Quantitative trait loci controlling sulfur containing amino acids, methionine and cysteine, in soybean seeds

Elemental sulfur concentration can be used as a rapid, reliable, and cost-effective predictor of sulfur amino acid content of soybean seeds

In this study, we have examined the feasibility of using elemental sulfur content of soybean seeds as a proxy for the overall sulfur amino acid content of soybean seeds. Earlier, we have identified by high throughput ionomic phenotyping several high and low sulfur containing soybean lines from the USDA Soybean Germplasm Collection. Here, we measured the cysteine and methionine content of select soybean lines by high-performance liquid chromatography. Our results demonstrate that those soybean lines which had high elemental sulfur content also had a higher cysteine and methionine content when compared to soybean lines with low elemental sulfur. SDS-PAGE and immunoblot analysis revealed that the accumulation of Bowman Birk protease inhibitor and lunasin in soybean seeds may only be marginally correlated with the elemental sulfur levels. However, we found a positive correlation between the levels of trypsin and chymotrypsin inhibitor activities and elemental sulfur and sulfur amino acid content of the seeds. Thus, elemental sulfur content and/or protease inhibitor activity measurement can be utilized as a rapid and cost-effective method to predict the overall sulfur amino acid content of soybean seeds. Our findings will benefit breeders in their endeavors to develop soybean cultivars with enhanced sulfur amino acid content.

Sulfate transport and metabolism: strategies to improve the seed protein quality

Sulfur-containing amino acids (SAA), namely methionine, and cysteine are crucial essential amino acids (EAA) considering the dietary requirements of humans and animals. However, a few crop plants, especially legumes, are characterized with suboptimal levels of these EAA thereby limiting their nutritive value. Hence, improved comprehension of the mechanistic perspective of sulfur transport and assimilation into storage reserve, seed storage protein (SSP), is imperative. Efforts to augment the level of SAA in seed storage protein form an integral component of strategies to balance nutritive quality and quantity. In this review, we highlight the emerging trends in the sulfur biofortification approaches namely transgenics, genetic and molecular breeding, and proteomic rebalancing with sulfur nutrition. The transgenic 'push and pull strategy' could enhance sulfur capture and storage by expressing genes that function as efficient transporters, sulfate assimilatory enzymes, sulfur-rich foreign protein sinks, or by suppressing catabolic enzymes. Modern molecular breeding approaches that adopt high throughput screening strategies and machine learning algorithms are invaluable in identifying candidate genes and alleles associated with SAA content and developing improved crop varieties. Sulfur is an essential plant nutrient and its optimal uptake is crucial for seed sulfur metabolism, thereby affecting seed quality and yields through proteomic rebalance between sulfur-rich and sulfur-poor seed storage proteins.

Soybean genetic resources contributing to sustainable protein production

KEY MESSAGE

Genetic resources contributes to the sustainable protein production in soybean. Soybean is an important crop for food, oil, and forage and is the main source of edible vegetable oil and vegetable protein. It plays an important role in maintaining balanced dietary nutrients for human health. The soybean protein content is a quantitative trait mainly controlled by gene additive effects and is usually negatively correlated with agronomic traits such as the oil content and yield. The selection of soybean varieties with high protein content and high yield to secure sustainable protein production is one of the difficulties in soybean breeding. The abundant genetic variation of soybean germplasm resources is the basis for overcoming the obstacles in breeding for soybean varieties with high yield and high protein content. Soybean has been cultivated for more than 5000 years and has spread from China to other parts of the world. The rich genetic resources play an important role in promoting the sustainable production of soybean protein worldwide. In this paper, the origin and spread of soybean and the current status of soybean production are reviewed; the genetic characteristics of soybean protein and the distribution of resources are expounded based on phenotypes; the discovery of soybean seed protein-related genes as well as transcriptomic, metabolomic, and proteomic studies in soybean are elaborated; the creation and utilization of high-protein germplasm resources are introduced; and the prospect of high-protein soybean breeding is described.

Increased sulfur-containing amino acid content and altered conformational characteristics of soybean proteins by rebalancing 11S and 7S compositions

Soybean proteins are limited by their low contents of methionine and cysteine. Herein, 7S globulin accumulation was reduced using RNA interference to silence CG-β-1 expression, and the content of the A2B1a subunit was largely increased under the soybean seed-specific oleosin8 promoter. The results showed that the sulfur-containing amino acid content in soybean seeds drastically improved, reaching 79.194 nmol/mg, and the 11S/7S ratio had a 1.89-fold increase compared to the wild-type acceptor. The secondary structures of 11S globulin were also altered, and the β-sheet content increased with decreasing β-turn content, which was confirmed by Fourier transform infrared spectroscopy, Raman spectroscopy and circular dichroism analysis. Our findings suggested that raising the accumulation of 11S glycinin at the expense of reducing the content of 7S globulin is an attractive and precise engineering strategy to increase the amount of sulfur-containing amino acids, and soybean proteins with A2B1a subunits of 11S isolates improved, and β-subunits of 7S fractions reduced simultaneously might be an effective new material for food production.

