Novel genetic resources associated with sucrose and stachyose content through genome-wide association study in soybean (Glycine max (L.) Merr.)

The nutritional value of soybean [Glycine max (L.) Merr.] for animals is influenced by soluble carbohydrates, such as sucrose and stachyose. Although sucrose is nutritionally desirable, stachyose is an antinutrient causing diarrhea and flatulence in non-ruminant animals. We conducted a genome-wide association study of 220 soybean accessions using 21,317 single nucleotide polymorphisms (SNPs) from the SoySNP50K iSelect Beadchip data to identify significant SNPs associated with sucrose and stachyose content. Seven significant SNPs were identified for sucrose content across chromosomes (Chrs.) 2, 8, 12, 17, and 20, while thirteen significant SNPs were identified for stachyose content across Chrs. 2, 5, 8, 9, 10, 13, 14, and 15. Among those significant SNPs, three sucrose-related SNPs on Chrs. 8 and 17 were novel, while twelve stachyose-related SNPs on Chrs. 2, 5, 8, 9, 10, 13, 14, and 15 were novel. Based on Phytozome, STRING, and GO annotation, 17 and 24 candidate genes for sucrose and stachyose content, respectively, were highly associated with the carbohydrate metabolic pathway. Among these, the publicly available RNA-seq Atlas database highlighted four candidate genes associated with sucrose (Glyma.08g361200 and Glyma.17g258100) and stachyose (Glyma.05g025300 and Glyma.13g077900) content, which had higher gene expression levels in developing seed and multiple parts of the soybean plant. The results of this study will extend knowledge of the molecular mechanism and genetic basis underlying sucrose and stachyose content in soybean seed. Furthermore, the novel candidate genes and SNPs can be valuable genetic resources that soybean breeders may utilize to modify carbohydrate profiles for animal and human usage

The association between food environment, diet quality and malnutrition in low‐ and middle‐income adult populations across the rural—Urban gradient in Vietnam

Background: Economic reforms and trade liberalisation in Vaietnm have transformed the food environment, influencing dietary patterns and malnutrition status. The present study focuses on the relationship between food environments (proximity and density of food outlets) and malnutrition (underweight, overweight, obesity) through diet quality in adult populations across urban, periurban and rural areas of Vietnam. Methods: We evaluated food environment by geospatial mapping of food outlets through a transect walk across the “food ecosystem” from rural to urban areas. Diet quality was assessed using the Diet Quality Index – Vietnamese (DQI‐V) comprising Variety, Adequacy, Moderation and Balance components. Malnutrition status was determined using body mass index. We performed a mediation analysis utilising mixed effect models to control for neighbourhood clustering effects. Confounders included age, education, income and nutrition knowledge score. Results: Analysis of data from 595 adult participants (mean ± SD age: 31.2 ± 6.4 years; 50% female) found that longer distance to the nearest food outlet was associated with higher overall DQI‐V (β = 2.0; 95% confidence interval = 0.2–3.8; p = 0.036) and the Moderation component (β = 2.6; 95% confidence interval = 1.2–4.0; p = 0.001). Outlet density shows a negative association with the odds of underweight among women (odds ratio = 0.62; 95% confidence interval = 0.37–0.96). However, we did not observe statistically significant relationships between diet quality and malnutrition. Education and nutrition knowledge scores were positively associated with diet diversity, while income was negatively associated with diet moderation. Conclusions: The findings of the present study have important implications for nutrition and dietetics practice in Vietnam and globally. It emphasises the need to consider various dimensions of sustainable diets, including economic, health and socio‐cultural/political factors. Longer distances to food outlets are associated with higher diet quality, whereas lower food outlet density increases the odds of underweight among women. This poses challenges in balancing modernisation and its adverse effects on sustainable food systems. Socio‐economic status consistently correlated with diet quality and malnutrition, necessitating further research to promote healthy diets across socio‐economic strata

Selection of a core set of RILs from Forrest × Williams 82 to develop a framework map in soybean

