Dataset Information

New sources of soybean seed meal and oil composition traits identified through TILLING.

ABSTRACT: BACKGROUND: Several techniques are available to study gene function, but many are less than ideal for soybean. Reverse genetics, a relatively new approach, can be utilized to identify novel mutations in candidate genes; this technique has not produced an allelic variant with a confirmed phenotype in soybean. Soybean raffinose synthase genes and microsomal omega-6 fatty acid desaturase genes were screened for novel alleles in mutagenized soybean populations. RESULTS: Four mutations in independent lines were identified in the raffinose synthase gene RS2; two mutations resulted in amino acid mutations and one resulted in an altered seed oligosaccharide phenotype. The resulting phenotype was an increase in seed sucrose levels as well as a decrease in both raffinose and stachyose seed oligosaccharide levels. Three mutations in independent lines were identified in the omega-6 fatty acid desaturase gene FAD2-1A; all three mutations resulted in missense amino acid mutations and one resulted in an altered seed fatty acid profile that led to an increase in oleic acid and a decrease in linoleic acid in the seed oil. CONCLUSION: The oligosaccharide phenotype controlled by the novel RS2 allele is similar to previously observed seed oligosaccharide phenotypes in RS2 mutant (PI 200508) allele-containing lines. Due to the anti-nutritional characteristics of raffinose and stachyose, this represents a positive change in seed composition. The fatty acid phenotype controlled by the novel FAD2-1A allele controls an increase in oleic acid in the seed oil, a phenotype also observed in a line previously characterized to have a null allele of the FAD2-1A gene. Molecular marker assays were developed to reliably detect the inheritance of the mutant alleles and can be used in efficient breeding for these desired seed phenotypes. Our results serve as the first demonstration of the identification of soybean mutants controlling seed phenotypes discovered through the reverse genetics technique TILLING.

SUBMITTER: Dierking EC

PROVIDER: S-EPMC2719642 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

New sources of soybean seed meal and oil composition traits identified through TILLING.

Dierking Emily C EC Bilyeu Kristin D KD

BMC plant biology 20090714

<h4>Background</h4>Several techniques are available to study gene function, but many are less than ideal for soybean. Reverse genetics, a relatively new approach, can be utilized to identify novel mutations in candidate genes; this technique has not produced an allelic variant with a confirmed phenotype in soybean. Soybean raffinose synthase genes and microsomal omega-6 fatty acid desaturase genes were screened for novel alleles in mutagenized soybean populations.<h4>Results</h4>Four mutations i ...[more]

PMID: 19602293

Similar Datasets

Project description:BackgroundThe yield and quality of soybean oil are determined by seed oil-related traits, and metabolites/lipids act as bridges between genes and traits. Although there are many studies on the mode of inheritance of metabolites or traits, studies on multi-dimensional genetic network (MDGN) are limited.ResultsIn this study, six seed oil-related traits, 59 metabolites, and 107 lipids in 398 recombinant inbred lines, along with their candidate genes and miRNAs, were used to construct an MDGN in soybean. Around 175 quantitative trait loci (QTLs), 36 QTL-by-environment interactions, and 302 metabolic QTL clusters, 70 and 181 candidate genes, including 46 and 70 known homologs, were previously reported to be associated with the traits and metabolites, respectively. Gene regulatory networks were constructed using co-expression, protein-protein interaction, and transcription factor binding site and miRNA target predictions between candidate genes and 26 key miRNAs. Using modern statistical methods, 463 metabolite-lipid, 62 trait-metabolite, and 89 trait-lipid associations were found to be significant. Integrating these associations into the above networks, an MDGN was constructed, and 128 sub-networks were extracted. Among these sub-networks, the gene-trait or gene-metabolite relationships in 38 sub-networks were in agreement with previous studies, e.g., oleic acid (trait)-GmSEI-GmDGAT1a-triacylglycerol (16:0/18:2/18:3), gene and metabolite in each of 64 sub-networks were predicted to be in the same pathway, e.g., oleic acid (trait)-GmPHS-D-glucose, and others were new, e.g., triacylglycerol (16:0/18:1/18:2)-GmbZIP123-GmHD-ZIPIII-10-miR166s-oil content.ConclusionsThis study showed the advantages of MGDN in dissecting the genetic relationships between complex traits and metabolites. Using sub-networks in MGDN, 3D genetic sub-networks including pyruvate/threonine/citric acid revealed genetic relationships between carbohydrates, oil, and protein content, and 4D genetic sub-networks including PLDs revealed the relationships between oil-related traits and phospholipid metabolism likely influenced by the environment. This study will be helpful in soybean quality improvement and molecular biological research.

Dataset Information

New sources of soybean seed meal and oil composition traits identified through TILLING.

Publications

New sources of soybean seed meal and oil composition traits identified through TILLING.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets