scholarly journals Genetic control of soybean seed isoflavone content: importance of statistical model and epistasis in complex traits

2009 ◽  
Vol 119 (6) ◽  
pp. 1069-1083 ◽  
Author(s):  
Juan Jose Gutierrez-Gonzalez ◽  
Xiaolei Wu ◽  
Juan Zhang ◽  
Jeong-Dong Lee ◽  
Mark Ellersieck ◽  
...  
Keyword(s):  
Statistical Model ◽  
Genetic Control ◽  
Complex Traits ◽  
Soybean Seed ◽  
Isoflavone Content ◽  
Seed Isoflavone

scholarly journals Genomic Regions That Underlie Soybean Seed Isoflavone Content

2001 ◽  
Vol 1 (1) ◽  
pp. 38-44 ◽  
Author(s):  
K. Meksem ◽  
V. N. Njiti ◽  
W. J. Banz ◽  
M. J. Iqbal ◽  
My. M. Kassem ◽  
...  
Keyword(s):  
Linkage Group ◽  
High Performance ◽  
Biological Effects ◽  
Recombinant Inbred Lines ◽  
Soybean Seed ◽  
Soybean Seeds ◽  
Isoflavone Content ◽  
Seed Isoflavone ◽  
Genomic Regions

Soy products contain isoflavones (genistein, daidzein, and glycitein) that display biological effects when ingested by humans and animals, these effects are species, dose and age dependent. Therefore, the content and quality of isoflavones in soybeans is a key to their biological effect. Our objective was to identify loci that underlie isoflavone content in soybean seeds. The study involved 100 recombinant inbred lines (RIL) from the cross of ‘Essex’ by ‘Forrest,’ two cultivars that contrast for isoflavone content. Isoflavone content of seeds from each RIL was determined by high performance liquid chromatography (HPLC). The distribution of isoflavone content was continuous and unimodal. The heritability estimates on a line mean basis were 79% for daidzein, 22% for genistein, and 88% for glycitein. Isoflavone content of soybean seeds was compared against 150 polymorphic DNA markers in a one-way analysis of variance. Four genomic regions were found to be significantly associated with the isoflavone content of soybean seeds across both locations and years. Molecular linkage group B1 contained a major QTL underlying glycitein content (P=0.0001,R 2=50.2%), linkage groupNcontained a QTL for glycitein (P=0.0033,R 2=11.1%) and a QTL for daidzein (P=0.0023,R 2=10.3%) and linkage groupA1contained a QTL for daidzein (P=0.0081,R 2=9.6%). Selection for these chromosomal regions in a marker assisted selection program will allow for the manipulation of amounts and profiles of isoflavones (genistein, daidzein, and glycitein) content of soybean seeds. In addition, tightly linked markers can be used in map based cloning of genes associated with isoflavone content.

Effect of Late Sowing on the Isoflavone Content of Soybean Seed in Southern Kyushu

2009 ◽  
Vol 78 (2) ◽  
pp. 250-254 ◽  
Author(s):  
Isao Akagi ◽  
Motoki Nishihara ◽  
Shigehide Ueda ◽  
Akitoshi Yokoyama ◽  
Yuichi Saeki
Keyword(s):  
Soybean Seed ◽  
Isoflavone Content ◽  
Late Sowing

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

2015 ◽  
Vol 134 (1) ◽  
pp. 78-84 ◽  
Author(s):  
Guiyun Zhao ◽  
Zhenfeng Jiang ◽  
Dongmei Li ◽  
Yingpeng Han ◽  
Haibo Hu ◽  
...  
Keyword(s):  
Pod Borer ◽  
Isoflavone Content ◽  
Seed Isoflavone

scholarly journals Interspecific Recombinant Congenic Strains Between C57BL/6 and Mice of theMus spretusSpecies: A Powerful Tool to Dissect Genetic Control of Complex Traits

Genetics ◽  
2007 ◽  
Vol 177 (4) ◽  
pp. 2321-2333 ◽  
Author(s):  
Gaëtan Burgio ◽  
Marek Szatanik ◽  
Jean-Louis Guénet ◽  
Maria-Rosa Arnau ◽  
Jean-Jacques Panthier ◽  
...  
Keyword(s):  
Genetic Control ◽  
Complex Traits ◽  
Congenic Strains ◽  
Recombinant Congenic Strains

scholarly journals Comparison of GWAS models to identify non-additive genetic control of flowering time in sunflower hybrids

2017 ◽  
Author(s):  
Fanny Bonnafous ◽  
Ghislain Fievet ◽  
Nicolas Blanchet ◽  
Marie-Claude Boniface ◽  
Sébastien Carrère ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Flowering Time ◽  
Genetic Control ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Association Studies ◽  
Additive Models ◽  
Genome Wide Association Studies ◽  
Trait Loci ◽  
Genomic Regions

AbstractGenome-wide association studies are a powerful and widely used tool to decipher the genetic control of complex traits. One of the main challenges for hybrid crops, such as maize or sunflower, is to model the hybrid vigor in the linear mixed models, considering the relatedness between individuals. Here, we compared two additive and three non-additive association models for their ability to identify genomic regions associated with flowering time in sunflower hybrids. A panel of 452 sunflower hybrids, corresponding to incomplete crossing between 36 male lines and 36 female lines, was phenotyped in five environments and genotyped for 2,204,423 SNPs. Intra-locus effects were estimated in multi-locus models to detect genomic regions associated with flowering time using the different models. Thirteen quantitative trait loci were identified in total, two with both model categories and one with only non-additive models. A quantitative trait loci on LG09, detected by both the additive and non-additive models, is located near a GAI homolog and is presented in detail. Overall, this study shows the added value of non-additive modeling of allelic effects for identifying genomic regions that control traits of interest and that could participate in the heterosis observed in hybrids.