Mapping and identification of QTL in 5601T × U99-310255 RIL population using SNP genotyping: soybean seed quality traits

BACKGROUND

Molecular markers have played and will continue to play a major role in the genetic characterization and improvement of soybeans. They have helped identify major loci for tolerance to abiotic stressors, disease resistance, herbicide resistance, soybean seed quality traits, and yield. However, most yield quantitative trait loci (QTL) are specific to a certain population, and the genetic variation found in the specific bi-parental population is not always shared in other populations. A major objective in soybean breeding is to develop high yielding cultivars. Unfortunately, soybean seed yield, as well as protein and oil content, are complex quantitative traits to characterize from the phenotypic and genotypic perspectives. The objectives of this study are to detect soybean genomic regions that increase protein content, while maintaining oil content and seed yield and to successfully identify soybean QTL associated with these seed quality traits.

METHODS AND RESULTS

To achieve these objectives, data from the 138 recombinant inbred lines grown in six environments were used to perform QTL detection analyses in search of significant genomic regions affecting soybean seed protein, oil, and yield.

CONCLUSIONS

A total of 21 QTL were successfully identified for yield, protein, oil, methionine, threonine, lodging, maturity, and meal. Knowledge of their locations and flanking markers will aid in marker assisted selection for plant breeders. This will lead to a more valuable soybean for farmers, processors, and animal nutritionists.

Identification of quantitative trait loci associated with seed quality traits between Canadian and Ukrainian mega-environments using genome-wide association study

KEY MESSAGE

Identifying QTL associated with soybean seed quality traits from a diverse GWAS panel cultivated in Canadian and Ukrainian mega-environments may facilitate future cultivar development for foreign markets. Understanding the complex genetic basis of seed quality traits for soybean in the mega-environments (MEs) is critical for developing a marker-assisted selection program that will lead to breeding superior cultivars adapted to specific regions. This study aimed to analyze the accumulation of 14 soybean seed quality traits in Canadian ME and two seed quality traits in Ukrainian ME and identify associated ME specific quantitative trait loci (QTLSP) and ME universal QTL (QTLU) for protein and oil using a genome-wide association study (GWAS) panel consisting of 184 soybean genotypes. The panel was planted in three locations in Canada and two locations in Ukraine in 2018 and 2019. Genotype plus genotype-by-environment biplot analysis was conducted to assess the accumulation of individual seed compounds across different locations. The protein accumulation was high in the Canadian ME and low in the Ukrainian ME, whereas the oil concentration showed the opposite trends between the two MEs. No QTLU were identified across the MEs for protein and oil concentrations. In contrast, nine Canadian QTLSP for protein were identified on various chromosomes, which were co-located with QTL controlling other traits identified in the Canadian ME. The lack of common QTLU for protein and oil suggests that it may be necessary to use QTLSP associated with these traits separately for the Canadian and Ukrainian ME. Additional Ukrainian data for seed compounds other than oil and protein are required to identify novel QTLSP and QTLU for such traits for the individual or combined Canadian and Ukrainian MEs.

Genome-Wide Association Study and Genomic Selection for Proteinogenic Methionine in Soybean Seeds

Soybean [Glycine max (L.) Merr.] seeds have an amino acid profile that provides excellent viability as a food and feed protein source. However, low concentrations of an essential amino acid, methionine, limit the nutritional utility of soybean protein. The objectives of this study were to identify genomic associations and evaluate the potential for genomic selection (GS) for methionine content in soybean seeds. We performed a genome-wide association study (GWAS) that utilized 311 soybean accessions from maturity groups IV and V grown in three locations in 2018 and 2019. A total of 35,570 single nucleotide polymorphisms (SNPs) were used to identify genomic associations with proteinogenic methionine content that was quantified by high-performance liquid chromatography (HPLC). Across four environments, 23 novel SNPs were identified as being associated with methionine content. The strongest associations were found on chromosomes 3 (ss715586112, ss715586120, ss715586126, ss715586203, and ss715586204), 8 (ss715599541 and ss715599547) and 16 (ss715625009). Several gene models were recognized within proximity to these SNPs, such as a leucine-rich repeat protein kinase and a serine/threonine protein kinase. Identification of these linked SNPs should help soybean breeders to improve protein quality in soybean seeds. GS was evaluated using k-fold cross validation within each environment with two SNP sets, the complete 35,570 set and a subset of 248 SNPs determined to be associated with methionine through GWAS. Average prediction accuracy (r ²) was highest using the SNP subset ranging from 0.45 to 0.62, which was a significant improvement from the complete set accuracy that ranged from 0.03 to 0.27. This indicated that GS utilizing a significant subset of SNPs may be a viable tool for soybean breeders seeking to improve methionine content.

Genome-wide association study and population structure analysis of seed-bound amino acids and total protein in watermelon

BACKGROUND

Watermelon seeds are a powerhouse of value-added traits such as proteins, free amino acids, vitamins, and essential minerals, offering a paleo-friendly dietary option. Despite the availability of substantial genetic variation, there is no sufficient information on the natural variation in seed-bound amino acids or proteins across the watermelon germplasm. This study aimed to analyze the natural variation in watermelon seed amino acids and total protein and explore underpinning genetic loci by genome-wide association study (GWAS).

METHODS

The study evaluated the distribution of seed-bound free amino acids and total protein in 211 watermelon accessions of Citrullus spp, including 154 of Citrullus lanatus, 54 of Citrullus mucosospermus (egusi) and three of Citrullus amarus. We used the GWAS approach to associate seed phenotypes with 11,456 single nucleotide polymorphisms (SNPs) generated by genotyping-by-sequencing (GBS).

