Complementary genetic and genomic approaches help characterize the linkage group I seed protein QTL in soybean

Identification of Gene-Allele System Conferring Alkali-Tolerance at Seedling Stage in Northeast China Soybean Germplasm

Salinization of cultivated soils may result in either high salt levels or alkaline conditions, both of which stress crops and reduce performance. We sampled genotypes included in the Northeast China soybean germplasm population (NECSGP) to identify possible genes that affect tolerance to alkaline soil conditions. In this study, 361 soybean accessions collected in Northeast China were tested under 220 mM NaHCO3:Na2CO3 = 9:1 (pH = 9.8) to evaluate the alkali-tolerance (ATI) at the seedling stage in Mudanjiang, Heilongjiang, China. The restricted two-stage multi-locus model genome-wide association study (RTM-GWAS) with gene-allele sequences as markers (6503 GASMs) based on simplified genome resequencing (RAD-sequencing) was accomplished. From this analysis, 132 main effect candidate genes with 359 alleles and 35 Gene × Environment genes with 103 alleles were identified, explaining 90.93% and 2.80% of the seedling alkali-tolerance phenotypic variation, respectively. Genetic variability of ATI in NECSGP was observed primarily within subpopulations, especially in ecoregion B, from which 80% of ATI-tolerant accessions were screened out. The biological functions of 132 candidate genes were classified into eight functional categories (defense response, substance transport, regulation, metabolism-related, substance synthesis, biological process, plant development, and unknown function). From the ATI gene-allele system, six key genes-alleles were identified as starting points for further study on understanding the ATI gene network.

Exploring SoySNP50K and USDA Germplasm Collection Data to Find New QTLs Associated with Protein and Oil Content in Brazilian Genotypes

Genetic diversity within a germplasm collection plays a vital role in the success of breeding programs. However, comprehending this diversity and identifying accessions with desirable traits pose significant challenges. This study utilized publicly available data to investigate SNP markers associated with protein and oil content in Brazilian soybeans. Through this research, twenty-two new QTLs (Quantitative Trait Loci) were identified, and we highlighted the substantial influence of Roanoke, Lee and Bragg ancestor on the genetic makeup of Brazilian soybean varieties. Our findings demonstrate that certain markers are being lost in modern cultivars, while others maintain or even increase their frequency. These observations indicate genomic regions that have undergone selection during soybean introduction in Brazil and could be valuable in breeding programs aimed at enhancing protein or oil content.

Introgression of a Danbaekkong high-protein allele across different genetic backgrounds in soybean

Soybean meal is a major component of livestock feed due to its high content and quality of protein. Understanding the genetic control of protein is essential to develop new cultivars with improved meal protein. Previously, a genomic region on chromosome 20 significantly associated with elevated protein content was identified in the cultivar Danbaekkong. The present research aimed to introgress the Danbaekkong high-protein allele into elite lines with different genetic backgrounds by developing and deploying robust DNA markers. A multiparent population consisting of 10 F5-derived populations with a total of 1,115 recombinant inbred lines (RILs) was developed using "Benning HP" as the donor parent of the Danbaekkong high-protein allele. A new functional marker targeting the 321-bp insertion in the gene Glyma.20g085100 was developed and used to track the Danbaekkong high-protein allele across the different populations and enable assessment of its effect and stability. Across all populations, the high-protein allele consistently increased the content, with an increase of 3.3% in seed protein. A total of 103 RILs were selected from the multiparent population for yield testing in five environments to assess the impact of the high-protein allele on yield and to enable the selection of new breeding lines with high protein and high yield. The results indicated that the high-protein allele impacts yield negatively in general; however, it is possible to select high-yielding lines with high protein content. An analysis of inheritance of the Chr 20 high-protein allele in Danbaekkong indicated that it originated from a Glycine soja line (PI 163453) and is the same as other G. soja lines studied. A survey of the distribution of the allele across 79 G. soja accessions and 35 Glycine max ancestors of North American soybean cultivars showed that the high-protein allele is present in all G. soja lines evaluated but not in any of the 35 North American soybean ancestors. These results demonstrate that G. soja accessions are a valuable source of favorable alleles for improvement of protein composition.

QTLs and Candidate Genes for Seed Protein Content in Two Recombinant Inbred Line Populations of Soybean

This study aimed to discover the quantitative trait loci (QTL) associated with a high seed protein content in soybean and unravel the potential candidate genes. We developed two recombinant inbred line populations: YS and SI, by crossing Saedanbaek (high protein) with YS2035-B-91-1-B-1 (low protein) and Saedanbaek with Ilmi (low protein), respectively, and evaluated the protein content for three consecutive years. Using single-nucleotide polymorphism (SNP)-marker-based linkage maps, four QTLs were located on chromosomes 15, 18, and 20 with high logarithm of odds values (5.9-55.0), contributing 5.5-66.0% phenotypic variance. In all three experimental years, qPSD20-1 and qPSD20-2 were stable and identified in overlapping positions in the YS and SI populations, respectively. Additionally, novel QTLs were identified on chromosomes 15 and 18. Considering the allelic sequence variation between parental lines, 28 annotated genes related to soybean seed protein-including starch, lipid, and fatty acid biosynthesis-related genes-were identified within the QTL regions. These genes could potentially affect protein accumulation during seed development, as well as sucrose and oil metabolism. Overall, this study offers insights into the genetic mechanisms underlying a high soybean protein content. The identified potential candidate genes can aid marker-assisted selection for developing soybean lines with an increased protein content.

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.

Quantitative Trait Loci (QTL) Analysis of Seed Protein and Oil Content in Wild Soybean (Glycine soja)

Soybean seeds consist of approximately 40% protein and 20% oil, making them one of the world's most important cultivated legumes. However, the levels of these compounds are negatively correlated with each other and regulated by quantitative trait loci (QTL) that are controlled by several genes. In this study, a total of 190 F₂ and 90 BC₁F₂ plants derived from a cross of Daepung (Glycine max) with GWS-1887 (G. soja, a source of high protein), were used for the QTL analysis of protein and oil content. In the F_2:3 populations, the average protein and oil content was 45.52% and 11.59%, respectively. A QTL associated with protein levels was detected at Gm20_29512680 on chr. 20 with a likelihood of odds (LOD) of 9.57 and an R² of 17.2%. A QTL associated with oil levels was also detected at Gm15_3621773 on chr. 15 (LOD: 5.80; R²: 12.2%). In the BC₁F_2:3 populations, the average protein and oil content was 44.25% and 12.14%, respectively. A QTL associated with both protein and oil content was detected at Gm20_27578013 on chr. 20 (LOD: 3.77 and 3.06; R² 15.8% and 10.7%, respectively). The crossover to the protein content of BC₁F_3:4 population was identified by SNP marker Gm20_32603292. Based on these results, two genes, Glyma.20g088000 (S-adenosyl-l-methionine-dependent methyltransferases) and Glyma.20g088400 (oxidoreductase, 2-oxoglutarate-Fe(II) oxygenase family protein), in which the amino acid sequence had changed and a stop codon was generated due to an InDel in the exon region, were identified.

