Impact of epistasis and QTL×environment interaction on the accumulation of seed mass of soybean (<i>Glycine max</i>L. Merr.)

Han, Yingpeng; Teng, Weili; Sun, Desheng; Du, Ye; Qiu, Lijuan; Xu, Xiangling; Li, Wenbin

doi:10.1017/s0016672308009865

Cited by 23 publications

(27 citation statements)

References 65 publications

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“…There has been a number of studies in which molecular markers have been used to investigated the developmental behavior of quantitative traits (Sun et al 2006;Han et al 2008). The results of these studies indicated that seed weight, pod number, and plant height are partially regulated by both conditional and unconditional QTL.…”

Section: Introductionmentioning

confidence: 99%

Identification of QTL underlying the filling rate of protein at different developmental stages of soybean seed

et al. 2010

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Seed protein content at the harvest stage is the sum of protein accumulation during seed filling. The aim of our investigation was to identify loci underlying the filling rate of seed protein at different developmental stages. To this end, we used 143 recombinant inbred lines (RILs) derived from the cross of soybean cultivars 'Charleston' and 'Dongnong 594' and composite interval mapping with a mixed genetic model. The genotype 9 environment interactions of the quantitative trait loci (QTL) were also evaluated. Thirty-nine unconditional QTL underlying the filling rate of seed protein at five developmental stages were mapped onto 14 linkage groups. The proportion of phenotypic variation explained by these QTL ranged from 4.88 to 26.05%. Thirty-eight conditional QTL underlying the filling rate of seed protein were mapped onto 16 linkage groups. The proportion of phenotypic variation explained by these QTL ranged from 1.87 to 31.34%. The numbers and types of QTL and their genetic effects on the filling rate of seed protein were different at each developmental stage. A G 9 E interaction effect was observed for some QTL.

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Section: Introductionmentioning

confidence: 99%

Identification of QTL underlying the filling rate of protein at different developmental stages of soybean seed

et al. 2010

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“…The main objective of the present study was to identify both conditional and unconditional QTL underlying the development of gain in seed weight and the QTL underlying final mean seed weight in soybean. An analysis of epistatic effects in seed weight development and formation were described in a separate paper submitted to Genetics Research (Han et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

QTL analyses of seed weight during the development of soybean (Glycine max L. Merr.)

Teng

Han

et al. 2008

Heredity

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At harvest traits such as seed weight are the sum of development and responses to stresses over the growing season and particularly during the reproductive phase of growth. The aim here was to measure quantitative trait loci (QTL) underlying the seed weight from early development to drying post harvest. One hundred forty-three F 5 derived recombinant inbred lines (RILs) developed from the cross of soybean cultivars 'Charleston' and 'Dongnong 594' were used for the analysis of QTL underlying mean 100-seed weight at six different developmental stages. QTL Â Environment interactions (QE) were analyzed by a mixed genetic mode based on 3 years' data. At an experiment-wise threshold of a ¼ 0.05 and by single-point analysis 94 QTL unaffected by QE underlay the mean seed weight at different developmental stages. Sixty-eight QTL affected by QE that also underlay mean seed weight were identified. From the 162 QTL 42 could be located on 12 linkage groups by composite interval mapping (LOD42.0). The numbers, locations and types of the QTL and the genetic effects were different at each developmental stage. On linkage group C2 the distantly linked QTL swC2-1, swC2-2 and swC2-3 each affected mean seed weight throughout the different developmental stages. The DNA markers linked to the QTL possessed potential for use in marker-assisted selection for soybean seed size. The identification of QTL with genetic main effects and QE interaction effects suggested that such interactions might significantly alter seed weight during seed development.

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“…This trend suggests that some genotype 9 pathotype interaction is present. We note that a genotype 9 environment interaction is not infrequent when dealing with quantitative characters, for example, the capsaicinoids content in pepper (Garcés-Claver et al 2007), the accumulation of seed mass in soybean (Han et al 2008) or the protein or sucrose contents in beans (Florez et al 2009). Moreover, Perchepied and Pitrat (2004) reported that quantitative, polygenic, racenonspecific resistance to a specialized pathogen often shows small race-specific effects, which may explain the above results.…”

Section: Discussionmentioning

confidence: 94%

Inheritance of race 1.2 Fusarium wilt resistance in four melon cultivars

Chikh-Rouhou¹,

González-Torres

Oumouloud

et al. 2011

Euphytica

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The resistance to Fusarium oxysporum f.sp. melonis (Fom) race 1.2 has been studied in melons, such as the Portuguese accession 'BG-5384' and in the Japanese 'Shiro Uri Okayama', 'Kogane Nashi Makuwa', and 'C-211', since a good characterization of the resistance is necessary before its introgression into commercial varieties. These four melon accessions showed a high level of resistance to races 0, 1, and 2 of Fom, indicating that the partial resistance to the race 1.2 previously detected may not have been race specific. To determine the mode of inheritance of the resistance to Fom race 1.2, the F 1 , F 2 , BCP R , and BCP S generations from the crosses between the four resistant accessions above and 'Piel de Sapo', a Fom race 1.2 susceptible melon, were developed. They were subsequently inoculated with two Fom isolates, one from the pathotype 1.2Y and the other from the pathotype 1.2W. The area under the disease progress curve was determined for each inoculated plant, and the data were analyzed. We show that the resistance seen in these accessions is polygenically inherited with a complex genetic control because many epistatic interactions were detected. The three epistatic effects; additivity 9 additivity, dominance 9 dominance, and dominance 9 additivity are present and significant, with differing magnitudes from one cross to the next. The relatively low heritabilities, and these epistatic effects make difficult the improvement of the resistance, from these sources, through a standard selection procedure.

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Impact of epistasis and QTL×environment interaction on the accumulation of seed mass of soybean (Glycine maxL. Merr.)

Cited by 23 publications

References 65 publications

Identification of QTL underlying the filling rate of protein at different developmental stages of soybean seed

Identification of QTL underlying the filling rate of protein at different developmental stages of soybean seed

QTL analyses of seed weight during the development of soybean (Glycine max L. Merr.)

Inheritance of race 1.2 Fusarium wilt resistance in four melon cultivars

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