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| Registros recuperados : 134 | |
| 81. |  | NASCIMENTO, C. S.; MACHADO, M. A.; GUIMARÃES, S. E. F.; MARTINS, M. F.; PEIXOTO, J. de O.; FURLONG, J.; PRATA, M. C. de A.; VERNEQUE, R. da S.; TEODORO, R. L.; LOPES, P. S. Expressed sequenced tags profiling of resistant and susceptible Gyr x Holstein cattle infested with the tick Rhipicephalus (Boophilus) microplus. Genetics and Molecular Research, v. 10, n. 4, 2011. 14 p.| Biblioteca(s): Embrapa Gado de Leite; Embrapa Suínos e Aves. |
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| 82. | | VIEIRA, F. O.; FONSECA, I.; PINTO, I. S. B.; SANTOS, A. S. O.; MARTINS, S. A. V.; FOGAÇA, G. N.; LIMA, K. R.; CARDOSO, F. F.; GUIMARÃES, S. E. F.; MARTINS, M. F. Expression analysis of CCL20 in cells from the milk of gyr cows before and 24 hours after artificial infection with Streptococcus agalactiae. In: CONGRESSO BRASILEIRO BRASILEIRO DE GENÉTICA, 59., 2013, Águas de Lindóia. Resumos... Águas de Lindóia: Sociedade Brasileira de Genética, 2013.| Biblioteca(s): Embrapa Gado de Leite; Embrapa Pecuária Sul. |
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| 83. | | VIEIRA, F. O.; PINTO, I. S. B.; SANTOS, A. S. O.; MARTINS, S. A. V.; FOGAÇA, G. N.; LIMA, K. R.; CARDOSO, F. F.; GUIMARÃES, S. E. F.; MARTINS, M. F. Expression analysis of CCL20 in cells from the milk of gyr cows before and 24 hours after artificial infection with Streptococcus agalactiae. In: Congresso Brasileiro de Genética, 59., 2013, Águas de Lindóia. Resumos...| Biblioteca(s): Embrapa Gado de Leite. |
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| 84. | | MARTINS, M. F.; FONSECA, I.; PINTO, I. S. B.; PEREIRA, W. P.; GUIMARÃES, S. E. F.; FERREIRA, M. B. D.; BRITO, M. A. V. P. e; BRANDAO, H. de M. Expression analysis of IL-1B in cells from the milk of gyr cows before and after artificial infection with Streptococcus agalactiae. In: CONGRESSO BRASILEIRO BRASILEIRO DE GENÉTICA, 57., 2011, Águas de Lindóia. Resumos... Brasília, DF: Sociedade Brasileira de Genética, 2011.| Biblioteca(s): Embrapa Gado de Leite. |
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| 85. | | DOMINGUES, R.; WOHLRES-VIANA, S.; REIS, D. R. de L.; TEIXEIRA, H. C.; FERREIRA, A. P.; GUIMARÃES, S. E. F.; PRATA, M. C. de A.; FURLONG, J.; VERNEQUE, R. da S.; MACHADO, M. A. Expression of immune response genes in peripheral blood of cattle infested with Rhipicephalus microplus. Genetics and Molecular Research, v. 13, n. 2, p. 4013-21, 2014.| Biblioteca(s): Embrapa Gado de Leite. |
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| 86. | | FONSECA, I.; SILVA, P. V.; LANGE, C. C.; GUIMARAES, M. F. M.; WELLER, M. M. D. C. A.; SOUSA, K. R. S.; LOPES, P. S.; GUIMARÃES, J. D.; GUIMARÃES, S. E. F. Expression profile of genes associated with mastitis in dairy cattle. Genetics and Molecular Biology, Ribeirão Preto, v. 32, n. 4, p. 776-781, 2009.| Biblioteca(s): Embrapa Gado de Leite. |
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| 87. | | FONSECA, I.; PINTO, I. S. B.; RETTORE, J. V. P.; FERREIRA, M. D. B.; BRITO, M. A. V. P. e; BRANDAO, H. de M.; GUIMARÃES, S. E. F.; MARTINS, M. F. Relative expression of IL-12 gene on milk cells from dairy gyr cows infected with Streptococcus agalactiae. In: CONGRESSO BRASILEIRO BRASILEIRO DE GENÉTICA, 57., 2011, Águas de Lindóia. Resumos... Brasília, DF: Sociedade Brasileira de Genética, 2011.| Biblioteca(s): Embrapa Gado de Leite. |
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| 88. | | ROCHA, R. de F. B.; OTTO, P. I.; SILVA, M. V. G. B.; MARTINS, M. F.; MACHADO, M. A.; VERONEZE, R.; LEANDRO, F. D.; PEREIRA, S. M.; GUIMARÃES, S. E. F.; PANETTO, J. C. do C. Repeatability and random regression models to estimate genetic parameters for oocyte and embryo production in the Gir breed. Animal Production Science, v. 62, n. 17, p. 1661-1670, 2022.| Biblioteca(s): Embrapa Gado de Leite. |