Soybean Protein and Oil Variants Identified through a Forward Genetic Screen for Seed Composition

Mutagenesis remains an important tool in soybean biology. In classical plant mutation breeding, mutagenesis has been a trusted approach for decades, creating stable non-transgenic variation, and many mutations have been incorporated into germplasm for several crops, especially to introduce favorable seed composition traits. We performed a genetic screen for aberrant oil or protein composition of soybean seeds, and as a result isolated over 100 mutant lines for seed composition phenotypes, with particular interest in high protein or high oil phenotypes. These lines were followed for multiple seasons and generations to select the most stable traits for further characterization. Through backcrossing and outcrossing experiments, we determined that a subset of the lines showed recessive inheritance, while others showed a dominant inheritance pattern that suggests the involvement of multiple loci and genetic mechanisms. These lines can be used as a resource for future studies of the genetic control of seed protein and oil content in soybean.

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.

Ensuring Global Food Security by Improving Protein Content in Major Grain Legumes Using Breeding and 'Omics' Tools

Grain legumes are a rich source of dietary protein for millions of people globally and thus a key driver for securing global food security. Legume plant-based 'dietary protein' biofortification is an economic strategy for alleviating the menace of rising malnutrition-related problems and hidden hunger. Malnutrition from protein deficiency is predominant in human populations with an insufficient daily intake of animal protein/dietary protein due to economic limitations, especially in developing countries. Therefore, enhancing grain legume protein content will help eradicate protein-related malnutrition problems in low-income and underprivileged countries. Here, we review the exploitable genetic variability for grain protein content in various major grain legumes for improving the protein content of high-yielding, low-protein genotypes. We highlight classical genetics-based inheritance of protein content in various legumes and discuss advances in molecular marker technology that have enabled us to underpin various quantitative trait loci controlling seed protein content (SPC) in biparental-based mapping populations and genome-wide association studies. We also review the progress of functional genomics in deciphering the underlying candidate gene(s) controlling SPC in various grain legumes and the role of proteomics and metabolomics in shedding light on the accumulation of various novel proteins and metabolites in high-protein legume genotypes. Lastly, we detail the scope of genomic selection, high-throughput phenotyping, emerging genome editing tools, and speed breeding protocols for enhancing SPC in grain legumes to achieve legume-based dietary protein security and thus reduce the global hunger risk.

Haplotype mapping uncovers unexplored variation in wild and domesticated soybean at the major protein locus cqProt-003

KEY MESSAGE

The major soy protein QTL, cqProt-003, was analysed for haplotype diversity and global distribution, and results indicate 304 bp deletion and variable tandem repeats in protein coding regions are likely causal candidates. Here, we present association and linkage analysis of 985 wild, landrace and cultivar soybean accessions in a pan genomic dataset to characterize the major high-protein/low-oil associated locus cqProt-003 located on chromosome 20. A significant trait-associated region within a 173 kb linkage block was identified, and variants in the region were characterized, identifying 34 high confidence SNPs, 4 insertions, 1 deletion and a larger 304 bp structural variant in the high-protein haplotype. Trinucleotide tandem repeats of variable length present in the second exon of gene Glyma.20G085100 are strongly correlated with the high-protein phenotype and likely represent causal variation. Structural variation has previously been found in the same gene, for which we report the global distribution of the 304 bp deletion and have identified additional nested variation present in high-protein individuals. Mapping variation at the cqProt-003 locus across demographic groups suggests that the high-protein haplotype is common in wild accessions (94.7%), rare in landraces (10.6%) and near absent in cultivated breeding pools (4.1%), suggesting its decrease in frequency primarily correlates with domestication and continued during subsequent improvement. However, the variation that has persisted in under-utilized wild and landrace populations holds high breeding potential for breeders willing to forego seed oil to maximize protein content. The results of this study include the identification of distinct haplotype structures within the high-protein population, and a broad characterization of the genomic context and linkage patterns of cqProt-003 across global populations, supporting future functional characterization and modification.

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.

Genome-Wide Mapping of Cytosine Methylation Revealed Dynamic DNA Methylation Patterns Associated with Sporophyte Development of Saccharina japonica

Cytosine methylation plays vital roles in regulating gene expression and plant development. However, the function of DNA methylation in the development of macroalgae remains unclear. Through the genome-wide bisulfite sequencing of cytosine methylation in holdfast, stipe and blade, we obtained the complete 5-mC methylation landscape of Saccharina japonica sporophyte. Our results revealed that the total DNA methylation level of sporophyte was less than 0.9%, and the content of CHH contexts was dominant. Moreover, the distribution of CHH methylation within the genes exhibited exon-enriched characteristics. Profiling of DNA methylation in three parts revealed the diverse methylation pattern of sporophyte development. These pivotal DMRs were involved in cell motility, cell cycle and cell wall/membrane biogenesis. In comparison with stipe and blade, hypermethylation of mannuronate C5-epimerase in holdfast decreased the transcript abundance, which affected the synthesis of alginate, the key component of cell walls. Additionally, 5-mC modification participated in the regulation of blade and holdfast development by the glutamate content respectively via glutamine synthetase and amidophosphoribosyl transferase, which may act as the epigenetic regulation signal. Overall, our study revealed the global methylation characteristics of the well-defined holdfast, stipe and blade, and provided evidence for epigenetic regulation of sporophyte development in brown macroalgae.

Genetic mapping high protein content QTL from soybean 'Nanxiadou 25' and candidate gene analysis

BACKGROUND

Soybean is a globally important legume crop that provides a primary source of high-quality vegetable protein and oil. Seed protein content (SPC) is a valuable quality trait controlled by multiple genes in soybean.

RESULTS

In this study, we performed quantitative trait loci (QTL) mapping, QTL-seq, and RNA sequencing (RNA-seq) to reveal the genes controlling protein content in the soybean by using the high protein content variety Nanxiadou 25. A total of 50 QTL for SPC distributed on 14 chromosomes except chromosomes 4, 12, 14, 17, 18, and 19 were identified by QTL mapping using 178 recombinant inbred lines (RILs). Among these QTL, the major QTL qSPC_20-1 and qSPC_20-2 on chromosome 20 were repeatedly detected across six tested environments, corresponding to the location of the major QTL detected using whole-genome sequencing-based QTL-seq. 329 candidate DEGs were obtained within the QTL region of qSPC_20-1 and qSPC_20-2 via gene expression profile analysis. Nine of which were associated with SPC, potentially representing candidate genes. Clone sequencing results showed that different single nucleotide polymorphisms (SNPs) and indels between high and low protein genotypes in Glyma.20G088000 and Glyma.16G066600 may be the cause of changes in this trait.