Soybean BAC-based physical maps provide a useful platform for gene and QTL map-based cloning, EST mapping, marker development, genome sequencing, and comparative genomic research. Soybean physical maps for “Forrest” and “Williams 82” representing the southern and northern US soybean germplasm base, respectively, have been constructed with different fingerprinting methods. These physical maps are complementary for coverage of gaps on the 20 soybean linkage groups. More than 5,000 genetic markers have been anchored onto the Williams 82 physical map, but only a limited number of markers have been anchored to the Forrest physical map. A mapping population of Forrest × Williams 82 made up of 1,025 F8 recombinant inbred lines (RILs) was used to construct a reference genetic map. A framework map with almost 1,000 genetic markers was constructed using a core set of these RILs. The core set of the population was evaluated with the theoretical population using equality, symmetry and representativeness tests. A high-resolution genetic map will allow integration and utilization of the physical maps to target QTL regions of interest, and to place a larger number of markers into a map in a more efficient way using a core set of RILs

Evaluation of Resistance Screening Methods for Sclerotinia Stem Rot of Soybean and Dry Bean

Three methods to identify levels of resistance to Sclerotinia sclerotiorum in soybean (Glycine max) and dry bean (Phaseolus vulgaris) were compared using multiple data analyses. The three methods were mycelial plug inoculations of cotyledons, cut stems, and detached leaves. Six S. sclerotiorum isolates of known relative aggressiveness were inoculated on each of three soybean and dry bean cultivars with varied response to S. sclerotiorum. For soybean, all three inoculation methods accurately identified isolate aggressiveness irrespective of cultivar, but identification of susceptible and partially resistant soybean cultivars was influenced by isolate. For dry bean, the cotyledon and cut stem methods accurately identified isolate aggressiveness, but identification of susceptible and partially resistant dry bean cultivars was influenced by isolate and inoculation method. The cut stem method had the smallest coefficient of variation and was more precise for detecting interactions. When considering root mean square residual error combined over species and experiments, coefficient of variation based on residual error, significance of isolate-by-cultivar interaction from ANOVA, rank correlation between pairs of methods, and sensitivity ratio for the three resistance screening methods under controlled environmental conditions, the cut stem method was statistically better than the cotyledon and detached leaf methods for evaluating resistance in soybean and dry bean cultivars

Molecular Characterization of Resistance to Soybean Rust (\u3ci\u3ePhakopsora pachyrhizi\u3c/i\u3e Syd. & Syd.) in Soybean Cultivar DT 2000 (PI 635999)

Resistance to soybean rust (SBR), caused by Phakopsora pachyrhizi Syd. & Syd., has been identified in many soybean germplasm accessions and is conferred by either dominant or recessive genes that have been mapped to six independent loci (Rpp1 -Rpp6), but No U. S. cultivars are resistant to SBR. The cultivar DT 2000 (PI 635999) has resistance to P. pachyrhizi isolates and field populations from the United States as well as Vietnam. A F6:7 recombinant inbred line (RIL) population derived from Williams 82 × DT 2000 was used to identify genomic regions associated with resistance to SBR in the field in Ha Noi, Vietnam, and in Quincy, Florida, in 2008. Bulked segregant analysis (BSA) was conducted using the soybean single nucleotide polymorphism (SNP) USLP 1.0 panel along with simple sequence repeat (SSR) markers to detect regions of the genome associated with resistance. BSA identified four BARC_SNP markers near the Rpp3 locus on chromosome (Chr.) 6. Genetic analysis identified an additional genomic region around the Rpp4 locus on Chr. 18 that was significantly associated with variation in the area under disease progress curve (AUDPC) values and sporulation in Vietnam. Molecular markers tightly linked to the DT 2000 resistance alleles on Chrs. 6 and 18 will be useful for marker-assisted selection and backcrossing in order to pyramid these genes with other available SBR resistance genes to develop new varieties with enhanced and durable resistance to SBR

Identification of Novel QTL Governing Root Architectural Traits in an Interspecific Soybean Population