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| 89. | | BARROSO, L. M. A.; NASCIMENTO, M.; NASCIMENTO, A. C. C.; SILVA, F. F.; SERÃO, N. V. L.; CRUZ, C. D.; RESENDE, M. D. V. de; SILVA, F. L.; AZEVEDO, C. F.; LOPES, P. S.; GUIMARÃES, S. E. F. Regularized quantile regression for SNP marker estimation of pig growth curves. Journal of Animal Science and Biotechnology, v. 8, n. 59, 2017. 9 p.| Biblioteca(s): Embrapa Florestas. |
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| 90. | | MARTINS, M. F.; FONSECA, I.; PINTO, I. S. B.; SANTOS, A. S. O.; VIEIRA, F. O.; MARTINS, S. A. V.; FOGAÇA, G. N.; LIMA, K. R.; CARDOSO, F. F.; GUIMARÃES, S. E. F. Gene expression profile of AATK in milk cells from dairy Gyr cows infected with Streptococcus agalactiae. In: CONGRESSO BRASILEIRO DE GENÉTICA, 59., 2013, Águas de Lindóia. Resumos... Ribeirão Preto: SBG, 2013. p. 187.| Biblioteca(s): Embrapa Pecuária Sul. |
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| 91. | | MARTINS, M. F.; PINTO, I. S. B.; SANTOS, A. S. O.; VIEIRA, F. O.; MARTINS, S. A. V.; FOGAÇA, G. N.; LIMA, K. R.; CARDOSO, F. F.; GUIMARÃES, S. E. F. Gene expression profile of AATK in milk cells from dairy gyr cows infected with Streptococcus agalactiae. In: CONGRESSO BRASILEIRO BRASILEIRO DE GENÉTICA, 59., 2013, Águas de Lindóia. Resumos... Águas de Lindóia: Sociedade Brasileira de Genética, 2013.| Biblioteca(s): Embrapa Gado de Leite. |
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| 92. | | FONSECA, I.; CARDOSO, F. F.; HIGA, R. H.; GIACHETTO, P. F.; BRANDAO, H. de M.; BRITO, M. A. V. P. e; FERREIRA, M. B. D.; GUIMARÃES, S. E. F.; MARTINS, M. F. Gene expression profile in zebu dairy cows (Bos taurus indicus) with mastitis caused by Streptococcus agalactiae. Livestock Science, v. 180, p. 47-57, Oct. 2015.| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Gado de Leite; Embrapa Pecuária Sul. |
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| 93. | | SILVA, F. F. e; RESENDE, M. D. V. de; ROCHA, G. S.; DUARTE, D. A. S.; LOPES, P. S.; BRUSTOLIN, O. J. B.; THUS, S.; VIANA, J. M. S.; GUIMARÃES, S. E. F. Genomic growth curves of an outbred pig population. Genetics and Molecular Biology, v. 36, n. 4, p. 520-527, 2013.| Biblioteca(s): Embrapa Florestas. |
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| 94. | | SOLLERO, B. P.; PAIVA, S. R.; FARIA, D. A.; GUIMARÃES, S. E. F.; BERTRANI, G. R.; MAMANI, E.; ALBUQUERQUE, M. S. M.; CASTRO, S. T. R.; GERMANO, J. L.; MARIANTE, A. S. Genetic diversity in naturalized and commercial pig breeds in Brazil. In: WORLD CONGRESS ON GENETICS APPLIED TO LIVESTOCK PRODUCTION, 8., 2006, Belo Horizonte, MG. Proceedings... Belo Horizonte: Instituto Prociência, 2006. Não paginado.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 95. | | SILVA, F. F. e; ZAMBRANO, M. F. B.; VARONA, L.; GLÓRIA, L. S.; LOPES, P. S.; SILVA, M. V. G. B.; ARBEX, W. A.; LÁZARO, S. F.; RESENDE, M. D. V. de; GUIMARÃES, S. E. F. Genome association study through nonlinear mixed models revealed new candidate genes for pig growth curves. Scientia Agricola, v. 74, n. 1, 2017. 7 P.| Biblioteca(s): Embrapa Florestas; Embrapa Gado de Leite. |
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| 96. | | DUARTE, D. A. S.; FORTES, M. R. S.; DUARTE, M. de S.; GUIMARÃES, S. E. F.; VERARDO, L. L.; VERONEZE, R.; RIBEIRO, A. M. F.; LOPES, P. S.; RESENDE, M. D. V. de; SILVA, F. F. e. Genome-wide association studies, meta-analyses and derived gene network for meat quality and carcass traits in pigs. Animal Production Science, v. 58, n. 6, p. 1100-1008, May 2018.| Biblioteca(s): Embrapa Florestas. |
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| 97. | | AZEVEDO, A. L. S.; NASCIMENTO, C. S.; STEINBERG, R. S.; CARVALHO, M. R. S.; PEIXOTO, M. G. C. D.; TEODORO, R. L.; VERNEQUE, R. S.; GUIMARÃES, S. E. F.; MACHADO, M. A. Genetic polymorphism of the kappa-casein gene in Brazilian cattle. Genetics and Molecular Research, Ribeirão Preto, v. 7, n. 3, p. 623-630, 2008.| Biblioteca(s): Embrapa Gado de Leite. |
