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Cinnamate 4-hydroxylase (C4H) is the first key cytochrome P450 monooxygenase (P450) enzyme in the phenylpropanoid pathway. It belongs to the CYP73 family of P450 superfamily, and catalyzes the conversion of trans -cinnamic acid to p -coumaric acid. Since p -coumaric acid serves as the precursor for the synthesis of a wide variety of metabolites involved in plant development and stress resistance, alteration in the expression of soybean C4H genes is expected to affect the downstream metabolite levels, and its ability to respond to stress. In this study, we identified four C4H genes in the soybean genome that are distributed into both class I and class II CYP73 family. GmC4H2 , GmC4H14 and GmC4H20 displayed tissue- and developmental stage-specific gene expression patterns with their transcript accumulation at the highest level in root tissues. GmC4H10 appears to be a pseudogene as its transcript was not detected in any soybean tissues. Furthermore, protein homology modelling revealed substrate docking only for GmC4H2, GmC4H14 and GmC4H20. To demonstrate the function of GmC4Hs, we modified a cloning vector for the heterologous expression of P450s in yeast, and used it for microsomal protein production and enzyme assay. Our results confirmed that GmC4H2, GmC4H14 and GmC4H20 contain the ability to hydroxylate trans -cinnamic acid with varying efficiencies.

Genome-wide association study (GWAS) has emerged in the past decade as a viable tool for identifying beneficial alleles from a genomic diversity panel. In an ongoing effort to improve soybean [ Glycine max (L.) Merr.], which is the third largest field crop in Canada, a GWAS was conducted to identify novel alleles underlying seed yield and seed quality and agronomic traits. The genomic panel consisted of 200 genotypes including lines derived from several generations of bi-parental crosses between modern Canadian × Chinese cultivars (CD-CH). The genomic diversity panel was field evaluated at two field locations in Ontario in 2019 and 2020. Genotyping-by-sequencing (GBS) was conducted and yielded almost 32 K high-quality SNPs. GWAS was conducted using Fixed and random model Circulating Probability Unification (FarmCPU) model on the following traits: seed yield, seed protein concentration, seed oil concentration, plant height, 100 seed weight, days to maturity, and lodging score that allowed to identify five QTL regions controlling seed yield and seed oil and protein content. A candidate gene search identified a putative gene for each of the three traits. The results of this GWAS study provide insight into potentially valuable genetic resources residing in Chinese modern cultivars that breeders may use to further improve soybean seed yield and seed quality traits.

Type I Diacylglycerol acyltransferase (DGAT1) catalyzes the final step of the biosynthesis process of triacylglycerol (TAG), the major storage lipids in plant seeds, through the esterification of diacylglycerol (DAG). To characterize the function of DGAT1 genes on the accumulation of oil and other seed composition traits in soybean, transgenic lines were generated via trans-acting siRNA technology, in which three DGAT1 genes (Glyma.13G106100, Glyma.09G065300, and Glyma.17G053300) were downregulated. The simultaneous downregulation of the three isoforms in transgenic lines was found to be associated with the reduction of seed oil concentrations by up to 18 mg/g (8.3%), which was correlated with increases in seed protein concentration up to 42 mg/g (11%). Additionally, the downregulations also influenced the fatty acid compositions in the seeds of transgenic lines through increasing the level of oleic acid, up to 121 mg/g (47.3%). The results of this study illustrate the importance of DGAT1 genes in determining the seed compositions in soybean through the development of new potential technology for manipulating seed quality in soybean to meet the demands for its various food and industrial applications.

