Selective Genotyping and Phenotyping for Optimization of Genomic Prediction Models for Populations with Different Diversity.

To overcome the different challenges to food security caused by a growing population and climate change, soybean (Glycine max (L.) Merr.) breeders are creating novel cultivars that have the potential to improve productivity while maintaining environmental sustainability. Genomic selection (GS) is an advanced approach that may accelerate the rate of genetic gain in breeding using genome-wide molecular markers. The accuracy of genomic selection can be affected by trait architecture and heritability, marker density, linkage disequilibrium, statistical models, and training set. The selection of a minimal and optimal marker set with high prediction accuracy can lower genotyping costs, computational time, and multicollinearity. Selective phenotyping could reduce the number of genotypes tested in the field while preserving the genetic diversity of the initial population. This study aimed to evaluate different methods of selective genotyping and phenotyping on the accuracy of genomic prediction for soybean yield. The evaluation was performed on three populations: recombinant inbred lines, multifamily diverse lines, and germplasm collection. Strategies adopted for marker selection were as follows: SNP (single nucleotide polymorphism) pruning, estimation of marker effects, randomly selected markers, and genome-wide association study. Reduction of the number of genotypes was performed by selecting a core set from the initial population based on marker data, yet maintaining the original population's genetic diversity. Prediction ability using all markers and genotypes was different among examined populations. The subsets obtained by the model-based strategy can be considered the most suitable for marker selection for all populations. The selective phenotyping based on makers in all cases had higher values of prediction ability compared to minimal values of prediction ability of multiple cycles of random selection, with the highest values of prediction obtained using AN approach and 75% population size. The obtained results indicate that selective genotyping and phenotyping hold great potential and can be integrated as tools for improving or retaining selection accuracy by reducing genotyping or phenotyping costs for genomic selection.

High-throughput phenotyping for non-destructive estimation of soybean fresh biomass using a machine learning model and temporal UAV data.

BACKGROUND: Biomass accumulation as a growth indicator can be significant in achieving high and stable soybean yields. More robust genotypes have a better potential for exploiting available resources such as water or sunlight. Biomass data implemented as a new trait in soybean breeding programs could be beneficial in the selection of varieties that are more competitive against weeds and have better radiation use efficiency. The standard techniques for biomass determination are invasive, inefficient, and restricted to one-time point per plot. Machine learning models (MLMs) based on the multispectral (MS) images were created so as to overcome these issues and provide a non-destructive, fast, and accurate tool for in-season estimation of soybean fresh biomass (FB). The MS photos were taken during two growing seasons of 10 soybean varieties, using six-sensor digital camera mounted on the unmanned aerial vehicle (UAV). For model calibration, canopy cover (CC), plant height (PH), and 31 vegetation index (VI) were extracted from the images and used as predictors in the random forest (RF) and partial least squares regression (PLSR) algorithm. To create a more efficient model, highly correlated VIs were excluded and only the triangular greenness index (TGI) and green chlorophyll index (GCI) remained. RESULTS: More precise results with a lower mean absolute error (MAE) were obtained with RF (MAE = 0.17 kg/m2) compared to the PLSR (MAE = 0.20 kg/m2). High accuracy in the prediction of soybean FB was achieved using only four predictors (CC, PH and two VIs). The selected model was additionally tested in a two-year trial on an independent set of soybean genotypes in drought simulation environments. The results showed that soybean grown under drought conditions accumulated less biomass than the control, which was expected due to the limited resources. CONCLUSION: The research proved that soybean FB could be successfully predicted using UAV photos and MLM. The filtration of highly correlated variables reduced the final number of predictors, improving the efficiency of remote biomass estimation. The additional testing conducted in the independent environment proved that model is capable to distinguish different values of soybean FB as a consequence of drought. Assessed variability in FB indicates the robustness and effectiveness of the proposed model, as a novel tool for the non-destructive estimation of soybean FB.

Lipidomics-Assisted GWAS (lGWAS) Approach for Improving High-Temperature Stress Tolerance of Crops.

