George L. Graef

Identification of putative QTL that underlie yield in interspecific soybean backcross populations

Glycine soja, the wild progenitor of soybean, is a potential source of useful genetic variation in soybean improvement. The objective of our study was to map quantitative trait loci (QTL) from G. soja that could improve the crop. Five populations of BC2F4-derived lines were developed using the Glycine max cultivar IA2008 as a recurrent parent and the G. soja plant introduction (PI) 468916 as a donor parent. There were between 57 and 112 BC2F4-derived lines in each population and a total of 468 lines for the five populations. The lines were evaluated with simple sequence repeat markers and in field tests for yield, maturity, plant height, and lodging. The field testing was done over 2 years and at two locations each year. Marker data were analyzed for linkage and combined with field data to identify QTL. Using an experimentwise significance threshold of P=0.05, four yield QTL were identified across environments on linkage groups C2, E, K, and M. For these yield QTL, the IA2008 marker allele was associated with significantly greater yield than the marker allele from G. soja. In addition, one lodging QTL, four maturity QTL, and five QTL for plant height were identified across environments. Of the 14 QTL identified, eight mapped to regions where QTL with similar effects were previously mapped. Many regions carrying the yield QTL were also significant for other traits, such as plant height and lodging. When the significance threshold was reduced and the data were analyzed with simple linear regression, four QTL with a positive allele for yield from G. soja were mapped. One epistatic interaction between two genetic regions was identified for yield using an experimentwise significance threshold of P=0.05. Additional research is needed to establish whether multiple trait associations are the result of pleiotropy or genetic linkage and to retest QTL with a positive effect from G. soja.

A high‐oleic‐acid and low‐palmitic‐acid soybean: agronomic performance and evaluation as a feedstock for biodiesel

Phenotypic characterization of soybean event 335-13, which possesses oil with an increased oleic acid content (> 85%) and reduced palmitic acid content (< 5%), was conducted across multiple environments during 2004 and 2005. Under these conditions, the stability of the novel fatty acid profile of the oil was not influenced by environment. Importantly, the novel soybean event 335-13 was not compromised in yield in both irrigated and non-irrigated production schemes. Moreover, seed characteristics, including total oil and protein, as well as amino acid profile, were not altered as a result of the large shift in the fatty acid profile. The novel oil trait was inherited in a simple Mendelian fashion. The event 335-13 was also evaluated as a feedstock for biodiesel. Extruded oil from event 335-13 produced a biodiesel with improved cold flow and enhanced oxidative stability, two critical fuel parameters that can limit the utility of this renewable transportation fuel.

Genotyping by sequencing for genomic prediction in a soybean breeding population

BackgroundAdvances in genotyping technology, such as genotyping by sequencing (GBS), are making genomic prediction more attractive to reduce breeding cycle times and costs associated with phenotyping. Genomic prediction and selection has been studied in several crop species, but no reports exist in soybean. The objectives of this study were (i) evaluate prospects for genomic selection using GBS in a typical soybean breeding program and (ii) evaluate the effect of GBS marker selection and imputation on genomic prediction accuracy. To achieve these objectives, a set of soybean lines sampled from the University of Nebraska Soybean Breeding Program were genotyped using GBS and evaluated for yield and other agronomic traits at multiple Nebraska locations.ResultsGenotyping by sequencing scored 16,502 single nucleotide polymorphisms (SNPs) with minor-allele frequency (MAF) > 0.05 and percentage of missing values ≤ 5% on 301 elite soybean breeding lines. When SNPs with up to 80% missing values were included, 52,349 SNPs were scored. Prediction accuracy for grain yield, assessed using cross validation, was estimated to be 0.64, indicating good potential for using genomic selection for grain yield in soybean. Filtering SNPs based on missing data percentage had little to no effect on prediction accuracy, especially when random forest imputation was used to impute missing values. The highest accuracies were observed when random forest imputation was used on all SNPs, but differences were not significant. A standard additive G-BLUP model was robust; modeling additive-by-additive epistasis did not provide any improvement in prediction accuracy. The effect of training population size on accuracy began to plateau around 100, but accuracy steadily climbed until the largest possible size was used in this analysis. Including only SNPs with MAF > 0.30 provided higher accuracies when training populations were smaller.ConclusionsUsing GBS for genomic prediction in soybean holds good potential to expedite genetic gain. Our results suggest that standard additive G-BLUP models can be used on unfiltered, imputed GBS data without loss in accuracy.

