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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
21/01/2016 |
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Data da última atualização: |
22/06/2016 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
TIZIOTO, P.; COUTINHO, L. L.; DECKER, J. E.; SCHNABEL, R. D.; ROSA, C. O.; OLIVEIRA, P. S. N.; SOUZA, M. M.; MOURÃO, G. B.; TULLIO, R. R.; CHAVES, A. S.; LANNA, D. P. D.; ZERLOTINI NETO, A.; MUDADU, M. A.; TAYLOR, J. F.; REGITANO, L. C. A. |
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Afiliação: |
POLYANA TIZIOTO, CPPSE, University of Missouri Columbia; LUIZ L. COUTINHO, Esalq/USP; JARED E. DECKER, University of Missouri Columbia; ROBERT D. SCHNABEL, University of Missouri Columbia; KAMILA O. ROSA, Unesp Jaboticabal; PRISCILA S. N. OLIVEIRA, UFSCar; MARCELA M. SOUZA, UFSCar; GERSON B. MOURÃO, Esalq/USP; RYMER RAMIZ TULLIO, CPPSE; AMÁLIA S. CHAVES, Esalq/USP; DANTE P. D. LANNA, Esalq/USP; ADHEMAR ZERLOTINI NETO, CNPTIA; MAURICIO DE ALVARENGA MUDADU, CPPSE; JEREMY F. TAYLOR, University of Missouri Columbia; LUCIANA CORREIA DE ALMEIDA REGITANO, CPPSE. |
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Título: |
Global liver gene expression differences in Nelore steers with divergent residual feed intake phenotypes. |
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Ano de publicação: |
2015 |
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Fonte/Imprenta: |
BMC Genomics, London, v. 16, p. 1-14, 2015. |
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DOI: |
DOI 10.1186/s12864-015-1464-x |
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Idioma: |
Inglês |
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Conteúdo: |
Background: Efficiency of feed utilization is important for animal production because it can reduce greenhouse gas emissions and improve industry profitability. However, the genetic basis of feed utilization in livestock remains poorly understood. Recent developments in molecular genetics, such as platforms for genome-wide genotyping and sequencing, provide an opportunity to identify genes and pathways that influence production traits. It is known that transcriptional networks influence feed efficiency-related traits such as growth and energy balance. This study sought to identify differentially expressed genes in animals genetically divergent for Residual Feed Intake (RFI), using RNA sequencing methodology (RNA-seq) to obtain information from genome-wide expression profiles in the liver tissues of Nelore cattle. Results: Differential gene expression analysis between high Residual Feed Intake (HRFI, inefficient) and low Residual Feed Intake (LRFI, efficient) groups was performed to provide insights into the molecular mechanisms that underlie feed efficiency-related traits in beef cattle. A total of 112 annotated genes were identified as being differentially expressed between animals with divergent RFI phenotypes. These genes are involved in ion transport and metal ion binding; act as membrane or transmembrane proteins; and belong to gene clusters that are likely related to the transport and catalysis of molecules through the cell membrane and essential mechanisms of nutrient absorption. Genes with functions in cellular signaling, growth and proliferation, cell death and survival were also differentially expressed. Among the over-represented pathways were drug or xenobiotic metabolism, complement and coagulation cascades, NRF2-mediated oxidative stress, melatonin degradation and glutathione metabolism. Conclusions: Our data provide new insights and perspectives on the genetic basis of feed efficiency in cattle. Some previously identified mechanisms were supported and new pathways controlling feed efficiency in Nelore cattle were discovered. We potentially identified genes and pathways that play key roles in hepatic metabolic adaptations to oxidative stress such as those involved in antioxidant mechanisms. These results improve our understanding of the metabolic mechanisms underlying feed efficiency in beef cattle and will help develop strategies for selection towards the desired phenotype. MenosBackground: Efficiency of feed utilization is important for animal production because it can reduce greenhouse gas emissions and improve industry profitability. However, the genetic basis of feed utilization in livestock remains poorly understood. Recent developments in molecular genetics, such as platforms for genome-wide genotyping and sequencing, provide an opportunity to identify genes and pathways that influence production traits. It is known that transcriptional networks influence feed efficiency-related traits such as growth and energy balance. This study sought to identify differentially expressed genes in animals genetically divergent for Residual Feed Intake (RFI), using RNA sequencing methodology (RNA-seq) to obtain information from genome-wide expression profiles in the liver tissues of Nelore cattle. Results: Differential gene expression analysis between high Residual Feed Intake (HRFI, inefficient) and low Residual Feed Intake (LRFI, efficient) groups was performed to provide insights into the molecular mechanisms that underlie feed efficiency-related traits in beef cattle. A total of 112 annotated genes were identified as being differentially expressed between animals with divergent RFI phenotypes. These genes are involved in ion transport and metal ion binding; act as membrane or transmembrane proteins; and belong to gene clusters that are likely related to the transport and catalysis of molecules through the cell membrane and essential mechanisms of nutrient... Mostrar Tudo |
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Palavras-Chave: |
Bioinformática; Feed efficiency; RFI; Sequenciamento genético; Transcriptoma. |
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Thesagro: |
Bos Indicus. |
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Thesaurus Nal: |
Bioinformatics; Feed conversion; Transcriptomics; Zebu. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/138317/1/Global-liver-Tizioto.pdf
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Marc: |
LEADER 03613naa a2200421 a 4500
001 2034697
005 2016-06-22
008 2015 bl uuuu u00u1 u #d
024 7 $aDOI 10.1186/s12864-015-1464-x$2DOI
100 1 $aTIZIOTO, P.
