Detecting the QTL-Allele System of Seed Oil Traits Using Multi-Locus Genome-Wide Association Analysis for Population Characterization and Optimal Cross Prediction in Soybean

Soybean is one of the world's major vegetative oil sources, while oleic acid and linolenic acid content are the major quality traits of soybean oil. The restricted two-stage multi-locus genome-wide association analysis (RTM-GWAS), characterized with error and false-positive control, has provided a potential approach for a relatively thorough detection of whole-genome QTL-alleles. The Chinese soybean landrace population (CSLRP) composed of 366 accessions was tested under four environments to identify the QTL-allele constitution of seed oil, oleic acid and linolenic acid content (SOC, OAC, and LAC). Using RTM-GWAS with 29,119 SNPLDBs (SNP linkage disequilibrium blocks) as genomic markers, 50, 98, and 50 QTLs with 136, 283, and 154 alleles (2–9 per locus) were detected, with their contribution 82.52, 90.31, and 83.86% to phenotypic variance, corresponding to their heritability 91.29, 90.97, and 90.24% for SOC, OAC, and LAC, respectively. The RTM-GWAS was shown to be more powerful and efficient than previous single-locus model GWAS procedures. For each trait, the detected QTL-alleles were organized into a QTL-allele matrix as the population genetic constitution. From which the genetic differentiation among 6 eco-populations was characterized as significant allele frequency differentiation on 28, 56, and 30 loci for the three traits, respectively. The QTL-allele matrices were also used for genomic selection for optimal crosses, which predicted transgressive potential up to 24.76, 40.30, and 2.37% for the respective traits, respectively. From the detected major QTLs, 38, 27, and 25 candidate genes were annotated for the respective traits, and two common QTL covering eight genes were identified for further study

A high-throughput phenotyping procedure for evaluation of antixenosis against common cutworm at early seedling stage in soybean

Abstract Background Common cutworm (CCW; Spodoptera litura Fabricius) is a major leaf-feeding pest of soybean in Asia. The previous methods of measuring antixenosis against CCW using adult plant under field or net-room conditions were time-consuming, labor-intensive and precision-inferior. To solve the problems, this study aimed at (i) establishing a high-throughput phenotyping method for evaluating antixenosis against CCW at early seedling stage, (ii) using the procedure to evaluate the antixenosis of an insect-resistant versus -susceptible germplasm population (IRSGP), (iii) validating the proposed method through comparing the results with the historical phenotypic data and phenotyping-genotyping consistency data using PAV (presence/absence variation) markers linked with the identified loci CCW-1 and CCW-2, (iv) and evaluating the efficiency of the novel method through comparisons to the previous methods. Results A dynamic and efficient evaluation procedure characterized with using V1 stage soybean seedlings infested with third-instar larvae in a micro-net-room in greenhouse with damaged leaf percentage (DLP) as indicator was established and designated V1TMD method. The middle term testing stage is the best dates for identifying resistant and susceptible accessions. The results from the V1TMD method were relatively stable, precise and accurate in comparison with the previous method with the detected most resistant and susceptible accessions consistent to the previous results. The DLP values differentiated obviously to coincide with the resistant and susceptible alleles of the PAV markers Gm07PAV0595 and Gm07PAV0389 tightly linked to the two resistance-related loci, CCW-1 and CCW-2, respectively, in IRSGP. Thus V1TMD is a high-throughput phenotyping method with its estimated efficiency 12 times and period shortening 4 times of those of the previous method. Conclusion A dynamic and efficient V1TMD method for testing antixenosis against CCW was established, with highly resistant and highly susceptible accessions as standard checks and DLP as indicator. The method is remarkably quick, highly reproducible, and capable of testing large samples, therefore, is a high-throughput phenotyping method

Effects of Fertilizer Level and Intercropping Planting Pattern with Corn on the Yield-Related Traits and Insect Community of Soybean

