Effect of Soybean Oil Fatty Acid Composition and Selenium Application on Biodiesel Properties

Biodiesel consisting principally of monounsaturated fatty acid methyl esters (FAME) has been reported to have the optimal balance between cold flow properties and oxidative stability, therefore producing a superior fuel. In addition, treating biodiesel with antioxidants such as selenium (Se) also increases oxidative stability. Fuel properties including acid value (AV), cloud point (CP), iodine value (IV), pour point (PP), peroxide value (PV), induction period (IP), onset temperature (OT), and kinematic viscosity (KV) were used to evaluate a newly developed Roundup Ready® soybean recombinant inbred line (RIL) and a commercial cultivar. The RIL had a fatty acid profile with elevated levels of monounsaturated FAME. TN07-93RR was determined as the more desirable line for production of biodiesel, based on its fatty acid composition and subsequent fuel properties. The commercial cultivar AG3906 contained the highest abundance of polyunsaturated FAME and exhibited comparatively high IV and low oxidative stability. AG3906 was therefore not acceptable under the European biodiesel standard, EN 14214. However, TN07-93RR and AG3906 both were considered satisfactory according to the American biodiesel standard, ASTM D6751. Foliar treatment of soybean plants with varying amounts of Se had no effect on subsequent biodiesel oxidative stabilities

An (E,E)-α-farnesene synthase gene of soybean has a role in defence against nematodes and is involved in synthesizing insect-induced volatiles

Plant terpene synthase genes (TPSs) have roles in diverse biological processes. Here, we report the functional characterization of one member of the soybean TPS gene family, which was designated GmAFS. Recombinant GmAFS produced in Escherichia coli catalysed the formation of a sesquiterpene (E,E)-a-farnesene. GmAFS is closely related to (E,E)-a-farnesene synthase gene from apple, both phylogenetically and structurally. GmAFS was further investigated for its biological role in defence against nematodes and insects. Soybean cyst nematode (SCN) is the most important pathogen of soybean. The expression of GmAFS in a SCN-resistant soybean was significantly induced by SCN infection compared with the control, whereas its expression in a SCN-susceptible soybean was not changed by SCN infection. Transgenic hairy roots overexpressing GmAFS under the control of the CaMV 35S promoter were generated in an SCN-susceptible soybean line. The transgenic lines showed significantly higher resistance to SCN, which indicates that GmAFS contributes to the resistance of soybean to SCN. In soybean leaves, the expression of GmAFS was found to be induced by Tetranychus urticate (two-spotted spider mites). Exogenous application of methyl jasmonate to soybean plants also induced the expression of GmAFS in leaves. Using headspace collection combined with gas chromatography–mass spectrometry analysis, soybean plants that were infested with T. urticae were shown to emit a mixture of volatiles with (E,E)-a-farnesene as one of the most abundant constituents. In summary, this study showed that GmAFS has defence roles in both below-ground and above-ground organs of soybean against nematodes and insects, respectively

Transgenic soybean overexpressing GmSAMT1 exhibits resistance to multiple-HG types of soybean cyst nematode Heterodera glycines

Soybean (Glycine max (L.) Merr.) salicylic acid methyl transferase (GmSAMT1) catalyses the conversion of salicylic acid to methyl salicylate. Prior results showed that when GmSAMT1 was overexpressed in transgenic soybean hairy roots, resistance is conferred against soybean cyst nematode (SCN), Heterodera glycines Ichinohe. In this study, we produced transgenic soybean overexpressing GmSAMT1 and characterized their response to various SCN races. Transgenic plants conferred a significant reduction in the development of SCN HG type 1.2.5.7 (race 2), HG type 0 (race 3) and HG type 2.5.7 (race 5). Among transgenic lines, GmSAMT1 expression in roots was positively associated with SCN resistance. In some transgenic lines, there was a significant decrease in salicylic acid titer relative to control plants. No significant seed yield differences were observed between transgenics and control soybean plants grown in one greenhouse with 22 °C day/night temperature, whereas transgenic soybean had higher yield than controls grown a warmer greenhouse (27 °C day/23 °C night) temperature. In a 1-year field experiment in Knoxville, TN, there was no significant difference in seed yield between the transgenic and nontransgenic soybean under conditions with negligible SCN infection. We hypothesize that GmSAMT1 expression affects salicylic acid biosynthesis, which, in turn, attenuates SCN development, without negative consequences to soybean yield or other morphological traits. Thus, we conclude that GmSAMT1 overexpression confers broad resistance to multiple SCN races, which would be potentially applicable to commercial production

