Multi-Population Selective Genotyping to Identify Soybean [Glycine max (L.) Merr.] Seed Protein and Oil QTLs

Construction of Genetic Map and QTL Mapping for Seed Size and Quality Traits in Soybean (Glycine max L.)

Soybean (Glycine max L.) is the main source of vegetable protein and edible oil for humans, with an average content of about 40% crude protein and 20% crude fat. Soybean yield and quality traits are mostly quantitative traits controlled by multiple genes. The quantitative trait loci (QTL) mapping for yield and quality traits, as well as for the identification of mining-related candidate genes, is of great significance for the molecular breeding and understanding the genetic mechanism. In this study, 186 individual plants of the F2 generation derived from crosses between Changjiangchun 2 and Yushuxian 2 were selected as the mapping population to construct a molecular genetic linkage map. A genetic map containing 445 SSR markers with an average distance of 5.3 cM and a total length of 2375.6 cM was obtained. Based on constructed genetic map, 11 traits including hundred-seed weight (HSW), seed length (SL), seed width (SW), seed length-to-width ratio (SLW), oil content (OIL), protein content (PRO), oleic acid (OA), linoleic acid (LA), linolenic acid (LNA), palmitic acid (PA), stearic acid (SA) of yield and quality were detected by the multiple- d size traits and 113 QTLs related to quality were detected by the multiple QTL model (MQM) mapping method across generations F2, F2:3, F2:4, and F2:5. A total of 71 QTLs related to seed size traits and 113 QTLs related to quality traits were obtained in four generations. With those QTLs, 19 clusters for seed size traits and 20 QTL clusters for quality traits were summarized. Two promising clusters, one related to seed size traits and the other to quality traits, have been identified. The cluster associated with seed size traits spans from position 27876712 to 29009783 on Chromosome 16, while the cluster linked to quality traits spans from position 12575403 to 13875138 on Chromosome 6. Within these intervals, a reference genome of William82 was used for gene searching. A total of 36 candidate genes that may be involved in the regulation of soybean seed size and quality were screened by gene functional annotation and GO enrichment analysis. The results will lay the theoretical and technical foundation for molecularly assisted breeding in soybean.

Genomic analysis and characterization of new loci associated with seed protein and oil content in soybeans

Breeding for increased protein without a reduction in oil content in soybeans [Glycine max (L.) Merr.] is a challenge for soybean breeders but an expected goal. Many efforts have been made to develop new soybean varieties with high yield in combination with desirable protein and/or oil traits. An elite line, R05-1415, was reported to be high yielding, high protein, and low oil. Several significant quantitative trait loci (QTL) for protein and oil were reported in this line, but many of them were unstable across environments or genetic backgrounds. Thus, a new study under multiple field environments using the Infinium BARCSoySNP6K BeadChips was conducted to detect and confirm stable genomic loci for these traits. Genetic analyses consistently detected a single major genomic locus conveying these two traits with remarkably high phenotypic variation explained (R2 ), varying between 24.2% and 43.5%. This new genomic locus is located between 25.0 and 26.7 Mb, distant from the previously reported QTL and did not overlap with other commonly reported QTL and the recently cloned gene Glyma.20G085100. Homolog analysis indicated that this QTL did not result from the paracentric chromosome inversion with an adjacent genomic fragment that harbors the reported QTL. The pleiotropic effect of this QTL could be a challenge for improving protein and oil simultaneously; however, a further study of four candidate genes with significant expressions in the seed developmental stages coupled with haplotype analysis may be able to pinpoint causative genes. The functionality and roles of these genes can be determined and characterized, which lay a solid foundation for the improvement of protein and oil content in soybeans.

Identification of quantitative trait loci controlling soybean seed protein and oil content

Soybean is a major source of seed protein and oil globally with an average composition of 40% protein and 20% oil in the seed. The goal of this study was to identify quantitative trait loci (QTL) conferring seed protein and oil content utilizing a population constructed by crossing an above average protein content line, PI 399084 to another line that had a low protein content value, PI 507429, both from the USDA soybean germplasm collection. The recombinant inbred line (RIL) population, PI 507429 x PI 399084, was evaluated in two replications over four years (2018-2021); the seeds were analyzed for seed protein and oil content using near-infrared reflectance spectroscopy. The recombinant inbred lines and the two parents were re-sequenced using genotyping by sequencing. A total of 12,761 molecular markers, which came from genotyping by sequencing, the SoySNP6k BeadChip and selected simple sequence repeat (SSR) markers from known protein QTL chromosomal regions were used for mapping. One QTL was identified on chromosome 2 explaining up to 56.8% of the variation for seed protein content and up to 43% for seed oil content. Another QTL identified on chromosome 15 explained up to 27.2% of the variation for seed protein and up to 41% of the variation for seed oil content. The protein and oil QTLs of this study and their associated molecular markers will be useful in breeding to improve nutritional quality in soybean.

