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Registro Completo |
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
20/01/2022 |
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Data da última atualização: |
20/01/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SILVA, J. O. da C. e; BRUCKNER, C. H.; CARNEIRO, P. C. S.; RESENDE, M. D. V. de; ALVES, R. S.; RIBEIRO, M. R.; SILVA, D. F. P. da. |
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Afiliação: |
JOSÉ OSMAR DA COSTA E SILVA, UFV; CLAUDIO HORST BRUCKNER, UFV; PEDRO CRESCÊNCIO SOUZA CARNEIRO, UFV; MARCOS DEON VILELA DE RESENDE, CNPCa; RODRIGO SILVA ALVES, UFV; MARIANA RODRIGUES RIBEIRO, UFV; DANIELLE FABÍOLA PEREIRA DA SILVA, UFG. |
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Título: |
Clonal selection in S0 and S1 peach trees evaluated in a subtropical environment. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Crop Breeding and Applied Biotechnology, v. 21, n. 1, e33012111, 2021. |
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DOI: |
https://doi.org/10.1590/1984-70332021v21n1a1 |
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Idioma: |
Inglês |
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Conteúdo: |
The aims of this study were to estimate genetic parameters, predict genotypic values, and analyze the genotypic divergence in S0 and S1 peach trees evaluated in a subtropical environment by the mixed model methodology. For this, twenty-two clones were evaluated for plant and fruit traits. Genotypic variance among clones was significant. The individual broad-sense heritabilities ranged from 0.11 to 0.84, and the individual repeatability coefficients ranged from 0.15 to 0.89. The genotypic coefficients of variation were higher than 10% for most of the traits. Clustering based on plant and fruit traits led to the formation of two and five mutually exclusive groups, respectively. Multivariate analysis of principal components indicated that some traits could be excluded from genetic evaluation. Considering the yield trait and the selection of five clones, predicted gain from selection was 70%, which shows the possibility of considerable genetic progress from clonal selection in peach trees. |
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Thesagro: |
Clone; Pêssego; Seleção Genética. |
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Thesaurus Nal: |
Fruit trees; Multivariate analysis; Peaches; Prunus persica var. nucipersica; Selection methods; Statistical models. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/230407/1/clonal-selection-in-S0-and-S1.pdf
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Marc: |
LEADER 01960naa a2200313 a 4500
001 2139209
005 2022-01-20
008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1590/1984-70332021v21n1a1$2DOI
100 1 $aSILVA, J. O. da C. e
245 $aClonal selection in S0 and S1 peach trees evaluated in a subtropical environment.$h[electronic resource]
260 $c2021
520 $aThe aims of this study were to estimate genetic parameters, predict genotypic values, and analyze the genotypic divergence in S0 and S1 peach trees evaluated in a subtropical environment by the mixed model methodology. For this, twenty-two clones were evaluated for plant and fruit traits. Genotypic variance among clones was significant. The individual broad-sense heritabilities ranged from 0.11 to 0.84, and the individual repeatability coefficients ranged from 0.15 to 0.89. The genotypic coefficients of variation were higher than 10% for most of the traits. Clustering based on plant and fruit traits led to the formation of two and five mutually exclusive groups, respectively. Multivariate analysis of principal components indicated that some traits could be excluded from genetic evaluation. Considering the yield trait and the selection of five clones, predicted gain from selection was 70%, which shows the possibility of considerable genetic progress from clonal selection in peach trees.
650 $aFruit trees
650 $aMultivariate analysis
650 $aPeaches
650 $aPrunus persica var. nucipersica
650 $aSelection methods
650 $aStatistical models
650 $aClone
650 $aPêssego
650 $aSeleção Genética
700 1 $aBRUCKNER, C. H.
700 1 $aCARNEIRO, P. C. S.
700 1 $aRESENDE, M. D. V. de
700 1 $aALVES, R. S.
700 1 $aRIBEIRO, M. R.
700 1 $aSILVA, D. F. P. da
773 $tCrop Breeding and Applied Biotechnology$gv. 21, n. 1, e33012111, 2021.
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Registro original: |
Embrapa Café (CNPCa) |
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Registro Completo
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Biblioteca(s): |
Embrapa Florestas; Embrapa Gado de Leite. |
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Data corrente: |
17/05/2017 |
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Data da última atualização: |
27/01/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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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. |
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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. |
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Título: |
Genome association study through nonlinear mixed models revealed new candidate genes for pig growth curves. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Scientia Agricola, v. 74, n. 1, 2017. |
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Páginas: |
7 P. |
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Idioma: |
Inglês
Português |
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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. |
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Thesaurus NAL: |
body weight. |
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Categoria do assunto: |
--
L Ciência Animal e Produtos de Origem Animal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/161512/1/Cnpgl-2017-SciAgric-Silva-Genome.pdf
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Marc: |
LEADER 02345naa a2200277 a 4500
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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Registro original: |
Embrapa Gado de Leite (CNPGL) |
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