Gut microbiota and diabetes: from pathogenesis to therapeutic perspective

More than several hundreds of millions of people will be diabetic and obese over the next decades in front of which the actual therapeutic approaches aim at treating the consequences rather than causes of the impaired metabolism. This strategy is not efficient and new paradigms should be found. The wide analysis of the genome cannot predict or explain more than 10–20% of the disease, whereas changes in feeding and social behavior have certainly a major impact. However, the molecular mechanisms linking environmental factors and genetic susceptibility were so far not envisioned until the recent discovery of a hidden source of genomic diversity, i.e., the metagenome. More than 3 million genes from several hundreds of species constitute our intestinal microbiome. First key experiments have demonstrated that this biome can by itself transfer metabolic disease. The mechanisms are unknown but could be involved in the modulation of energy harvesting capacity by the host as well as the low-grade inflammation and the corresponding immune response on adipose tissue plasticity, hepatic steatosis, insulin resistance and even the secondary cardiovascular events. Secreted bacterial factors reach the circulating blood, and even full bacteria from intestinal microbiota can reach tissues where inflammation is triggered. The last 5 years have demonstrated that intestinal microbiota, at its molecular level, is a causal factor early in the development of the diseases. Nonetheless, much more need to be uncovered in order to identify first, new predictive biomarkers so that preventive strategies based on pre- and probiotics, and second, new therapeutic strategies against the cause rather than the consequence of hyperglycemia and body weight gain

Molecular Mapping and Identification of Soybean Fatty Acid Modifier Quantitative Trait Loci

Altering FA content in soybean [Glycine max (L.) Merr.] oil for improved functionality is a research goal of many soybean breeders. Several of the genes that alter palmitic, stearic, oleic, linoleic, and linolenic acids are modifier genes with small effects, causing these FA traits to act as quantitative traits. The objective of this study was to identify modifier FA quantitative trait loci (QTL) in soybean. A recombinant inbred line population was created from two prominent ancestors of currently avail-able U.S. cultivars (Essex and Williams) and grown in five environments. One hundred simple se-quence repeat markers spaced throughout the genome were mapped in this population. QTL were found for all five FA traits on the soybean linkage groups C2, D2, D1b, F, K, and L. A single marker interval on linkage group L contained the largest QTL for palmitic (r2 = 13.1%), oleic (r2 = 35.3%), linoleic (r2 = 50.5%), and linolenic acids (r2 = 24.8%); however, this interval also contained the gene for growth habit (Dt1) and was significantly associated with maturity. Other modifier QTL found in this study may be of use in marker-assisted selection to enable breeders to increase genetic gains for desirable FA composition of soybean

Context-Specific Genomic Selection Strategies Outperform Phenotypic Selection for Soybean Quantitative Traits in the Progeny Row Stage

Evaluating different breeding selection strategies for relative utility is necessary to choose those that maximize efficiency. Soybean [Glycine max (L.) Merr.] seed yield and fatty acid, protein, and oil contents are all commercially important traits that display complex quantitative inheritance. A soybean population consisting of 860 F5–derived recombinant inbred lines (RILs), genotyped with 4867 polymorphic single nucleotide polymorphism (SNPs) was used to compare phenotypic and context specific genomic selection (GS) strategies. To simulate progeny rows, each RIL was grown in a single plot in 2010 in Knoxville, TN, and phenotype was recorded. A subset of 276 RILs with similar maturity was then grown in multilocation, replicated field trials in 2013 to compare the performance of each selection method in field conditions. Notably, the preferred method for each trait was GS. Of the GS approaches evaluated, Epistacy performed best for yield, and BayesB and/or genomic best linear unbiased prediction (G-BLUP) were preferred for each of the other traits. Yield was the only trait for which the predictions had a large change when the number of SNPs and the number of RILs were randomly reduced for the G-BLUP model, with the best predictions occurring when RILs with different maturity that were not grown in 2013 were removed from the training set. These findings provide important information on how soybean breeders can maximize selections from the progeny row stage for yield and fatty acid, protein, and oil contents by using appropriate selection strategies

Soybean BARCSoySNP6K: An assay for soybean genetics and breeding research

The limited number of recombinant events in recombinant inbred lines suggests that for a biparental population with a limited number of recombinant inbred lines, it is unnecessary to genotype the lines with many markers. For genomic prediction and selection, previous studies have demonstrated that only 1000–2000 genome-wide common markers across all lines/accessions are needed to reach maximum efficiency of genomic prediction in populations. Evaluation of too many markers will not only increase the cost but also generate redundant information. We developed a soybean (Glycine max) assay, BARCSoySNP6K, containing 6000 markers, which were carefully chosen from the SoySNP50K assay based on their position in the soybean genome and haplotype block, polymorphism among accessions and genotyping quality. The assay includes 5000 single nucleotide polymorphisms (SNPs) from euchromatic and 1000 from heterochromatic regions. The percentage of SNPs with minor allele frequency \u3e0.10 was 95% and 91% in the euchromatic and heterochromatic regions, respectively. Analysis of progeny from two large families genotyped with SoySNP50K versus BARCSoySNP6K showed that the position of the common markers and number of unique bins along linkage maps were consistent based on the SNPs genotyped with the two assays; however, the rate of redundant markers was dramatically reduced with the BARCSoySNP6K. The BARCSoySNP6K assay is proven as an excellent tool for detecting quantitative trait loci, genomic selection and assessing genetic relationships. The assay is commercialized by Illumina Inc. and being used by soybean breeders and geneticists and the list of SNPs in the assay is an ideal resource for SNP genotyping by targeted amplicon sequencing