Genetic analysis of protein content and oil content in soybean by genome-wide association study

Soybean seed protein content (PC) and oil content (OC) have important economic value. Detecting the loci/gene related to PC and OC is important for the marker-assisted selection (MAS) breeding of soybean. To detect the stable and new loci for PC and OC, a total of 320 soybean accessions collected from the major soybean-growing countries were used to conduct a genome-wide association study (GWAS) by resequencing. The PC ranged from 37.8% to 46.5% with an average of 41.1% and the OC ranged from 16.7% to 22.6% with an average of 21.0%. In total, 23 and 29 loci were identified, explaining 3.4%-15.4% and 5.1%-16.3% of the phenotypic variations for PC and OC, respectively. Of these, eight and five loci for PC and OC, respectively, overlapped previously reported loci and the other 15 and 24 loci were newly identified. In addition, nine candidate genes were identified, which are known to be involved in protein and oil biosynthesis/metabolism, including lipid transport and metabolism, signal transduction, and plant development pathway. These results uncover the genetic basis of soybean protein and oil biosynthesis and could be used to accelerate the progress in enhancing soybean PC and OC.

Genetic mapping and functional genomics of soybean seed protein

Soybean is an utterly important crop for high-quality meal protein and vegetative oil. Soybean seed protein content has become a key factor in nutrients for livestock feed as well as human dietary consumption. Genetic improvement of soybean seed protein is highly desired to meet the demands of rapidly growing world population. Molecular mapping and genomic analysis in soybean have identified many quantitative trait loci (QTL) underlying seed protein content control. Exploring the mechanisms of seed storage protein regulation will be helpful to achieve the improvement of protein content. However, the practice of breeding higher protein soybean is challenging because soybean seed protein is negatively correlated with seed oil content and yield. To overcome the limitation of such inverse relationship, deeper insights into the property and genetic control of seed protein are required. Recent advances of soybean genomics have strongly enhanced the understandings for molecular mechanisms of soybean with better seed quality. Here, we review the research progress in the genetic characteristics of soybean storage protein, and up-to-date advances of molecular mappings and genomics of soybean protein. The key factors underlying the mechanisms of the negative correlation between protein and oil in soybean seeds are elaborated. We also briefly discuss the future prospects of breaking the bottleneck of the negative correlation to develop high protein soybean without penalty of oil and yield.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01373-5.

Development of molecular inversion probes for soybean progeny genomic selection genotyping

Increasing rate of genetic gain for key agronomic traits through genomic selection requires the development of new molecular methods to run genome-wide single-nucleotide polymorphisms (SNPs). The main limitation of current methods is the cost is too high to screen breeding populations. Molecular inversion probes (MIPs) are a targeted genotyping-by-sequencing (GBS) method that could be used for soybean [Glycine max (L.) Merr.] that is both cost-effective, high-throughput, and provides high data quality to screen breeder's germplasm for genomic selection. A 1K MIP SNP set was developed for soybean with uniformly distributed markers across the genome. The SNPs were selected to maximize the number of informative markers in germplasm being tested in soybean breeding programs located in the northern-central and middle-southern regions of the United States. The 1K SNP MIP set was tested on diverse germplasm and a recombinant inbred line (RIL) population. Targeted sequencing with MIPs obtained an 85% enrichment for the targeted SNPs. The MIP genotyping accuracy was 93% overall, whereas homozygous call accuracy was 98% with <10% missing data. The accuracy of MIPs combined with its low per-sample cost makes it a powerful tool to enable genomic selection within soybean breeding programs.

