEL, F. S.; CARVALHEIRO, R.; BUZANSKAS, M. E.; ROSA, J. O.; MUDADU, M. de A.; SILVA, M. V. G. B.; MOKRY, F. B.; MARCONDES, C. R.; REGITANO, L. C. de A.; MUNARI, D. P. Strategies for genotype imputation in composite beef cattle. BMC Genomics, v. 16, n. 99, 2015. 10 p.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Pecuária Sudeste. |
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