CONCLUSIONS

These results provide the basis for research on candidate genes and marker-assisted selection (MAS) in soybean breeding for seed protein content.

Dissecting the Genetic Architecture of Seed Protein and Oil Content in Soybean from the Yangtze and Huaihe River Valleys Using Multi-Locus Genome-Wide Association Studies

Soybean is a globally important legume crop that provides a primary source of high-quality vegetable protein and oil. Seed protein and oil content are two valuable quality traits controlled by multiple genes in soybean. In this study, the restricted two-stage multi-locus genome-wide association analysis (RTM-GWAS) procedure was performed to dissect the genetic architecture of seed protein and oil content in a diverse panel of 279 soybean accessions from the Yangtze and Huaihe River Valleys in China. We identified 26 quantitative trait loci (QTLs) for seed protein content and 23 for seed oil content, including five associated with both traits. Among these, 39 QTLs corresponded to previously reported QTLs, whereas 10 loci were novel. As reported previously, the QTL on chromosome 20 was associated with both seed protein and oil content. This QTL exhibited opposing effects on these traits and contributed the most to phenotype variation. From the detected QTLs, 55 and 51 candidate genes were identified for seed protein and oil content, respectively. Among these genes, eight may be promising candidate genes for improving soybean nutritional quality. These results will facilitate marker-assisted selective breeding for soybean protein and oil content traits.

Eco-Friendly Iron-Humic Nanofertilizers Synthesis for the Prevention of Iron Chlorosis in Soybean (Glycine max) Grown in Calcareous Soil

Iron deficiency is a frequent problem for many crops, particularly in calcareous soils and iron humates are commonly applied in the Mediterranean basin in spite of their lesser efficiency than iron synthetic chelates. Development and application of new fertilizers using nanotechnology are one of the potentially effective options of enhancing the iron humates, according to the sustainable agriculture. Particle size, pH, and kinetics constrain the iron humate efficiency. Thus, it is relevant to understand the iron humate mechanism in the plant-soil system linking their particle size, characterization and iron distribution in plant and soil using ⁵⁷Fe as a tracer tool. Three hybrid nanomaterials (F, S, and M) were synthesized as iron-humic nanofertilizers (⁵⁷Fe-NFs) from leonardite potassium humate and ⁵⁷Fe used in the form of ⁵⁷Fe(NO₃)₃ or ⁵⁷Fe₂(SO₄)₃. They were characterized using Mössbauer spectroscopy, X-ray diffraction (XRD), extended X-ray absorption fine structure spectroscopy (EXAFS), transmission electron microscopy (TEM) and tested for iron availability in a calcareous soil pot experiment carried out under growth chamber conditions. Three doses (35, 75, and 150 μmol pot^-1) of each iron-humic material were applied to soybean iron deficient plants and their iron nutrition contributions were compared to ⁵⁷FeEDDHA and leonardite potassium humate as control treatments. Ferrihydrite was detected as the main structure of all three ⁵⁷Fe-NFs and the plants tested with iron-humic compounds exhibited continuous long-term statistically reproducible iron uptake and showed high shoot fresh weight. Moreover, the ⁵⁷Fe from the humic nanofertilizers remained available in soil and was detected in soybean pods. The Fe-NFs offers a natural, low cost and environmental option to the traditional iron fertilization in calcareous soils.

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.

Development of sequence-based markers for seed protein content in pigeonpea

Pigeonpea is an important source of dietary protein to over a billion people globally, but genetic enhancement of seed protein content (SPC) in the crop has received limited attention for a long time. Use of genomics-assisted breeding would facilitate accelerating genetic gain for SPC. However, neither genetic markers nor genes associated with this important trait have been identified in this crop. Therefore, the present study exploited whole genome re-sequencing (WGRS) data of four pigeonpea genotypes (~ 12X coverage) to identify sequence-based markers and associated candidate genes for SPC. By combining a common variant filtering strategy on available WGRS data with knowledge of gene functions in relation to SPC, 108 sequence variants from 57 genes were identified. These genes were assigned to 19 GO molecular function categories with 56% belonging to only two categories. Furthermore, Sanger sequencing confirmed presence of 75.4% of the variants in 37 genes. Out of 30 sequence variants converted into CAPS/dCAPS markers, 17 showed high level of polymorphism between low and high SPC genotypes. Assay of 16 of the polymorphic CAPS/dCAPS markers on an F₂ population of the cross ICP 5529 (high SPC) × ICP 11605 (low SPC), resulted in four of the CAPS/dCAPS markers significantly (P < 0.05) co-segregated with SPC. In summary, four markers derived from mutations in four genes will be useful for enhancing/regulating SPC in pigeonpea crop improvement programs.

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.

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.

Identification of quantitative trait loci underlying seed protein content of soybean including main, epistatic, and QTL × environment effects in different regions of Northeast China

The objective here was to identify QTL underlying soybean protein content (PC), and to evaluate the additive and epistatic effects of the QTLs. A mapping population, consisting of 129 recombinant inbred lines (RILs), was created by crossing 'Dongnong 46' and 'L-100'. Phenotypic data of the parents and RILs were collected for 4 years in three locations of Heilongjiang Province of China. A total of 213 SSR markers were used to construct a genetic linkage map. Eight QTLs, located on seven chromosomes (Chr), were identified to be associated with PC among the 10 tested environments. Of the seven QTLs, five QTLs, qPR-2 (Satt710, on Chr9), qPR-3 (Sat_122, on Chr12), qPR-5 (Satt543, on Chr17), qPR-7 (Satt163, on Chr18), and qPR-8 (Satt614, on Chr20), were detected in six, seven, seven, six, and seven environments, respectively, implying relatively stable QTLs. qPR-3 could explain 3.33%-11.26% of the phenotypic variation across eight tested environments. qPR-5 and qPR-8 explained 3.64%-10.1% and 11.86%-18.40% of the phenotypic variation, respectively, across seven tested environments. Eight QTLs associated with PC exhibited additive and (or) additive × environment interaction effects. The results showed that environment-independent QTLs often had higher additive effects. Moreover, five epistatic pairwise QTLs were identified in the 10 environments.