Genetic architecture of protein and oil content in soybean seed and meal

Soybean is grown primarily for the protein and oil extracted from its seed and its value is influenced by these components. The objective of this study was to map marker-trait associations (MTAs) for the concentration of seed protein, oil, and meal protein using the soybean nested association mapping (SoyNAM) population. The composition traits were evaluated on seed harvested from over 5000 inbred lines of the SoyNAM population grown in 10 field locations across 3 years. Estimated heritabilities were at least 0.85 for all three traits. The genotyping of lines with single nucleotide polymorphism markers resulted in the identification of 107 MTAs for the three traits. When MTAs for the three traits that mapped within 5 cM intervals were binned together, the MTAs were mapped to 64 intervals on 19 of the 20 soybean chromosomes. The majority of the MTA effects were small and of the 107 MTAs, 37 were for protein content, 39 for meal protein, and 31 for oil content. For cases where a protein and oil MTAs mapped to the same interval, most (94%) significant effects were opposite for the two traits, consistent with the negative correlation between these traits. A coexpression analysis identified candidate genes linked to MTAs and 18 candidate genes were identified. The large number of small effect MTAs for the composition traits suggest that genomic prediction would be more effective in improving these traits than marker-assisted selection.

Identification of loci governing soybean seed protein content via genome-wide association study and selective signature analyses

Soybean [Glycine max (L.) Merr.] is an excellent source of protein. Understanding the genetic basis of protein content (PC) will accelerate breeding efforts to increase soybean quality. In the present study, a genome-wide association study (GWAS) was applied to detect quantitative trait loci (QTL) for PC in soybean using 264 re-sequenced soybean accessions and a high-quality single nucleotide polymorphism (SNP) map. Eleven QTL were identified as associated with PC. The QTL qPC-14 was detected by GWAS in both environments and was shown to have undergone strong selection during soybean improvement. Fifteen candidate genes were identified in qPC-14, and three candidate genes showed differential expression between a high-PC and a low-PC variety during the seed development stage. The QTL identified here will be of significant use in molecular breeding efforts, and the candidate genes will play essential roles in exploring the mechanisms of protein biosynthesis.

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.

Novel Fusarium wilt resistance genes uncovered in natural and cultivated strawberry populations are found on three non-homoeologous chromosomes

Several Fusarium wilt resistance genes were discovered, genetically and physically mapped, and rapidly deployed via marker-assisted selection to develop cultivars resistant to Fusarium oxysporum f. sp. fragariae, a devastating soil-borne pathogen of strawberry. Fusarium wilt, a soilborne disease caused by Fusarium oxysporum f. sp. fragariae, poses a significant threat to strawberry (Fragaria [Formula: see text] ananassa) production in many parts of the world. This pathogen causes wilting, collapse, and death in susceptible genotypes. We previously identified a dominant gene (FW1) on chromosome 2B that confers resistance to race 1 of the pathogen, and hypothesized that gene-for-gene resistance to Fusarium wilt was widespread in strawberry. To explore this, a genetically diverse collection of heirloom and modern cultivars and octoploid ecotypes were screened for resistance to Fusarium wilt races 1 and 2. Here, we show that resistance to both races is widespread in natural and domesticated populations and that resistance to race 1 is conferred by partially to completely dominant alleles among loci (FW1, FW2, FW3, FW4, and FW5) found on three non-homoeologous chromosomes (1A, 2B, and 6B). The underlying genes have not yet been cloned and functionally characterized; however, plausible candidates were identified that encode pattern recognition receptors or other proteins known to confer gene-for-gene resistance in plants. High-throughput genotyping assays for SNPs in linkage disequilibrium with FW1-FW5 were developed to facilitate marker-assisted selection and accelerate the development of race 1 resistant cultivars. This study laid the foundation for identifying the genes encoded by FW1-FW5, in addition to exploring the genetics of resistance to race 2 and other races of the pathogen, as a precaution to averting a Fusarium wilt pandemic.

Fine mapping and cloning of the major seed protein quantitative trait loci on soybean chromosome 20

Soybean is the most important source of protein meal worldwide and the quantitative trait loci (QTL) cqSeed protein‐003 on chromosome 20 exerts the greatest additive effect of any protein QTL mapped in the crop. Through genetic mapping and candidate gene downregulation, we identified that an insertion/deletion variant in Glyma.20G85100 is the likely gene that underlies this important QTL.

