Genetic mapping reveals the complex genetic architecture controlling slow canopy wilting in soybean.

In soybean [Glycine max (L.) Merr.], drought stress is the leading cause of yield loss from abiotic stress in rain-fed US growing areas. Only 10% of the US soybean production is irrigated; therefore, plants must possess physiological mechanisms to tolerate drought stress. Slow canopy wilting is a physiological trait that is observed in a few exotic plant introductions (PIs) and may lead to yield improvement under drought stress. Canopy wilting of 130 recombinant inbred lines (RILs) derived from Hutcheson × PI 471938 grown under drought stress was visually evaluated and genotyped with the SoySNP6K BeadChip. Over four years, field evaluations of canopy wilting were conducted under rainfed conditions at three locations across the US (Georgia, Kansas, and North Carolina). Due to the variation in weather among locations and years, the phenotypic data were collected from seven environments. Substantial variation in canopy wilting was observed among the genotypes in the RIL population across environments. Three QTLs were identified for canopy wilting from the RIL population using composite interval mapping on chromosomes (Chrs) 2, 8, and 9 based on combined environmental analyses. These QTLs inherited the favorable alleles from PI 471938 and accounted for 11, 10, and 14% of phenotypic variation, respectively. A list of 106 candidate genes were narrowed down for these three QTLs based on the published information. The QTLs identified through this research can be used as targets for further investigation to understand the mechanisms of slow canopy wilting. These QTLs could be deployed to improve drought tolerance through a targeted selection of the genomic regions from PI 471938.

Genomic prediction of optimal cross combinations to accelerate genetic improvement of soybean (Glycine max).

Improving yield is a primary soybean breeding goal, as yield is the main determinant of soybean's profitability. Within the breeding process, selection of cross combinations is one of most important elements. Cross prediction will assist soybean breeders in identifying the best cross combinations among parental genotypes prior to crossing, increasing genetic gain and breeding efficiency. In this study optimal cross selection methods were created and applied in soybean and validated using historical data from the University of Georgia soybean breeding program, under multiple training set compositions and marker densities utilizing multiple genomic selection models for marker evaluation. Plant materials consisted of 702 advanced breeding lines evaluated in multiple environments and genotyped using SoySNP6k BeadChips. An additional marker set, the SoySNP3k marker set, was tested in this study as well. Optimal cross selection methods were used to predict the yield of 42 previously made crosses and compared to the performance of the cross's offspring in replicated field trials. The best prediction accuracy was obtained when using Extended Genomic BLUP with the SoySNP6k marker set, consisting of 3,762 polymorphic markers, with an accuracy of 0.56 with a training set maximally related to the crosses predicted and 0.4 in a training set with minimized relatedness to predicted crosses. Prediction accuracy was most significantly impacted by training set relatedness to the predicted crosses, marker density, and the genomic model used to predict marker effects. The usefulness criterion selected had an impact on prediction accuracy within training sets with low relatedness to the crosses predicted. Optimal cross prediction provides a useful method that assists plant breeders in selecting crosses in soybean breeding.

Parsimonious root systems and better root distribution can improve biomass production and yield of soybean.

Enhancing the acquisition of belowground resources has been identified as an opportunity for improving soybean productivity worldwide. Root system architecture is gaining interest as a selection criterion in breeding programs for enhancing soil resource acquisition and developing climate-resilient varieties. Here we are presenting two novel characteristics of soybean root system architecture that improve aboveground growth and yield. Eleven selected soybean genotypes were tested under rain-fed conditions in 2019 and 2020 at two locations in South Carolina, in which one of the locations was characterized by compacted soils. The elite SC breeding line SC07-1518RR, exotic pedigree line N09-12854, and slow wilting line N09-13890 were superior genotypes in terms of biomass production, seed yield, and/or water use efficiency. Genotypes N09-12854 and N09-13890 demonstrated reduced root development (based on total root count and length), likely to restrict belowground growth and allocate more resources for shoot growth. This characteristic, which can be referred as a parsimonious root phenotype, might be advantageous for soybean improvement in high-input production systems (characterized by adequate fertilizer application and soil fertility) that exist in many parts of the world. Genotype SC07-1518RR exhibited a similar strategy: while it maintained its root system at an intermediate size through reduced levels of total root count and length, it selectively distributed more roots at deeper depths (53-70 cm). The increased root distribution of SC07-1518RR at deeper depths in compacted soil indicates its root penetrability and suitability for clayey soils with high penetration resistance. The beneficial root phenotypes identified in this study (parsimonious root development and selective root distribution in deeper depths) and the genotypes that possessed those phenotypes (SC07-1518RR, N09-12854, and N09-13890) will be useful for breeding programs in developing varieties for optimal, drought, and compacted-soil conditions.

Quantitative Trait Loci Associated with Rotylenchulus reniformis Host Suitability in Soybean.

Reniform nematode (Rotylenchulus reniformis) is a yield-limiting pathogen of soybean (Glycine max) in the southeastern region of the United States. A population of 250 recombinant inbred lines (RIL) (F2:8) developed from a cross between reniform nematode resistant soybean cultivar Forrest and susceptible cultivar Williams 82 was utilized to identify regions associated with host suitability. A genetic linkage map was constructed using single-nucleotide polymorphism markers generated by genotyping-by-sequencing. The phenotype was measured in the RIL population and resistance was characterized using normalized and transformed nematode reproduction indices in an optimal univariate cluster analysis. Quantitative trait loci (QTL) analysis using normalized phenotype scores identified two QTLs on each arm of chromosome 18 (rrn-1 and rrn-2). The same QTL analysis performed with log10(x) transformed phenotype data also identified two QTLs: one on chromosome 18 overlapping the same region in the other analysis (rrn-1), and one on chromosome 11 (rrn-3). While rrn-1 and rrn-3 have been reported associated with reduced reproduction of reniform nematode, this is the first report of the rrn-2 region associated with host suitability to reniform nematode. The resistant parent allele at rrn-2 showed an inverse relationship with the resistance phenotype, correlating with an increase in nematode reproduction or host suitability. Several candidate genes within these regions corresponded with host plant defense systems. Interestingly, a characteristic pathogen resistance gene with a leucine-rich repeat was discovered within rrn-2. These genetic markers can be used by soybean breeders in marker-assisted selection to develop lines with resistance to reniform nematode.

