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Biblioteca(s): |
Embrapa Instrumentação. |
Data corrente: |
05/04/2021 |
Data da última atualização: |
10/06/2022 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
CÔNSOLO, N. R. B.; BUARQUE, V. L. M.; SILVA, J.; POLETI, M. D.; BARBOSA, L. C. G. S.; HIGUERA-PADILLA, A.; GOMEZ, J. F. M.; COLNAGO, L. A.; GERRARD, D. E.; SARAN NETO, A.; SILVA, S. L. |
Afiliação: |
LUIZ ALBERTO COLNAGO, CNPDIA. |
Título: |
Muscle and liver metabolomic signatures associated with residual feed intake in Nellore cattle. |
Ano de publicação: |
2021 |
Fonte/Imprenta: |
Animal Feed Science and Technology, v. 271, 114757, 2021. |
ISSN: |
0377-8401 |
DOI: |
https://doi.org/10.1016/j.anifeedsci.2020.114757 |
Idioma: |
Inglês |
Conteúdo: |
Identification of those cattle genetics with superior feed efficiency is necessary to increase the productivity of the entire beef industry. The aim of this study was to investigate metabolites profiling in the liver and muscle to identify physiological changes in animals in the livestock system with low or high residual feed intake. Liver and muscle were collected after slaughter from Nellore males, with high and low residual feed intake (H-RFI, n = 10 and L-RFI, n = 10, respectively). Metabolites were extracted with cold methanol/water solution (4:3 v/v). Metabolomics analyses were performed by 1D 1 H nuclear magnetic resonance. Metabolites were identified using Chenomx and analysed using MetaboAnalyst 4.0. The residual feed intake classification did not change most of animal performance traits; however, animals with lower residual feed intake presented greater carcass dressing, lower carcass fat deposition. Sixty-three compounds were identified in the liver and 31 in muscle. Coexpression network analysis was carried out and identified four metabolite network modules correlated with the phenotypic traits, indicating common metabolites with a variate important projection score that influences residual feed intake. Metabolites in liver samples was correlated with energy and protein metabolism and on muscle with fat metabolism. Differences on energetic metabolism, including of carbohydrate- and fat-correlated compounds, according to residual feed intake can be assessed by importance of concentration of citrate, isocitrate, glucose-6-phosphate, nicotinamide adenine dinucleotide + hydrogen and creatine phosphate (in liver) and choline, glycine, glycerol, malonate, glucose-6- phosphate and 3-hydroxybutyrate (in muscle). Moreover, differences on protein metabolism, MenosIdentification of those cattle genetics with superior feed efficiency is necessary to increase the productivity of the entire beef industry. The aim of this study was to investigate metabolites profiling in the liver and muscle to identify physiological changes in animals in the livestock system with low or high residual feed intake. Liver and muscle were collected after slaughter from Nellore males, with high and low residual feed intake (H-RFI, n = 10 and L-RFI, n = 10, respectively). Metabolites were extracted with cold methanol/water solution (4:3 v/v). Metabolomics analyses were performed by 1D 1 H nuclear magnetic resonance. Metabolites were identified using Chenomx and analysed using MetaboAnalyst 4.0. The residual feed intake classification did not change most of animal performance traits; however, animals with lower residual feed intake presented greater carcass dressing, lower carcass fat deposition. Sixty-three compounds were identified in the liver and 31 in muscle. Coexpression network analysis was carried out and identified four metabolite network modules correlated with the phenotypic traits, indicating common metabolites with a variate important projection score that influences residual feed intake. Metabolites in liver samples was correlated with energy and protein metabolism and on muscle with fat metabolism. Differences on energetic metabolism, including of carbohydrate- and fat-correlated compounds, according to residual feed intake can be assessed by imp... Mostrar Tudo |
Palavras-Chave: |
Muscle; Residual feed intake. |
Categoria do assunto: |
-- |
Marc: |