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| 98. | | ROCHA, R. de F. B.; OTTO, P. I.; GARCIA, A. O.; SANTOS, M. G. dos; SILVA, M. V. G. B.; MARTINS, M. F.; MACHADO, M. A.; PANETTO, J. C. do C.; CALUS, M. P. L.; GUIMARÃES, S. E. F. A genética envolvida na produção de oócitos e embriões em Gir leiteiro. Balde Branco, ano 59, n. 703, p. 56-59, 2024.| Biblioteca(s): Embrapa Gado de Leite. |
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| 99. | | ARAUJO, A. M. de; GUIMARÃES, S. E. F.; MACHADO, T. M. M.; LOPES, P. S.; PEREIRA, C. S.; SILVA, F. L. R. da; RODRIGUES, M. T.; COLUMBIANO, V. de S.; FONSECA, C. G. da. Genetic diversity between herds of Alpine and Saanen dairy goats and the naturalized Brazilian Moxotó breed. Genetics and Molecular Biology, São Paulo, v. 29, n. 1, p. 67-79, 2006.| Biblioteca(s): Embrapa Caprinos e Ovinos. |
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| 100. | | SOLLERO, B. P.; PAIVA, S. R.; FARIA, D. A.; GUIMARÃES, S. E. F.; CASTRO, S. T. R.; EGITO, A. A.; ALBUQUERQUE, M. S. M.; PIOVEZAN, U.; BERTANI, G. R.; MARIANTE, A. da S. Genetic diversity of brazilian pig breeds evidenced by microsatellite markers. Livestock Science, v. 123, p. 8-15, 2009.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| Registros recuperados : 134 | |
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Registro Completo
|
Biblioteca(s): |
Embrapa Florestas; Embrapa Gado de Leite. |
|
Data corrente: |
17/05/2017 |
|
Data da última atualização: |
27/01/2023 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Circulação/Nível: |
A - 1 |
|
Autoria: |
SILVA, F. F. e; ZAMBRANO, M. F. B.; VARONA, L.; GLÓRIA, L. S.; LOPES, P. S.; SILVA, M. V. G. B.; ARBEX, W. A.; LÁZARO, S. F.; RESENDE, M. D. V. de; GUIMARÃES, S. E. F. |
|
Afiliação: |
Fabyano Fonseca e Silva, UFV/VIÇOSA; Maria Fernanda Betancur Zambrano, UFV/VIÇOSA; Luis Varona, University of Zaragoza; Leonardo Siqueira Glória, UFV/VIÇOSA; Paulo Sávio Lopes, UFV; MARCOS VINICIUS GUALBERTO B SILVA, CNPGL; WAGNER ANTONIO ARBEX, CNPGL; Sirlene Fernandes Lázaro, UFV/VIÇOSA; MARCOS DEON VILELA DE RESENDE, CNPF; Simone Eliza Facioni Guimarães, UFV/VIÇOSA. |
|
Título: |
Genome association study through nonlinear mixed models revealed new candidate genes for pig growth curves. |
|
Ano de publicação: |
2017 |
|
Fonte/Imprenta: |
Scientia Agricola, v. 74, n. 1, 2017. |
|
Páginas: |
7 P. |
|
Idioma: |
Inglês
Português |
|
Conteúdo: |
Genome association analyses have been successful in identifying quantitative trait
loci (QTLs) for pig body weights measured at a single age. However, when considering the whole
weight trajectories over time in the context of genome association analyses, it is important to
look at the markers that affect growth curve parameters. The easiest way to consider them is
via the two-step method, in which the growth curve parameters and marker effects are estimated
separately, thereby resulting in a reduction of the statistical power and the precision of
estimates. One efficient solution is to adopt nonlinear mixed models (NMM), which enables a joint
modeling of the individual growth curves and marker effects. Our aim was to propose a genome
association analysis for growth curves in pigs based on NMM as well as to compare it with the
traditional two-step method. In addition, we also aimed to identify the nearest candidate genes
related to significant SNP (single nucleotide polymorphism) markers. The NMM presented a
higher number of significant SNPs for adult weight (A) and maturity rate (K), and provided a direct
way to test SNP significance simultaneously for both the A and K parameters. Furthermore, all
significant SNPs from the two-step method were also reported in the NMM analysis. The ontology
of the three candidate genes (SH3BGRL2, MAPK14, and MYL9) derived from significant SNPs
(simultaneously affecting A and K) allows us to make inferences with regards to their contribution
to the pig growth process in the population studied. MenosGenome association analyses have been successful in identifying quantitative trait