RESULTS

Our results demonstrate a significant natural variation in different free amino acids and total protein content across accessions and geographic regions. The accessions with high protein content and proportion of essential amino acids warrant its use for value-added benefits in the food and feed industries via biofortification. The GWAS analysis identified 188 SNPs coinciding with 167 candidate genes associated with watermelon seed-bound amino acids and total protein. Clustering of SNPs associated with individual amino acids found by principal component analysis was independent of the speciation or cultivar groups and was not selected during the domestication of sweet watermelon. The identified candidate genes were involved in metabolic pathways associated with amino acid metabolism, such as Argininosuccinate synthase, explaining 7% of the variation in arginine content, which validate their functional relevance and potential for marker-assisted analysis selection. This study provides a platform for exploring potential gene loci involved in seed-bound amino acids metabolism, useful in genetic analysis and development of watermelon varieties with superior seed nutritional values.

Development of soybean experimental lines with enhanced protein and sulfur amino acid content

Soybean is the preferred protein source for both poultry and swine feed. However, this preferred status is being challenged due to competition from alternative feed ingredients. To overcome this, it becomes necessary for breeders to develop soybean cultivars that contain higher protein and better nutritional composition. In this study, we have developed experimental soybean lines that not only contain significantly higher amounts of protein but also improved sulfur amino acid content. This objective was achieved by crossing a O-acetylserine sulfhydrylase (OASS) overexpressing transgenic soybean line with elevated levels of sulfur amino acid content (CS) with a high protein Korean soybean cultivar (Lee 5). Introgression of high protein and overexpression of OASS was monitored in the experimental lines at each successive generation (F2-F6) by measuring protein content and OASS activity. The average protein content of transgenic CS and Lee 5 seeds were 34.8 % and 44.7 %, while in the experimental soybean lines the protein content ranged from 41.3 %-47.7 %, respectively. HPLC and inductively coupled plasma-mass spectrometry analyses revealed that all the experimental lines developed in this study contained significantly higher amounts of sulfur containing amino acids and elemental sulfur in the seeds. The sulfur amino acid (cysteine + methionine) content of the experimental lines ranged from 1.1 % to 1.26 % while the parents Lee 5 and CS had 0.79 % and 1.1 %, respectively. SDS-PAGE and western blot analysis demonstrated that the accumulation of Bowman-Birk protease inhibitor and lunasin, two sulfur amino acid rich peptides, were elevated in experimental soybean lines. High-resolution 2D-gel electrophoresis and Delta2D gel analysis validated that an overall increase in the different subunits of 7S β-conglycinin and 11S glycinin were mainly responsible for the observed increase in the total amount of protein in experimental lines.

Fine mapping QTL and mining genes for protein content in soybean by the combination of linkage and association analysis

Soybean is one main source of dietary protein; therefore, improving protein content is an important objective in breeding programs. There is a significant negative correlation between protein and oil content, which influenced mapping quantitative trait locus (QTL) and quantitative trait nucleotides for these two traits. In this study, a linkage map was created with 2232 single-nucleotide polymorphism markers for the four-way recombinant inbred line (FW-RIL) population derived from the cross (Kenfeng 14 × Kenfeng 15) × (Heinong 48 × Kenfeng 19), and then conditional and unconditional QTL analyses were carried out by inclusive complete interval mapping based on the phenotypic data of protein and oil content collected in 10 different environments. As shown in the results of linkage analysis, a total of 85 QTL have been detected. We have performed association analysis using 109,676 markers after quality filtering for FW-RIL, and the results have shown that a total of 60 QTNs were detected. We have performed association analysis using 63,306 markers after quality filtering for resource population, and the results have shown that a total of 123 QTNs were detected. We have combined linkage and association analysis, and there are six QTNs verified by FW-RIL and resource population. We have performed pathway analysis on the genes in these six QTN attenuation regions, and the result shows that a total of four candidate genes are related to the synthesis or metabolism of soybean protein. These findings will facilitate marker-assisted selection and molecular breeding of soybean.

Genome-wide association identifies several QTLs controlling cysteine and methionine content in soybean seed including some promising candidate genes

Soybean is an important source of protein, oil and carbohydrates, as well as other beneficial nutrients. A major function of proteins in nutrition is to supply adequate amounts of amino acids. Although they are essential for human nutrition, the sulfur-containing amino acids cysteine (Cys) and methionine (Met) are often limited and the genetic control of their content in soybean seeds is poorly characterized. This study aimed to characterize the phenotypic variation and identify quantitative trait loci (QTL) associated with Cys and Met content in a core set of 137 soybean lines, representative of the genetic diversity among Canadian short-season soybean, spanning maturity groups 000-II (MG000-II). Significant phenotypic differences were found among these lines for Cys, Met and Cys + Met content. Using both a mixed linear model and six multi-locus methods with a catalogue of 2.18 M SNPs, we report a total of nine QTLs and seventeen QTNs of which seven comprise promising candidate genes. This work allowed us to reproducibly detect multiple novel loci associated with sulfur-containing amino acid content. The markers and genes identified in this study may be useful for soybean genetic improvement aiming to increase Cys and Met content.

