Quantitative trait loci underlying the development of seed composition in soybean (<i>Glycine max</i>L. Merr.)

Li, Wenbin LiW.; Sun, Desheng; Du, Ye; Chen, Qingshan ChenQ.; Zhang, Zhongchen ZhangZ.; Qiu, Lijuan; Sun, Genlou

doi:10.1139/g07-080

Cited by 24 publications

(19 citation statements)

References 29 publications

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“…The association of developmental behavior of quantitative traits with molecular markers had been reported in rice and cotton (Wu et al, 1999;Ye et al, 2003;Yan et al, 1998a, b), and morphological traits and seed quality traits in soybean (Sun et al, 2006;Li et al, 2007;Xin et al, 2008). 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.…”

Section: Introductionmentioning

confidence: 69%

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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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Section: Introductionmentioning

confidence: 69%

“…Developmental programs are very important factors controlling the development of quantitative traits such as seed composition, yield and plant height (Yan et al, 1998b;Sun et al, 2006;Li et al, 2007). The development of some quantitative traits occurs through the actions and interactions of many genes.…”

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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“…), seed composition (Li et al. ) and seed weight (Teng et al. ) of soybean during different developmental stages have been reported.…”

Section: Discussionmentioning

confidence: 99%

Dynamic quantitative trait loci underlies isoflavone accumulation in soybean seed

Han

Zhao

et al. 2016

Plant Breeding

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Most of quantitative trait loci (QTL) underlying soybean seed isoflavone contents were derived from the harvest stage of plant development, which uncover the genetic effects that were expressed in earlier seed developmental stages. The aim of this study was to detect conditional QTL associated with isoflavone accumulation during the entire seed development. A total of 112 recombinant inbred lines developed from the cross between 'Zhongdou 27' (higher seed isoflavone content) and 'Jiunong 20' (lower seed isoflavone content) were used for the conditional QTL analysis of daidzein (DZ), genistein (GT), glycitein (GC) and total isoflavone (TI) accumulations through composite interval mapping with mixed genetic model. The results indicated that the number and type of QTL and their additive effects for individual and total isoflavone accumulations were different among R3 to R8 developmental stages. Three unconditional QTL and six conditional QTL for DZ, four unconditional QTL and five conditional QTL for GT, six unconditional QTL and five conditional QTL for GC, six unconditional QTL and seven conditional QTL for TI were identified at different developmental stages, respectively. Unconditional and conditional QTL that affect individual and total isoflavone accumulations exhibited multiple expression patterns, implying that some QTL are active for long period and others are transient. Two genomic regions, Satt144-Satt569 in linkage group F (LG F; chromosome 13, chr 13) for DZ, GC, GT and TI accumulations and Satt540-Sat_240 in LG M (chr 07) for TI and GC accumulations, were found to significantly affect individual and total isoflavone accumulations in multiple developmental stages, suggesting that the accumulation of soybean seed isoflavones is governed by time-dependent gene expression.

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“…By combining unconditional and conditional QTL mapping, it is possible to reveal the dynamic gene expressions for the development of quantitative traits. The genetic basis of the developmental behavior of pod number in the main stem (Sun et al 2006), plant height (Sun et al 2006), seed weight (Han et al 2008;Teng et al 2009) and seed composition (Li et al 2007) have been dissected using unconditional and conditional QTL analysis strategy, and a number of conditional QTL were detected at different developmental stages. All these studies, by both unconditional and conditional QTL analysis method, were able to fully reveal the action of the genes during the development of the traits.…”

Section: Discussionmentioning

confidence: 99%

Impact of epistasis and QTL × environmental interaction on the oil filling rate of soybean seed at different developmental stages

et al. 2010

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The oil accumulation in the developing soybean seed has been shown to be a dynamic process with different rates and activities at different phases affected by both genotype and environment. The objective of the present study was to investigate additive, epistatic and quantitative trait loci (QTL) 9 environment interaction (QE) effects of the QTL controlling oil filling rate in soybean seed. A total of 143 recombinant inbred lines (RILs) derived from the cross of Charleston and Dongnong 594 were used in this study to obtain 2 years of field data (2004 and 2005). A total of 26 QTL with significantly unconditional and conditional additive (a) effect and/ or additive 9 environment interaction (ae) effect at different filling stages were identified on 14 linkage groups. Among the QTL with significant a effects, 18 QTL showed positive effects and 6 QTL had negative effects on seed filling rate of oil content during seed development. A total of 29 epistatic pairwise QTL underlying seed filling rate were identified at different filling stages. About 28 pairs of the QTL showed additive 9 additive epistatic (aa) effects and 14 pairs of the QTL showed aa 9 environment interaction (aae) effects at different filling stages. QTL with aa and aae (additive 9 additive 9 environment) effects appeared to vary at different filling stages. Our results demonstrated that oil filling rate in soybean seed were under genetic, developmental and environmental control.Keywords Oil filling rate Á Additive 9 additive epistatic (aa) effect Á Aa 9 environment interaction (aae) Á Soybean

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Quantitative trait loci underlying the development of seed composition in soybean (Glycine maxL. Merr.)

Cited by 24 publications

References 29 publications

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

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

Dynamic quantitative trait loci underlies isoflavone accumulation in soybean seed

Impact of epistasis and QTL × environmental interaction on the oil filling rate of soybean seed at different developmental stages

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