Cultivated soybean (Glycine max L.) cv. Dunbar (PI 552538) and wild G. soja (PI 326582A) exhibited significant differences in root architecture and root-related traits. In this study, phenotypic variability for root traits among 251 BC2F5 backcross inbred lines (BILs) developed from the cross Dunbar/PI 326582A were identified. The root systems of the parents and BILs were evaluated in controlled environmental conditions using a cone system at seedling stage. The G. max parent Dunbar contributed phenotypically favorable alleles at a major quantitative trait locus on chromosome 8 (Satt315-I locus) that governed root traits (tap root length and lateral root number) and shoot length. This QTL accounted for \u3e10% of the phenotypic variation of both tap root and shoot length. This QTL region was found to control various shoot- and root-related traits across soybean genetic backgrounds. Within the confidence interval of this region, eleven transcription factors (TFs) were identified. Based on RNA sequencing and Affymetrix expression data, key TFs including MYB, AP2-EREBP and bZIP TFs were identified in this QTL interval with high expression in roots and nodules. The backcross inbred lines with different parental allelic combination showed different expression pattern for six transcription factors selected based on their expression pattern in root tissues. It appears that the marker interval Satt315–I locus on chromosome 8 contain an essential QTL contributing to early root and shoot growth in soybean

Identification of new loci for salt tolerance in soybean by high-resolution genome-wide association mapping

Abstract Background Salinity is an abiotic stress that negatively affects soybean [Glycine max (L.) Merr.] seed yield. Although a major gene for salt tolerance was identified and consistently mapped to chromosome (Chr.) 3 by linkage mapping studies, it does not fully explain genetic variability for tolerance in soybean germplasm. In this study, a genome-wide association study (GWAS) was performed to map genomic regions for salt tolerance in a diverse panel of 305 soybean accessions using a single nucleotide polymorphism (SNP) dataset derived from the SoySNP50K iSelect BeadChip. A second GWAS was also conducted in a subset of 234 accessions using another 3.7 M SNP dataset derived from a whole-genome resequencing (WGRS) study. In addition, three gene-based markers (GBM) of the known gene, Glyma03g32900, on Chr. 3 were also integrated into the two datasets. Salt tolerance among soybean lines was evaluated by leaf scorch score (LSS), chlorophyll content ratio (CCR), leaf sodium content (LSC), and leaf chloride content (LCC). Results For both association studies, a major locus for salt tolerance on Chr. 3 was confirmed by a number of significant SNPs, of which three gene-based SNP markers, Salt-20, Salt14056 and Salt11655, had the highest association with all four traits studied. Also, additional genomic regions on Chrs. 1, 8, and 18 were found to be associated with various traits measured in the second GWAS using the WGRS-derived SNP dataset. Conclusions A region identified on Chr. 8 was identified to be associated with all four traits and predicted as a new minor locus for salt tolerance in soybean. The candidate genes harbored in this minor locus may help reveal the molecular mechanism involved in salt tolerance and to improve tolerance in soybean cultivars. The significant SNPs will be useful for marker-assisted selection for salt tolerance in soybean breeding programs

Expanding omics resources for improvement of soybean seed composition traits

Food resources of the modern world are strained due to the increasing population. There is an urgent need for innovative methods and approaches to augment food production. Legume seeds are major resources of human food and animal feed with their unique nutrient compositions including oil, protein, carbohydrates, and other beneficial nutrients. Recent advances in next-generation sequencing (NGS) together with ‘omics’ technologies have considerably strengthened soybean research. The availability of well annotated soybean genome sequence along with hundreds of identified quantitative trait loci (QTL) associated with different seed traits can be used for gene discovery and molecular marker development for breeding applications. Despite the remarkable progress in these technologies, the analysis and mining of existing seed genomics data are still challenging due to the complexity of genetic inheritance, metabolic partitioning, and developmental regulations. Integration of ‘omics tools’ is an effective strategy to discover key regulators of various seed traits. In this review, recent advances in ‘omics’ approaches and their use in soybean seed trait investigations are presented along with the available databases and technological platforms and their applicability in the improvement of soybean. This article also highlights the use of modern breeding approaches, such as genome-wide association studies (GWAS), genomic selection (GS), and marker-assisted recurrent selection (MARS) for developing superior cultivars. A catalog of available important resources for major seed composition traits, such as seed oil, protein, carbohydrates, and yield traits are provided to improve the knowledge base and future utilization of this information in the soybean crop improvement programs