An updated 'Essex' by 'Forrest' linkage map and first composite interval map of QTL underlying six soybean traits

QTL mapping reveals key factors related to the isoflavone contents and agronomic traits of soybean (Glycine max)

BACKGROUND

Soybean is a valuable source of edible protein and oil, as well as secondary metabolites that can be used in food products, cosmetics, and medicines. However, because soybean isoflavone content is a quantitative trait influenced by polygenes and environmental interactions, its genetic basis remains unclear.

RESULTS

This study was conducted to identify causal quantitative trait loci (QTLs) associated with soybean isoflavone contents. A mutant-based F2 population (190 individuals) was created by crossing the Korean cultivar Hwanggeum with low isoflavone contents (1,558 µg g-1) and the soybean mutant DB-088 with high isoflavone contents (6,393 µg g-1). A linkage map (3,049 cM) with an average chromosome length of 152 cM was constructed using the 180K AXIOM® SoyaSNP array. Thirteen QTLs related to agronomic traits were mapped to chromosomes 2, 3, 11, 13, 19, and 20, whereas 29 QTLs associated with isoflavone contents were mapped to chromosomes 1, 3, 8, 11, 14, 15, and 17. Notably, the qMGLI11, qMGNI11, qADZI11, and qTI11, which located Gm11_9877690 to Gm11_9955924 interval on chromosome 11, contributed to the high isoflavone contents and explained 11.9% to 20.1% of the phenotypic variation. This QTL region included four candidate genes, encoding β-glucosidases 13, 14, 17-1, and 17-2. We observed significant differences in the expression levels of these genes at various seed developmental stages. Candidate genes within the causal QTLs were functionally characterized based on enriched GO terms and KEGG pathways, as well as the results of a co-expression network analysis. A correlation analysis indicated that certain agronomic traits (e.g., days to flowering, days to maturity, and plant height) are positively correlated with isoflavone content.

CONCLUSIONS

Herein, we reported that the major QTL associated with isoflavone contents was located in the interval from Gm11_9877690 to Gm11_9955924 (78 kb) on chromosome 11. Four β-glucosidase genes were identified that may be involved in high isoflavone contents of soybean DB-088. Thus, the mutant alleles from soybean DB-088 may be useful for marker-assisted selection in developing soybean lines with high isoflavone contents and superior agronomic traits.

Breeding for disease resistance in soybean: a global perspective

KEY MESSAGE

This review provides a comprehensive atlas of QTLs, genes, and alleles conferring resistance to 28 important diseases in all major soybean production regions in the world. Breeding disease-resistant soybean [Glycine max (L.) Merr.] varieties is a common goal for soybean breeding programs to ensure the sustainability and growth of soybean production worldwide. However, due to global climate change, soybean breeders are facing strong challenges to defeat diseases. Marker-assisted selection and genomic selection have been demonstrated to be successful methods in quickly integrating vertical resistance or horizontal resistance into improved soybean varieties, where vertical resistance refers to R genes and major effect QTLs, and horizontal resistance is a combination of major and minor effect genes or QTLs. This review summarized more than 800 resistant loci/alleles and their tightly linked markers for 28 soybean diseases worldwide, caused by nematodes, oomycetes, fungi, bacteria, and viruses. The major breakthroughs in the discovery of disease resistance gene atlas of soybean were also emphasized which include: (1) identification and characterization of vertical resistance genes reside rhg1 and Rhg4 for soybean cyst nematode, and exploration of the underlying regulation mechanisms through copy number variation and (2) map-based cloning and characterization of Rps11 conferring resistance to 80% isolates of Phytophthora sojae across the USA. In this review, we also highlight the validated QTLs in overlapping genomic regions from at least two studies and applied a consistent naming nomenclature for these QTLs. Our review provides a comprehensive summary of important resistant genes/QTLs and can be used as a toolbox for soybean improvement. Finally, the summarized genetic knowledge sheds light on future directions of accelerated soybean breeding and translational genomics studies.

The Soybean High Density 'Forrest' by 'Williams 82' SNP-Based Genetic Linkage Map Identifies QTL and Candidate Genes for Seed Isoflavone Content

Isoflavones are secondary metabolites that are abundant in soybean and other legume seeds providing health and nutrition benefits for both humans and animals. The objectives of this study were to construct a single nucleotide polymorphism (SNP)-based genetic linkage map using the ‘Forrest’ by ‘Williams 82’ (F×W82) recombinant inbred line (RIL) population (n = 306); map quantitative trait loci (QTL) for seed daidzein, genistein, glycitein, and total isoflavone contents in two environments over two years (NC-2018 and IL-2020); identify candidate genes for seed isoflavone. The FXW82 SNP-based map was composed of 2075 SNPs and covered 4029.9 cM. A total of 27 QTL that control various seed isoflavone traits have been identified and mapped on chromosomes (Chrs.) 2, 4, 5, 6, 10, 12, 15, 19, and 20 in both NC-2018 (13 QTL) and IL-2020 (14 QTL). The six QTL regions on Chrs. 2, 4, 5, 12, 15, and 19 are novel regions while the other 21 QTL have been identified by other studies using different biparental mapping populations or genome-wide association studies (GWAS). A total of 130 candidate genes involved in isoflavone biosynthetic pathways have been identified on all 20 Chrs. And among them 16 have been identified and located within or close to the QTL identified in this study. Moreover, transcripts from four genes (Glyma.10G058200, Glyma.06G143000, Glyma.06G137100, and Glyma.06G137300) were highly abundant in Forrest and Williams 82 seeds. The identified QTL and four candidate genes will be useful in breeding programs to develop soybean cultivars with high beneficial isoflavone contents.

Identification of a candidate gene associated with isoflavone content in soybean seeds using genome-wide association and linkage mapping

Isoflavone, a secondary metabolite produced by Glycine max (L.) Merr. (soybean), is valuable for human and plant health. The genetic architecture of soybean isoflavone content remains unclear, however, despite several mapping studies. We generated genomic data for 200 soybean cultivars and 150 recombinant inbred lines (RILs) to localize putative loci associated with soybean seed isoflavone content. Using a genome-wide association study (GWAS), we identified 87 single-nucleotide polymorphisms (SNPs) that were significantly associated with isoflavone concentration. Using linkage mapping, we identified 37 quantitative trait loci (QTLs) underlying the content of four isoflavones found in the RILs. A major locus on chromosome 8 (qISO8-1) was co-located by both the GWAS and linkage mapping. qISO8-1 was fine mapped to a 99.5-kb region, flanked by SSR_08_1651 and SSR_08_1656, in a BC2 F5 population. GmMPK1, encoding a mitogen-activated protein kinase, was identified as the causal gene in qISO8-1, and two natural GmMPK1 polymorphisms were significantly associated with isoflavone content. Overexpression of GmMPK1 in soybean hairy roots resulted in increased isoflavone concentrations. Overexpressing GmMPK1 in transgenic soybeans had greater resistance to Phytophthora root rot, suggesting that GmMPK1 might increase soybean resistance to biotic stress by influencing isoflavone content. Our results not only increase our understanding of the genetic architecture of soybean seed isoflavone content, but also provide a framework for the future marker-assisted breeding of high isoflavone content in soybean cultivars.