High-temperature stress (HT) over crop productivity is an important environmental factor demanding more attention as recent global warming trends are alarming and pose a potential threat to crop production. According to the Sixth IPCC report, future years will have longer warm seasons and frequent heat waves. Thus, the need arises to develop HT-tolerant genotypes that can be used to breed high-yielding crops. Several physiological, biochemical, and molecular alterations are orchestrated in providing HT tolerance to a genotype. One mechanism to counter HT is overcoming high-temperature-induced membrane superfluidity and structural disorganizations. Several HT lipidomic studies on different genotypes have indicated the potential involvement of membrane lipid remodelling in providing HT tolerance. Advances in high-throughput analytical techniques such as tandem mass spectrometry have paved the way for large-scale identification and quantification of the enormously diverse lipid molecules in a single run. Physiological trait-based breeding has been employed so far to identify and select HT tolerant genotypes but has several disadvantages, such as the genotype-phenotype gap affecting the efficiency of identifying the underlying genetic association. Tolerant genotypes maintain a high photosynthetic rate, stable membranes, and membrane-associated mechanisms. In this context, studying the HT-induced membrane lipid remodelling, resultant of several up-/down-regulations of genes and post-translational modifications, will aid in identifying potential lipid biomarkers for HT tolerance/susceptibility. The identified lipid biomarkers (LIPIDOTYPE) can thus be considered an intermediate phenotype, bridging the gap between genotype-phenotype (genotype-LIPIDOTYPE-phenotype). Recent works integrating metabolomics with quantitative genetic studies such as GWAS (mGWAS) have provided close associations between genotype, metabolites, and stress-tolerant phenotypes. This review has been sculpted to provide a potential workflow that combines MS-based lipidomics and the robust GWAS (lipidomics assisted GWAS-lGWAS) to identify membrane lipid remodelling related genes and associations which can be used to develop HS tolerant genotypes with enhanced membrane thermostability (MTS) and heat stable photosynthesis (HP).

Genomics Associated Interventions for Heat Stress Tolerance in Cool Season Adapted Grain Legumes.

Cool season grain legumes occupy an important place among the agricultural crops and essentially provide multiple benefits including food supply, nutrition security, soil fertility improvement and revenue for farmers all over the world. However, owing to climate change, the average temperature is steadily rising, which negatively affects crop performance and limits their yield. Terminal heat stress that mainly occurred during grain development phases severely harms grain quality and weight in legumes adapted to the cool season, such as lentils, faba beans, chickpeas, field peas, etc. Although, traditional breeding approaches with advanced screening procedures have been employed to identify heat tolerant legume cultivars. Unfortunately, traditional breeding pipelines alone are no longer enough to meet global demands. Genomics-assisted interventions including new-generation sequencing technologies and genotyping platforms have facilitated the development of high-resolution molecular maps, QTL/gene discovery and marker-assisted introgression, thereby improving the efficiency in legumes breeding to develop stress-resilient varieties. Based on the current scenario, we attempted to review the intervention of genomics to decipher different components of tolerance to heat stress and future possibilities of using newly developed genomics-based interventions in cool season adapted grain legumes.

Author Correction: Increase of isoflavones in the aglycone form in soybeans by targeted crossings of cultivated breeding material.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Increase of isoflavones in the aglycone form in soybeans by targeted crossings of cultivated breeding material.

Isoflavones are a group of phytoestrogens, naturally-occurring substances important for their role in human health. Legumes, particularly soybeans (Glycine max (L.) Merr.), are the richest source of isoflavones in human diet. Since there is not much current data on genetics of isoflavones in soybean, particularly in the aglycone form, elucidation of the mode of inheritance is necessary in order to design an efficient breeding strategy for the development of high-isoflavone soybean genotypes. Based on the isoflavone content in 23 samples of soybeans from four different maturity groups (00, 0, I and II), three crosses were made in order to determine the inheritance pattern and increase the content of total isoflavones and their aglycone form. Genotype with the lowest total isoflavone content (NS-L-146) was crossed with the low- (NS Zenit), medium (NS Maximus), and high- (NS Virtus) isoflavone genotypes. There were no significant differences in the total isoflavone content (TIF) between F2 populations, and there was no transgression among genotypes within the populations. Each genotype within all three populations had a higher TIF value than the lower parent (NS-L-146), while genotypes with a higher TIF value than the better parent were found only in the NS-L-146 × NS Zenit cross. However, significant differences in the aglycone ratio (ratio of aglycone to glycone form of isoflavones) were found between the populations. The highest aglycone ratio was found in the NS-L-146 × NS Maximus cross. The results indicate that the genetic improvement for the trait is possible.

Allelic Variation and Distribution of the Major Maturity Genes in Different Soybean Collections.