Detection of Quantitative Trait Loci (QTL) Associated with the Fruit Morphology of Tomato

Tomato (Solanum lycopersicum L.) is the second most-consumed vegetable in the world. The market value and culinary purpose of tomato are often determined by fruit size and shape, which makes the genetic improvement of these traits a priority for tomato breeders. The main objective of the study was to detect quantitative trait loci (QTL) associated with the tomato fruit shape and size. The use of elite breeding materials in the genetic mapping studies will facilitate the detection of genetic loci of direct relevance to breeders. We performed QTL analysis in an intra-specific population of tomato developed from a cross between two elite breeding lines NC 30P × NC-22L-1(2008) consisting of 110 recombinant inbred lines (RIL). The precision software Tomato Analyzer (TA) was used to measure fruit morphology attributes associated with fruit shape and size traits. The RIL population was genotyped with the SolCAP 7720 SNP array. We identified novel QTL controlling elongated fruit shape on chromosome 10, explaining up to 24% of the phenotypic variance. This information will be useful in improving tomato fruit morphology traits.

Effects of Harvest-Aids on Seed Nutrition in Soybean under Midsouth USA Conditions

Interest in using harvest aids (defoliants or crop desiccants) such as paraquat, carfentrazone-ethyl, glyphosate, and sodium chlorate (NaClO₃) have become increasingly important to assure harvest efficiency, producer profit, and to maintain seed quality. However, information on the effects of harvest aids on seed nutrition (composition) (protein, oil, fatty acids, sugars, and amino acids) in soybean is very limited. The objective of this research was to investigate the influence of harvest aids on seed protein, oil, fatty acids, sugars, and amino acids in soybean. Our hypothesis was that harvest aid may influence seed nutrition, especially at R6 as at R6 the seeds may still undergo biochemical changes. Field experiments were conducted in 2012 and 2013 under Midsouth USA environmental conditions in which harvest aids were applied at R6 (seed-fill) and R7 (yellow pods) growth stages. Harvest aids applied included an untreated control, 0.28 kg ai ha⁻¹ of paraquat, 0.28 kg ai ha⁻¹ of paraquat, and 1.015 kg ai ha⁻¹ of carfentrazone-ethyl (AIM); 6.72 kg ai ha⁻¹ sodium chlorate, 1.015 kg ai ha⁻¹ carfentrazone-ethyl; and 2.0 kg ae ha⁻¹ glyphosate. Results showed that the application of harvest aids at either R6 or R7 resulted in the alteration of some seed composition such as protein, oil, oleic acid, fructose, and little effects on amino acids. In addition, harvest aids affected seed composition constituents differently depending on year and growth stage. This research demonstrated the possible alteration of some nutrients by harvest aids. This research helps growers and scientists to advance the understanding and management of harvest aids and investigate possible effects of harvest aids on seed nutrition.

Genome-wide association study of seed protein, oil and amino acid contents in soybean from maturity groups I to IV

KEY MESSAGE

Genomic regions associated with seed protein, oil and amino acid contents were identified by genome-wide association analyses. Geographic distributions of haplotypes indicate scope of improvement of these traits. Soybean [Glycine max (L.) Merr.] protein and oil are used worldwide in feed, food and industrial materials. Increasing seed protein and oil contents is important; however, protein content is generally negatively correlated with oil content. We conducted a genome-wide association study using phenotypic data collected from five environments for 621 accessions in maturity groups I-IV and 34,014 markers to identify quantitative trait loci (QTL) for seed content of protein, oil and several essential amino acids. Three and five genomic regions were associated with seed protein and oil contents, respectively. One, three, one and four genomic regions were associated with cysteine, methionine, lysine and threonine content (g kg-1 crude protein), respectively. As previously shown, QTL on chromosomes 15 and 20 were associated with seed protein and oil contents, with both exhibiting opposite effects on the two traits, and the chromosome 20 QTL having the most significant effect. A multi-trait mixed model identified trait-specific QTL. A QTL on chromosome 5 increased oil with no effect on protein content, and a QTL on chromosome 10 increased protein content with little effect on oil content. The chromosome 10 QTL co-localized with maturity gene E2/GmGIa. Identification of trait-specific QTL indicates feasibility to reduce the negative correlation between protein and oil contents. Haplotype blocks were defined at the QTL identified on chromosomes 5, 10, 15 and 20. Frequencies of positive effect haplotypes varied across maturity groups and geographic regions, providing guidance on which alleles have potential to contribute to soybean improvement for specific regions.

Genome-Wide Association Studies of Photosynthetic Traits Related to Phosphorus Efficiency in Soybean

Photosynthesis is the basis of plant growth and development, and is seriously affected by low phosphorus (P) stress. However, few studies have reported for the genetic foundation of photosynthetic response to low P stress in soybean. To address this issue, 219 soybean accessions were genotyped by 292,035 high-quality single nucleotide polymorphisms (SNPs) and phenotyped under normal and low P conditions in 2015 and 2016. These datasets were used to identify quantitative trait nucleotides (QTNs) for photosynthesis-related traits using mrMLM, ISIS EM-BLASSO, pLARmEB, FASTmrMLM, FASTmrEMMA, and pKWmEB methods. As a result, 159 QTNs within 31 genomic regions were found to be associated with four photosynthesis-related traits under different P stress conditions. Among the 31 associated regions, five (q7-2, q8-1, q9, q13-1, and q20-2) were detected commonly under both normal and low P conditions, indicating the insensitivity of these candidate genes to low P stress; five were detected only under normal P condition, indicating the sensitivity of these candidate genes to low P stress; six were detected only under low P condition, indicating the tolerantness of these candidate genes to low P stress; 20 were reported in previous studies. Around the 159 QTNs, 52 candidate genes were mined. These results provide the important information for marker-assisted breeding in soybean and further reveal the basis for the application of P tolerance to photosynthetic capacity.