Linkage Mapping for Foliar Necrosis of Soybean Sudden Death Syndrome

Sudden death syndrome (SDS) foliar symptoms consist of foliar chlorosis, foliar necrosis, leaf marginal curling, and premature defoliation, but resistance screening has been evaluated mostly based on the overall SDS foliar severity rather than on a specific foliar symptom. This study generated an F2 population derived from crossing the susceptible variety Sloan and the resistant germplasm line PI 243518, which exhibits resistance to both foliar chlorosis and necrosis. A total of 400 F2 lines were evaluated for foliar chlorosis, foliar necrosis, and overall SDS foliar symptoms, separately. Genotyping-by-sequencing was applied to obtain single nucleotide polymorphisms (SNPs) in the F2 population, and linkage mapping using 135 F2 lines with 969 high-quality SNPs identified a locus on chromosome 13 for foliar necrosis and SDS foliar symptoms. The locus partially overlaps with loci previously reported for SDS on chromosome 13, which is the third time the region from 15.98 to 21.00 Mbp has been reproduced independently and therefore qualifies this locus for a new nomenclature proposed as Rfv13-02. In summary, this study generated a new biparental population that enables not only the discovery of a locus for foliar necrosis and SDS foliar symptoms on chromosome 13 but also the potential for advanced exploration of SDS foliar resistance derived from the germplasm line PI 243518.

Comparative genomic analyses of two segregating mutants reveal seven genes likely involved in resistance to Fusarium equiseti in soybean via whole genome re-sequencing

KEY MESSAGE

The candidate genes involved in resistance to Fusarium equiseti in soybean PI 437654 were identified through comparative genomic analyses of mutants via whole genome re-sequencing. The fungus Fusarium infects each stage of the growth and development of soybean and causes soybean (Glycine max (L.)) seed and root rot and seedling damping-off and wilt with a large quantity of annual yield loss worldwide. It is very important to identify the resistant genes in soybean to prevent and control this pathogen. One Fusarium equiseti isolate was previously identified to be incompatible with 'PI 437654' but compatible with a Chinese soybean cultivar 'Zhonghuang 13'. In this study, with the infection of this isolate on the seedling roots of developed PI 437654 mutants, 6 mutants were identified from 500 mutants to significantly alter their phenotypes to F. equiseti compared to wild-type PI 437654. Then, two identified segregating mutants were selected to directly perform whole genome re-sequencing. Finally, through comparative genomic analyses 7 genes including one cluster of 4 nucleotide binding site-leucine-rich repeat genes on one genomic region of chromosome 7, a 60S ribosomal protein L12 gene and 2 uncharacterized genes were identified to be likely involved in the resistance to F. equiseti. These genes will facilitate the breeding of resistant germplasm resources and the identification of resistance of soybean to Fusarium spp.

Is Chickpea a Potential Substitute for Soybean? Phenolic Bioactives and Potential Health Benefits

Legume seeds are rich sources of protein, fiber, and minerals. In addition, their phenolic compounds as secondary metabolites render health benefits beyond basic nutrition. Lowering apolipoprotein B secretion from HepG2 cells and decreasing the level of low-density lipoprotein (LDL)-cholesterol oxidation are mechanisms related to the prevention of cardiovascular diseases (CVD). Likewise, low-level chronic inflammation and related disorders of the immune system are clinical predictors of cardiovascular pathology. Furthermore, DNA-damage signaling and repair are crucial pathways to the etiology of human cancers. Along CVD and cancer, the prevalence of obesity and diabetes is constantly increasing. Screening the ability of polyphenols in inactivating digestive enzymes is a good option in pre-clinical studies. In addition, in vivo studies support the role of polyphenols in the prevention and/or management of diabetes and obesity. Soybean, a well-recognized source of phenolic isoflavones, exerts health benefits by decreasing oxidative stress and inflammation related to the above-mentioned chronic ailments. Similar to soybeans, chickpeas are good sources of nutrients and phenolic compounds, especially isoflavones. This review summarizes the potential of chickpea as a substitute for soybean in terms of health beneficial outcomes. Therefore, this contribution may guide the industry in manufacturing functional foods and/or ingredients by using an undervalued feedstock.

Genome wide association study identifies novel single nucleotide polymorphic loci and candidate genes involved in soybean sudden death syndrome resistance

Fusarium virguliforme is a soil borne root pathogen that causes sudden death syndrome (SDS) in soybean [Glycine max (L.) Merrill]. Once the fungus invades the root xylem tissues, the pathogen secretes toxins that cause chlorosis and necrosis in foliar tissues leading to defoliation, flower and pod drop and eventually death of plants. Resistance to F. virguliforme in soybean is partial and governed by over 80 quantitative trait loci (QTL). We have conducted genome-wide association study (GWAS) for a group of 254 plant introductions lines using a panel of approximately 30,000 SNPs and identified 19 single nucleotide polymorphic loci (SNPL) that are associated with 14 genomic regions encoding foliar SDS and eight SNPL associated with seven genomic regions for root rot resistance. Of the identified 27 SNPL, six SNPL for foliar SDS resistance and two SNPL for root rot resistance co-mapped to previously identified QTL for SDS resistance. This study identified 13 SNPL associated with eight novel genomic regions containing foliar SDS resistance genes and six SNPL with five novel regions for root-rot resistance. This study identified five genes carrying nonsynonymous mutations: (i) three of which mapped to previously identified QTL for foliar SDS resistance and (ii) two mapped to two novel regions containing root rot resistance genes. Of the three genes mapped to QTL for foliar SDS resistance genes, two encode LRR-receptors and third one encodes a novel protein with unknown function. Of the two genes governing root rot resistance, Glyma.01g222900.1 encodes a soybean-specific LEA protein and Glyma.10g058700.1 encodes a heparan-alpha-glucosaminide N-acetyltransferase. In the LEA protein, a conserved serine residue was substituted with asparagine; and in the heparan-alpha-glucosaminide N-acetyltransferase, a conserved histidine residue was substituted with an arginine residue. Such changes are expected to alter functions of these two proteins regulated through phosphorylation. The five genes with nonsynonymous mutations could be considered candidate SDS resistance genes and should be suitable molecular markers for breeding SDS resistance in soybean. The study also reports desirable plant introduction lines and novel genomic regions for enhancing SDS resistance in soybean.

Comprehensive RNA sequencing and co-expression network analysis to complete the biosynthetic pathway of coumestrol, a phytoestrogen

Coumestrol (CMS), a coumestan isoflavone, plays key roles in nodulation through communication with rhizobia, and has been used as phytoestrogens for hormone replacement therapy in humans. Because CMS content is controlled by multiple genetic factors, the genetic basis of CMS biosynthesis has remained unclear. We identified soybean genotypes with consistently high (Daewonkong) or low (SS0903-2B-21-1-2) CMS content over 2 years. We performed RNA sequencing of leaf samples from both genotypes at developmental stage R7, when CMS levels are highest. Within the phenylpropanoid biosynthetic pathway, 41 genes were tightly connected in a functional co-expression gene network; seven of these genes were differentially expressed between two genotypes. We identified 14 candidate genes involved in CMS biosynthesis. Among them, seven were annotated as encoding oxidoreductases that may catalyze the transfer of electrons from daidzein, a precursor of CMS. Two of the other genes, annotated as encoding a MYB domain protein and a MLP-like protein, may increase CMS accumulation in response to stress conditions. Our results will help to complete our understanding of the CMS biosynthetic pathway, and should facilitate development of soybean cultivars with high CMS content that could be used to promote the fitness of plants and human beings.