Intercropping of corn and soybean is widely practiced in agricultural production. However, few studies have investigated the effect of intercropping and fertilizer reduction on soybean yield. In the present study, corn and soybean were interplanted in 2:2, 2:3 and 2:4 ratios. Two fertilizer levels (normal: 600 kg/ha VS. reduced: 375 kg/ha) were set. The effects of fertilizer levels and intercropping planting patterns on the growth and yield of intercropping soybeans were studied based on the changes in enzyme activities related to nitrogen metabolism and insect community in the field. The results show that fertilizer reduction significantly reduced the biomass, 100-seed weight and yield of soybean. Intercropping also reduced these yield-related traits; a decreasing trend was more obvious with a decrease in soybean ratio. Intercropping had greater effect on soybean plant biomass, 100-seed weight and yield than fertilizer reduction. Reduction in fertilizer reduced the activities of nitrogen-metabolism-related enzymes in soybean. In addition to increased NR (nitrate reductase) enzyme activity in R5, intercropping planting pattern also had negative effect on the activities of nitrogen-metabolism-related enzymes in soybean. Reduced fertilizer only significantly reduced the Pielou evenness index. Reduced fertilizer application was beneficial with respect to the outbreak of greenhouse whitefly. However, an intercropping planting pattern can significantly increase the number of species, as well as the Shannon–Wiener diversity index and the Pielou evenness index of the insect community, and significantly reduce the Simpson dominance index and the population of the important pest, green leafhopper. In conclusion, C2S4 (two corn rows with four rows of soybean) is a scientific intercropping planting pattern that can reduce the occurrence of pests through ecological regulation and does not significantly reduce the activity of enzymes-related to nitrogen metabolism in most cases, ensuring soybean yield

MOESM1 of A high-throughput phenotyping procedure for evaluation of antixenosis against common cutworm at early seedling stage in soybean

Additional file 1: Table S1. The DLPs of all accessions at all evaluation dates in Test 1 and Test 2 of Experiment 1

Effects of Corn Intercropping with Soybean/Peanut/Millet on the Biomass and Yield of Corn under Fertilizer Reduction

Corn (Zea mays L.) is one of the key grain crops in China. In fields, the two crops of soybean (Glycine max L.) and peanut (Arachis hypogaea L.), which have nitrogen-fixing capacity (NFC), are generally used to intercrop with corn to improve plant physiology and production ability of corn even under fertilizer reduction. To explore a more scientific and reasonable way to plant corn, and simultaneously reduce the use of chemical fertilizers and pesticides, the impacts of corn intercropping with two NFC crops (including soybean and peanut) and the a non-NFC crop (i.e., millet (Setaria italica)) through five planting patterns, including three intercropping patterns (2 corn rows to 2, 3, and 4 NFC-crop rows or 2, 4, and 6 millet rows) and two sole crop patterns of corn and soybean, peanut, or millet under normal (600 kg/ha) and reduced (375 kg/ha) levels of NPK (N:P2O5:K2O = 15:15:15) fertilization levels on the activity of N-metabolism-related enzymes in corn rhizosphere soil and corn leaves, and plant biomass and yield of corn were researched in this study. The results showed that fertilizer reduction significantly decreased the plant biomass and grain yield of the sole crop corn. The intercropping type and planting pattern both had significant effects on the activities of N-metabolism-related enzyme of soil alkaline protease (S-ALPT), and glutamine oxoglutarate aminotransferase (GOGAT), glutamate synthetase (GS), and nitrate reductase (NR) in the leaves of corn plants. The intercropping type of corn with soybean through the planting pattern of 2 corn rows to 4 soybean rows significantly improved the activities of N-metabolism-related enzymes in soil and corn leaves even under the fertilizer reduction. The intercropping pattern of corn-soybean was the most beneficial to increase the total nitrogen content in soil and corn leaves. In addition, the intercropping significantly increased the soil microbial diversity under normal fertilizer. Furthermore, fertilizer reduction significantly increased soil microbial diversity of the corn sole crop. Therefore, it is concluded that for corn in intercropping systems, the best and the worst companion crop were, respectively, soybean and millet