Soybean time of flowering and maturity are genetically controlled by E genes. Different allelic combinations of these genes determine soybean adaptation to a specific latitude. The paper describes the first attempt to assess adaptation of soybean genotypes developed and realized at Institute of Field and Vegetable Crops, Novi Sad, Serbia [Novi Sad (NS) varieties and breeding lines] based on E gene variation, as well as to comparatively assess E gene variation in North-American (NA), Chinese, and European genotypes, as most of the studies published so far deal with North-American and Chinese cultivars and breeding material. Allelic variation and distribution of the major maturity genes (E1, E2, E3, and E4) has been determined in 445 genotypes from soybean collections of NA ancestral lines, Chinese germplasm, and European varieties, as well as NS varieties and breeding lines. The study showed that allelic combinations of E1-E4 genes significantly determined the adaptation of varieties to different geographical regions, although they have different impacts on maturity. In general, each collection had one major E genotype haplogroup, comprising over 50% of the lines. The exceptions were European varieties that had two predominant haplogroups and NA ancestral lines distributed almost evenly among several haplogroups. As e1-as/e2/E3/E4 was the most common genotype in NS population, present in the best-performing genotypes in terms of yield, this specific allele combination was proposed as the optimal combination for the environments of Central-Eastern Europe.

Polyphenol content and antioxidant properties of colored soybean seeds from central Europe.

The antioxidant activity and contents of various polyphenol classes in the seeds of seven soybean varieties of different seed color and one yellow seed cultivar, representing a reference genotype, were evaluated. Total polyphenols and tannins were determined after extraction of plant material with 70% aqueous acetone, and total flavonoids were extracted with methanol and acetic acid, whereas anthocyanins were extracted with 20% aqueous ethanol. In addition, isoflavone content and composition were determined using high-performance liquid chromatography analysis. Antioxidant activity of seed extracts was evaluated by the 2,2-diphenyl-1-picrylhydrazyl free radical scavenging activity assay. A positive linear correlation between antioxidant activity and contents of total polyphenols and anthocyanins was established. The highest antioxidant activity was observed in the extracts of black and brown varieties, which also showed high levels of all polyphenol classes examined. Yellow seed had the highest total isoflavone content (3.62 mg/g of dry material). The highest concentration of total daidzein was determined in black seeds (>2.0 mg/g of dry material), and the highest total glycitein and genistein contents occurred in the yellow cultivar (0.53 and 1.49 mg/g of dry material, respectively). According to our results, varieties of black and brown seeds could be of special interest not only for their large content of total polyphenols, ranging from 4.94 to 6.22 mg of gallic acid equivalents/g of dry material, but also for their high content of natural antioxidants such as anthocyanins.

Changes in antioxidant systems in soybean as affected by Sclerotinia sclerotiorum (Lib.) de Bary.

Changes in antioxidant systems in soybean [Glycine max (L.) Merr., Fabaceae] genotypes infected with Sclerotinia sclerotiorum were studied 12, 24, 48 and 72h after inoculation. Generation of superoxide and hydroxyl radicals was evaluated together with the production of malonyldialdehyde, main end product of lipid peroxidation. Several enzymatic and non-enzymatic parameters were monitored as well, such as the activity of antioxidant enzymes superoxide dismutase and pyrogallol and guaiacol peroxidases, reduced glutathione, soluble proteins and total carotenoids content. Results showed that genotypes expressed oxidative burst as well as different antioxidant systems in response to biotic stress caused by pathogen invasion. It has been confirmed that, although hypersensitive cell death is efficient against biotrophic pathogens, it does not protect soybean plants against infection by the necrotrophic pathogen such as S. sclerotiorum. Still, some genotypes showed distinctive and combined activity of several biochemical parameters which may point to further directions in exploring host-pathogen relations and lead to selection and production of new genotypes with higher levels of tolerance.

Isoflavone composition, total polyphenolic content, and antioxidant activity in soybeans of different origin.

Twenty soybean cultivars, originating from the United States, Russia, Serbia, and China, were analyzed for their isoflavone composition, total polyphenolic content, and antioxidant activity. Isoflavones were extracted by aqueous methanol (80%) and analyzed by high-performance liquid chromatography/diode array detection. Precision and linearity of the applied method were within the standard limits of validation. The highest and the lowest total isoflavone contents were 4.59 and 1.45 mg/g of dried soybean weight, respectively. A significant difference (P < .05) was found in isoflavone concentration among the different cultivars, but it was observed that origin is not a significant factor that could influence isoflavone content in soybeans. Total polyphenolic content varied between 2.13 and 3.45 mg of gallic acid equivalents/g of dried soybean weight. The free radical scavenging activity of soybean extracts assayed by 2,2-diphenyl-1-picrylhydrazyl in terms of 50% inhibitory concentration (IC(50)) ranged from 1.40 to 3.35 mg/mL. Negative correlation between total polyphenolic content and IC(50) was observed, but there was no correlation between total isoflavone content and IC(50). On the basis of this study, soybean cultivars with larger potency for biological activity could be recognized.