Identification of Major Quantitative Trait Loci for Seed Oil Content in Soybeans by Combining Linkage and Genome-Wide Association Mapping

Soybean oil is the most widely produced vegetable oil in the world and its content in soybean seed is an important quality trait in breeding programs. More than 100 quantitative trait loci (QTLs) for soybean oil content have been identified. However, most of them are genotype specific and/or environment sensitive. Here, we used both a linkage and association mapping methodology to dissect the genetic basis of seed oil content of Chinese soybean cultivars in various environments in the Jiang-Huai River Valley. One recombinant inbred line (RIL) population (NJMN-RIL), with 104 lines developed from a cross between M8108 and NN1138-2, was planted in five environments to investigate phenotypic data, and a new genetic map with 2,062 specific-locus amplified fragment markers was constructed to map oil content QTLs. A derived F2 population between MN-5 (a line of NJMN-RIL) and NN1138-2 was also developed to confirm one major QTL. A soybean breeding germplasm population (279 lines) was established to perform a genome-wide association study (GWAS) using 59,845 high-quality single nucleotide polymorphism markers. In the NJMN-RIL population, 8 QTLs were found that explained a range of phenotypic variance from 6.3 to 26.3% in certain planting environments. Among them, qOil-5-1, qOil-10-1, and qOil-14-1 were detected in different environments, and qOil-5-1 was further confirmed using the secondary F2 population. Three loci located on chromosomes 5 and 20 were detected in a 2-year long GWAS, and one locus that overlapped with qOil-5-1 was found repeatedly and treated as the same locus. qOil-5-1 was further localized to a linkage disequilibrium block region of approximately 440 kb. These results will not only increase our understanding of the genetic control of seed oil content in soybean, but will also be helpful in marker-assisted selection for breeding high seed oil content soybean and gene cloning to elucidate the mechanisms of seed oil content.

Fine-mapping qFS07.1 controlling fiber strength in upland cotton (Gossypium hirsutum L.)

KEY MESSAGE: qFS07.1 controlling fiber strength was fine-mapped to a 62.6-kb region containing four annotated genes. RT-qPCR and sequence of candidate genes identified an LRR RLK gene as the most likely candidate. Fiber strength is an important component of cotton fiber quality and is associated with other properties, such as fiber maturity, fineness, and length. Stable QTL qFS07.1, controlling fiber strength, had been identified on chromosome 7 in an upland cotton recombinant inbred line (RIL) population from a cross (CCRI35 × Yumian1) described in our previous studies. To fine-map qFS07.1, an F₂ population with 2484 individual plants from a cross between recombinant line RIL014 and CCRI35 was established. A total of 1518 SSR primer pairs, including 1062, designed from chromosome 1 of the Gossypium raimondii genome and 456 from chromosome 1 of the G. arboreum genome (corresponding to the QTL region) were used to fine-map qFS07.1, and qFS07.1 was mapped into a 62.6-kb genome region which contained four annotated genes on chromosome A07 of G. hirsutum. RT-qPCR and comparative analysis of candidate genes revealed a leucine-rich repeat protein kinase (LRR RLK) family protein to be a promising candidate gene for qFS07.1. Fine mapping and identification of the candidate gene for qFS07.1 will play a vital role in marker-assisted selection (MAS) and the study of mechanism of cotton fiber development.

QTLomics in Soybean: A Way Forward for Translational Genomics and Breeding

Food legumes play an important role in attaining both food and nutritional security along with sustainable agricultural production for the well-being of humans globally. The various traits of economic importance in legume crops are complex and quantitative in nature, which are governed by quantitative trait loci (QTLs). Mapping of quantitative traits is a tedious and costly process, however, a large number of QTLs has been mapped in soybean for various traits albeit their utilization in breeding programmes is poorly reported. For their effective use in breeding programme it is imperative to narrow down the confidence interval of QTLs, to identify the underlying genes, and most importantly allelic characterization of these genes for identifying superior variants. In the field of functional genomics, especially in the identification and characterization of gene responsible for quantitative traits, soybean is far ahead from other legume crops. The availability of genic information about quantitative traits is more significant because it is easy and effective to identify homologs than identifying shared syntenic regions in other crop species. In soybean, genes underlying QTLs have been identified and functionally characterized for phosphorous efficiency, flowering and maturity, pod dehiscence, hard-seededness, α-Tocopherol content, soybean cyst nematode, sudden death syndrome, and salt tolerance. Candidate genes have also been identified for many other quantitative traits for which functional validation is required. Using the sequence information of identified genes from soybean, comparative genomic analysis of homologs in other legume crops could discover novel structural variants and useful alleles for functional marker development. The functional markers may be very useful for molecular breeding in soybean and harnessing benefit of translational research from soybean to other leguminous crops. Thus, soybean crop can act as a model crop for translational genomics and breeding of quantitative traits in legume crops. In this review, we summarize current status of identification and characterization of genes underlying QTLs for various quantitative traits in soybean and their significance in translational genomics and breeding of other legume crops.

Effect of tris(3-hydroxy-4-pyridinonate) iron(III) complexes on iron uptake and storage in soybean (Glycine max L.)

Iron deficiency chlorosis (IDC) is a serious environmental problem affecting the growth of several crops in the world. The application of synthetic Fe(III) chelates is still one of the most common measures to correct IDC and the search for more effective Fe chelates remains an important issue. Herein, we propose a tris(3-hydroxy-4-pyridinonate) iron(III) complex, Fe(mpp)3, as an IDC corrector. Different morphological, biochemical and molecular parameters were assessed as a first step towards understanding its mode of action, compared with that of the commercial fertilizer FeEDDHA. Plants treated with the pyridinone iron(III) complexes were significantly greener and had increased biomass. The total Fe content was measured using ICP-OES and plants treated with pyridinone complexes accumulated about 50% more Fe than those treated with the commercial chelate. In particular, plants supplied with compound Fe(mpp)3 were able to translocate iron from the roots to the shoots and did not elicit the expression of the Fe-stress related genes FRO2 and IRT1. These results suggest that 3,4-HPO iron(III) chelates could be a potential new class of plant fertilizing agents.