An evaluation of formability using micro-embossing on an ultrafine-grained magnesium AZ31 alloy processed by high-pressure torsion

An ultrafine-grained (UFG) magnesium AZ31 alloy was achieved with an average grain size of ?200?nm by high-pressure torsion (HPT) at room temperature (RT) under a pressure of 6.0?GPa through 5 turns. Micro-embossing tests were conducted in a V-groove die having a width of 100??m in the temperature range of 298 to 523?K. The formability of UFG AZ31 alloy was evaluated by measuring the percentage of material flowing into the V-groove. The results show that refinement of grain size can significantly improve the formability by increasing the stain rate sensitivity by comparison with the as-drawn AZ31 alloy. The results demonstrate that the UFG AZ31 alloy exhibits excellent formability for fabricating MEMS components with complicated structures

An evaluation of formability using micro-embossing on an ultrafine-grained magnesium AZ31 alloy processed by high-pressure torsion

An ultrafine-grained (UFG) magnesium AZ31 alloy was achieved with an average grain size of ∼200 nm by high-pressure torsion (HPT) at room temperature (RT) under a pressure of 6.0 GPa through 5 turns. Micro-embossing tests were conducted in a V-groove die having a width of 100 μm in the temperature range of 298 to 523 K. The formability of UFG AZ31 alloy was evaluated by measuring the percentage of material flowing into the V-groove. The results show that refinement of grain size can significantly improve the formability by increasing the stain rate sensitivity by comparison with the as-drawn AZ31 alloy. The results demonstrate that the UFG AZ31 alloy exhibits excellent formability for fabricating MEMS components with complicated structures

Composite Interval Mapping Based on Lattice Design for Error Control May Increase Power of Quantitative Trait Locus Detection.

Experimental error control is very important in quantitative trait locus (QTL) mapping. Although numerous statistical methods have been developed for QTL mapping, a QTL detection model based on an appropriate experimental design that emphasizes error control has not been developed. Lattice design is very suitable for experiments with large sample sizes, which is usually required for accurate mapping of quantitative traits. However, the lack of a QTL mapping method based on lattice design dictates that the arithmetic mean or adjusted mean of each line of observations in the lattice design had to be used as a response variable, resulting in low QTL detection power. As an improvement, we developed a QTL mapping method termed composite interval mapping based on lattice design (CIMLD). In the lattice design, experimental errors are decomposed into random errors and block-within-replication errors. Four levels of block-within-replication errors were simulated to show the power of QTL detection under different error controls. The simulation results showed that the arithmetic mean method, which is equivalent to a method under random complete block design (RCBD), was very sensitive to the size of the block variance and with the increase of block variance, the power of QTL detection decreased from 51.3% to 9.4%. In contrast to the RCBD method, the power of CIMLD and the adjusted mean method did not change for different block variances. The CIMLD method showed 1.2- to 7.6-fold higher power of QTL detection than the arithmetic or adjusted mean methods. Our proposed method was applied to real soybean (Glycine max) data as an example and 10 QTLs for biomass were identified that explained 65.87% of the phenotypic variation, while only three and two QTLs were identified by arithmetic and adjusted mean methods, respectively

Microhardness, microstructure and tensile behavior of an AZ31 magnesium alloy processed by high-pressure torsion

An AZ31 magnesium alloy was processed by high-pressure torsion (HPT) at room temperature under an imposed pressure of 6.0 GPa. Microstructural analysis showed that the HPT processing introduced significant grain refinement with a reduction in grain size from ~35 ?m in the initial annealed condition to ~110 nm after ten turns of HPT. Microhardness measurements showed that a reasonable level of hardness homogeneity was achieved across the disk processed through ten turns. The results from tensile testing demonstrated that the ultrafine-grained (UFG) AZ31 alloy processed by HPT exhibits high ductility with a maximum elongation of ~400 % at the relatively low testing temperature of 423 K. The results confirm that the UFG AZ31 magnesium alloy processed by HPT through ten turns has a strong potential for use in micro-forming applications