Phenotyping and Quantitative Trait Locus Analysis for the Limited Transpiration Trait in an Upper-Mid South Soybean Recombinant Inbred Line Population ("Jackson" × "KS4895"): High Throughput Aquaporin Inhibitor Screening

Soybean is most often grown under rainfed conditions and negatively impacted by drought stress in the upper mid-south of the United States. Therefore, identification of drought-tolerance traits and their corresponding genetic components are required to minimize drought impacts on productivity. Limited transpiration (TRlim) under high vapor pressure deficit (VPD) is one trait that can help conserve soybean water-use during late-season drought. The main research objective was to evaluate a recombinant inbred line (RIL) population, from crossing two mid-south soybean lines ("Jackson" × "KS4895"), using a high-throughput technique with an aquaporin inhibitor, AgNO3, for the TRlim trait. A secondary objective was to undertake a genetic marker/quantitative trait locus (QTL) genetic analysis using the AgNO3 phenotyping results. A set of 122 soybean genotypes (120-RILs and parents) were grown in controlled environments (32/25-d/n °C). The transpiration rate (TR) responses of derooted soybean shoots before and after application of AgNO3 were measured under 37°C and >3.0 kPa VPD. Then, the decrease in transpiration rate (DTR) for each genotype was determined. Based on DTR rate, a diverse group (slow, moderate, and high wilting) of 26 RILs were selected and tested for the whole plant TRs under varying levels of VPD (0.0-4.0 kPa) at 32 and 37°C. The phenotyping results showed that 88% of slow, 50% of moderate, and 11% of high wilting genotypes expressed the TRlim trait at 32°C and 43, 10, and 0% at 37°C, respectively. Genetic mapping with the phenotypic data we collected revealed three QTL across two chromosomes, two associated with TRlim traits and one associated with leaf temperature. Analysis of Gene Ontologies of genes within QTL regions identified several intriguing candidate genes, including one gene that when overexpressed had previously been shown to confer enhanced tolerance to abiotic stress. Collectively these results will inform and guide ongoing efforts to understand how to deploy genetic tolerance for drought stress.

Comparative transcriptome analysis during seeds development between two soybean cultivars

Soybean is one of the important economic crops, which supplies a great deal of vegetable oil and proteins for human. The content of nutrients in different soybean seeds is different, which is related to the expression of multiple genes, but the mechanisms are complicated and still largely uncertain. In this study, to reveal the possible causes of the nutrients difference in soybeans A7 (containing low oil and high protein) and A35 (containing high oil and low protein), RNA-seq technology was performed to compare and identify the potential differential expressed genes (DEGs) at different seed developmental stages. The results showed that DEGs mainly presented at the early stages of seeds development and more DEGs were up-regulated at the early stage than the late stages. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed that the DEGs have diverged in A7 and A35. In A7, the DEGs were mainly involved in cell cycle and stresses, while in A35 were the fatty acids and sugar metabolism. Specifically, when the DEGs contributing to oil and protein metabolic pathways were analyzed, the differences between A7 and A35 mainly presented in fatty acids metabolism and seeds storage proteins (SSPs) synthesis. Furthermore, the enzymes, fatty acid dehydrogenase 2, 3-ketoacyl-CoA synthase and 9S-lipoxygenase, in the synthesis and elongation pathways of fatty acids, were revealed probably to be involved in the oil content difference between A7 and A35, the SSPs content might be due to the transcription factors: Leafy Cotyledon 2 and Abscisic acid-intensitive 3, while the sugar transporter, SWEET10a, might contribute to both oil and protein content differences. Finally, six DEGs were selected to analyze their expression using qRT-PCR, and the results were consistent with the RNA-seq results. Generally, the study provided a comprehensive and dynamic expression trends for the seed development processes, and uncovered the potential DEGs for the differences of oil in A7 and A35.

Genome-wide association mapping for protein, oil and water-soluble protein contents in soybean

As a globally important legume crop, soybean provides excellent sources of protein and oil for human and livestock nutrition. Improving seed protein and oil contents has always been an important objective in soybean breeding. Water-soluble protein plays a significant role in the processing and efficacy of soybean protein. Here, a genome-wide association study (GWAS) of seed compositions (protein, oil, and water-soluble protein contents) was conducted using 211 diverse soybean accessions genotyped with a 355 K SoySNP array. Three, four, and five QTLs were identified related to the protein, oil, and water-soluble protein contents, respectively. Furthermore, five QTLs (qPC-15-1, qOC-8-1, qOC-12-1, qOC-20-1 and qWSPC-8-1) were detected in multiple environments. Analysis of the favorable alleles for oil and water-soluble protein contents showed that qOC-8-1 (qWSPC-8-1) exerted inverse effects on oil and water-soluble protein synthesis. Relative expression analysis suggested that Glyma.15G049200 in qPC-15-1 affects protein synthesis and Glyma.08G107800 in qOC-8-1 and qWSPC-8-1 might be involved in oil and water-soluble protein synthesis, producing opposite effects. The candidate genes and significant SNPs detected in the present study will allow a deeper understanding of the genetic basis for the regulation of protein, oil and water-soluble protein contents and provide important information that could be utilized in marker-assisted selection for soybean quality improvement.