Determination of phytoestrogen composition in soybean cultivars in Serbia.

The growing clinical interest and use of soybean-based food products and extracts to increase dietary phytoestrogen intake have led to medical interest in the precise determination of the phytoestrogen composition of soybean products. We have analyzed the composition of these compounds in 20 domestic and introduced varieties of genetically non-modified soybean genotypes grown under the same agroecological conditions. The isoflavone content of soybeans cultivated in this region of Serbia has not been previously reported. The assays were performed, after extraction with methanol-water (8:2, v/v), by C18 reversed phase high-performance liquid chromatography coupled with photodiode array detection. The total phytoestrogen concentration was found to be between 2.24 and 3.79 mg g(-1) dry bean weight. The total concentration of daidzein and its derivatives ranged from 0.96 to 1.82 mg g(-1), total glyciteines from 0.34-0.53 mg g(-1), and all genistein derivatives from 0.86-1.67 mg g(-1) dry bean weight. Given the high biological potency of phytoestrogens and their metabolic conversion products, our data suggest that phytoestrogen content screening could be a useful tool in the selection of soybean genotypes with improved health promoting characteristics.

Polyphenol contents and antioxidant activity of soybean seed extracts.

The antioxidant activity and contents of various polyphenol classes in the seeds of 20 soybean hybrids were evaluated. Total polyphenols, tannins and proanthocyanidins were determined after extraction of plant material with 70% aqueous acetone. In addition, flavonoid content was determined. Antioxidant activity of seed extracts was evaluated by DPPH free radical scavenging activity assay. A positive linear correlation between antioxidant activity and contents of total phenols, tannins and proanthocyanidins was established. The highest antioxidant activity was observed in the extracts of hybrids which have higher levels of all polyphenol classes examined. The most of the single-cross hybrids were poor in tannins which recommend them as good source for ensiled livestock feed. Results suggested that polyphenol content should be considered as an important feature of the soybean seed.

Phenolic content and antioxidant properties of soybean (Glycine max (L.) Merr.) seeds.

The contents and antioxidant ability of various classes of phenolic compounds present in the seeds of twenty soybean hybrids were evaluated. Total phenolics, tannins and proanthocyanidins were determined spectrophotometrically, after extraction of seeds with 70% aqueous acetone. In addition, the flavonoid contents were determined. The antioxidant activity of aqueous acetone extracts was evaluated by the 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical scavenging activity assay. The highest contents of total phenolics were found in Serbian cultivar 1511 and Chinese cultivar LN92-7369, which also displayed the highest total antioxidant activity. Conversely, genotypes poor in phenolics also showed low levels of DPPH-radical scavenging activity. The results suggested that besides protein and oil contents, the phenolic contents should be also considered as an important characteristic feature of soybean seeds, and as a potential selection criterion for antioxidant activity in soybean.

Evaluation of nonstarch polysaccharides and oligosaccharide content of different soybean varieties (Glycine max) by near-infrared spectroscopy and proteomics.

A total of 832 samples of soybeans were screened by near-infrared (NIR) reflectance spectroscopy, to identify soybean samples with a lower content of oligosaccharides and nonstarch polysaccharides (NSP). Of these, 38 samples were identified on the basis of variation in protein content and agronomic value and submitted to high-resolution NIR spectroscopy. On the basis of the NIR data, 12 samples were further selected for chromatographic characterization of carbohydrate composition (mono-, di-, and oligosaccharides and NSP). Their soluble proteins were separated by two-dimensional gel electrophoresis (2DE). Using partial least-squares regression (PLSR), it was possible to predict the content of total NSP from the high-resolution NIR spectra, suggesting that NIR is a suitable and rapid nondestructive method to determine carbohydrate composition in soybeans. The 2DE analyses showed varying intensities of several proteins, including the glycinin G1 precursor. PLSR analysis showed a negative correlation between this protein and insoluble NSP and total uronic acid (UA).