Relationships between nuclear DNA content and seed and leaf size in soybean

Abstract A correlation between genome size and agronomically important traits has been observed in many plant species. The goal of the present research was to determine the relationship between genome size, seed size, and leaf width and length in soybean [Glycine max (L.) Merr.] Twelve soybean strains, representing three distinct seed size groups, were analyzed. Flow cytometry was used to estimate their 2C nuclear DNA contents. Data on seed size and leaf size of the 12 strains were obtained from 1994 and 1995 field experiments. Variation of 2C nuclear DNA among the 12 soybean strains was 4.6%, ranging from 2.37 pg for a small-seed strain to 2.48 pg for a large-seed strain. Strain seed size was positively associated with leaf width (r=0.92) and leaf length (r=0.93). Genome size was highly correlated with seed size (r=0.97), leaf width (r=0.90) , and leaf length (r=0.93). The results of our study indicate that there is a significant correlation between genome size and leaf and seed size in soybean. It is possible that selection for greater seed size either leads to, or results from, greater genome size. If so, this relationship might be worth exploring at a more fundamental level.

RFLP mapping using near-isogenic lines in the soybean [Glycine max (L.) Merr].

SummaryA molecular marker analysis of a near-isogenic line (NIL), its donor parent (DP), and its recurrent parent (RP) can provide information about linkages between molecular markers and a conventional marker introgressed into the NIL. If the DP and RP possess different alleles for a given molecular marker, and if the NIL possesses the same allele as the DP, then it is reasonable to presume a linkage between that molecular marker and the introgressed marker. In this study, we examined the utility of RFLPs as molecular markers for the NIL genemapping approach. The allelic status of fifteen RFLP loci was determined in 116 soybean RP/NIL/DP line sets; 66 of the ‘Clark’ RP type and 50 of the ‘Harosoy’ RP type. Of the 1740 possible allelic comparisons (116 NILs x 15 RFLP loci), 1638 were tested and 462 (33.9%) of those were informative (i.e., the RP and DP had different RFLP alleles). In 15 (3.2%) of these 462 cases the NIL possessed the DP-derived RFLP allele, leading to a presumption of linkage between the RFLP locus and the introgressed conventional marker locus. Two presumptive linkages, pK-3 — and pK-472 — Lfi, were subsequently confirmed by cosegregation linkage analysis. Although not yet confirmed, two other associations, pk-7 ab and pK-229 — y9 seemed to be plausible linkages, primarily because the pk-7 — ab association was detected in two independently derived NILs and both markers of the pK-229 — y9 association were known to be linked to Pb. The data obtained in this investigation indicated that RFLP loci were useful molecular markers for the NIL gene-mapping technique.

Effect of dietary supplementation of selenite on pulmonary metastasis of melanoma cells in mice

The purpose of the present study was to determine the effect of dietary supplementation of selenite on experimental pulmonary metastasis of B16BL6 murine melanoma cells in C57BL/6 mice by means of an intravenous injection model. Three groups of mice were fed a basal AIN-93G diet containing 0.1 ppm selenium (control group) or the basal diet supplemented with 2 or 4 ppm selenium as selenite (experimental groups). Mice were fed the diet for two weeks before and after the intravenous injection of 0.75 x 10(5) viable tumor cells. At necropsy the number of tumors that developed in the lungs and their cross-sectional area were determined, and tumor volume was calculated. In the control group, 12 of the 15 mice had > or = 1 lung tumors. In contrast, only 4 of the 15 mice in each of the selenite-supplemented groups had > or = 11 tumors. The incidence of metastasis in mice fed the control and the 2- and 4-ppm selenium diets was 93%, 73%, and 53%, respectively. The median number of lung tumors was 53, 1, and 1 in mice fed the basal and the 2- and 4-ppm selenium diets, respectively. Tumor cross-sectional area and tumor volume were significantly decreased in selenite-supplemented groups. These results demonstrate that dietary supplementation of selenite reduced pulmonary metastasis of B16BL6 melanoma cells in C57BL/6 mice and also inhibited the growth of the metastatic tumors that developed in the lungs. It is concluded that selenite may be a useful adjuvant to prevent metastatic diseases in cancer patients.

A multi-sensor system for high throughput field phenotyping in soybean and wheat breeding

A multi-sensor system for high throughput field phenotyping was developed.The system measured canopy height, temperature, NDVI, reflectance, and RGB image.The sensor system was successfully tested in soybean and wheat field trials.In-season sensor traits revealed the growth pattern of plots during the season.Final yield is significantly correlated with the sensor traits at early and late season. Collecting plant phenotypic data with sufficient resolution (in both space and time) and accuracy represents a long standing challenge in plant science research, and has been a major limiting factor for the effective use of genomic data for crop improvement. This is particularly true in plant breeding where collecting large-scale field-based plant phenotypes can be very labor intensive and costly. In this paper we reported a multi-sensor system for high throughput phenotyping in plant breeding. The system comprised five sensor modules (ultrasonic distance sensors, thermal infrared radiometers, NDVI sensors, portable spectrometers, and RGB web cameras) to measure crop canopy traits from field plots. A GPS was used to geo-reference the sensor measurements. Two environmental sensors (a solar radiation sensor and air temperature/relative humidity sensor) were also integrated into the system to collect simultaneous environmental data. A LabVIEW program was developed to control and synchronize measurements from all sensor modules and stored sensor readings in the host computer. Canopy reflectance spectra (by portable spectrometers) were post processed to extract NDVI and red-edge NDVI spectral indices; and RGB images were post processed to extract canopy green pixel fraction (as a proxy for biomass). The sensor system was tested in a soybean and wheat field trial. The results showed strong correlations among the sensor-based plant traits at both early and late growing season. Significant correlations were also found between the sensor-based traits and final grain yield at the early season (Pearsons correlation coefficient r ranged from 0.41 to 0.55) and late season (r from 0.55 to 0.70), suggesting the potential use of the sensor system to assist in phenotypic selection for plant breeding. The sensor system performed satisfactorily and robustly in the field tests. It was concluded that the sensor system could be a powerful tool for plant breeders to collect field-based, high throughput plant phenotyping data.

