Mapeamento de QTL para conteúdos de proteína e óleo em soja

Rodrigues, Josiane Isabela da Silva; Miranda, Fábio Demolinari de; Ferreira, Adésio; Borges, Leandro Luiz; Ferreira, Márcia Flores da Silva; God, Pedro Ivo Vieira Good; Piovesan, Newton Deniz; Barros, Everaldo Gonçalves de; Cruz, Cosme Damião; Moreira, Maurílio Alves

doi:10.1590/s0100-204x2010000500006

Cited by 23 publications

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References 23 publications

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“…Oil and protein contents were negatively correlated, which agrees with the literature (Liang et al, 2010;Rodrigues et al, 2010). These correlations were high, with small variation (r = -0.80** to -0.92**), revealing the degree of genetic association between the characters and explaining the difficulties for simultaneous selection.…”

Section: Resultssupporting

confidence: 89%

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Biometric analysis of protein and oil contents of soybean genotypes in different environments

Rodrigues

Arruda

Cruz

et al. 2014

Pesq. agropec. bras.

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The objective of this work was to identify by biometric analyses the most stable soybean parents, with higher oil or protein contents, cultivated at different seasons and locations of the state of Minas Gerais, Brazil. Forty-nine genotypes were evaluated in the municipalities of Viçosa, Visconde do Rio Branco, and São Gotardo, in the state of Minas Gerais, from 2009 to 2011. Protein and oil contents were analyzed by infrared spectrometry using a FT-NIR analyzer. The effects of genotype, environment, and genotype x environment interaction were significant. The BARC-8 soybean genotype is the best parent to increase protein contents in the progenies, followed by BR 8014887 and CS 3032PTA276-3-4. Selection for high oil content is more efficient when the crossings involve the Suprema, CD 01RR8384, and A7002 genotypes, which show high mean phenotypic values, wide adaptability, and greater stability to environmental variation.

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Section: Resultssupporting

confidence: 89%

“…Both protein and oil contents are in part determined by additive gene action, with heritability values ranging from medium to high (Rodrigues et al, 2010;Jaureguy et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Biometric analysis of protein and oil contents of soybean genotypes in different environments

Rodrigues

Arruda

Cruz

et al. 2014

Pesq. agropec. bras.

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“…A single QTL explaining 65% of the variation in protein content was mapped on the linkage group by Sebolt, Shoemaker, & Diers, (2000) and other QTLs were mapped in the same genomic region by Nichols, Lgover, Carlson, Specht & Diers (2006);Bolon, Joseph, Cannon, Graham, Diers, Farmer, May, Muehlbauer, Specht, Tu, Weeks, Xu, Shoemaker & Vance (2010);and Rodrigues, Miranda, Borges, Silva, Good-God, Piovesan, Barros, Cruz & Moreira (2010). In addition, this analysis reveals the presence of genetic variation in the main region of the linkage group I, which is the most reported and related to the protein content in soybean.…”

Section: Discussionmentioning

confidence: 88%

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et al. 2017

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Pre-mejoramiento vegetal para el volumen incrementado de proteína en soya Glycine max (L. ) AbstractThe aim of this research were to determine protein content and genetic divergence of soybean genotypes in QTL regions of the trait grain protein content for plant breeding purposes. Twenty-nine soybean genotypes were grown in the field in four environments (Viçosa-MG Dec/2009, Visconde do Rio Branco-MG Feb/2010, São Gotardo-MG Feb/2010, and São Gotardo-MG Oct/2011) using the randomized block design with three replicates. The grain protein content was quantified by the infrared spectrometry method. The genetic divergence was estimated by the analysis of 39 microsatellite markers from QTL regions for the soybean grain protein content. The pairs of genotypes with greater genetic distances and protein contents were as follows: BARC-8/CS3032PTA276-3-4 (D=0.71) (45.18%/44.31%); BARC-8/CS3032PTA276-1-2 (D=0.71) (45.18%/43.75%); BARC-8/CS3032PTA190-5-1 (D=0.71) (45.18%/43.63%); B3PTA382-2-10/CS3032PTA276-3-4 (D=0.62) (43.80%/44.31%); CS3032PTA276-1-2/ B3PTA382-2-10 (D=0.62) (43.75%/43.80%); B3PTA382-2-10/CS3032PTA190-5-1 (D=0.62) (43.80%/43.63%); B3PTA216-1-9/CS3032PTA276-3-4 (D=0.61) (43.48%/44.31%); and B3PTA216-1-9/CS3032PTA276-1-2 (D=0.61) (43.48%/43.75%), respectively. Other promising combinations for the improvement of protein content were as follows: BR8014887/CS3032PTA190-5-1 (D=0.57) (44.71%/43.63%); BARC-8/CS3032PTA182 (D=0.78) (45.18%/41.84%); BR8014887/CS3032PTA182 (D=0.65) (44.71%/41.84%); BR8014887/PI417360 (D=0.76) (44.71%/41.01%), respectively; and PI417360/B3PTA216-1-9 (D=0.80) (41.01%/43.48%). These pairs of genotypes when crossed should produce populations with higher means and genetic variances and greater gains with selection.

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“…A utilização de marcadores moleculares em programas de melhoramento implementados pela seleção assistida por marcadores pode beneficiar os processos de seleção, quando se admitem características de baixa e média herdabilidade, em que o ambiente tem considerável participação na expressão fenotípica (Rodrigues et al 2010, Sousa et al 2011 Avaliou-se o acasalamento seletivo entre os genitores, seguindo-se o princípio da genotipagem seletiva (distribuição dos extremos). Nesta estratégia, os machos e as fêmeas selecionados foram ordenados separadamente, com base no número de marcadores associados aos locos quantitativos (informatividade dos marcadores).…”

Section: Methodsunclassified

Abordagem multivariada para endogamia e valor fenotípico utilizando diferentes estratégias de cruzamento

Jangarelli

2014

Pesqui. Agropecu. Trop.

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A simulação tem contribuído para o avanço do melhoramento genético. Este estudo objetivou avaliar o acasalamento seletivo, utilizando a distribuição dos extremos para maximizar o incremento fenotípico e retardar o acréscimo da endogamia, por meio de abordagem multivariada. Dados simulados foram utilizados para avaliar estratégias de acasalamento, em diferentes tamanhos de família, no decorrer de 20 gerações. A análise de agrupamento possibilitou diferenciar o acasalamento seletivo das demais estratégias, em cada tamanho de família. Combinando-se estratégia de acasalamento e tamanho de família, a análise de agrupamento assinalou superioridade do acasalamento seletivo, na capacidade de otimizar o valor fenotípico e retardar o incremento da endogamia. Os métodos de agrupamento apresentaram equivalência na formação de grupos com estratégias homogêneas, para as estimativas dos valores fenotípicos médios e endogamia média. A análise multivariada corroborou incrementos fenotípicos superiores, para o acasalamento seletivo, bem como menores níveis endogâmicos, ao longo das gerações.

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Mapeamento de QTL para conteúdos de proteína e óleo em soja

Cited by 23 publications

References 23 publications

Biometric analysis of protein and oil contents of soybean genotypes in different environments

Biometric analysis of protein and oil contents of soybean genotypes in different environments

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Abordagem multivariada para endogamia e valor fenotípico utilizando diferentes estratégias de cruzamento

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