loci (QTLs) for pig body weights measured at a single age. However, when considering the whole
weight trajectories over time in the context of genome association analyses, it is important to
look at the markers that affect growth curve parameters. The easiest way to consider them is
via the two-step method, in which the growth curve parameters and marker effects are estimated
separately, thereby resulting in a reduction of the statistical power and the precision of
estimates. One efficient solution is to adopt nonlinear mixed models (NMM), which enables a joint
modeling of the individual growth curves and marker effects. Our aim was to propose a genome
association analysis for growth curves in pigs based on NMM as well as to compare it with the
traditional two-step method. In addition, we also aimed to identify the nearest candidate genes
related to significant SNP (single nucleotide polymorphism) markers. The NMM presented a
higher number of significant SNPs for adult weight (A) and maturity rate (K), and provided a direct
way to test SNP significance simultaneously for both the A and K parameters. Furthermore, all
significant SNPs from the two-step method were also reported in the NMM analysis. The ontology
of the three candidate genes (SH3BGRL2, MAPK14, and MYL9) derived from significant SNPs
(simultaneously affecting A and K) allows us to make inferences with regards to their contribution
... Mostrar Tudo |
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Palavras-Chave: |
Longitudinal data; SNP markers. |
|
Thesaurus NAL: |
body weight. |
|
Categoria do assunto: |
--
L Ciência Animal e Produtos de Origem Animal |
|
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/161512/1/Cnpgl-2017-SciAgric-Silva-Genome.pdf
|
|
Marc: |
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001 2072227
005 2023-01-27
008 2017 bl uuuu u00u1 u #d
100 1 $aSILVA, F. F. e
245 $aGenome association study through nonlinear mixed models revealed new candidate genes for pig growth curves.$h[electronic resource]
260 $c2017
300 $a7 P.
520 $aGenome association analyses have been successful in identifying quantitative trait loci (QTLs) for pig body weights measured at a single age. However, when considering the whole weight trajectories over time in the context of genome association analyses, it is important to look at the markers that affect growth curve parameters. The easiest way to consider them is via the two-step method, in which the growth curve parameters and marker effects are estimated separately, thereby resulting in a reduction of the statistical power and the precision of estimates. One efficient solution is to adopt nonlinear mixed models (NMM), which enables a joint modeling of the individual growth curves and marker effects. Our aim was to propose a genome association analysis for growth curves in pigs based on NMM as well as to compare it with the traditional two-step method. In addition, we also aimed to identify the nearest candidate genes related to significant SNP (single nucleotide polymorphism) markers. The NMM presented a higher number of significant SNPs for adult weight (A) and maturity rate (K), and provided a direct way to test SNP significance simultaneously for both the A and K parameters. Furthermore, all significant SNPs from the two-step method were also reported in the NMM analysis. The ontology of the three candidate genes (SH3BGRL2, MAPK14, and MYL9) derived from significant SNPs (simultaneously affecting A and K) allows us to make inferences with regards to their contribution to the pig growth process in the population studied.
650 $abody weight
653 $aLongitudinal data
653 $aSNP markers
700 1 $aZAMBRANO, M. F. B.
700 1 $aVARONA, L.
700 1 $aGLÓRIA, L. S.
700 1 $aLOPES, P. S.
700 1 $aSILVA, M. V. G. B.
700 1 $aARBEX, W. A.
700 1 $aLÁZARO, S. F.
700 1 $aRESENDE, M. D. V. de
700 1 $aGUIMARÃES, S. E. F.
773 $tScientia Agricola$gv. 74, n. 1, 2017.
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Embrapa Gado de Leite (CNPGL) |
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