Understanding genetic control of root system architecture in soybean: Insights into the genetic basis of lateral root number

Developing crops with better root systems is a promising strategy to ensure productivity in both optimum and stress environments. Root system architectural traits in 397 soybean accessions were characterized and a high-density single nucleotide polymorphisms (SNPs)-based genome-wide association study was performed to identify the underlying genes associated with root structure. SNPs associated with root architectural traits specific to landraces and elite germplasm pools were detected. Four loci were detected in landraces for lateral root number (LRN) and distribution of root thickness in diameter Class I with a major locus on chromosome 16. This major loci was detected in the coding region of unknown protein, and subsequent analyses demonstrated that root traits are affected with mutated haplotypes of the gene. In elite germplasm pool, 3 significant SNPs in alanine-glyoxalate aminotransferase, Leucine-Rich Repeat receptor/No apical meristem, and unknown functional genes were found to govern multiple traits including root surface area and volume. However, no major loci were detected for LRN in elite germplasm. Nucleotide diversity analysis found evidence of selective sweeps around the landraces LRN gene. Soybean accessions with minor and mutated allelic variants of LRN gene were found to perform better in both water-limited and optimal field conditions.

GWAS of a soybean breeding collection from South East and South Kazakhstan for resistance to fungal diseases

Soybean (Glycine max(L.) Merr) is an essential food, feed, and technical culture. In Kazakhstan the area under soybean is increasing every year, helping to solve the problem of protein deficiency in human nutrition and animal feeding. One of the main problems of soybean production is fungal diseases causing yields losses of up to 30 %. Modern genomic studies can be applied to facilitate efficient breeding research for improvement of soybean fungal disease tolerance. Therefore, the objective of this genome-wide association study (GWAS) was analysis of a soybean collection consisting of 182 accessions in relation to fungal diseases in the conditions of South East and South Kazakh­stan. Field evaluation of the soybean collection suggested thatFusariumspp. andCercospora sojinaaffected plants in the South region (RIBSP), andSeptoria glycines– in the South East region (KRIAPP). The major objective of the study was identification of QTL associated with resistance to fusarium root rot (FUS), frogeye leaf spot (FLS), and brown spot (BS). GWAS using 4 442 SNP (single nucleotide polymorphism) markers of Illumina iSelect array allowed for identification of fifteen marker trait associations (MTA) resistant to the three diseases at two different stages of growth. Two QTL both for FUS (chromosomes 13 and 17) and BS (chromosomes 14 and 17) were genetically mapped, including one presumably novel QTL for BS (chromo­some 17). Also, five presumably novel QTL for FLS were genetically mapped on chromosomes 2, 7, and 15. The results can be used for improvement of the local breeding projects based on marker-assisted selection approach.          

Mapping of new quantitative trait loci for sudden death syndrome and soybean cyst nematode resistance in two soybean populations

KEY MESSAGE

Novel QTL conferring resistance to both the SDS and SCN was detected in two RIL populations. Dual resistant RILs could be used in breeding programs for developing resistant soybean cultivars. Soybean cultivars, susceptible to the fungus Fusarium virguliforme, which causes sudden death syndrome (SDS), and to the soybean cyst nematode (SCN) (Heterodera glycines), suffer yield losses valued over a billion dollars annually. Both pathogens may occur in the same production fields. Planting of cultivars genetically resistant to both pathogens is considered one of the most effective means to control the two pathogens. The objective of the study was to map quantitative trait loci (QTL) underlying SDS and SCN resistances. Two recombinant inbred line (RIL) populations were developed by crossing 'A95-684043', a high-yielding maturity group (MG) II line resistant to SCN, with 'LS94-3207' and 'LS98-0582' of MG IV, resistant to both F. virguliforme and SCN. Two hundred F7 derived recombinant inbred lines from each population AX19286 (A95-684043 × LS94-3207) and AX19287 (A95-684043 × LS98-0582) were screened for resistance to each pathogen under greenhouse conditions. Five hundred and eighty and 371 SNP markers were used for mapping resistance QTL in each population. In AX19286, one novel SCN resistance QTL was mapped to chromosome 8. In AX19287, one novel SDS resistance QTL was mapped to chromosome 17 and one novel SCN resistance QTL was mapped to chromosome 11. Previously identified additional SDS and SCN resistance QTL were also detected in the study. Lines possessing superior resistance to both pathogens were also identified and could be used as germplasm sources for breeding SDS- and SCN-resistant soybean cultivars.

Integration of sudden death syndrome resistance loci in the soybean genome

KEY MESSAGE

Complexity and inconsistencies in resistance mapping publications of soybean sudden death syndrome (SDS) result in interpretation difficulty. This review integrates SDS mapping literature and proposes a new nomenclature system for reproducible SDS resistance loci. Soybean resistance to sudden death syndrome (SDS) is composed of foliar resistance to phytotoxins and root resistance to pathogen invasion. There are more than 80 quantitative trait loci (QTL) and dozens of single nucleotide polymorphisms (SNPs) associated with soybean resistance to SDS. The validity of these QTL and SNPs is questionable because of the complexity in phenotyping methodologies, the disease synergism between SDS and soybean cyst nematode (SCN), the variability from the interactions between soybean genotypes and environments, and the inconsistencies in the QTL nomenclature. This review organizes SDS mapping results and proposes the Rfv (resistance to Fusarium virguliforme) nomenclature based on supporting criteria described in the text. Among ten reproducible loci receiving our Rfv nomenclature, Rfv18-01 is mostly supported by field studies and it co-localizes to the SCN resistance locus rhg1. The possibility that Rfv18-01 is a pleiotropic resistance locus and the concern about Rfv18-01 being confounded with Rhg1 is discussed. On the other hand, Rfv06-01, Rfv06-02, Rfv09-01, Rfv13-01, and Rfv16-01 were identified both by screening soybean leaves against phytotoxic culture filtrates and by evaluating SDS severity in fields. Future phenotyping using leaf- and root-specific resistance screening methodologies may improve the precision of SDS resistance, and advanced genetic studies may further clarify the interactions among soybean genotypes, F. virguliforme, SCN, and environments. The review provides a summary of the SDS resistance literature and proposes a framework for communicating SDS resistance loci for future research considering molecular interactions and genetic breeding for soybean SDS resistance.

Fine-mapping of QTLs for individual and total isoflavone content in soybean (Glycine max L.) using a high-density genetic map

KEY MESSAGE

Fifteen stable QTLs were identified using a high-density soybean genetic map across multiple environments. One major QTL, qIF5-1, contributing to total isoflavone content explained phenotypic variance 49.38, 43.27, 46.59, 45.15 and 52.50%, respectively. Soybeans (Glycine max L.) are a major source of dietary isoflavones. To identify novel quantitative trait loci (QTL) underlying isoflavone content, and to improve the accuracy of marker-assisted breeding in soybean, a valuable mapping population comprised of 196 F7:8-10 recombinant inbred lines (RILs, Huachun 2 × Wayao) was utilized to evaluate individual and total isoflavone content in plants grown in four different environments in Guangdong. A high-density genetic linkage map containing 3469 recombination bin markers based on 0.2 × restriction site-associated DNA tag sequencing (RAD-seq) technology was used to finely map QTLs for both individual and total isoflavone contents. Correlation analyses showed that total isoflavone content, and that of five individual isoflavone, was significantly correlated across the four environments. Based on the high-density genetic linkage map, a total of 15 stable quantitative trait loci (QTLs) associated with isoflavone content across multiple environments were mapped onto chromosomes 02, 05, 07, 09, 10, 11, 13, 16, 17, and 19. Further, one of them, qIF5-1, localized to chromosomes 05 (38,434,171-39,045,620 bp) contributed to almost all isoflavone components across all environments, and explained 6.37-59.95% of the phenotypic variance, especially explained 49.38, 43.27, 46.59, 45.15 and 52.50% for total isoflavone. The results obtained in the present study will pave the way for a better understanding of the genetics of isoflavone accumulation and reveals the scope available for improvement of isoflavone content through marker-assisted selection.