245 $aGlobal liver gene expression differences in Nelore steers with divergent residual feed intake phenotypes.$h[electronic resource]
260 $c2015
520 $aBackground: Efficiency of feed utilization is important for animal production because it can reduce greenhouse gas emissions and improve industry profitability. However, the genetic basis of feed utilization in livestock remains poorly understood. Recent developments in molecular genetics, such as platforms for genome-wide genotyping and sequencing, provide an opportunity to identify genes and pathways that influence production traits. It is known that transcriptional networks influence feed efficiency-related traits such as growth and energy balance. This study sought to identify differentially expressed genes in animals genetically divergent for Residual Feed Intake (RFI), using RNA sequencing methodology (RNA-seq) to obtain information from genome-wide expression profiles in the liver tissues of Nelore cattle. Results: Differential gene expression analysis between high Residual Feed Intake (HRFI, inefficient) and low Residual Feed Intake (LRFI, efficient) groups was performed to provide insights into the molecular mechanisms that underlie feed efficiency-related traits in beef cattle. A total of 112 annotated genes were identified as being differentially expressed between animals with divergent RFI phenotypes. These genes are involved in ion transport and metal ion binding; act as membrane or transmembrane proteins; and belong to gene clusters that are likely related to the transport and catalysis of molecules through the cell membrane and essential mechanisms of nutrient absorption. Genes with functions in cellular signaling, growth and proliferation, cell death and survival were also differentially expressed. Among the over-represented pathways were drug or xenobiotic metabolism, complement and coagulation cascades, NRF2-mediated oxidative stress, melatonin degradation and glutathione metabolism. Conclusions: Our data provide new insights and perspectives on the genetic basis of feed efficiency in cattle. Some previously identified mechanisms were supported and new pathways controlling feed efficiency in Nelore cattle were discovered. We potentially identified genes and pathways that play key roles in hepatic metabolic adaptations to oxidative stress such as those involved in antioxidant mechanisms. These results improve our understanding of the metabolic mechanisms underlying feed efficiency in beef cattle and will help develop strategies for selection towards the desired phenotype.
650 $aBioinformatics
650 $aFeed conversion
650 $aTranscriptomics
650 $aZebu
650 $aBos Indicus
653 $aBioinformática
653 $aFeed efficiency
653 $aRFI
653 $aSequenciamento genético
653 $aTranscriptoma
700 1 $aCOUTINHO, L. L.
700 1 $aDECKER, J. E.
700 1 $aSCHNABEL, R. D.
700 1 $aROSA, C. O.
700 1 $aOLIVEIRA, P. S. N.
700 1 $aSOUZA, M. M.
700 1 $aMOURÃO, G. B.
700 1 $aTULLIO, R. R.
700 1 $aCHAVES, A. S.
700 1 $aLANNA, D. P. D.
700 1 $aZERLOTINI NETO, A.
700 1 $aMUDADU, M. A.
700 1 $aTAYLOR, J. F.
700 1 $aREGITANO, L. C. A.
773 $tBMC Genomics, London$gv. 16, p. 1-14, 2015.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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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. |
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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Circulação/Nível: |
A - 2 |
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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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