Genetic Analysis of High Protein Content in 'AC Proteus' Related Soybean Populations Using SSR, SNP, DArT and DArTseq Markers

Key message: Several AC Proteus derived genomic regions (QTLs, SNPs) have been identified which may prove useful for further development of high yielding high protein cultivars and allele-specific marker developments. High seed protein content is a trait which is typically difficult to introgress into soybean without an accompanying reduction in seed yield. In a previous study, 'AC Proteus' was used as a high protein source and was found to produce populations that did not exhibit the typical association between high protein and low yield. Five high x low protein RIL populations and a high x high protein RIL population were evaluated by either quantitative trait locus (QTL) analysis or bulk segregant analyses (BSA) following phenotyping in the field. QTL analysis in one population using SSR, DArT and DArTseq markers found two QTLs for seed protein content on chromosomes 15 and 20. The BSA analyses suggested multiple genomic regions are involved with high protein content across the five populations, including the two previously mentioned QTLs. In an alternative approach to identify high protein genes, pedigree analysis identified SNPs for which the allele associated with high protein was retained in seven high protein descendants of AC Proteus on chromosomes 2, 17 and 18. Aside from the two identified QTLs (five genomic regions in total considering the two with highly elevated test statistic, but below the statistical threshold and the one with epistatic interactions) which were some distance from Meta-QTL regions and which were also supported by our BSA analysis within five populations. These high protein regions may prove useful for further development of high yielding high protein cultivars.

Insight Into the Prospects for the Improvement of Seed Starch in Legume-A Review

In addition to proteins and/or oils, mature seeds of most legume crops contain important carbohydrate components, including starches and sugars. Starch is also an essential nutritional component of human and animal diets and has various food and non-food industrial applications. Starch is a primary insoluble polymeric carbohydrate produced by higher plants and consists of amylose and amylopectin as a major fraction. Legume seeds are an affordable source of not only protein but also the starch, which has an advantage of being resistant starch compared with cereal, root, and tuber starch. For these reasons, legume seeds form a good source of resistant starch-rich healthy food with a high protein content and can be utilized in various food applications. The genetics and molecular details of starch and other carbohydrate components are well studied in cereal crops but have received little attention in legumes. In order to improve legume starch content, quality, and quantity, it is necessary to understand the genetic and molecular factors regulating carbohydrate metabolism in legume crops. In this review, we assessed the current literature reporting the genetic and molecular basis of legume carbohydrate components, primarily focused on seed starch content. We provided an overview of starch biosynthesis in the heterotrophic organs, the chemical composition of major consumable legumes, the factors influencing starch digestibility, and advances in the genetic, transcriptomic, and metabolomic studies in important legume crops. Further, we discussed breeding and biotechnological approaches for the improvement of the starch composition in major legume crops. The information reviewed in this study will be helpful in facilitating the food and non-food applications of legume starch and provide economic benefits to farmers and industries.

Genomic changes and biochemical alterations of seed protein and oil content in a subset of fast neutron induced soybean mutants

BACKGROUND

Soybean is subjected to genetic manipulation by breeding, mutation, and transgenic approaches to produce value-added quality traits. Among those genetic approaches, mutagenesis through fast neutrons radiation is intriguing because it yields a variety of mutations, including single/multiple gene deletions and/or duplications. Characterizing the seed composition of the fast neutron mutants and its relationship with gene mutation is useful towards understanding oil and protein traits in soybean.