Review: The promise and limits for enhancing sulfur-containing amino acid content of soybean seed

Soybeans are an excellent source of protein in monogastric diets and rations with ∼75% of soybeans produced worldwide used primarily for animal feed. Even though soybeans are protein-rich and have a well-balanced amino acid profile, the nutritive quality of this important crop could be further improved by elevating the concentrations of certain amino acids. The levels of the sulfur-containing amino acids cysteine and methionine in soybean seed proteins are inadequate for optimal growth and development of monogastric animals, which necessitates dietary supplementation. Subsequently, concerted efforts have been made to increase the concentrations of cysteine and methionine in soybean seeds by both classical breeding and genetic engineering; however, these efforts have met with only limited success. In this review, we discuss the strengths and weakness of different approaches in elevating the sulfur amino acid content of soybeans. Manipulation of enzymes involved in the sulfur assimilatory pathway appears to be a viable avenue for improving sulfur amino acid content. This approach requires a through biochemical characterization of sulfur assimilatory enzymes in soybean seeds. We highlight recent studies targeting key sulfur assimilatory enzymes and the manipulation of sulfur metabolism in transgenic soybeans to improve the nutritive value of soybean proteins.

Genome-wide Scan for Seed Composition Provides Insights into Soybean Quality Improvement and the Impacts of Domestication and Breeding

The complex genetic architecture of quality traits has hindered efforts to modify seed nutrients in soybean. Genome-wide association studies were conducted for seed composition, including protein, oil, fatty acids, and amino acids, using 313 diverse soybean germplasm accessions genotyped with a high-density SNP array. A total of 87 chromosomal regions were identified to be associated with seed composition, explaining 8%-89% of genetic variances. The candidate genes GmSAT1, AK-HSDH, SACPD-C, and FAD3A of known function, and putative MtN21 nodulin, FATB, and steroid-5-α-reductase involved in N2 fixation, amino acid biosynthesis, and fatty acid metabolism were found at the major-effect loci. Further analysis of additional germplasm accessions indicated that these major-effect loci had been subjected to domestication or modern breeding selection, and the allelic variants and distributions were relevant to geographic regions. We also revealed that amino acid concentrations related to seed weight and to total protein had a different genetic basis. This helps uncover the in-depth genetic mechanism of the intricate relationships among the seed compounds. Thus, our study not only provides valuable genes and markers for soybean nutrient improvement, both quantitatively and qualitatively, but also offers insights into the alteration of soybean quality during domestication and breeding.

Molecular mapping and genomics of soybean seed protein: a review and perspective for the future

KEY MESSAGE

Genetic improvement of soybean protein meal is a complex process because of negative correlation with oil, yield, and temperature. This review describes the progress in mapping and genomics, identifies knowledge gaps, and highlights the need of integrated approaches. Meal protein derived from soybean [Glycine max (L) Merr.] seed is the primary source of protein in poultry and livestock feed. Protein is a key factor that determines the nutritional and economical value of soybean. Genetic improvement of soybean seed protein content is highly desirable, and major quantitative trait loci (QTL) for soybean protein have been detected and repeatedly mapped on chromosomes (Chr.) 20 (LG-I), and 15 (LG-E). However, practical breeding progress is challenging because of seed protein content's negative genetic correlation with seed yield, other seed components such as oil and sucrose, and interaction with environmental effects such as temperature during seed development. In this review, we discuss rate-limiting factors related to soybean protein content and nutritional quality, and potential control factors regulating seed storage protein. In addition, we describe advances in next-generation sequencing technologies for precise detection of natural variants and their integration with conventional and high-throughput genotyping technologies. A syntenic analysis of QTL on Chr. 15 and 20 was performed. Finally, we discuss comprehensive approaches for integrating protein and amino acid QTL, genome-wide association studies, whole-genome resequencing, and transcriptome data to accelerate identification of genomic hot spots for allele introgression and soybean meal protein improvement.

Meta-Analyses of QTLs Associated with Protein and Oil Contents and Compositions in Soybean [Glycine max (L.) Merr.] Seed

Soybean [Glycine max (L.) Merr.] is a valuable and nutritious crop in part due to the high protein meal and vegetable oil produced from its seed. Soybean producers desire cultivars with both elevated seed protein and oil concentrations as well as specific amino acid and fatty acid profiles. Numerous studies have identified quantitative trait loci (QTLs) associated with seed composition traits, but validation of these QTLs has rarely been carried out. In this study, we have collected information, including genetic location and additive effects, on each QTL for seed contents of protein and oil, as well as amino acid and fatty acid compositions from over 80 studies. Using BioMercator V. 4.2, a meta-QTL analysis was performed with genetic information comprised of 175 QTLs for protein, 205 QTLs for oil, 156 QTLs for amino acids, and 113 QTLs for fatty acids. A total of 55 meta-QTL for seed composition were detected on 6 out of 20 chromosomes. Meta-QTL possessed narrower confidence intervals than the original QTL and candidate genes were identified within each meta-QTL. These candidate genes elucidate potential natural genetic variation in genes contributing to protein and oil biosynthesis and accumulation, providing meaningful information to further soybean breeding programs.