Mapping by sequencing in cotton (Gossypium hirsutum) line MD52ne identified candidate genes for fiber strength and its related quality attributes

Three QTL regions controlling three fiber quality traits were validated and further fine-mapped with 27 new single nucleotide polymorphism (SNP) markers. Transcriptome analysis suggests that receptor-like kinases found within the validated QTLs are potential candidate genes responsible for superior fiber strength in cotton line MD52ne. Fiber strength, length, maturity and fineness determine the market value of cotton fibers and the quality of spun yarn. Cotton fiber strength has been recognized as a critical quality attribute in the modern textile industry. Fine mapping along with quantitative trait loci (QTL) validation and candidate gene prediction can uncover the genetic and molecular basis of fiber quality traits. Four previously-identified QTLs (qFBS-c3, qSFI-c14, qUHML-c14 and qUHML-c24) related to fiber bundle strength, short fiber index and fiber length, respectively, were validated using an F3 population that originated from a cross of MD90ne × MD52ne. A group of 27 new SNP markers generated from mapping-by-sequencing (MBS) were placed in QTL regions to improve and validate earlier maps. Our refined QTL regions spanned 4.4, 1.8 and 3.7 Mb of physical distance in the Gossypium raimondii reference genome. We performed RNA sequencing (RNA-seq) of 15 and 20 days post-anthesis fiber cells from MD52ne and MD90ne and aligned reads to the G. raimondii genome. The QTL regions contained 21 significantly differentially expressed genes (DEGs) between the two near-isogenic parental lines. SNPs that result in non-synonymous substitutions to amino acid sequences of annotated genes were identified within these DEGs, and mapped. Taken together, transcriptome and amino acid mutation analysis indicate that receptor-like kinase pathway genes are likely candidates for superior fiber strength and length in MD52ne. MBS along with RNA-seq demonstrated a powerful strategy to elucidate candidate genes for the QTLs that control complex traits in a complex genome like tetraploid upland cotton.

Fine mapping and RNA-Seq unravels candidate genes for a major QTL controlling multiple fiber quality traits at the T1 region in upland cotton

BACKGROUND

Improving fiber quality is a major challenge in cotton breeding, since the molecular basis of fiber quality traits is poorly understood. Fine mapping and candidate gene prediction of quantitative trait loci (QTL) controlling cotton fiber quality traits can help to elucidate the molecular basis of fiber quality. In our previous studies, one major QTL controlling multiple fiber quality traits was identified near the T1 locus on chromosome 6 in Upland cotton.

RESULTS

To finely map this major QTL, the F2 population with 6975 individuals was established from a cross between Yumian 1 and a recombinant inbred line (RIL118) selected from a recombinant inbred line population (T586 × Yumian 1). The QTL was mapped to a 0.28-cM interval between markers HAU2119 and SWU2302. The QTL explained 54.7 % (LOD = 222.3), 40.5 % (LOD = 145.0), 50.0 % (LOD = 194.3) and 30.1 % (LOD = 100.4) of phenotypic variation with additive effects of 2.78, -0.43, 2.92 and 1.90 units for fiber length, micronaire, strength and uniformity, respectively. The QTL region corresponded to a 2.7-Mb interval on chromosome 10 in the G. raimondii genome sequence and a 5.3-Mb interval on chromosome A06 in G. hirsutum. The fiber of Yumian 1 was much longer than that of RIL118 from 3 DPA to 7 DPA. RNA-Seq of ovules at 0 DPA and fibers at 5 DPA from Yumian 1 and RIL118 showed four genes in the QTL region of the G. raimondii genome to be extremely differentially expressed. RT-PCR analysis showed three genes in the QTL region of the G. hirsutum genome to behave similarly.

CONCLUSIONS

This study mapped a major QTL influencing four fiber quality traits to a 0.28-cM interval and identified three candidate genes by RNA-Seq and RT-PCR analysis. Integration of fine mapping and RNA-Seq is a powerful strategy to uncover candidates for QTL in large genomes.

Landscape of genomic diversity and trait discovery in soybean

Cultivated soybean [Glycine max (L.) Merr.] is a primary source of vegetable oil and protein. We report a landscape analysis of genome-wide genetic variation and an association study of major domestication and agronomic traits in soybean. A total of 106 soybean genomes representing wild, landraces, and elite lines were re-sequenced at an average of 17x depth with a 97.5% coverage. Over 10 million high-quality SNPs were discovered, and 35.34% of these have not been previously reported. Additionally, 159 putative domestication sweeps were identified, which includes 54.34 Mbp (4.9%) and 4,414 genes; 146 regions were involved in artificial selection during domestication. A genome-wide association study of major traits including oil and protein content, salinity, and domestication traits resulted in the discovery of novel alleles. Genomic information from this study provides a valuable resource for understanding soybean genome structure and evolution, and can also facilitate trait dissection leading to sequencing-based molecular breeding.

Development of INDEL Markers for Genetic Mapping Based on Whole Genome Resequencing in Soybean

Soybean [Glycine max (L.) Merrill] is an important crop worldwide. In this study, a Chinese local soybean cultivar, Hedou 12, was resequenced by next generation sequencing technology to develop INsertion/DELetion (INDEL) markers for genetic mapping. 49,276 INDEL polymorphisms and 242,059 single nucleotide polymorphisms were detected between Hedou 12 and the Williams 82 reference sequence. Of these, 243 candidate INDEL markers ranging from 5-50 bp in length were chosen for validation, and 165 (68%) of them revealed polymorphisms between Hedou 12 and Williams 82. The validated INDEL markers were also tested in 12 other soybean cultivars. The number of polymorphisms in the pairwise comparisons of 14 soybean cultivars varied from 27 to 165. To test the utility of these INDEL markers, they were used to perform genetic mapping of a crinkly leaf mutant, and the CRINKLY LEAF locus was successfully mapped to a 360 kb region on chromosome 7. This research shows that high-throughput sequencing technologies can facilitate the development of genome-wide molecular markers for genetic mapping in soybean.

Soybean seeds overexpressing asparaginase exhibit reduced nitrogen concentration

In soybean seed, a correlation has been observed between the concentration of free asparagine at mid-maturation and protein concentration at maturity. In this study, a Phaseolus vulgaris K⁺ -dependent asparaginase cDNA, PvAspG2, was expressed in transgenic soybean under the control of the embryo specific promoter of the β-subunit of β-conglycinin. Three lines were isolated having high expression of the transgene at the transcript, protein and enzyme activity levels at mid-maturation, with a 20- to 40-fold higher asparaginase activity in embryo than a control line expressing β-glucuronidase. Increased asparaginase activity was associated with a reduction in free asparagine levels as a percentage of total free amino acids, by 11-18%, and an increase in free aspartic acid levels, by 25-60%. Two of the lines had reduced nitrogen concentration in mature seed as determined by nitrogen analysis, by 9-13%. Their levels of extractible globulins were reduced by 11-30%. This was accompanied by an increase in oil concentration, by 5-8%. The lack of change in nitrogen concentration in the third transgenic line was correlated with an increase in free glutamic acid levels by approximately 40% at mid-maturation.