RESULTS

From a large population of fast neutron mutagenized plants, we selected ten mutants based on a screening of total oil and protein content using near infra-red spectroscopy. These ten mutants were regrown, and the seeds were analyzed for oil by GC-MS, protein profiling by SDS-PAGE and gene mapping by comparative genomic hybridization. The mutant 2R29C14Cladecr233cMN15 (nicknamed in this study as L10) showed higher protein and lower oil content compared to the wild type, followed by three other lines (nicknamed in this study as L03, L05, and L06). We characterized the fatty acid methyl esters profile of the trans-esterified oil and found the presence of five major fatty acids (palmitic, stearic, oleic, linoleic, and linolenic acids) at varying proportions among the mutants. Protein profile using SDS-PAGE of the ten mutants did exhibit discernable variation between storage (glycinin and β-conglycinin) and anti-nutritional factor (trypsin inhibitor) proteins. In addition, we physically mapped the position of the gene deletions or duplications in each mutant using comparative genomic hybridization.

CONCLUSION

Characterization of oil and protein profile in soybean fast neutron mutants will assist scientist and breeders to develop new value-added soybeans with improved protein and oil quality traits.

Identification and mapping of QTLs associated with drought tolerance traits in rice by a cross between Super Basmati and IR55419-04

Water stress, in a climate change scenario is one of the major threats for sustainable rice productivity. Combining drought resistance with yield and desirable economic traits is the most promising solution for the researchers. Although several studies resulted in the identification of QTLs for drought resistance in rice, but none of them serve as a milestone. Therefore, there is always a quest to find the new QTLs. The present investigation was carried out to map QTLs involved in drought resistance and yield related parameter in a cross of IR55419-04 and Super Basmati. An F₂ population of 418 individuals was used as the mapping population. The raised nursery was transplanted in lyzimeters. Two extreme sets of tolerant (23 Nos.) and sensitive (23 Nos.) individuals were selected based on total water uptake under water stress conditions. Two hundred thirty microsatellite markers staggered on the whole genome were used for identifying polymorphic markers between the two parents. The selected 73 polymorphic microsatellites were used to genotype individuals and were scattered on a distance of 1735 cM on all 12 linkage groups. QTL analysis was performed by using the WinQTL Cartographer 2.5 V. A total of 21 QTLs were detected using composite interval mapping. The QTLs relating to drought tolerance at the vegetative stage were found on chromosome 1. Novel genomic regions were detected in the marker interval RM520-RM143 and RM168-RM520. The region has a significant QTL qTWU3.1 for total water uptake. Root morphological trait QTLs were found on chromosome 3. QTLs responsible for additive effects were due to the alleles of the IR55419-04. These novel QTLs can be used for marker assisted breeding to develop new drought-tolerant rice varieties and fine mapping can be used to explore the functional relationship between the QTLs and phenotypic traits.

Dissecting genomic hotspots underlying seed protein, oil, and sucrose content in an interspecific mapping population of soybean using high-density linkage mapping

The cultivated [Glycine max (L) Merr.] and wild [Glycine soja Siebold & Zucc.] soybean species comprise wide variation in seed composition traits. Compared to wild soybean, cultivated soybean contains low protein, high oil, and high sucrose. In this study, an interspecific population was derived from a cross between G. max (Williams 82) and G. soja (PI 483460B). This recombinant inbred line (RIL) population of 188 lines was sequenced at 0.3× depth. Based on 91 342 single nucleotide polymorphisms (SNPs), recombination events in RILs were defined, and a high-resolution bin map was developed (4070 bins). In addition to bin mapping, quantitative trait loci (QTL) analysis for protein, oil, and sucrose was performed using 3343 polymorphic SNPs (3K-SNP), derived from Illumina Infinium BeadChip sequencing platform. The QTL regions from both platforms were compared, and a significant concordance was observed between bin and 3K-SNP markers. Importantly, the bin map derived from next-generation sequencing technology enhanced mapping resolution (from 1325 to 50 Kb). A total of five, nine, and four QTLs were identified for protein, oil, and sucrose content, respectively, and some of the QTLs coincided with soybean domestication-related genomic loci. The major QTL for protein and oil were mapped on Chr. 20 (qPro_20) and suggested negative correlation between oil and protein. In terms of sucrose content, a novel and major QTL were identified on Chr. 8 (qSuc_08) and harbours putative genes involved in sugar transport. In addition, genome-wide association using 91 342 SNPs confirmed the genomic loci derived from QTL mapping. A QTL-based haplotype using whole-genome resequencing of 106 diverse soybean lines identified unique allelic variation in wild soybean that could be utilized to widen the genetic base in cultivated soybean.