Comparative Lipidomic Analysis Reveals Heat Stress Responses of Two Soybean Genotypes Differing in Temperature Sensitivity.

Heat-induced changes in lipidome and their influence on stress adaptation are not well-defined in plants. We investigated if lipid metabolic changes contribute to differences in heat stress responses in a heat-tolerant soybean genotype DS25-1 and a heat-susceptible soybean genotype DT97-4290. Both genotypes were grown at optimal temperatures (OT; 30/20 °C) for 15 days. Subsequently, half of the plants were exposed to heat stress (38/28 °C) for 11 days, and the rest were kept at OT. Leaf samples were collected for lipid and RNA extractions on the 9th and 11th days of stress, respectively. We observed a decline in the lipid unsaturation level due to a decrease in the polyunsaturated linolenic acid (18:3) content in DS25-1. When examined under OT conditions, DS25-1 and DT97-4290 showed no significant differences in the expression pattern of the Fatty Acid Desaturase (FAD) 2-1A, FAD2-2B, FAD2-2C, FAD3A genes. Under heat stress conditions, substantial reductions in the expression levels of the FAD3A and FAD3B genes, which convert 18:2 lipids to 18:3, were observed in DS25-1. Our results suggest that decrease in levels of lipids containing 18:3 acyl chains under heat stress in DS25-1 is a likely consequence of reduced FAD3A and FAD3B expression, and the decrease in 18:3 contributes to DS25-1's maintenance of membrane functionality and heat tolerance.

Evaluation of soybean [Glycine max (L.) Merr.] genotypes for yield, water use efficiency, and root traits.

Drought stress has been identified as the major environmental factor limiting soybean [Glycine max (L.) Merr.] yield worldwide. Current breeding efforts in soybean largely focus on identifying genotypes with high seed yield and drought tolerance. Water use efficiency (WUE) that results in greater yield per unit rainfall is an important parameter in determining crop yields in many production systems, and is often related with crop drought tolerance. Even though roots are major plant organs that perceive and respond to drought stress, their utility in improving soybean yield and WUE under different environmental and management conditions are largely unclear. The objectives of this research was to evaluate soybean cultivars and breeding and germplasm lines for yield, WUE, root penetrability of hardpan, and root morphology. Field experiments were conducted at two locations in South Carolina (southeastern United States) during the 2017 cropping season to test the genotypes for yield and root morphology under irrigated and non-irrigated conditions. Two independent controlled-environmental experiments were conducted to test the genotypes for WUE and root penetrability of synthetic hardpans. The slow wilting lines NTCPR94-5157 and N09-13890 had equal or greater yield than the checks- cultivar NC-Raleigh and the elite South Carolina breeding line SC07-1518RR, under irrigated and non-irrigated conditions. The high yielding genotypes NTCPR94-5157, N09-13890, and SC07-1518RR exhibited root parsimony (reduced root development). This supported the recent hypothesis in literature that root parsimony would have adaptational advantage to improve yield under high input field conditions. The high yielding genotypes NTCPR94-5157, N09-13890, NC-Raleigh, and SC07-1518RR and a cultivar Boggs (intermediate in yield) possessed high WUE and had increased root penetrability of hardpans. These genotypes offer useful genetic materials for soybean breeding programs for improving yield, drought tolerance, and/or hardpan penetrability.

Characterization of a soybean (Glycine max L. Merr.) germplasm collection for root traits.

Root systems that improve resource uptake and penetrate compacted soil (hardpan) are important for improving soybean (Glycine max L. Merr.) productivity in optimal and sub-optimal environments. The objectives of this research were to evaluate a soybean germplasm collection of 49 genotypes for root traits, determine whether root traits are related with plant height, shoot dry weight, chlorophyll index, and seed size, and identify genotypes that can penetrate a hardpan. Plants were maintained under optimal growth conditions in a greenhouse. Single plants were grown in mesocosms, constructed of two stacked columns (top and bottom columns had 25 and 46 cm height, respectively, and 15 cm inside diameter) with a 2-cm thick wax layer (synthetic hardpan; penetration resistance, 1.5 MPa at 30°C) in between. Plants were harvested at 42 days after planting. Significant genetic variability was observed for root traits in the soybean germplasm collection, and genotypes that penetrated the synthetic hardpan were identified. Genotypes NTCPR94-5157, NMS4-1-83, and N09-13128 were ranked high and PI 424007 and R01-581F were ranked low for most root traits. Shoot dry weight and chlorophyll index were positively related with total root length, surface area, and volume, and fine root length (Correlation coefficient, r ≥ 0.60 and P-value < 0.0001 for shoot dry weight and r ≥ 0.37 and P-value < 0.01 for chlorophyll index]. Plant height was negatively correlated with total root surface area, total root volume, and average root diameter (|r| ≥ 0.29, P-value < 0.05). Seed size was not correlated with any root traits. The genetic variability identified in this research for root traits and penetration are critical for soybean improvement programs in choosing genotypes with improved root characteristics to increase yield in stressful or optimum environments.