The quest for tolerant varieties: the importance of integrating "omics" techniques to phenotyping

The primary objective of crop breeding is to improve yield and/or harvest quality while minimizing inputs. Global climate change and the increase in world population are significant challenges for agriculture and call for further improvements to crops and the development of new tools for research. Significant progress has been made in the molecular and genetic analysis of model plants. However, is science generating false expectations? Are 'omic techniques generating valuable information that can be translated into the field? The exploration of crop biodiversity and the correlation of cellular responses to stress tolerance at the plant level is currently a challenge. This viewpoint reviews concisely the problems one encounters when working on a crop and provides an outline of possible workflows when initiating cellular phenotyping via "-omic" techniques (transcriptomics, proteomics, metabolomics).

A near-isogenic line (NIL) collection in diploid strawberry and its use in the genetic analysis of morphologic, phenotypic and nutritional characters

First near-isogenic line collection in diploid strawberry, a tool for morphologic, phenotypic and nutritional QTL analysis. Diploid strawberry (Fragaria vesca), with a small genome, has a high degree of synteny with the octoploid cultivated strawberry (F. × ananassa), so can be used as a simplified model for genetic analysis of the octoploid species. Agronomically interesting traits are usually inherited quantitatively and they need to be studied in large segregating progenies well characterized with molecular markers. Near-isogenic lines (NILs) are tools to dissect quantitative characters and identify some of their components as Mendelian traits. NILs are fixed homozygous lines that share the same genetic background from a recurrent parent with a single introgression region from a donor parent. Here, we developed the first NIL collection in Fragaria, with F. vesca cv. Reine des Vallées as the recurrent parent and F. bucharica as the donor parent. A collection of 39 NILs was identified using a set of single sequence repeat markers. The NILs had an average introgression of 32 cM (6 % of genome) and were phenotyped over several years in two locations. This collection segregates for agronomic characters, such as flowering, germination, fruit size and shape, and nutritional content. At least 16 QTLs for morphological and reproductive traits, such as round fruits and vegetative propagation, and seven for nutritional traits such as sugar composition and total polyphenol content, were identified. The NIL collection of F. vesca can significantly facilitate understanding of the genetics of many traits and provide insight into the more complex F. × ananassa genome.

Identification of loci governing eight agronomic traits using a GBS-GWAS approach and validation by QTL mapping in soya bean

Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome-wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping-by-sequencing (GBS) approach was used to provide dense genome-wide marker coverage (>47,000 SNPs) for a panel of 304 short-season soya bean lines. A subset of 139 lines, representative of the diversity among these, was characterized phenotypically for eight traits under six environments (3 sites × 2 years). Marker coverage proved sufficient to ensure highly significant associations between the genes known to control simple traits (flower, hilum and pubescence colour) and flanking SNPs. Between one and eight genomic loci associated with more complex traits (maturity, plant height, seed weight, seed oil and protein) were also identified. Importantly, most of these GWAS loci were located within genomic regions identified by previously reported quantitative trait locus (QTL) for these traits. In some cases, the reported QTLs were also successfully validated by additional QTL mapping in a biparental population. This study demonstrates that integrating GBS and GWAS can be used as a powerful complementary approach to classical biparental mapping for dissecting complex traits in soya bean.

Detecting SNPs underlying domestication-related traits in soybean

BACKGROUND

Cultivated soybean (Glycine max) experienced a severe genetic bottleneck during its domestication and a further loss in diversity during its subsequent selection. Here, a panel of 65 wild (G. soja) and 353 cultivated accessions was genotyped at 552 single-nucleotide polymorphism loci to search for signals of selection during and after domestication.

RESULTS

The wild and cultivated populations were well differentiated from one another. Application of the Fst outlier test revealed 64 loci showing evidence for selection. Of these, 35 related to selection during domestication, while the other 29 likely gradually became monomorphic as a result of prolonged selection during post domestication. Two of the SNP locus outliers were associated with testa color.

CONCLUSIONS

Identifying genes controlling domestication-related traits is important for maintaining the diversity of crops. SNP locus outliers detected by a combined forward genetics and population genetics approach can provide markers with utility for the conservation of wild accessions and for trait improvement in the cultivated genepool.

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.

Integrating omic approaches for abiotic stress tolerance in soybean

Soybean production is greatly influenced by abiotic stresses imposed by environmental factors such as drought, water submergence, salt, and heavy metals. A thorough understanding of plant response to abiotic stress at the molecular level is a prerequisite for its effective management. The molecular mechanism of stress tolerance is complex and requires information at the omic level to understand it effectively. In this regard, enormous progress has been made in the omics field in the areas of genomics, transcriptomics, and proteomics. The emerging field of ionomics is also being employed for investigating abiotic stress tolerance in soybean. Omic approaches generate a huge amount of data, and adequate advancements in computational tools have been achieved for effective analysis. However, the integration of omic-scale information to address complex genetics and physiological questions is still a challenge. In this review, we have described advances in omic tools in the view of conventional and modern approaches being used to dissect abiotic stress tolerance in soybean. Emphasis was given to approaches such as quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and genomic selection (GS). Comparative genomics and candidate gene approaches are also discussed considering identification of potential genomic loci, genes, and biochemical pathways involved in stress tolerance mechanism in soybean. This review also provides a comprehensive catalog of available online omic resources for soybean and its effective utilization. We have also addressed the significance of phenomics in the integrated approaches and recognized high-throughput multi-dimensional phenotyping as a major limiting factor for the improvement of abiotic stress tolerance in soybean.

Transcriptome analysis of shade-induced inhibition on leaf size in relay intercropped soybean

Multi-species intercropping is a sustainable agricultural practice worldwide used to utilize resources more efficiently. In intercropping systems, short crops often grow under vegetative shade of tall crops. Soybean, one important legume, is often planted in intercropping. However, little is known about the mechanisms of shade inhibition effect on leaf size in soybean leaves at the transcriptome level. We analyzed the transcriptome of shaded soybean leaves via RNA-Seq technology. We found that transcription 1085 genes in mature leaves and 1847 genes in young leaves were significantly affected by shade. Gene ontology analyses showed that expression of genes enriched in polysaccharide metabolism was down-regulated, but genes enriched in auxin stimulus were up-regulated in mature leaves; and genes enriched in cell cycling, DNA-replication were down-regulated in young leaves. These results suggest that the inhibition of higher auxin content and shortage of sugar supply on cell division and cell expansion contribute to smaller and thinner leaf morphology, which highlights potential research targets such as auxin and sugar regulation on leaves for crop adaptation to shade in intercropping.