Quantitative Trait Loci (QTL) Mapping for Glycinin and β-Conglycinin Contents in Soybean (Glycine max L. Merr.)

Compared to β-conglycinin, glycinin contains 3-4 times the methionine and cysteine (sulfur-containing amino acids), accounting for approximately 40 and 30%, respectively, of the total storage protein in soybean. Increasing the soybean storage protein content while improving the ratio of glycinin to β-conglycinin is of great significance for soybean breeding and soy food products. The objective of this study is to analyze the genetic mechanism regulating the glycinin and β-conglycinin contents of soybean by using a recombinant inbred line (RIL) population derived from a cross between Kefeng No. 1 and Nannong 1138-2. Two hundred and twenty-one markers were used to map quantitative trait loci (QTLs) for glycinin (11S) and β-conglycinin (7S) contents, the ratio of glycinin to β-conglycinin (RGC), and the sum of glycinin and β-conglycinin (SGC). A total of 35 QTLs, 3 pairs of epistatic QTLs, and 5 major regions encompassing multiple QTLs were detected. Genes encoding the subunits of β-conglycinin were localized to marker intervals sat_418-satt650 and sat_196-sat_303, which are linked to RGC and SGC; marker sat_318, associated with 11S, 7S, and SGC, was located near Glyma10g04280 (Gy4), which encodes a subunit of glycinin. These results, which take epistatic interactions into account, will improve our understanding of the genetic basis of 11S and 7S contents and will lay a foundation for marker-assisted selection (MAS) breeding of soybean and improving the quality of soybean products.

QTL mapping based on the embryo and maternal genetic systems for non-essential amino acids in rapeseed (Brassica napus L.) meal

BACKGROUND

Non-essential amino acids are a good source of nitrogen and also very important contributors to the metabolic process. Analysis of quantitative trait locus (QTL) simultaneously located on the amphidiploid embryo and maternal plant nuclear genomes for non-essential amino acid contents in rapeseed meal across different environments was conducive to further clarify the genetic mechanism of seed quality traits.

RESULTS

Twenty-eight QTLs associated with arginine (five QTLs), histidine (four QTLs), glutamic acid (three QTLs), glycine (three QTLs), proline (three QTLs), alanine (four QTLs) and aspartic acid (six QTLs) contents were identified in present study. All of these QTLs had significant additive main effects from embryo and maternal plant nuclear genomes with eight of them showing significant embryo dominance main effects and 12 showing notable QTL × environment interaction effects. Among them, 12 QTLs were major QTLs which could explain 13.27-35.71% of the phenotypic variation. Specially, five QTL clusters associated with several QTLs related to multiple traits were distributed on chromosomes A1, A4, A5, A7 and C2.

CONCLUSION

Non-essential amino acids in rapeseed meal could be simultaneously controlled by the genetic effects from the QTLs which were located on the chromosomes both in the embryo and maternal plant genetic systems.

QTL for seed protein and amino acids in the Benning × Danbaekkong soybean population

KEY MESSAGE

We identified QTL associated with protein and amino acids in a soybean mapping population that was grown in five environments. These QTL could be used in MAS to improve these traits. Soybean, rather than nitrogen-containing forages, is the primary source of quality protein in feed formulations for domestic swine, poultry, and dairy industries. As a sole dietary source of protein, soybean is deficient in the amino acids lysine (Lys), threonine (Thr), methionine (Met), and cysteine (Cys). Increasing these amino acids would benefit the feed industry. The objective of the present study was to identify quantitative trait loci (QTL) associated with crude protein (cp) and amino acids in the 'Benning' × 'Danbaekkong' population. The population was grown in five southern USA environments. Amino acid concentrations as a fraction of cp (Lys/cp, Thr/cp, Met/cp, Cys/cp, and Met + Cys/cp) were determined by near-infrared reflectance spectroscopy. Four QTL associated with the variation in crude protein were detected on chromosomes (Chr) 14, 15, 17, and 20, of which, a QTL on Chr 20 explained 55 % of the phenotypic variation. In the same chromosomal region, QTL for Lys/cp, Thr/cp, Met/cp, Cys/cp and Met + Cys/cp were detected. At these QTL, the Danbaekkong allele resulted in reduced levels of these amino acids and increased protein concentration. Two additional QTL for Lys/cp were detected on Chr 08 and 20, and three QTL for Thr/cp on Chr 01, 09, and 17. Three QTL were identified on Chr 06, 09 and 10 for Met/cp, and one QTL was found for Cys/cp on Chr 10. The study provides information concerning the relationship between crude protein and levels of essential amino acids and may allow for the improvement of these traits in soybean using marker-assisted selection.

Construction of a high-density genetic map based on large-scale markers developed by specific length amplified fragment sequencing (SLAF-seq) and its application to QTL analysis for isoflavone content in Glycine max

BACKGROUND

Quantitative trait locus (QTL) mapping is an efficient approach to discover the genetic architecture underlying complex quantitative traits. However, the low density of molecular markers in genetic maps has limited the efficiency and accuracy of QTL mapping. In this study, specific length amplified fragment sequencing (SLAF-seq), a new high-throughput strategy for large-scale SNP discovery and genotyping based on next generation sequencing (NGS), was employed to construct a high-density soybean genetic map using recombinant inbred lines (RILs, Luheidou2×Nanhuizao, F5:8). With this map, the consistent QTLs for isoflavone content across various environments were identified.