In conjunction with big data analysis methods, plant omics technologies have provided scientists with cost-effective and promising tools for discovering genetic architectures of complex agronomic traits using large breeding populations. In recent years, there has been significant progress in plant phenomics and genomics approaches for generating reliable large datasets. However, selecting an appropriate data integration and analysis method to improve the efficiency of phenome-phenome and phenome-genome association studies is still a bottleneck. This study proposes a hyperspectral wide association study (HypWAS) approach as a phenome-phenome association analysis through a hierarchical data integration strategy to estimate the prediction power of hyperspectral reflectance bands in predicting soybean seed yield. Using HypWAS, five important hyperspectral reflectance bands in visible, red-edge, and near-infrared regions were identified significantly associated with seed yield. The phenome-genome association analysis of each tested hyperspectral reflectance band was performed using two conventional genome-wide association studies (GWAS) methods and a machine learning mediated GWAS based on the support vector regression (SVR) method. Using SVR-mediated GWAS, more relevant QTL with the physiological background of the tested hyperspectral reflectance bands were detected, supported by the functional annotation of candidate gene analyses. The results of this study have indicated the advantages of using hierarchical data integration strategy and advanced mathematical methods coupled with phenome-phenome and phenome-genome association analyses for a better understanding of the biology and genetic backgrounds of hyperspectral reflectance bands affecting soybean yield formation. The identified yield-related hyperspectral reflectance bands using HypWAS can be used as indirect selection criteria for selecting superior genotypes with improved yield genetic gains in large breeding populations.

Cytochrome P450 monooxygenases (P450) participate in the catalytic conversion of biological compounds in a plethora of metabolic pathways, such as the biosynthesis of alkaloids, terpenoids, phenylpropanoids, and hormones in plants. Plants utilize these metabolites for growth and defense against biotic and abiotic stress. In this study, we identified 346 P450 (GmP450) enzymes encoded by 317 genes in soybean where 26 GmP450 genes produced splice variants. The genome-wide comparison of both A-type and non-A-type GmP450s for their motifs composition, gene structure, tissue-specific expression, and their chromosomal distribution were determined. Even though conserved P450 signature motifs were found in all GmP450 families, larger variation within a specific motif was observed in the non-A-type GmP450s as compared with the A-type. Here, we report that the length of variable region between two conserved motifs is exact in the members of the same family in majority of the A-type GmP450. Analyses of the transcriptomic datasets from soybean- Phytophthora sojae interaction studies, quantitative trait loci (QTL) associated with P. sojae resistance, and co-expression analysis identified some GmP450s that may be, in part, play an important role in partial resistance against P. sojae. The findings of our CYPome study provides novel insights into the functions of GmP450s and their involvements in metabolic pathways in soybean. Further experiments will elucidate their roles in general and legume-specific function.

Drought stress significantly limits soybean [ Glycine max (L.) Merr.] yields in Ontario, Canada. Many studies of genetic variation for drought tolerance compare commercial lines with exotic, unadapted germplasm. We hypothesized that even current commercial cultivars adapted to Ontario would differ significantly for traits related to drought tolerance. In a greenhouse experiment, we grew fifteen soybean cultivars in field soil amended with sand in 1-m rooting columns, which allowed for simulation of field-like soil water profiles and rooting depths. Two watering treatments were imposed from the first flower until maturity by daily restoration of soil water to either 100% (control), or 50% (drought stress) of the maximum soil water holding capacity. Throughout the experiment, we measured volumetric soil water content at different depths in the soil profile, but found no evidence at any developmental stage that the cultivars differed for their ability to extract soil water from different depths. Drought stress reduced seed yield by 51% on average. Similar to the effects of drought in the field, pod number was the yield component most affected, with effects on seeds per pod and single-seed weight being comparatively minor. There were significant cultivar × treatment interactions for seed yield, pod number, shoot dry matter, and water use. We identified two drought-sensitive ( Saska and OAC Drayton ) and three drought-tolerant ( OAC Lakeview , OAC Champion , and PRO 2715R ) cultivars based on their ratios of seed yield under drought stress to seed yield under control conditions (seed yield ratio, SYR). Regression and principal component analyses revealed that drought-tolerant (high-SYR) cultivars were consistently those that maintained relatively high values for water use, biomass accumulation and pod number under drought stress; high water use efficiency under drought stress was also associated with a high SYR. One of the cultivars, OAC Lakeview , displayed a distinct mode of drought tolerance, maintaining a very high fraction of its control pod number under drought stress. This study helps define the physiological basis of soybean cultivar differences in drought tolerance, and provides direction for soybean breeders to select traits that could improve yield under drought stress.