Legume genomics: understanding biology through DNA and RNA sequencing

BACKGROUND

The legume family (Leguminosae) consists of approx. 17 000 species. A few of these species, including, but not limited to, Phaseolus vulgaris, Cicer arietinum and Cajanus cajan, are important dietary components, providing protein for approx. 300 million people worldwide. Additional species, including soybean (Glycine max) and alfalfa (Medicago sativa), are important crops utilized mainly in animal feed. In addition, legumes are important contributors to biological nitrogen, forming symbiotic relationships with rhizobia to fix atmospheric N2 and providing up to 30 % of available nitrogen for the next season of crops. The application of high-throughput genomic technologies including genome sequencing projects, genome re-sequencing (DNA-seq) and transcriptome sequencing (RNA-seq) by the legume research community has provided major insights into genome evolution, genomic architecture and domestication.

SCOPE AND CONCLUSIONS

This review presents an overview of the current state of legume genomics and explores the role that next-generation sequencing technologies play in advancing legume genomics. The adoption of next-generation sequencing and implementation of associated bioinformatic tools has allowed researchers to turn each species of interest into their own model organism. To illustrate the power of next-generation sequencing, an in-depth overview of the transcriptomes of both soybean and white lupin (Lupinus albus) is provided. The soybean transcriptome focuses on analysing seed development in two near-isogenic lines, examining the role of transporters, oil biosynthesis and nitrogen utilization. The white lupin transcriptome analysis examines how phosphate deficiency alters gene expression patterns, inducing the formation of cluster roots. Such studies illustrate the power of next-generation sequencing and bioinformatic analyses in elucidating the gene networks underlying biological processes.

A genome-wide association study of seed protein and oil content in soybean

BACKGROUND

Association analysis is an alternative to conventional family-based methods to detect the location of gene(s) or quantitative trait loci (QTL) and provides relatively high resolution in terms of defining the genome position of a gene or QTL. Seed protein and oil concentration are quantitative traits which are determined by the interaction among many genes with small to moderate genetic effects and their interaction with the environment. In this study, a genome-wide association study (GWAS) was performed to identify quantitative trait loci (QTL) controlling seed protein and oil concentration in 298 soybean germplasm accessions exhibiting a wide range of seed protein and oil content.

RESULTS

A total of 55,159 single nucleotide polymorphisms (SNPs) were genotyped using various methods including Illumina Infinium and GoldenGate assays and 31,954 markers with minor allele frequency >0.10 were used to estimate linkage disequilibrium (LD) in heterochromatic and euchromatic regions. In euchromatic regions, the mean LD (r2) rapidly declined to 0.2 within 360 Kbp, whereas the mean LD declined to 0.2 at 9,600 Kbp in heterochromatic regions. The GWAS results identified 40 SNPs in 17 different genomic regions significantly associated with seed protein. Of these, the five SNPs with the highest associations and seven adjacent SNPs were located in the 27.6-30.0 Mbp region of Gm20. A major seed protein QTL has been previously mapped to the same location and potential candidate genes have recently been identified in this region. The GWAS results also detected 25 SNPs in 13 different genomic regions associated with seed oil. Of these markers, seven SNPs had a significant association with both protein and oil.

CONCLUSIONS

This research indicated that GWAS not only identified most of the previously reported QTL controlling seed protein and oil, but also resulted in narrower genomic regions than the regions reported as containing these QTL. The narrower GWAS-defined genome regions will allow more precise marker-assisted allele selection and will expedite positional cloning of the causal gene(s).

Soybean seed proteome rebalancing

The soybean seed's protein content and composition are regulated by both genetics and physiology. Overt seed protein content is specified by the genotype's genetic framework and is selectable as a breeding trait. Within the genotype-specified protein content phenotype soybeans have the capacity to rebalance protein composition to create differing proteomes. Soybeans possess a relatively standardized proteome, but mutation or targeted engineering can induce large-scale proteome rebalancing. Proteome rebalancing shows that the output traits of seed content and composition result from two major types of regulation: genotype and post-transcriptional control of the proteome composition. Understanding the underlying mechanisms that specifies the seed proteome can enable engineering new phenotypes for the production of a high-quality plant protein source for food, feed, and industrial proteins.

Molecular footprints of domestication and improvement in soybean revealed by whole genome re-sequencing

BACKGROUND

Artificial selection played an important role in the origin of modern Glycine max cultivars from the wild soybean Glycine soja. To elucidate the consequences of artificial selection accompanying the domestication and modern improvement of soybean, 25 new and 30 published whole-genome re-sequencing accessions, which represent wild, domesticated landrace, and Chinese elite soybean populations were analyzed.

RESULTS

A total of 5,102,244 single nucleotide polymorphisms (SNPs) and 707,969 insertion/deletions were identified. Among the SNPs detected, 25.5% were not described previously. We found that artificial selection during domestication led to more pronounced reduction in the genetic diversity of soybean than the switch from landraces to elite cultivars. Only a small proportion (2.99%) of the whole genomic regions appear to be affected by artificial selection for preferred agricultural traits. The selection regions were not distributed randomly or uniformly throughout the genome. Instead, clusters of selection hotspots in certain genomic regions were observed. Moreover, a set of candidate genes (4.38% of the total annotated genes) significantly affected by selection underlying soybean domestication and genetic improvement were identified.

CONCLUSIONS

Given the uniqueness of the soybean germplasm sequenced, this study drew a clear picture of human-mediated evolution of the soybean genomes. The genomic resources and information provided by this study would also facilitate the discovery of genes/loci underlying agronomically important traits.

Gene divergence of homeologous regions associated with a major seed protein content QTL in soybean

Understanding several modes of duplication contributing on the present genome structure is getting an attention because it could be related to numerous agronomically important traits. Since soybean serves as a rich protein source for animal feeds and human consumption, breeding efforts in soybean have been directed toward enhancing seed protein content. The publicly available soybean sequences and its genomically featured elements facilitate comprehending of quantitative trait loci (QTL) for seed protein content in concordance with homeologous regions in soybean genome. Although parts of chromosome (Chr) 20 and Chr 10 showed synteny, QTLs for seed protein content present only on Chr 20. Using comparative analysis of gene contents in recently duplicated genomic regions harboring QTL for protein/oil content on Chrs 20 and 10, a total of 27 genes are present in duplicated regions of both Chrs. Notably, 4 tandem duplicates of the putative homeobox protein 22 (HB22) are present only on Chr 20 and this Medicago truncatula homolog expressed in endosperm at seed filling stage. These tandem duplicates could contribute on the protein/oil QTL of Chr 20. Our study suggests that non-shared gene contents within the duplicated genomic regions might lead to absence/presence of QTL related to protein/oil content.