RESULTS

In total, 23 Gb of data containing 87,604,858 pair-end reads were obtained. The average coverage for each SLAF marker was 11.20-fold for the female parent, 12.51-fold for the male parent, and an average of 3.98-fold for individual RILs. Among the 116,216 high-quality SLAFs obtained, 9,948 were polymorphic. The final map consisted of 5,785 SLAFs on 20 linkage groups (LGs) and spanned 2,255.18 cM in genome size with an average distance of 0.43 cM between adjacent markers. Comparative genomic analysis revealed a relatively high collinearity of 20 LGs with the soybean reference genome. Based on this map, 41 QTLs were identified that contributed to the isoflavone content. The high efficiency and accuracy of this map were evidenced by the discovery of genes encoding isoflavone biosynthetic enzymes within these loci. Moreover, 11 of these 41 QTLs (including six novel loci) were associated with isoflavone content across multiple environments. One of them, qIF20-2, contributed to a majority of isoflavone components across various environments and explained a high amount of phenotypic variance (8.7%-35.3%). This represents a novel major QTL underlying isoflavone content across various environments in soybean.

CONCLUSIONS

Herein, we reported a high-density genetic map for soybean. This map exhibited high resolution and accuracy. It will facilitate the identification of genes and QTLs underlying essential agronomic traits in soybean. The novel major QTL for isoflavone content is useful not only for further study on the genetic basis of isoflavone accumulation, but also for marker-assisted selection (MAS) in soybean breeding in the future.

The genetic architecture of seed composition in soybean is refined by genome-wide association scans across multiple populations

Soybean oil and meal are major contributors to world-wide food production. Consequently, the genetic basis for soybean seed composition has been intensely studied using family-based mapping. Population-based mapping approaches, in the form of genome-wide association (GWA) scans, have been able to resolve loci controlling moderately complex quantitative traits (QTL) in numerous crop species. Yet, it is still unclear how soybean's unique population history will affect GWA scans. Using one of the populations in this study, we simulated phenotypes resulting from a range of genetic architectures. We found that with a heritability of 0.5, ∼100% and ∼33% of the 4 and 20 simulated QTL can be recovered, respectively, with a false-positive rate of less than ∼6×10(-5) per marker tested. Additionally, we demonstrated that combining information from multi-locus mixed models and compressed linear-mixed models improves QTL identification and interpretation. We applied these insights to exploring seed composition in soybean, refining the linkage group I (chromosome 20) protein QTL and identifying additional oil QTL that may allow some decoupling of highly correlated oil and protein phenotypes. Because the value of protein meal is closely related to its essential amino acid profile, we attempted to identify QTL underlying methionine, threonine, cysteine, and lysine content. Multiple QTL were found that have not been observed in family-based mapping studies, and each trait exhibited associations across multiple populations. Chromosomes 1 and 8 contain strong candidate alleles for essential amino acid increases. Overall, we present these and additional data that will be useful in determining breeding strategies for the continued improvement of soybean's nutrient portfolio.

Identification of the quantitative trait loci (QTL) underlying water soluble protein content in soybean

Water soluble protein content (SPC) plays an important role in the functional efficacy of protein in food products. Therefore, for the identification of quantitative trait loci (QTL) associated with SPC, 212 F(2:9) lines of the recombinant inbred line (RIL) population derived from the cross of ZDD09454 × Yudou12 were grown along with the parents, in six different environments (location × year) to determine inheritance and map solubility-related genes. A linkage map comprising of 301 SSR markers covering 3,576.81 cM was constructed in the RIL population. Seed SPC was quantified with a macro-Kjeldahl procedure in samples collected over multiple years from three locations (Nantong in 2007 and 2008, Zhengzhou in 2007 and 2008, and Xinxiang in 2008 and 2009). SPC demonstrated transgressive segregation, indicating a complementary genetic structure between the parents. Eleven putative QTL were associated with SPC explaining 4.5-18.2 % of the observed phenotypic variation across the 6 year/location environments. Among these, two QTL (qsp8-4, qsp8-5) near GMENOD2B and Sat_215 showed an association with SPC in multiple environments, suggesting that they were key QTL related to protein solubility. The QTL × environment interaction demonstrated the complex genetic mechanism of SPC. These SPC-associated QTL and linked markers in soybean will provide important information that can be utilized by breeders to improve the functional quality of soybean varieties.

From sulfur to homoglutathione: thiol metabolism in soybean

Sulfur is an essential plant nutrient and is metabolized into the sulfur-containing amino acids (cysteine and methionine) and into molecules that protect plants against oxidative and environmental stresses. Although studies of thiol metabolism in the model plant Arabidopsis thaliana (thale cress) have expanded our understanding of these dynamic processes, our knowledge of how sulfur is assimilated and metabolized in crop plants, such as soybean (Glycine max), remains limited in comparison. Soybean is a major crop used worldwide for food and animal feed. Although soybeans are protein-rich, they do not contain high levels of the sulfur-containing amino acids, cysteine and methionine. Ultimately, unraveling the fundamental steps and regulation of thiol metabolism in soybean is important for optimizing crop yield and quality. Here we review the pathways from sulfur uptake to glutathione and homoglutathione synthesis in soybean, the potential biotechnology benefits of understanding and modifying these pathways, and how information from the soybean genome may guide the next steps in exploring this biochemical system.