Genetic Architecture of Soybean Yield and Agronomic Traits

Soybean is the world's leading source of vegetable protein and demand for its seed continues to grow. Breeders have successfully increased soybean yield, but the genetic architecture of yield and key agronomic traits is poorly understood. We developed a 40-mating soybean nested association mapping (NAM) population of 5,600 inbred lines that were characterized by single nucleotide polymorphism (SNP) markers and six agronomic traits in field trials in 22 environments. Analysis of the yield, agronomic, and SNP data revealed 23 significant marker-trait associations for yield, 19 for maturity, 15 for plant height, 17 for plant lodging, and 29 for seed mass. A higher frequency of estimated positive yield alleles was evident from elite founder parents than from exotic founders, although unique desirable alleles from the exotic group were identified, demonstrating the value of expanding the genetic base of US soybean breeding.

Impact of seed protein alleles from three soybean sources on seed composition and agronomic traits

KEY MESSAGE

Evaluation of seed protein alleles in soybean populations showed that an increase in protein concentration is generally associated with a decrease in oil concentration and yield. Soybean [Glycine max (L.) Merrill] meal is one of the most important plant-based protein sources in the world. Developing cultivars high in seed protein concentration and seed yield is a difficult task because the traits have an inverse relationship. Over two decades ago, a protein quantitative trait loci (QTL) was mapped on chromosome (chr) 20, and this QTL has been mapped to the same position in several studies and given the confirmed QTL designation cqSeed protein-003. In addition, the wp allele on chr 2, which confers pink flower color, has also been associated with increased protein concentration. The objective of our study was to evaluate the effect of cqSeed protein-003 and the wp locus on seed composition and agronomic traits in elite soybean backgrounds adapted to the Midwestern USA. Segregating populations of isogenic lines were developed to test the wp allele and the chr 20 high protein QTL alleles from Danbaekkong (PI619083) and Glycine soja PI468916 at cqSeed protein-003. An increase in protein concentration and decrease in yield were generally coupled with the high protein alleles at cqSeed protein-003 across populations, whereas the effects of wp on protein concentration and yield were variable. These results not only demonstrate the difficulty in developing cultivars with increased protein and yield but also provide information for breeding programs seeking to improve seed composition and agronomic traits simultaneously.

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.

Identification of QTL with large effect on seed weight in a selective population of soybean with genome-wide association and fixation index analyses

BACKGROUND

Soybean seed weight is not only a yield component, but also a critical trait for various soybean food products such as sprouts, edamame, soy nuts, natto and miso. Linkage analysis and genome-wide association study (GWAS) are two complementary and powerful tools to connect phenotypic differences to the underlying contributing loci. Linkage analysis is based on progeny derived from two parents, given sufficient sample size and biological replication, it usually has high statistical power to map alleles with relatively small effect on phenotype, however, linkage analysis of the bi-parental population can't detect quantitative trait loci (QTL) that are fixed in the two parents. Because of the small seed weight difference between the two parents in most families of previous studies, these populations are not suitable to detect QTL that have considerable effects on seed weight. GWAS is based on unrelated individuals to detect alleles associated with the trait under investigation. The ability of GWAS to capture major seed weight QTL depends on the frequency of the accessions with small and large seed weight in the population being investigated. Our objective was to identify QTL that had a pronounced effect on seed weight using a selective population of soybean germplasm accessions and the approach of GWAS and fixation index analysis.

RESULTS

We selected 166 accessions from the USDA Soybean Germplasm Collection with either large or small seed weight and could typically grow in the same location. The accessions were evaluated for seed weight in the field for two years and genotyped with the SoySNP50K BeadChip containing >42,000 SNPs. Of the 17 SNPs on six chromosomes that were significantly associated with seed weight in two years based on a GWAS of the selective population, eight on chromosome 4 or chromosome 17 had significant Fst values between the large and small seed weight sub-populations. The seed weight difference of the two alleles of these eight significant SNPs varied from 8.1 g to 11.7 g/100 seeds in two years. We also identified haplotypes in three haplotype blocks with significant effects on seed weight. These findings were validated in a panel with 3753 accessions from the USDA Soybean Germplasm Collection.

CONCLUSION

This study highlighted the usefulness of selective genotyping populations coupled with GWAS and fixation index analysis for the identification of QTL with substantial effects on seed weight in soybean. This approach may help geneticists and breeders to more efficiently identify major QTL controlling other traits. The major regions and haplotypes we have identified that control seed weight differences in soybean will facilitate the identification of genes regulating this important trait.