Genomic heterogeneity and structural variation in soybean near isogenic lines

Near isogenic lines (NILs) are a critical genetic resource for the soybean research community. The ability to identify and characterize the genes driving the phenotypic differences between NILs is limited by the degree to which differential genetic introgressions can be resolved. Furthermore, the genetic heterogeneity extant among NIL sub-lines is an unaddressed research topic that might have implications for how genomic and phenotypic data from NILs are utilized. In this study, a recently developed high-resolution comparative genomic hybridization (CGH) platform was used to investigate the structure and diversity of genetic introgressions in two classical soybean NIL populations, respectively varying in protein content and iron deficiency chlorosis (IDC) susceptibility. There were three objectives: assess the capacity for CGH to resolve genomic introgressions, identify introgressions that are heterogeneous among NIL sub-lines, and associate heterogeneous introgressions with susceptibility to IDC. Using the CGH approach, introgression boundaries were refined and previously unknown introgressions were revealed. Furthermore, heterogeneous introgressions were identified within seven sub-lines of the IDC NIL "IsoClark." This included three distinct introgression haplotypes linked to the major iron susceptible locus on chromosome 03. A phenotypic assessment of the seven sub-lines did not reveal any differences in IDC susceptibility, indicating that the genetic heterogeneity among the lines does not have a significant impact on the primary NIL phenotype.

Relationship between asparagine metabolism and protein concentration in soybean seed

The relationship between asparagine metabolism and protein concentration was investigated in soybean seed. Phenotyping of a population of recombinant inbred lines adapted to Illinois confirmed a positive correlation between free asparagine levels in developing seeds and protein concentration at maturity. Analysis of a second population of recombinant inbred lines adapted to Ontario associated the elevated free asparagine trait with two of four quantitative trait loci determining population variation for protein concentration, including a major one on chromosome 20 (linkage group I) which has been reported in multiple populations. In the seed coat, levels of asparagine synthetase were high at 50 mg and progressively declined until 150 mg seed weight, suggesting that nitrogenous assimilates are pre-conditioned at early developmental stages to enable a high concentration of asparagine in the embryo. The levels of asparaginase B1 showed an opposite pattern, being low at 50 mg and progressively increased until 150 mg, coinciding with an active phase of storage reserve accumulation. In a pair of genetically related cultivars, ∼2-fold higher levels of asparaginase B1 protein and activity in seed coat, were associated with high protein concentration, reflecting enhanced flux of nitrogen. Transcript expression analyses attributed this difference to a specific asparaginase gene, ASPGB1a. These results contribute to our understanding of the processes determining protein concentration in soybean seed.

Evolutionary and comparative analyses of the soybean genome

The soybean genome assembly has been available since the end of 2008. Significant features of the genome include large, gene-poor, repeat-dense pericentromeric regions, spanning roughly 57% of the genome sequence; a relatively large genome size of ~1.15 billion bases; remnants of a genome duplication that occurred ~13 million years ago (Mya); and fainter remnants of older polyploidies that occurred ~58 Mya and >130 Mya. The genome sequence has been used to identify the genetic basis for numerous traits, including disease resistance, nutritional characteristics, and developmental features. The genome sequence has provided a scaffold for placement of many genomic feature elements, both from within soybean and from related species. These may be accessed at several websites, including http://www.phytozome.net, http://soybase.org, http://comparative-legumes.org, and http://www.legumebase.brc.miyazaki-u.ac.jp. The taxonomic position of soybean in the Phaseoleae tribe of the legumes means that there are approximately two dozen other beans and relatives that have undergone independent domestication, and which may have traits that will be useful for transfer to soybean. Methods of translating information between species in the Phaseoleae range from design of markers for marker assisted selection, to transformation with Agrobacterium or with other experimental transformation methods.

Accelerating yield potential in soybean: potential targets for biotechnological improvement

Soybean (Glycine max Merr.) is the world's most widely grown legume and provides an important source of protein and oil. Global soybean production and yield per hectare increased steadily over the past century with improved agronomy and development of cultivars suited to a wide range of latitudes. In order to meet the needs of a growing world population without unsustainable expansion of the land area devoted to this crop, yield must increase at a faster rate than at present. Here, the historical basis for the yield gains realized in the past 90 years are examined together with potential metabolic targets for achieving further improvements in yield potential. These targets include improving photosynthetic efficiency, optimizing delivery and utilization of carbon, more efficient nitrogen fixation and altering flower initiation and abortion. Optimization of investment in photosynthetic enzymes, bypassing photorespiratory metabolism, engineering the electron transport chain and engineering a faster recovery from the photoprotected state are different strategies to improve photosynthesis in soybean. These potential improvements in photosynthetic carbon gain will need to be matched by increased carbon and nitrogen transport to developing soybean pods and seeds in order to maximize the benefit. Better understanding of control of carbon and nitrogen transport along with improved knowledge of the regulation of flower initiation and abortion will be needed to optimize sink capacity in soybean. Although few single targets are likely to deliver a quantum leap in yields, biotechnological advances in molecular breeding techniques that allow for alteration of the soybean genome and transcriptome promise significant yield gains.

Crop improvement in the era of climate change: an integrated, multi-disciplinary approach for common bean (Phaseolus vulgaris)

Climate change and global population increase are two converging forces that will jointly challenge researchers to design programs that ensure crop production systems meet the world's food demand. Climate change will potentially reduce productivity while a global population increase will require more food. If productivity is not improved for future climatic conditions, food insecurity may foster major economic and political uncertainty. Given the importance of grain legumes in general - common bean (Phaseolus vulgaris L.) in particular - a workshop entitled 'Improving Tolerance of Common Bean to Abiotic Stresses' was held with the goal of developing an interdisciplinary research agenda designed to take advantage of modern genotyping and breeding approaches that are coupled with large scale phenotyping efforts to improve common bean. Features of the program included a multinational phenotyping effort to evaluate the major common bean core germplasm collections and appropriate genetic populations. The phenotyping effort will emphasise the response of root and shoot traits to individual and combined stress conditions. These populations would also be genotyped using newly emerging high density single nucleotide polymorphism (SNP) marker arrays or next generation sequencing technology. Association analysis of the core collections aims to identify key loci associated with the response to the stress conditions. Companion bi-parental quantitative trait loci (QTL) experiments will act as confirmation experiments for the association analysis. The upcoming release of the genome sequence of common bean will be leveraged by utilising population genomic approaches to discover genomic regions that differentiate stress-responsive and non-responsive genotypes. The genome sequence will also enable global gene expression studies that will highlight specific molecular-based stress responses. This collective knowledge will inform the selection of parental lines to improve the efficiency of common bean improvement programs.