Reserve accumulation in legume seeds

The accumulation of seed reserves is the result of distinct processes occurring in parallel in the main seed compartments of either maternal (seed coats) or zygotic (embryo, endosperm) origin. With the development of legume genomic resources, recent advances have been made toward understanding the metabolic control of seed filling and the regulatory network underlying reserve accumulation. Genetic variability for seed composition has been studied along with the environmental factors influencing reserve accumulation. Nutrient availability and sink strength were both found to be limiting for reserve accumulation. Genes and/or QTL controlling seed protein content and sulfur-amino acid levels have been identified. These new findings will support our attempts to engineer legume seed composition for added end user value.

Seed storage protein deficiency improves sulfur amino acid content in common bean (Phaseolus vulgaris L.): redirection of sulfur from gamma-glutamyl-S-methyl-cysteine

The contents of sulfur amino acids in seeds of common bean ( Phaseolus vulgaris L.) are suboptimal for nutrition. They accumulate large amounts of a gamma-glutamyl dipeptide of S-methyl-cysteine, a nonprotein amino acid that cannot substitute for methionine or cysteine in the diet. Protein accumulation and amino acid composition were characterized in three genetically related lines integrating a progressive deficiency in major seed storage proteins, phaseolin, phytohemagglutinin, and arcelin. Nitrogen, carbon, and sulfur contents were comparable among the three lines. The contents of S-methyl-cysteine and gamma-glutamyl-S-methyl-cysteine were progressively reduced in the mutants. Sulfur was shifted predominantly to the protein cysteine pool, while total methionine was only slightly elevated. Methionine and cystine contents (mg per g protein) were increased by up to ca. 40%, to levels slightly above FAO guidelines on amino acid requirements for human nutrition. These findings may be useful to improve the nutritional quality of common bean.

Developmental genes have pleiotropic effects on plant morphology and source capacity, eventually impacting on seed protein content and productivity in pea

Increasing pea (Pisum sativum) seed nutritional value and particularly seed protein content, while maintaining yield, is an important challenge for further development of this crop. Seed protein content and yield are complex and unstable traits, integrating all the processes occurring during the plant life cycle. During filling, seeds are the main sink to which assimilates are preferentially allocated at the expense of vegetative organs. Nitrogen seed demand is satisfied partly by nitrogen acquired by the roots, but also by nitrogen remobilized from vegetative organs. In this study, we evaluated the respective roles of nitrogen source capacity and sink strength in the genetic variability of seed protein content and yield. We showed in eight genotypes of diverse origins that both the maximal rate of nitrogen accumulation in the seeds and nitrogen source capacity varied among genotypes. Then, to identify the genetic factors responsible for seed protein content and yield variation, we searched for quantitative trait loci (QTL) for seed traits and for indicators of sink strength and source nitrogen capacity. We detected 261 QTL across five environments for all traits measured. Most QTL for seed and plant traits mapped in clusters, raising the possibility of common underlying processes and candidate genes. In most environments, the genes Le and Afila, which control internode length and the switch between leaflets and tendrils, respectively, determined plant nitrogen status. Depending on the environment, these genes were linked to QTL of seed protein content and yield, suggesting that source-sink adjustments depend on growing conditions.

Identification of glycinin and beta-conglycinin subunits that contribute to the increased protein content of high-protein soybean lines

Seed protein concentration of commercial soybean cultivars calculated on a dry weight basis ranges from approximately 37 to 42% depending on genotype and location. A concerted research effort is ongoing to further increase protein concentration. Several soybean plant introductions (PI) are known to contain greater than 50% protein. These PIs are exploited by breeders to incorporate the high-protein trait into commercial North American cultivars. Currently, limited information is available on the biochemical and genetic mechanisms that regulate high-proteins. In this study, we have carried out proteomic and molecular analysis of seed proteins of LG00-13260 and its parental high-protein lines PI 427138 and BARC-6. Sodium dodecyl sulfate polyacrylamide gel electrophoresis analysis revealed that the high-protein lines accumulated increased amounts of beta-conglycinin and glycinins, when compared with Williams 82. High-resolution two-dimensional electrophoresis utilizing pH 4-7 and pH 6-11 ampholytes enabled improved resolution of soybean seed proteins. A total of 38 protein spots, representing the different subunits of beta-conglycinin and glycinin, were identified by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. High-protein was correlated with an increase in the accumulation of most of the subunits representing beta-conglycinin and glycinin. Comparisons of the amino acid profiles of high-protein soybean lines revealed that the concentration of sulfur amino acids, a reflection of protein quality, was not influenced by the protein concentration. Southern blot analysis showed the presence of genotypic variation at the DNA level between PI 427138 and BARC-6 for the genes encoding group1 glycinin, beta-conglycinin, Bowman-Birk inhibitor (BBI), and the Kunitz trypsin inhibitor (KTI). LG00-13260 inherited the allelic variants of the parental line PI 427138 for glycinin, beta-conglycinin, and KTI, while BBI was inherited from the parental line BARC-6. The results of our study indicate that high-seed protein concentration is attributed to greater accumulation of specific components of beta-conglycinin and glycinin subunits presumably mediated by preferential expression of these genes during seed development.