'MN1606SP' by 'Spencer' filial soybean population reveals novel quantitative trait loci and interactions among loci conditioning SDS resistance

KEY MESSAGE

Four novel QTL and interactions among QTL were identified in this research, using as a parent line the most SDS-resistant genotype within soybean cultivars of the US early maturity groups. Soybean sudden death syndrome (SDS) reduces soybean yield in most of the growing areas of the world. The causal agent of SDS, soilborne fungus Fusarium virguliforme (Fv), releases phytotoxins taken up by the plant to produce chlorosis and necrosis in the leaves. Planting resistant cultivars is the most successful management practice to control the disease. The objective of this study was to identify quantitative trait loci (QTL) associated with the resistance response of MN1606SP to SDS. A mapping population of F 2:3 lines created by crossing the highly resistant cultivar 'MN1606SP' and the susceptible cultivar 'Spencer' was phenotyped in the greenhouse at three different planting times, each with three replications. Plants were artificially inoculated using SDS infested sorghum homogeneously mixed with the soil. Data were collected on three disease criteria, foliar disease incidence (DI), foliar leaf scorch disease severity (DS), and root rot severity. Disease index (DX) was calculated as DI × DS. Ten QTL were identified for the different disease assessment criteria, three for DI, four for DX, and three for root rot severity. Three QTL identified for root rot severity and one QTL for disease incidence are considered novel, since no previous reports related to these QTL are available. Among QTL, two interactions were detected between four different QTL. The interactions suggest that resistance to SDS is not only dependent on additive gene effects. The novel QTL and the interactions observed in this study will be useful to soybean breeders for improvement of SDS resistance in soybean germplasm.

Detecting the QTL-allele system of seed isoflavone content in Chinese soybean landrace population for optimal cross design and gene system exploration

KEY MESSAGE

Utilizing an innovative GWAS in CSLRP, 44 QTL 199 alleles with 72.2 % contribution to SIFC variation were detected and organized into a QTL-allele matrix for cross design and gene annotation. The seed isoflavone content (SIFC) of soybeans is of great importance to health care. The Chinese soybean landrace population (CSLRP) as a genetic reservoir was studied for its whole-genome quantitative trait loci (QTL) system of the SIFC using an innovative restricted two-stage multi-locus genome-wide association study procedure (RTM-GWAS). A sample of 366 landraces was tested under four environments and sequenced using RAD-seq (restriction-site-associated DNA sequencing) technique to obtain 116,769 single nucleotide polymorphisms (SNPs) then organized into 29,119 SNP linkage disequilibrium blocks (SNPLDBs) for GWAS. The detected 44 QTL 199 alleles on 16 chromosomes (explaining 72.2 % of the total phenotypic variation) with the allele effects (92 positive and 107 negative) of the CSLRP were organized into a QTL-allele matrix showing the SIFC population genetic structure. Additional differentiation among eco-regions due to the SIFC in addition to that of genome-wide markers was found. All accessions comprised both positive and negative alleles, implying a great potential for recombination within the population. The optimal crosses were predicted from the matrices, showing transgressive potentials in the CSLRP. From the detected QTL system, 55 candidate genes related to 11 biological processes were χ (2)-tested as an SIFC candidate gene system. The present study explored the genome-wide SIFC QTL/gene system with the innovative RTM-GWAS and found the potentials of the QTL-allele matrix in optimal cross design and population genetic and genomic studies, which may have provided a solution to match the breeding by design strategy at both QTL and gene levels in breeding programs.

Quantitative trait loci underlying host responses of soybean to Fusarium virguliforme toxins that cause foliar sudden death syndrome

KEY MESSAGE

Soybean deploys multiple genetic mechanisms to confer tolerance to Fusarium virguliforme toxins. This study revealed that F. virguliforme culture filtrates could be used in mapping QTL underlying foliar SDS resistance. Sudden death syndrome (SDS) is a major soybean disease throughout most of the soybean growing regions in the world including the United States. The disease is caused by the fungal pathogen, Fusarium virguliforme (Fv). The fungus produces several toxins that are responsible for development of interveinal leaf chlorosis and necrosis, which are typical foliar SDS symptoms. Growing of resistant cultivars has been the most effective method in controlling the disease. The objective of the present study was to identify quantitative trait loci (QTL) underlying host responses of soybean to Fv toxins present in culture filtrates. To accomplish this objective, two recombinant inbred line (RIL) populations, AX19286 (A95-684043 × LS94-3207) and AX19287 (A95-684043 × LS98-0582), segregating for SDS resistance were evaluated for foliar symptom development by applying two screening protocols, the stem cutting and the root feeding assays. The AX19286 population revealed two major and seven minor QTL for SDS resistance. In the AX19287 population, we identified five major QTL and three minor QTL. The two QTL mapped to Chromosome 7 [molecular linkage group (MLG) M] and Chromosome 20 (MLG I) are most likely novel, and were detected through screening of the AX19287 population with stem cutting and root feeding assays, respectively. This study established that Fv culture filtrates could be employed in mapping QTL underlying foliar SDS resistance. The outcomes of the research also suggest that multiple genetic mechanisms might be used by soybean to overcome the toxic effects of the toxins secreted by the pathogen into culture filtrates.

Association mapping and genomic prediction for resistance to sudden death syndrome in early maturing soybean germplasm

Sudden death syndrome (SDS), caused by Fusarium virguliforme, has spread to northern soybean growing regions in the US causing significant yield losses. The objectives of this study were to identify loci underlying variation in plant responses to SDS through association mapping (AM) and to assess prediction accuracy of genomic selection (GS) in a panel of early maturing soybean germplasm. A set of 282 soybean breeding lines was selected from the University of Minnesota soybean breeding program and then genotyped using a genome-wide panel of 1536 single-nucleotide polymorphism markers. Four resistance traits, root lesion severity (RLS), foliar symptom severity (FSS), root retention (RR), and dry matter reduction (DMR), were evaluated using soil inoculation in the greenhouse. AM identified significant peaks in genomic regions of known SDS resistance quantitative trait loci cqSDS001, cqRfs4, and SDS11-2. Additionally, two novel loci, one on chromosome 3 and another on chromosome 18, were tentatively identified. A ninefold cross-validation scheme was used to assess the prediction accuracy of GS for SDS resistance. The prediction accuracy of single-trait GS (ST-GS) was 0.64 for RLS, but less than 0.30 for RR, DMR, and FSS. Compared to ST-GS, none of multi-trait GS (MT-GS) models significantly improved the prediction accuracy due to weak correlations between the four traits. This study suggests both AM and GS hold promise for implementation in genetic improvement of SDS resistance in existing soybean breeding programs.

