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 | Acesso ao texto completo restrito à biblioteca da Embrapa Suínos e Aves. Para informações adicionais entre em contato com cnpsa.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Suínos e Aves. |
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Data corrente: |
28/11/2019 |
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Data da última atualização: |
06/12/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
MOREIRA, G. C. M.; POLETI, M. D.; PÉRTILLE, F.; BOSCHIERO, C.; CESAR, A. S. M.; GODOY, T. F.; LEDUR, M. C.; REECY, J. M.; GARRICK, D. J.; COUTINHO, L. L. |
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Afiliação: |
GABRIEL COSTA MONTEIRO MOREIRA, USP; USP; USP; CLARISSA BOSCHIERO, USP; ALINE SILVA MELLO CESAR, USP; THAIS FERNANDA GODOY, USP; MONICA CORREA LEDUR, CNPSA; JAMES M. REECY, USP; DORIAN J. GARRICK, USP; LUIZ LEHMANN COUTINHO, USP. |
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Título: |
Unraveling genomic associations with feed efficiency and body weight traits in chickens through an integrative approach. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
BMC Genetics, v. 20, n. 83, 2019. |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract Background: Feed efficiency and growth rate have been targets for selection to improve chicken production. The incorporation of genomic tools may help to accelerate selection. We genotyped 529 individuals using a high-density SNP chip (600 K, Affymetrix®) to estimate genomic heritability of performance traits and to identify genomic regions and their positional candidate genes associated with performance traits in a Brazilian F2 Chicken Resource population. Regions exhibiting selection signatures and a SNP dataset from resequencing were integrated with the genomic regions identified using the chip to refine the list of positional candidate genes and identify potential causative mutations. Results: Feed intake (FI), feed conversion ratio (FC), feed efficiency (FE) and weight gain (WG) exhibited low genomic heritability values (i.e. from 0.0002 to 0.13), while body weight at hatch (BW1), 35 days-of-age (BW35), and 41 days-of-age (BW41) exhibited high genomic heritability values (i.e. from 0.60 to 0.73) in this F2 population. Twenty unique 1-Mb genomic windows were associated with BW1, BW35 or BW41, located on GGA1?4, 6?7, 10, 14, 24, 27 and 28. Thirty-eight positional candidate genes were identified within these windows, and three of them overlapped with selection signature regions. Thirteen predicted deleterious and three high impact sequence SNPs in these QTL regions were annotated in 11 positional candidate genes related to osteogenesis, skeletal muscle development, growth, energy metabolism and lipid metabolism, which may be associated with body weight in chickens. Conclusions: The use of a high-density SNP array to identify QTL which were integrated with whole genome sequence signatures of selection allowed the identification of candidate genes and candidate causal variants. One novel QTL was detected providing additional information to understand the genetic architecture of body weight traits. We identified QTL for body weight traits, which were also associated with fatness in the same population. Our findings form a basis for further functional studies to elucidate the role of specific genes in regulating body weight and fat deposition in chickens, generating useful information for poultry breeding programs. MenosAbstract Background: Feed efficiency and growth rate have been targets for selection to improve chicken production. The incorporation of genomic tools may help to accelerate selection. We genotyped 529 individuals using a high-density SNP chip (600 K, Affymetrix®) to estimate genomic heritability of performance traits and to identify genomic regions and their positional candidate genes associated with performance traits in a Brazilian F2 Chicken Resource population. Regions exhibiting selection signatures and a SNP dataset from resequencing were integrated with the genomic regions identified using the chip to refine the list of positional candidate genes and identify potential causative mutations. Results: Feed intake (FI), feed conversion ratio (FC), feed efficiency (FE) and weight gain (WG) exhibited low genomic heritability values (i.e. from 0.0002 to 0.13), while body weight at hatch (BW1), 35 days-of-age (BW35), and 41 days-of-age (BW41) exhibited high genomic heritability values (i.e. from 0.60 to 0.73) in this F2 population. Twenty unique 1-Mb genomic windows were associated with BW1, BW35 or BW41, located on GGA1?4, 6?7, 10, 14, 24, 27 and 28. Thirty-eight positional candidate genes were identified within these windows, and three of them overlapped with selection signature regions. Thirteen predicted deleterious and three high impact sequence SNPs in these QTL regions were annotated in 11 positional candidate genes related to osteogenesis, skeletal muscle development... Mostrar Tudo |
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Palavras-Chave: |
Características de desempenho; Genomic heritability; Genotypic data; GWAS; Herdabilidade genômica; Performance traits. |
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Thesagro: |
Frango de Corte; Genoma; Seleção Genótipa. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 03240naa a2200337 a 4500
001 2115438
005 2019-12-06
008 2019 bl uuuu u00u1 u #d
100 1 $aMOREIRA, G. C. M.