Effect of dietary supplementation of soybeans on experimental metastasis of melanoma cells in mice.

The purpose of the present study was to determine the effect of dietary supplementation of soybean protein isolate (SPI) on experimental metastasis of B16BL6 murine melanoma cells in C57BL/6 mice. Four groups of mice were fed a basal AIN-93G diet or the basal diet supplemented with 10%, 15%, or 20% SPI for two weeks before and after the intravenous injection of 0.75 x 10(5) cells. At necropsy the number of tumors that developed in the lungs and their cross-sectional area were determined, and tumor volume was calculated. In the control group, 12 of the 15 mice had > or = 11 lung tumors. In contrast, only 3 or 4 of the 15 mice fed the SPI diets had > or = 11 tumors. The incidence of metastasis was 93%, 60%, 53%, and 53%, and the median number of lung tumors was 53, 2, 2, and 1 in mice fed the basal, 10%, 15%, and 20% SPI diets, respectively. Tumor cross-sectional area and tumor volume of SPI groups were significantly decreased compared with the controls. These results demonstrate that dietary supplementation of SPI reduced pulmonary metastasis of B16BL6 cells in mice and inhibited the growth of tumors that developed in the lungs. It is concluded that soybeans may be a useful adjuvant for preventing metastatic diseases in cancer patients.

Response of Soybean Cultivars to Bean pod mottle virus Infection

Bean pod mottle virus (BPMV) has become increasingly common in soybean throughout the north-central region of the United States. Yield loss assessments on southern soybean germplasm have reported reductions ranging from 3 to 52%. Currently, no soybean cultivars have been identified with resistance to BPMV. The objective of this study was to determine the impact of BPMV infection on soybean cultivars representing a broad range of northern soybean germ-plasm by comparing inoculated and noninoculated soybean plants in paired row studies. In all, 30 and 24 cultivars were evaluated in Nebraska (NE) in which soybean plants were inoculated at the V3 to V4 growth stage. Eleven cultivars from public and breeding lines were inoculated at the VC and R5 to R6 growth stages in Ohio (OH). Disease severity, yield, and percent seed coat mottling were assessed at both locations, whereas protein and oil content also were assessed at NE. Yield and percent seed coat mottling was significantly reduced following inoculation at the VC (OH) and V3 to V4 (NE) growth stages. In addition, seed oil and protein composition were impacted in 1 of the 2 years of the study. This study demonstrates that substantial yield losses can occur in soybean due to BPMV infection. In addition, protein and oil may be affected depending on the environment during the production season.

Effects of voluntary running and soy supplementation on diet-induced metabolic disturbance and inflammation in mice.

We investigated the effects of diet (AIN93G or high-fat), physical activity (sedentary or voluntary running), and protein source (casein or soy protein isolate (SPI)) and their interactions on metabolic disturbance and inflammation in mice. After 14 weeks of feeding, the high-fat diet increased body weight gain by 34.5% (p < 0.01), whereas running reduced weight gain by 30.5% (p < 0.01) compared to their respective AIN93G and sedentary controls; SPI did not affect weight gain. The high-fat diet significantly increased plasma concentrations of insulin, glucose, triglycerides, leptin, and monocyte chemotactic protein-1 (MCP-1); running and SPI significantly reduced these parameters compared to their respective controls. The high-fat diet significantly increased and running significantly reduced plasma plasminogen activator inhibitor-1. A unique finding was that SPI supplementation to the high-fat diet reduced plasma insulin by 11% (p < 0.05), MCP-1 by 21% (p = 0.03), and tumor necrosis factor-α (TNF-α) by 50% (p = 0.05) compared to casein. As adipose tissues produce many adipocytokines, including MCP-1 and TNF-α, that contribute to a state of chronic low grade systemic inflammation and facilitate metabolic disturbance in obesity, further investigations are warranted into the roles of soy protein in reducing the risk of obesity.