Quantitative trait loci underlying resistance to sudden death syndrome (SDS) in MD96-5722 by 'Spencer' recombinant inbred line population of soybean

The best way to protect yield loss of soybean [Glycine max (L.) Merr.] due to sudden death syndrome (SDS), caused by Fusarium virguliforme (Aoki, O'Donnel, Homma & Lattanzi), is the development and use of resistant lines. Mapping quantitative trait loci (QTL) linked to SDS help developing resistant soybean germplasm through molecular marker-assisted selection strategy. QTL for SDS presented herein are from a high-density SNP-based genetic linkage map of MD 96-5722 (a.k.a 'Monocacy') by 'Spencer' recombinant inbred line using SoySNP6K Illumina Infinium BeadChip genotyping array. Ninety-four F5:7 lines were evaluated for 2 years (2010 and 2011) at two locations (Carbondale and Valmeyer) in southern Illinois, USA to identify QTL controlling SDS resistance using disease index (DX). Composite interval mapping identified 19 SDS controlling QTL which were mapped on 11 separate linkage group (LG) or chromosomes (Chr) out of 20 LG or Chr of soybean genome. Many of these significant QTL identified in one environment/year were confirmed in another year or environment, which suggests a common genetic effects and modes of the pathogen. These new QTL are useful sources for SDS resistance studies in soybean breeding, complementing previously reported loci.

Mapping isoflavone QTL with main, epistatic and QTL × environment effects in recombinant inbred lines of soybean

Soybean (Glycine max (L.) Merr.) isoflavone is important for human health and plant defense system. To identify novel quantitative trait loci (QTL) and epistatic QTL underlying isoflavone content in soybean, F5:6, F5:7 and F5:8 populations of 130 recombinant inbred (RI) lines, derived from the cross of soybean cultivar 'Zhong Dou 27' (high isoflavone) and 'Jiu Nong 20' (low isoflavone), were analyzed with 95 new SSR markers. A new linkage map including 194 SSR markers and covering 2,312 cM with mean distance of about 12 cM between markers was constructed. Thirty four QTL for both individual and total seed isoflavone contents of soybean were identified. Six, seven, ten and eleven QTL were associated with daidzein (DZ), glycitein (GC), genistein (GT) and total isoflavone (TI), respectively. Of them 23 QTL were newly identified. The qTIF_1 between Satt423 and Satt569 shared the same marker Satt569 with qDZF_2, qGTF_1 and qTIF_2. The qGTD2_1 between Satt186 and Satt226 was detected in four environments and explained 3.41%-10.98% of the phenotypic variation. The qGTA2_1, overlapped with qGCA2_1 and detected in four environments, was close to the previously identified major QTL for GT, which were responsible for large a effects. QTL (qDZF_2, qGTF_1 and qTIF_2) between Satt144-Satt569 were either clustered or pleiotropic. The qGCM_1, qGTM_1 and qTIM_1 between Satt540-Sat_244 explained 2.02%-9.12% of the phenotypic variation over six environments. Moreover, the qGCE_1 overlapped with qGTE_1 and qTIE_1, the qTIH_2 overlapped with qGTH_1, qGCI_1 overlapped with qDZI_1, qTIL_1 overlapped with qGTL_1, and qTIO_1 overlapped with qGTO_1. In this study, some of unstable QTL were detected in different environments, which were due to weak expression of QTL, QTL by environment interaction in the opposite direction to a effects, and/or epistasis. The markers identified in multi-environments in this study could be applied in the selection of soybean cultivars for higher isoflavone content and in the map-based gene cloning.

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.

Genome-wide association mapping of quantitative resistance to sudden death syndrome in soybean

BACKGROUND

Sudden death syndrome (SDS) is a serious threat to soybean production that can be managed with host plant resistance. To dissect the genetic architecture of quantitative resistance to the disease in soybean, two independent association panels of elite soybean cultivars, consisting of 392 and 300 unique accessions, respectively, were evaluated for SDS resistance in multiple environments and years. The two association panels were genotyped with 52,041 and 5,361 single nucleotide polymorphisms (SNPs), respectively. Genome-wide association mapping was carried out using a mixed linear model that accounted for population structure and cryptic relatedness.

RESULT

A total of 20 loci underlying SDS resistance were identified in the two independent studies, including 7 loci localized in previously mapped QTL intervals and 13 novel loci. One strong peak of association on chromosome 18, associated with all disease assessment criteria across the two panels, spanned a physical region of 1.2 Mb around a previously cloned SDS resistance gene (GmRLK18-1) in locus Rfs2. An additional variant independently associated with SDS resistance was also found in this genomic region. Other peaks were within, or close to, sequences annotated as homologous to genes previously shown to be involved in plant disease resistance. The identified loci explained an average of 54.5% of the phenotypic variance measured by different disease assessment criteria.

CONCLUSIONS

This study identified multiple novel loci and refined the map locations of known loci related to SDS resistance. These insights into the genetic basis of SDS resistance can now be used to further enhance durable resistance to SDS in soybean. Additionally, the associations identified here provide a basis for further efforts to pinpoint causal variants and to clarify how the implicated genes affect SDS resistance in soybean.

Expression quantitative trait loci infer the regulation of isoflavone accumulation in soybean (Glycine max L. Merr.) seed

BACKGROUND

Mapping expression quantitative trait loci (eQTL) of targeted genes represents a powerful and widely adopted approach to identify putative regulatory variants. Linking regulation differences to specific genes might assist in the identification of networks and interactions. The objective of this study is to identify eQTL underlying expression of four gene families encoding isoflavone synthetic enzymes involved in the phenylpropanoid pathway, which are phenylalanine ammonia-lyase (PAL; EC 4.3.1.5), chalcone synthase (CHS; EC 2.3.1.74), 2-hydroxyisoflavanone synthase (IFS; EC1.14.13.136) and flavanone 3-hydroxylase (F3H; EC 1.14.11.9). A population of 130 recombinant inbred lines (F5:11), derived from a cross between soybean cultivar 'Zhongdou 27' (high isoflavone) and 'Jiunong 20' (low isoflavone), and a total of 194 simple sequence repeat (SSR) markers were used in this study. Overlapped loci of eQTLs and phenotypic QTLs (pQTLs) were analyzed to identify the potential candidate genes underlying the accumulation of isoflavone in soybean seed.

RESULTS

Thirty three eQTLs (thirteen cis-eQTLs and twenty trans-eQTLs) underlying the transcript abundance of the four gene families were identified on fifteen chromosomes. The eQTLs between Satt278-Sat_134, Sat_134-Sct_010 and Satt149-Sat_234 underlie the expression of both IFS and CHS genes. Five eQTL intervals were overlapped with pQTLs. A total of eleven candidate genes within the overlapped eQTL and pQTL were identified.

CONCLUSIONS

These results will be useful for the development of marker-assisted selection to breed soybean cultivars with high or low isoflavone contents and for map-based cloning of new isoflavone related genes.

Quantitative trait loci analysis of individual and total isoflavone contents in soybean seeds

Soybean isoflavones play diverse roles in human health, including cancers, osteoporosis, heart disease, menopausal symptoms and pabulums. The objective of this study was to identify the quantitative trait loci (QTL) associated with the isoflavones daidzein (DC), genistein (GeC), glycitein (GlC) and total isoflavone contents (TIC) in soybean seeds. A population of 184 F2:10 recombinant inbred lines derived from a 'Xiaoheidou' x 'GR8836' cross was planted in pot and field conditions to evaluate soybean isoflavones. Twenty-one QTL were detected by composite interval mapping. Several QTL were associated with the traits for DC, GeC, GlC and TIC only. QDGeGlTIC4_1 and QDGlTIC12_1 are reported first in this study and were associated with the DC, GeC, GlC and TIC traits simultaneously. The QTL identified have potential value for marker-assisted selection to develop soybean varieties with desirable isoflavone content.