LEADER 02667naa a2200289 a 4500 001 2131049 005 2022-06-10 008 2021 bl uuuu u00u1 u #d 022 $a0377-8401 024 7 $ahttps://doi.org/10.1016/j.anifeedsci.2020.114757$2DOI 100 1 $aCÔNSOLO, N. R. B. 245 $aMuscle and liver metabolomic signatures associated with residual feed intake in Nellore cattle.$h[electronic resource] 260 $c2021 520 $aIdentification of those cattle genetics with superior feed efficiency is necessary to increase the productivity of the entire beef industry. The aim of this study was to investigate metabolites profiling in the liver and muscle to identify physiological changes in animals in the livestock system with low or high residual feed intake. Liver and muscle were collected after slaughter from Nellore males, with high and low residual feed intake (H-RFI, n = 10 and L-RFI, n = 10, respectively). Metabolites were extracted with cold methanol/water solution (4:3 v/v). Metabolomics analyses were performed by 1D 1 H nuclear magnetic resonance. Metabolites were identified using Chenomx and analysed using MetaboAnalyst 4.0. The residual feed intake classification did not change most of animal performance traits; however, animals with lower residual feed intake presented greater carcass dressing, lower carcass fat deposition. Sixty-three compounds were identified in the liver and 31 in muscle. Coexpression network analysis was carried out and identified four metabolite network modules correlated with the phenotypic traits, indicating common metabolites with a variate important projection score that influences residual feed intake. Metabolites in liver samples was correlated with energy and protein metabolism and on muscle with fat metabolism. Differences on energetic metabolism, including of carbohydrate- and fat-correlated compounds, according to residual feed intake can be assessed by importance of concentration of citrate, isocitrate, glucose-6-phosphate, nicotinamide adenine dinucleotide + hydrogen and creatine phosphate (in liver) and choline, glycine, glycerol, malonate, glucose-6- phosphate and 3-hydroxybutyrate (in muscle). Moreover, differences on protein metabolism, 653 $aMuscle 653 $aResidual feed intake 700 1 $aBUARQUE, V. L. M. 700 1 $aSILVA, J. 700 1 $aPOLETI, M. D. 700 1 $aBARBOSA, L. C. G. S. 700 1 $aHIGUERA-PADILLA, A. 700 1 $aGOMEZ, J. F. M. 700 1 $aCOLNAGO, L. A. 700 1 $aGERRARD, D. E. 700 1 $aSARAN NETO, A. 700 1 $aSILVA, S. L. 773 $tAnimal Feed Science and Technology$gv. 271, 114757, 2021.
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Embrapa Instrumentação (CNPDIA) |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
Data corrente: |
31/08/2012 |
Data da última atualização: |
27/02/2024 |
Tipo da produção científica: |
Resumo em Anais de Congresso |
Autoria: |
YAMAGISHI, M. E. B.; HERAI, R. |
Afiliação: |
MICHEL EDUARDO BELEZA YAMAGISHI, CNPTIA; ROBERTO HERAI, University of California San Diego. |
Título: |
Identification of repetitive sequences within gene loci. |
Ano de publicação: |
2012 |
Fonte/Imprenta: |
In: INTERNATIONAL PLANT & ANIMAL GENOME, 20., 2012, San Diego. Abstracts... Jersey City: Scherago International, 2012. |
Descrição Física: |
1 pôster. |
Idioma: |
Inglês |
Notas: |
PAG 2012. P0983. |
Conteúdo: |
We developed a Web-based software, called RepGraph, that identify and graphically display the intron-exon structure of those sequences for several model organisms. |
Palavras-Chave: |
Bioinformática; Genomas; Genomes; Sequência genética; Software; Software RepGraph. |
Thesaurus NAL: |
Bioinformatics; Gene banks. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/65420/1/geneLoci.pdf
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Marc: |
LEADER 00888nam a2200241 a 4500 001 1932792 005 2024-02-27 008 2012 bl uuuu u00u1 u #d 100 1 $aYAMAGISHI, M. E. B. 245 $aIdentification of repetitive sequences within gene loci.$h[electronic resource] 260 $aIn: INTERNATIONAL PLANT & ANIMAL GENOME, 20., 2012, San Diego. Abstracts... Jersey City: Scherago International$c2012 300 $c1 pôster. 500 $aPAG 2012. P0983. 520 $aWe developed a Web-based software, called RepGraph, that identify and graphically display the intron-exon structure of those sequences for several model organisms. 650 $aBioinformatics 650 $aGene banks 653 $aBioinformática 653 $aGenomas 653 $aGenomes 653 $aSequência genética 653 $aSoftware 653 $aSoftware RepGraph 700 1 $aHERAI, R.
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