Identification of QTL underlying the resistance of soybean to pod borer, Leguminivora glycinivorella (Mats.) obraztsov, and correlations with plant, pod and seed traits

Zhao, Guangyao; Wang, Jian; Han, Yingpeng; Teng, Weili; Sun, Genlou; Li, Wenbin

doi:10.1007/s10681-008-9728-z

Cited by 34 publications

(30 citation statements)

References 45 publications

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“…Significant progress has been made in understanding and predicting genetic interaction networks that affect quantitative traits by utilizing the unique resources and experimental designs available for model organisms (Mackay et al 2009;Mackay 2014). The mechanism of epistasis in the genomic control of complex traits is more complicated than the detection of individual gene effects and might decrease the effect of individual QTLs (Zhao et al 2008;Palomeque et al 2010;Korir et al 2011). If epistasis is ignored, individual loci might not be detected, and the QTL contribution to the phenotype could be neglected, which could lead to an incorrect application to MAS, weaken the ability of QTL identification and reduce the predicted economic gain.…”

Section: Discussionmentioning

confidence: 99%

Identification of major QTLs and epistatic interactions for seed protein concentration in soybean under multiple environments based on a high-density map

Pan

Han

et al. 2016

Mol Breeding

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The concentration of protein in soybean is an important trait that drives successful soybean quality. A recombinant inbred line derived from a cross between the Charleston and Dongnong594 cultivars was planted in one location across 10 years and two locations across 5 years in China (20 environments in total), and the genetic effects were partitioned into additive main effects, epistatic main effects and their environmental interaction effects using composite interval mapping and inclusive composite interval mapping models based on a high-density genetic map. Ten main-effect quantitative trait loci (QTLs) were identified on chromosomes 3, 6, 7, 13, 15 and 20 and detected in more than three environments, with each of the main-effect QTLs contributing a phenotypic variation of around 10 %.Between the intervals of the main-effect QTLs, 93 candidate genes were screened for their involvement in seed protein storage and/or amino acid biosynthesis and metabolism processes based on gene ontology and annotation information. Furthermore, an analysis of epistatic interactions showed that three epistatic QTL pairs were detected, and could explain approximately 50 % of the phenotypic variation. The additive maineffect QTLs and epistatic QTL pairs contributed to high phenotypic variation under multiple environments, and the results were also validated and corroborated with previous research, indicating that marker-assisted selection can be used to improve soybean protein concentrations and that the candidate genes can also be used as a foundation data set for research on gene function.

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Section: Discussionmentioning

confidence: 99%

Identification of major QTLs and epistatic interactions for seed protein concentration in soybean under multiple environments based on a high-density map

Pan

Han

et al. 2016

Mol Breeding

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“…Insecticides have been used to protect economically important crops from SPB infestations over the past three decades. However, ensuring the insecticides contact the SPB larvae within soybean pods under a closed canopy is difficult and sometimes necessitates the use of excessive amounts of insecticide. However, insecticides may kill beneficial insects, induce the development of insecticide‐resistant insect populations, pollute the environment and have other unintended adverse effects.…”

Section: Introductionmentioning

confidence: 99%

Expression of the double‐stranded RNA of the soybean pod borer Leguminivora glycinivorella (Lepidoptera: Tortricidae) ribosomal protein P0 gene enhances the resistance of transgenic soybean plants

Meng

Zang

et al. 2017

Pest Management Science

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“…MAS can reduce costs and time to cultivar release, and thereby increase the efficiency of breeding programmes (Zhao et al. , , Huang et al. ).…”

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confidence: 99%

“…However, few QTL underlying SPB resistance were identified by 2014 (Zhao , Zhao et al. ). The objectives of this study were to identify QTL for SPB resistance, to identify QTL associated with seed isoflavone content and to facilitate genetic improvement of soybean to combine both SPB resistance and high isoflavone content by MAS.…”

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confidence: 99%

Molecular loci associated with seed isoflavone content may underlie resistance to soybean pod borer (Leguminivora glycinivorella)

Zhao

Jiang

et al. 2015

Plant Breeding

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Soybean pod borer (SPB) (Leguminivora glycinivorella (Mats.) Obraztsov) causes severe loss of soybean (Glycine max L. Merr.) seed yield and quality in some regions of the world, especially in north-eastern China, Japan and Russia. Isoflavones in soybean seed play a crucial role in plant resistance to diseases and pests. The aim of this study was to find whether SPB resistance QTL are associated with soybean seed isoflavone content. A cross was made between 'Zhongdou 27' (higher isoflavone content) and 'Jiunong 20' (lower isoflavone content). One hundred and twelve F 5:10 recombinant inbred lines were derived through single-seed descent. A plastic-net cabinet was used to cover the plants in early August, and thirty SPB moths per square metre were put in to infest the soybean green pods. The results indicated that the percentage of seeds damaged by SPB was positively correlated with glycitein content (GC), whereas it was negatively correlated with genistein (GT), daidzein (DZ) and total isoflavone content (TI). Four QTL underlying SPB damage to seeds were identified and the phenotypic variation for SPB resistance explained by the four QTL ranged from 2% to 14% on chromosomes Gm7, 10, 13 and 17. Moreover, eleven QTL underlying isoflavone content were identified, and ten of them were encompassed within the same four marker intervals as the SPB QTL (BARC-Satt208-Sat292, Satt144-Sat074, Satt540-Sat244 and Satt345-Satt592). These QTL could be useful in marker-assisted selection for breeding soybean cultivars with both SPB resistance and high seed isoflavone content.

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Identification of QTL underlying the resistance of soybean to pod borer, Leguminivora glycinivorella (Mats.) obraztsov, and correlations with plant, pod and seed traits

Cited by 34 publications

References 45 publications

Identification of major QTLs and epistatic interactions for seed protein concentration in soybean under multiple environments based on a high-density map

Identification of major QTLs and epistatic interactions for seed protein concentration in soybean under multiple environments based on a high-density map

Expression of the double‐stranded RNA of the soybean pod borer Leguminivora glycinivorella (Lepidoptera: Tortricidae) ribosomal protein P0 gene enhances the resistance of transgenic soybean plants

Molecular loci associated with seed isoflavone content may underlie resistance to soybean pod borer (Leguminivora glycinivorella)

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