Genetic diversity and association mapping of seed vigor in rice (Oryza sativa L.)

Seed vigor is closely related to direct seeding in rice (Oryza sativa L.). Previous quantitative trait locus (QTL) studies for seed vigor were mainly derived from bi-parental segregating populations and no report from natural populations. In this study, association mapping for seed vigor was performed on a selected sample of 540 rice cultivars (419 from China and 121 from Vietnam). Population structure was estimated on the basis of 262 simple sequence repeat (SSR) markers. Seed vigor was evaluated by root length (RL), shoot length (SL) and shoot dry weight in 2011 and 2012. Abundant phenotypic and genetic diversities were found in the studied population. The population was divided into seven subpopulations, and the levels of linkage disequilibrium (LD) ranged from 10 to 80 cM. We identified 27 marker-trait associations involving 18 SSR markers for three traits. According to phenotypic effects for alleles of the detected QTLs, elite alleles were mined. These elite alleles could be used to design parental combinations and the expected results would be obtained by pyramiding or substituting the elite alleles per QTL (apart from possible epistatic effects). Our results demonstrate that association mapping can complement and enhance previous QTL information for marker-assisted selection and breeding by design.

Quantitative trait loci for seed isoflavone contents in 'MD96-5722' by 'Spencer' recombinant inbred lines of soybean

Isoflavones from soybeans [ Glycine max (L.) Merr.] have a significant impact on human health to reduce the risk of several major diseases. Breeding soybean for high isoflavone content in the seed is possible through marker-assisted selection (MAS) which can be based on quantitative trait loci (QTL). The objective of this study was to identify QTL controlling isoflavone content in a set of 'MD96-5722' by 'Spencer' recombinant inbred line (RIL) populations of soybean. Wide variations were found for seed concentrations of daidzein, glycitein, genistein, and total isoflavones among the RIL populations. Three QTL were identified on three different linkage groups (LG) represented by three different chromosomes (Chr). One QTL that controlled daidzein content was identified on LG A1 (Chr 5), and two QTL that underlay glycitein content were identified on LG K (Chr 9) and LG B2 (Chr 14). Identified QTL could be functional in developing soybean with preferable isoflavone concentrations in the seeds through MAS.

Identification of QTLs for seed and pod traits in soybean and analysis for additive effects and epistatic effects of QTLs among multiple environments

Soybean seed and pod traits are important yield components. Selection for high yield style in seed and pod along with agronomic traits is a goal of many soybean breeders. The intention of this study was to identify quantitative trait loci (QTL) underlying seed and pod traits in soybean among eleven environments in China. 147 recombinant inbred lines were advanced through single-seed-descent method. The population was derived from a cross between Charleston (an American high yield soybean cultivar) and DongNong594 (a Chinese high yield soybean cultivar). A total of 157 polymorphic simple sequence repeat markers were used to construct a genetic linkage map. The phenotypic data of seed and pod traits [number of one-seed pod, number of two-seed pod, number of three-seed pod, number of four-seed pod, number of (two plus three)-seed pod, number of (three plus four)-seed pod, seed weight per plant, number of pod per plant] were recorded in eleven environments. In the analysis of single environment, fourteen main effect QTLs were identified. In the conjoint analysis of multiple environments, twenty-four additive QTLs were identified, and additive QTLs by environments interactions (AE) were evaluated and analyzed at the same time among eleven environments; twenty-three pairs of epistatic QTLs were identified, and epistasis (additive by additive) by environments interactions (AAE) were also analyzed and evaluated among eleven environments. Comparing the results of identification between single environment mapping and multiple environments conjoint mapping, three main effect QTLs with positive additive values and another three main effect QTLs with negative additive values, had no interactions with all environments, supported that these QTLs could be used in molecular assistant breeding in the future. These different effect QTLs could supply a good foundation to the gene clone and molecular asisstant breeding of soybean seed and pod traits.

Usefulness of 10 genomic regions in soybean associated with sudden death syndrome resistance

Sudden death syndrome (SDS) is an important soybean [Glycine max (L) Merrill] disease caused by the soilborne fungus Fusarium virguliforme. Currently, 14 quantitative trait loci (QTL) had been confirmed associated with resistance or tolerance to SDS. The objective of the study was to evaluate usefulness of 10 of these QTL in controlling disease expression. Six populations were developed providing a total of 321 F2-derived lines for the study. Recombinant inbred lines (RIL) used as parents were obtained from populations of 'Essex' × 'Forrest' (EF), 'Flyer' × 'Hartwig' (FH), and 'Pyramid' × 'Douglas' (PD). Disease resistance was evaluated in the greenhouse at three different planting times, each with four replications, using sorghum infested with F. virguliforme homogeneously mixed in the soil (Luckew et al., Crop Sci 52:2215-2223, 2012). Four disease assessment criteria-foliar disease incidence (DI), foliar leaf scorch disease severity (DS), area under the disease progress curve (AUDPC), and root rot severity-were used. QTL were identified in more than one of the disease assessment criteria, mainly associated with lines in the most resistant categories. Five QTL (qRfs4, qRfs5, qRfs7, qRfs12, and Rfs16) were associated with at least one of the disease assessments across multiple populations. Of the five, qRfs4 was associated with DI, AUDPC, and root rot severity, and Rfs16 with AUDPC and root rot severity. The findings suggest it may be possible for plant breeders to focus on stacking a subset of the previously identified QTL to improve resistance to SDS in soybean.

Mapping of QTLs associated with biological nitrogen fixation traits in soybean

Biological nitrogen fixation (BNF) is a key process, but despite the economic and environmental importance, few studies about quantitative trait loci (QTL) controlling BNF traits are available, even in the economically important crop soybean Glycine max (L.) Merr. In this study, a population of 157 F2:7 RILs derived from crossing soybean cultivars Bossier (high BNF capacity) and Embrapa 20 (medium BNF capacity) was genotyped with 105 simple sequence repeat markers (SSRs). The genetic map obtained has 1231.2 cM and covers about 50% of the genome, with an average interval of 18.1 cM. Three traits, nodule number (NN), the ratio nodule dry weight (NDW)/NN and shoot dry weight (SDW) were used to evaluate BNF performance. A composite interval mapping for multiple traits method (mCIM) analysis mapped two QTLs for SDW (LGs E and L), three for NN (LGs B1, E and I), and one for NDW/NN (LG I); all QTLs were of small effect (R-values ranging from 1.7% to 10.0%) and explained 15.4%, 13.8% and 6.5% of total variation for these three traits, respectively.