scholarly journals Genomic basis underlying the metabolome-mediated drought adaptation of maize

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Fei Zhang ◽  
Jinfeng Wu ◽  
Nir Sade ◽  
Si Wu ◽  
Aiman Egbaria ◽  
...  
Keyword(s):  
Environmental Stress ◽  
Candidate Genes ◽  
Genetic Control ◽  
Stress Responses ◽  
Complex Traits ◽  
Inbred Lines ◽  
Drought Response ◽  
Eqtl Analysis ◽  
Drought Adaptation ◽  
Hub Genes

Abstract Background Drought is a major environmental disaster that causes crop yield loss worldwide. Metabolites are involved in various environmental stress responses of plants. However, the genetic control of metabolomes underlying crop environmental stress adaptation remains elusive. Results Here, we perform non-targeted metabolic profiling of leaves for 385 maize natural inbred lines grown under well-watered as well as drought-stressed conditions. A total of 3890 metabolites are identified and 1035 of these are differentially produced between well-watered and drought-stressed conditions, representing effective indicators of maize drought response and tolerance. Genetic dissections reveal the associations between these metabolites and thousands of single-nucleotide polymorphisms (SNPs), which represented 3415 metabolite quantitative trait loci (mQTLs) and 2589 candidate genes. 78.6% of mQTLs (2684/3415) are novel drought-responsive QTLs. The regulatory variants that control the expression of the candidate genes are revealed by expression QTL (eQTL) analysis of the transcriptomes of leaves from 197 maize natural inbred lines. Integrated metabolic and transcriptomic assays identify dozens of environment-specific hub genes and their gene-metabolite regulatory networks. Comprehensive genetic and molecular studies reveal the roles and mechanisms of two hub genes, Bx12 and ZmGLK44, in regulating maize metabolite biosynthesis and drought tolerance. Conclusion Our studies reveal the first population-level metabolomes in crop drought response and uncover the natural variations and genetic control of these metabolomes underlying crop drought adaptation, demonstrating that multi-omics is a powerful strategy to dissect the genetic mechanisms of crop complex traits.

scholarly journals Effect of different planting times on the quantitative variation of total seed isoflavone content and composition in Korean soybean cultivars (Glycine max (L.) Merr.)

2020 ◽  
Author(s):  
Hong-Sik Kim ◽  
Beom-Kyu Kang ◽  
Jeong-Hyun Seo ◽  
Hyun-Tae Kim ◽  
Tae-Joung Ha ◽  
...  
Keyword(s):  
Ecological Environment ◽  
Average Content ◽  
Functional Ingredients ◽  
Black Soybean ◽  
Planting Time ◽  
Soybean Cultivars ◽  
Isoflavone Content ◽  
Glycine Max L ◽  
Seed Isoflavone ◽  
Total Seed

Abstract There is great interest in the enhancement of isoflavones as one of the functional ingredients in soybean. This study aimed to investigate the effects of changes in the ecological environment over different planting times on isoflavone content. A total of 28 Korean soybean cultivars were grown at different planting times in late May, mid-June, and early July and their isoflavone content was measured over 2 years (2017 and 2018). Analyses of variance revealed significant effects of genotypes, planting times, years, and their interactions on isoflavone content. The average content of total isoflavone, as well as its component groups of malonylglucoside and aglycon, increased significantly as the seed planting time was delayed from late May to early July. The accumulation of each isoflavone component varied with changes in the planting time. The isoflavone content of the soybean cultivars for soy-sprout and soy-paste and tofu were higher for plantings in early July than for those in late May and/or mid-June, except for the black soybean cultivars. Despite significant correlations of the isoflavone content of the 28 cultivars among the three planting times, the responses of individual cultivars varied in isoflavone content by planting time. When planting was delayed, the time to flowering and maturity was also delayed and the number of days of growth from planting or flowering to maturity decreased; however, this was not related to isoflavone content. When planting was delayed, the temperature during the ripening period from flowering to maturity was lower, which was inversely related to the isoflavone content.

A Statistical Model and Analysis for Genetic and Environmental Effects in Responses From Twin-Family Studies

1981 ◽  
Vol 30 (1) ◽  
pp. 9-38 ◽  
Author(s):  
James S. Williams ◽  
Hariharan Iyer
Keyword(s):  
Statistical Model ◽  
Genetic Control ◽  
Environmental Effects ◽  
Family Study ◽  
Smoking Habit ◽  
Cluster Sampling ◽  
Model Parameters ◽  
Social Environments ◽  
Correlation Data ◽  
Height Data

A statistical model and analysis for genetic and environmental effects in twin-family data are presented. The model is used to derive expressions for phenotypic correlations of 22 essential pair relationships in twin-family units. The analysis proceeds in two steps. First, differential effects of sex, generation, and sex-zygosity of twin-family units and correlations due to cluster sampling are eliminated from correlation data. Then, estimates and tests of model parameters are calculated from the adjusted data. The theory and methods were developed for a Swedish twin-family study of many behaviors possibly related to the smoking habit. There, it is important to screen for behaviors that clearly are under genetic control and to assess relative influences of various biological and social environments on the development of all behaviors. Height data from the Swedish study are used to illustrate concepts and methods presented in this paper.

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