Key messageSignificant QTL for sucrose concentration have been identified using a historical soybean genomic panel, which could aid in the development of food-grade soybean cultivars.Soybean (Glycine max (L.) Merr) is a crop of global importance for both human and animal consumption, which was domesticated in China more than 6000 years ago. A concern about losing genetic diversity as a result of decades of breeding has been expressed by soybean researchers. In order to develop new cultivars, it is critical for breeders to understand the genetic variability present for traits of interest in their program germplasm. Sucrose concentration is becoming an increasingly important trait for the production of soy-food products. The objective of this study was to use a genome-wide association study (GWAS) to identify putative QTL for sucrose concentration in soybean seed. A GWAS panel consisting of 266 historic and current soybean accessions was genotyped with 76 k genotype-by-sequencing (GBS) SNP data and phenotyped in four field locations in Ontario (Canada) from 2015 to 2017. Seven putative QTL were identified on chromosomes 1, 6, 8, 9, 10, 13 and 14. A key gene related to sucrose synthase (Glyma.06g182700) was found to be associated with the QTL located on chromosome 6. This information will facilitate efforts to increase the available genetic variability for sucrose concentration in soybean breeding programs and develop new and improved high-sucrose soybean cultivars suitable for the soy-food industry.

Multi-Parent Advanced Generation Inter-Cross (MAGIC) populations are emerging genetic platforms for high-resolution and fine mapping of quantitative traits, such as agronomic and seed composition traits in soybean ( Glycine max L.). We have established an eight-parent MAGIC population, comprising 721 recombinant inbred lines (RILs), through conical inter-mating of eight soybean lines. The parental lines were genetically diverse elite cultivars carrying different agronomic and seed composition characteristics, including amino acids and fatty acids, as well as oil and protein concentrations. This study aimed to introduce soybean MAGIC (SoyMAGIC) population as an unprecedented platform for genotypic and phenotypic investigation of agronomic and seed quality traits in soybean. The RILs were evaluated for important seed composition traits using replicated field trials during 2020 and 2021. To measure the seed composition traits, near-infrared reflectance (NIR) was employed. The RILs were genotyped using genotyping-by-sequencing (GBS) method to decipher the genome and discover single-nucleotide polymorphic (SNP) markers among the RILs. A high-density linkage map was constructed through inclusive composite interval mapping (ICIM). The linkage map was 3,770.75 cM in length and contained 12,007 SNP markers. Chromosomes 11 and 18 were recorded as the shortest and longest linkage groups with 71.01 and 341.15 cM in length, respectively. Observed transgressive segregation of the selected traits and higher recombination frequency across the genome confirmed the capability of MAGIC population in reshuffling the diversity in the soybean genome among the RILs. The assessment of haplotype blocks indicated an uneven distribution of the parents’ genomes in RILs, suggesting cryptic influence against or in favor of certain parental genomes. The SoyMAGIC population is a recombined genetic material that will accelerate further genomic studies and the development of soybean cultivars with improved seed quality traits through the development and implementation of reliable molecular-based toolkits.

Breeding apples is a long-term endeavour and it is imperative that new cultivars are selected to have outstanding consumer appeal. This study has taken the approach of merging sensory science with genome wide association analyses in order to map the human perception of apple flavour and texture onto the apple genome. The goal was to identify genomic associations that could be used in breeding apples for improved fruit quality. A collection of 85 apple cultivars was examined over two years through descriptive sensory evaluation by a trained sensory panel. The trained sensory panel scored randomized sliced samples of each apple cultivar for seventeen taste, flavour and texture attributes using controlled sensory evaluation practices. In addition, the apple collection was subjected to genotyping by sequencing for marker discovery. A genome wide association analysis suggested significant genomic associations for several sensory traits including juiciness, crispness, mealiness and fresh green apple flavour. The findings include previously unreported genomic regions that could be used in apple breeding and suggest that similar sensory association mapping methods could be applied in other plants.