Soybean [Glycine max (L.) Merr.] is a versatile crop due to its multitude of uses as a high protein meal and vegetable oil. Soybean seed traits such as seed protein and oil concentration and seed size are important quantitative traits. The objective of this study was to identify representative protein, oil, and seed size quantitative trait loci (QTL) in soybean. A recombinant inbred line (RIL) population consisting of 131 F6-derived lines was created from two prominent ancestors of North American soybeans ('Essex' and 'Williams') and the RILs were grown in six environments. One hundred simple sequence repeat (SSR) markers spaced throughout the genome were mapped in this population. There were a total of four protein, six oil, and seven seed size QTL found in this population. The QTL found in this study may assist breeders in marker-assisted selection (MAS) to retain current positive QTL in modern soybeans while simultaneously pyramiding additional QTL from new germplasm.

Background Plants have evolved intimate interactions with soil microbes for a range of beneficial functions including nutrient acquisition, pathogen resistance and stress tolerance. Further understanding of this system is a promising way to advance sustainable agriculture by exploiting the versatile benefits offered by the plant microbiome. The rhizosphere is the interface between plant and soil, and functions as the first step of plant defense and root microbiome recruitment. It features a specialized microbial community, intensive microbe-plant and microbe-microbe interactions, and complex signal communication. To decipher the rhizosphere microbiome assembly of soybean ( Glycine max ), we comprehensively characterized the soybean rhizosphere microbial community using 16S rRNA gene sequencing and evaluated the structuring influence from both host genotype and soil source. Results Comparison of the soybean rhizosphere to bulk soil revealed significantly different microbiome composition, microbe-microbe interactions and metabolic capacity. Soil type and soybean genotype cooperatively modulated microbiome assembly with soil type predominantly shaping rhizosphere microbiome assembly while host genotype slightly tuned this recruitment process. The undomesticated progenitor species, Glycine soja , had higher rhizosphere diversity in both soil types tested in comparison to the domesticated soybean genotypes. Rhizobium , Novosphingobium , Phenylobacterium , Streptomyces , Nocardioides, etc. were robustly enriched in soybean rhizosphere irrespective of the soil tested. Co-occurrence network analysis revealed dominant soil type effects and genotype specific preferences for key microbe-microbe interactions. Functional prediction results demonstrated converged metabolic capacity in the soybean rhizosphere between soil types and among genotypes, with pathways related to xenobiotic degradation, plant-microbe interactions and nutrient transport being greatly enriched in the rhizosphere. Conclusion This comprehensive comparison of the soybean microbiome between soil types and genotypes expands our understanding of rhizosphere microbe assembly in general and provides foundational information for soybean as a legume crop for this assembly process. The cooperative modulating role of the soil type and host genotype emphasizes the importance of integrated consideration of soil condition and plant genetic variability for future development and application of synthetic microbiomes. Additionally, the detection of the tuning role by soybean genotype in rhizosphere microbiome assembly provides a promising way for future breeding programs to integrate host traits participating in beneficial microbiota assembly. Electronic supplementary material The o...

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. AbstractMeal 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.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-017-2955-8) contains supplementary material, which is available to authorized users.

to increase the concentration of one at the expense of the other. Soybean [Glycine max (L.) Merr.] is an important crop becauseHardiness, brittleness, and gumminess are important of its high oil and protein concentration. However, there is an inverse relationship between seed protein and oil concentration, making it physical properties, which determine the overall quality difficult to improve both traits simultaneously. Molecular breeding of tofu. Protein concentration, particularly glycinin, demay be helpful to facilitate a balanced accumulation of desirable termines these properties in tofu, whereas seed size dealleles. The objective of this study was to identify quantitative trait termines the quality of soy sprouts (Liu, 1997). Small loci (QTL) governing soybean protein, oil and seed size. To achieve seeded soybeans are generally desired for high quality this objective, 101 F 6 -derived recombinant inbred lines (RIL) from soy sprouts and natto production, and combining higher a population developed from a cross of N87-984-16 ϫ TN93-99 were protein with large seed size is desirable for tofu producused. Heritability estimates on an entry mean basis for protein and tion. Genomic regions for seed size along with protein oil concentrations, and seed size were 0.66, 0.54, and 0.71, respectively. and oil QTL could be used in marker-assisted selection A total of 585 simple sequence repeat (SSR) molecular genetic mark-(MAS) for desired soybean types for soy food appliers were screened and 94 were polymorphic in the RIL. Single factor ANOVA was used to identify candidate QTL, which were then con-cations. firmed by composite interval mapping. One novel molecular marker Despite moderately high heritabilities (Burton, 1987), (Satt570) on molecular linkage group (MLG) G associated with a it is difficult to improve seed traits, particularly protein protein QTL was detected. Novel molecular markers (Satt274, Satt420, and oil concentration, simultaneously. MAS might be useand Satt479) located on MLG D1b, O, and O respectively and a ful in achieving specific goals if genomic regions controlpreviously reported marker (Satt317) located on MLG H were associling protein and oil concentration and seed size could be ated with oil QTL in this study. Molecular markers Satt002 (MLG D2) identified to improve selection indices more precisely. and Satt184 (MLG D1a) associated with seed size QTL were verified Several researchers have paved the way toward this whereas Satt147 (MLG D1a) was novel. The individual QTL explained goal (Brummer et al., 1997; Chung et al., 2003; Diers et 20.2, 9.4-15, and 10 to 16.5% of the phenotypic variation for protein al., 1992;Lee et al., 2001; Lee et al., 1996c). Qiu et al. and oil concentrations, and seed size, respectively. Thus, we identified major loci for improving soybean seed quality.

BackgroundA landmark in soybean research, Glyma1.01, the first whole genome sequence of variety Williams 82 (Glycine max L. Merr.) was completed in 2010 and is widely used. However, because the assembly was primarily built based on the linkage maps constructed with a limited number of markers and recombinant inbred lines (RILs), the assembled sequence, especially in some genomic regions with sparse numbers of anchoring markers, needs to be improved. Molecular markers are being used by researchers in the soybean community, however, with the updating of the Glyma1.01 build based on the high-resolution linkage maps resulting from this research, the genome positions of these markers need to be mapped.ResultsTwo high density genetic linkage maps were constructed based on 21,478 single nucleotide polymorphism loci mapped in the Williams 82 x G. soja (Sieb. & Zucc.) PI479752 population with 1083 RILs and 11,922 loci mapped in the Essex x Williams 82 population with 922 RILs. There were 37 regions or single markers where marker order in the two populations was in agreement but was not consistent with the physical position in the Glyma1.01 build. In addition, 28 previously unanchored scaffolds were positioned. Map data were used to identify false joins in the Glyma1.01 assembly and the corresponding scaffolds were broken and reassembled to the new assembly, Wm82.a2.v1. Based upon the plots of the genetic on physical distance of the loci, the euchromatic and heterochromatic regions along each chromosome in the new assembly were delimited. Genomic positions of the commonly used markers contained in BARCSOYSSR_1.0 database and the SoySNP50K BeadChip were updated based upon the Wm82.a2.v1 assembly.ConclusionsThe information will facilitate the study of recombination hot spots in the soybean genome, identification of genes or quantitative trait loci controlling yield, seed quality and resistance to biotic or abiotic stresses as well as other genetic or genomic research.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2344-0) contains supplementary material, which is available to authorized users.