245 $aUnraveling genomic associations with feed efficiency and body weight traits in chickens through an integrative approach.$h[electronic resource]
260 $c2019
520 $aAbstract Background: Feed efficiency and growth rate have been targets for selection to improve chicken production. The incorporation of genomic tools may help to accelerate selection. We genotyped 529 individuals using a high-density SNP chip (600 K, Affymetrix®) to estimate genomic heritability of performance traits and to identify genomic regions and their positional candidate genes associated with performance traits in a Brazilian F2 Chicken Resource population. Regions exhibiting selection signatures and a SNP dataset from resequencing were integrated with the genomic regions identified using the chip to refine the list of positional candidate genes and identify potential causative mutations. Results: Feed intake (FI), feed conversion ratio (FC), feed efficiency (FE) and weight gain (WG) exhibited low genomic heritability values (i.e. from 0.0002 to 0.13), while body weight at hatch (BW1), 35 days-of-age (BW35), and 41 days-of-age (BW41) exhibited high genomic heritability values (i.e. from 0.60 to 0.73) in this F2 population. Twenty unique 1-Mb genomic windows were associated with BW1, BW35 or BW41, located on GGA1?4, 6?7, 10, 14, 24, 27 and 28. Thirty-eight positional candidate genes were identified within these windows, and three of them overlapped with selection signature regions. Thirteen predicted deleterious and three high impact sequence SNPs in these QTL regions were annotated in 11 positional candidate genes related to osteogenesis, skeletal muscle development, growth, energy metabolism and lipid metabolism, which may be associated with body weight in chickens. Conclusions: The use of a high-density SNP array to identify QTL which were integrated with whole genome sequence signatures of selection allowed the identification of candidate genes and candidate causal variants. One novel QTL was detected providing additional information to understand the genetic architecture of body weight traits. We identified QTL for body weight traits, which were also associated with fatness in the same population. Our findings form a basis for further functional studies to elucidate the role of specific genes in regulating body weight and fat deposition in chickens, generating useful information for poultry breeding programs.
650 $aFrango de Corte
650 $aGenoma
650 $aSeleção Genótipa
653 $aCaracterísticas de desempenho
653 $aGenomic heritability
653 $aGenotypic data
653 $aGWAS
653 $aHerdabilidade genômica
653 $aPerformance traits
700 1 $aPOLETI, M. D.
700 1 $aPÉRTILLE, F.
700 1 $aBOSCHIERO, C.
700 1 $aCESAR, A. S. M.
700 1 $aGODOY, T. F.
700 1 $aLEDUR, M. C.
700 1 $aREECY, J. M.
700 1 $aGARRICK, D. J.
700 1 $aCOUTINHO, L. L.
773 $tBMC Genetics$gv. 20, n. 83, 2019.
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Embrapa Suínos e Aves (CNPSA) |
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Registro Completo
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Biblioteca(s): |
Embrapa Soja. |
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Data corrente: |
30/10/2018 |
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Data da última atualização: |
30/10/2018 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
LORINI, I.; FRANÇA-NETO, J. B.; HENNING, A. A.; KRZYZANOWSKI, F. C.; HENNING, F. A.; OLIVEIRA, M. A. de; MANDARINO, J. M. G.; HIRAKURI, M. H.; BENASSI, V. T. |
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Afiliação: |
IRINEU LORINI, CNPSO; JOSE DE BARROS FRANCA NETO, CNPSO; ADEMIR ASSIS HENNING, CNPSO; FRANCISCO CARLOS KRZYZANOWSKI, CNPSO; FERNANDO AUGUSTO HENNING, CNPSO; MARCELO ALVARES DE OLIVEIRA, CNPSO; JOSE MARCOS GONTIJO MANDARINO, CNPSO; MARCELO HIROSHI HIRAKURI, CNPSO; VERA DE TOLEDO BENASSI, CNPSO. |
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Título: |
Determinação dos grãos de soja danificados por percevejos (IN11) nas safras 2014/15 a 2016/17. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
In: CONFERÊNCIA BRASILEIRA DE PÓS-COLHEITA, 7; SIMPÓSIO PARANAENSE DE PÓS-COLHEITA DE GRÃOS, 10, 2018, Londrina. Anais... Londrina: ABRAPOS, 2018. Trabalho 16. |
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Páginas: |
p. 238-244. |
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Idioma: |
Português |
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Notas: |
Organizado por Irineu Lorini, Marcelo Alvares de Oliveira, Lêda Rita D'Antonino Faroni, Vildes Maria Scussel. |
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Thesagro: |
Armazenamento de Alimento; Dano; Grão; Padrão de Alimento; Percevejo; Soja. |
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Thesaurus NAL: |
Grain quality; Soybeans; Storage pests; Stored grain. |
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Categoria do assunto: |
O Insetos e Entomologia |
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Marc: |
LEADER 01178nam a2200337 a 4500
001 2098512
005 2018-10-30
008 2018 bl uuuu u00u1 u #d
100 1 $aLORINI, I.
245 $aDeterminação dos grãos de soja danificados por percevejos (IN11) nas safras 2014/15 a 2016/17.$h[electronic resource]
260 $aIn: CONFERÊNCIA BRASILEIRA DE PÓS-COLHEITA, 7; SIMPÓSIO PARANAENSE DE PÓS-COLHEITA DE GRÃOS, 10, 2018, Londrina. Anais... Londrina: ABRAPOS, 2018. Trabalho 16.$c2018
300 $ap. 238-244.
500 $aOrganizado por Irineu Lorini, Marcelo Alvares de Oliveira, Lêda Rita D'Antonino Faroni, Vildes Maria Scussel.
650 $aGrain quality
650 $aSoybeans
650 $aStorage pests
650 $aStored grain
650 $aArmazenamento de Alimento
650 $aDano
650 $aGrão
650 $aPadrão de Alimento
650 $aPercevejo
650 $aSoja
700 1 $aFRANÇA-NETO, J. B.
700 1 $aHENNING, A. A.
700 1 $aKRZYZANOWSKI, F. C.
700 1 $aHENNING, F. A.
700 1 $aOLIVEIRA, M. A. de
700 1 $aMANDARINO, J. M. G.
700 1 $aHIRAKURI, M. H.
700 1 $aBENASSI, V. T.
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