Molecular mapping and breeding with microsatellite markers

In genetics databases for crop plant species across the world, there are thousands of mapped loci that underlie quantitative traits, oligogenic traits, and simple traits recognized by association mapping in populations. The number of loci will increase as new phenotypes are measured in more diverse genotypes and genetic maps based on saturating numbers of markers are developed. A period of locus reevaluation will decrease the number of important loci as those underlying mega-environmental effects are recognized. A second wave of reevaluation of loci will follow from developmental series analysis, especially for harvest traits like seed yield and composition. Breeding methods to properly use the accurate maps of QTL are being developed. New methods to map, fine map, and isolate the genes underlying the loci will be critical to future advances in crop biotechnology. Microsatellite markers are the most useful tool for breeders. They are codominant, abundant in all genomes, highly polymorphic so useful in many populations, and both economical and technically easy to use. The selective genotyping approaches, including genotype ranking (indexing) based on partial phenotype data combined with favorable allele data and bulked segregation event (segregant) analysis (BSA), will be increasingly important uses for microsatellites. Examples of the methods for developing and using microsatellites derived from genomic sequences are presented for monogenic, oligogenic, and polygenic traits. Examples of successful mapping, fine mapping, and gene isolation are given. When combined with high-throughput methods for genotyping and a genome sequence, the use of association mapping with microsatellite markers will provide critical advances in the analysis of crop traits.

Identification of positive yield QTL alleles from exotic soybean germplasm in two backcross populations

Increasing seed yield is an important breeding goal of soybean [Glycine max (L.) Merr.] improvement efforts. Due to the small number of ancestors and subsequent breeding and selection, the genetic base of current soybean cultivars in North America is narrow. The objective of this study was to map quantitative trait loci (QTL) in two backcross populations developed using soybean plant introductions as donor parents. The first population included 116 BC(2)F(3)-derived lines developed using "Elgin" as the recurrent parent and PI 436684 as the donor parent (E population). The second population included 93 BC(3)F(3)-derived lines developed with "Williams 82" as the recurrent parent and PI 90566-1 as the donor parent (W population). The two populations were evaluated with 1,536 SNP markers and during 2 years for seed yield and other agronomic traits. Genotypic and phenotypic data were analyzed using the programs MapQTL and QTLNetwork to identify major QTL and epistatic QTL. In the E population, two yield QTL were identified by both MapQTL and QTLNetwork, and the PI 436684 alleles were associated with yield increases. In the W population, a QTL allele from PI 90566-1 accounted for 30 % of the yield variation; however, the PI region was also associated with later maturity and shorter plant height. No epistasis for seed yield was identified in either population. No yield QTL was previously reported at the regions where these QTL map indicating that exotic germplasm can be a source of new alleles that can improve soybean yield.

Identification of a new soybean rust resistance gene in PI 567102B

Soybean rust (SBR) caused by Phakopsora pachyrhizi Syd. and P. Syd. is one of the most economically important diseases of soybean (Glycine max (L.) Merr.). Durable resistance to P. pachyrhizi is the most effective long-term strategy to control SBR. The objective of this study was to investigate the genetics of resistance to P. pachyrhizi in soybean accession PI 567102B. This accession was previously identified as resistant to SBR in Paraguay and to P. pachyrhizi isolates from seven states in the USA (Alabama, Florida, Georgia, Louisiana, Mississippi, South Carolina, and Texas). Analysis of two independent populations, one in which F(2) phenotypes were inferred from F(2)-derived F(3) (F(2:3)) families and the other in which F(2) plants had phenotypes measured directly, showed that the resistance in PI 567102B was controlled by a single dominant gene. Two different isolates (MS06-1 and LA04-1) at different locations (Stoneville, MS and Ft. Detrick, MD) were used to independently assay the two populations. Linkage analysis of both populations indicated that the resistance locus was located on chromosome 18 (formerly linkage group G), but at a different location than either Rpp1 or Rpp4, which were previously mapped to this linkage group. Therefore, the SBR resistance in PI 567102B appeared to be conditioned by a previously unreported locus, with an underlying single dominant gene inferred. We propose this gene to be designated Rpp6. Incorporating Rpp6 into improved soybean cultivars may have wide benefits as PI 567102B has been shown to provide resistance to P. pachyrhizi isolates from Paraguay and the US.

Recombination suppression at the dominant Rhg1/Rfs2 locus underlying soybean resistance to the cyst nematode

Host resistance to "yellow dwarf" or "moonlight" disease cause by any population (Hg type) of Heterodera glycines I., the soybean cyst nematode (SCN), requires a functional allele at rhg1. The host resistance encoded appears to mimic an apoptotic response in the giant cells formed at the nematode feeding site about 24-48 h after nematode feeding commences. Little is known about how the host response to infection is mediated but a linked set of 3 genes has been identified within the rhg1 locus. This study aimed to identify the role of the genes within the locus that includes a receptor-like kinase (RLK), a laccase and an ion antiporter. Used were near isogeneic lines (NILs) that contrasted at their rhg1 alleles, gene-based markers, and a new Hg type 0 and new recombination events. A syntenic gene cluster on Lg B1 was found. The effectiveness of SNP probes from the RLK for distinguishing homolog sequence variants on LgB1 from alleles at the rhg1 locus on LgG was shown. The resistant allele of the rhg1 locus was shown to be dominant in NILs. None of the recombination events were within the cluster of the three candidate genes. Finally, rhg1 was shown to reduce the plant root development. A model for rhg1 as a dominant multi-gene resistance locus based on the developmental control was inferred.

Identification of single nucleotide polymorphisms and haplotypes associated with yield and yield components in soybean (Glycine max) landraces across multiple environments

Genome-wide association analysis is a powerful approach to identify the causal genetic polymorphisms underlying complex traits. In this study, we evaluated a population of 191 soybean landraces in five environments to detect molecular markers associated with soybean yield and its components using 1,536 single-nucleotide polymorphisms (SNPs) and 209 haplotypes. The analysis revealed that abundant phenotypic and genetic diversity existed in the studied population. This soybean population could be divided into two subpopulations and no or weak relatedness was detected between pair-wise landraces. The level of intra-chromosomal linkage disequilibrium was about 500 kb. Genome-wide association analysis based on the unified mixed model identified 19 SNPs and 5 haplotypes associated with soybean yield and yield components in three or more environments. Nine markers were found co-associated with two or more traits. Many markers were located in or close to previously reported quantitative trait loci mapped by linkage analysis. The SNPs and haplotypes identified in this study will help to further understand the genetic basis of soybean yield and its components, and may facilitate future high-yield breeding by marker-assisted selection in soybean.

Major locus and other novel additive and epistatic loci involved in modulation of isoflavone concentration in soybean seeds

Seeds of soybean [Glycine max (L.) Merr.] accumulate more isoflavones than any tissue of any plant species. In other plant parts, isoflavones are usually released to counteract the effects of various biotic and abiotic stresses. Because of the benefits to the plant and positive implications that consumption may have on human health, increasing isoflavones is a goal of many soybean breeding programs. However, altering isoflavone levels through marker-assisted selection (MAS) has been impractical due to the small and often environmentally variable contributions that each individual quantitative trait locus (QTL) has on total isoflavones. In this study, we developed a Magellan × PI 437654 F(7)-RIL population to construct a highly saturated non-redundant linkage map that encompassed 451 SNP and SSR molecular markers and used it to locate genomic regions that govern accumulation of isoflavones in the seeds of soybean. Five QTLs were found that contribute to the concentration of isoflavones, having single or multiple additive effects on isoflavone component traits. We also validated a major locus which alone accounted for up to 10% of the phenotypic variance for glycitein, and 35-37% for genistein, daidzein and the sum of all three soybean isoflavones. This QTL was consistently associated with increased concentration of isoflavones across different locations, years and crosses. It was the most important QTL in terms of net increased amounts of all isoflavone forms. Our results suggest that this locus would be an excellent candidate to target for MAS. Also, several minor QTLs were identified that interacted in an additive-by-additive epistatic manner, to increase isoflavone concentration.

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

Soybean BAC-based physical maps provide a useful platform for gene and QTL map-based cloning, EST mapping, marker development, genome sequencing, and comparative genomic research. Soybean physical maps for "Forrest" and "Williams 82" representing the southern and northern US soybean germplasm base, respectively, have been constructed with different fingerprinting methods. These physical maps are complementary for coverage of gaps on the 20 soybean linkage groups. More than 5,000 genetic markers have been anchored onto the Williams 82 physical map, but only a limited number of markers have been anchored to the Forrest physical map. A mapping population of Forrest × Williams 82 made up of 1,025 F(8) recombinant inbred lines (RILs) was used to construct a reference genetic map. A framework map with almost 1,000 genetic markers was constructed using a core set of these RILs. The core set of the population was evaluated with the theoretical population using equality, symmetry and representativeness tests. A high-resolution genetic map will allow integration and utilization of the physical maps to target QTL regions of interest, and to place a larger number of markers into a map in a more efficient way using a core set of RILs.

The genetic control of tolerance to aluminum toxicity in the 'Essex' by 'Forrest' recombinant inbred line population

Aluminum (Al) toxicity to plant roots is a major problem of acidic soils. The main chemical reaction involved is Al hydrolysis. Application of lime or nitrate fertilizers to raise soil pH reduces Al toxicity but not as economically as a plant genotypes with natural tolerance against this stress. Ammonium fertilization of crops and assimilation of ammonium (even that derived from dinitrogen) are particularly acidifying of the root zone. The aims of the present study were to find genotypes of soybean tolerant to aluminum stress and identify QTL underlying that trait. Used were recombinant inbred lines (RILs) derived from the cross of 'Essex' by 'Forrest'. RILs were grown in a greenhouse for 3 weeks and then transferred to hydroponics in a growth chamber. Root lengths (RL) were measured before and 72 h after Al treatment. RL before and after Al treatment were measured and used to calculate root tolerance index (RTI) and relative mean growth (RMG). RILs 1, 85, 40 and 83 had significant (P<0.005) tolerance to Al stress judged by RL after Al, RTI and RMG. Eleven minor but significant marker-trait associations (P<0.05) were detected using one-way ANOVA but only two major loci were significant in composite interval maps (LOD>3.0). The QTL on linkage group F (chromosome 13) was in the interval Satt160-Satt252 with a peak at 24 cM (peak LOD was 3.3). The QTL underlay 31% of trait variation and the Essex allele provided an additional 1.61 cm of root growth over 72 h in the presence of Al. The QTL on linkage group C2 (probably chromosome 4) was in the interval from Satt202 to Satt371 with a peak at 3.2 cM (peak LOD was 14.7). The QTL underlay 34% of trait variation or 1.81 cm of growth over 72 h in the presence of Al. Both loci encompassed genes implicated in citrate metabolism, a method of aluminum detoxification known to vary among soybean cultivars. Two major loci and at least nine minor loci were inferred to underlie tolerance to Al. RILs and markers may be used to select alleles that increase tolerance to soybean against Al stress.

Identification of QTL in soybean underlying resistance to herbivory by Japanese beetles (Popillia japonica, Newman)

Soybean [Glycine max (L.) Merr.] was one of the most important legume crops in the world in 2010. Japanese beetles (JB; Popillia japonica, Newman) in the US were an introduced and potentially damaging insect pest for soybean. JBs are likely to spread across the US if global warming occurs. Resistance to JB in soybean was previously reported only in plant introductions. The aims here were to identify loci underlying resistance to JB herbivory in recombinant inbred lines (RILs) derived from the cross of Essex x Forrest cultivars (EF94) and to correlate those with loci with factors that confer insect resistance in soybean cultivars. The RIL population was used to map 413 markers, 238 satellite markers and 177 other DNA markers. Field data were from two environments over 2 years. Pest severity (PS) measured defoliation on a 0-9 scale. Pest incidence (PI) was the percentage of plants within each RIL with beetles on them. Antibiosis and antixenosis data were from feeding assays with detached leaves in petri plates. Five QTL were detected for the mean PS field trait (16% < R (2) < 27%). The loci were within the intervals Satt632-A2D8 on linkage group (LG) A2 (chromosome 8); Satt583-Satt415 on LG B1 (11); Satt009-Satt530 on LG N (3); and close to two markers OB02_140 (LG E; 20 cM from Satt572) and OZ15_150 LG (19 cM from Satt291 C2). Two QTL were detected for the mean PI field trait (16% < R (2) < 18%) close to Satt385 on LG A1 and Satt440 on LG I. The no choice feeding studies detected three QTL that were significant; two for antixenosis (22% < R (2) < 24%) between Satt632-A2D8 on LG A2 (8) and Sat_039-Satt160 on LG F (13); and a major locus effect (R (2) = 54%) for antibiosis on LG D2 (17) between Satt464-Satt488. Therefore, loci underlying resistance to JB herbivory were a mixture of major and minor gene effects. Some loci were within regions underlying resistance to soybean cyst nematode (LGs A2 and I) and root knot nematode (LG F) but not other major loci underlying resistance to nematode or insect pests (LGs G, H and M).

Intricate environment-modulated genetic networks control isoflavone accumulation in soybean seeds

BACKGROUND

Soybean (Glycine max [L] Merr.) seed isoflavones have long been considered a desirable trait to target in selection programs for their contribution to human health and plant defense systems. However, attempts to modify seed isoflavone contents have not always produced the expected results because their genetic basis is polygenic and complex. Undoubtedly, the extreme variability that seed isoflavones display over environments has obscured our understanding of the genetics involved.

RESULTS

In this study, a mapping population of RILs with three replicates was analyzed in four different environments (two locations over two years). We found a total of thirty-five main-effect genomic regions and many epistatic interactions controlling genistein, daidzein, glycitein and total isoflavone accumulation in seeds. The use of distinct environments permitted detection of a great number of environment-modulated and minor-effect QTL. Our findings suggest that isoflavone seed concentration is controlled by a complex network of multiple minor-effect loci interconnected by a dense epistatic map of interactions. The magnitude and significance of the effects of many of the nodes and connections in the network varied depending on the environmental conditions. In an attempt to unravel the genetic architecture underlying the traits studied, we searched on a genome-wide scale for genomic regions homologous to the most important identified isoflavone biosynthetic genes. We identified putative candidate genes for several of the main-effect and epistatic QTL and for QTL reported by other groups.

CONCLUSIONS

To better understand the underlying genetics of isoflavone accumulation, we performed a large scale analysis to identify genomic regions associated with isoflavone concentrations. We not only identified a number of such regions, but also found that they can interact with one another and with the environment to form a complex adaptable network controlling seed isoflavone levels. We also found putative candidate genes in several regions and overall we advanced the knowledge of the genetics underlying isoflavone synthesis.

Genetic control of soybean seed isoflavone content: importance of statistical model and epistasis in complex traits

A major objective for geneticists is to decipher genetic architecture of traits associated with agronomic importance. However, a majority of such traits are complex, and their genetic dissection has been traditionally hampered not only by the number of minor-effect quantitative trait loci (QTL) but also by genome-wide interacting loci with little or no individual effect. Soybean (Glycine max [L.] Merr.) seed isoflavonoids display a broad range of variation, even in genetically stabilized lines that grow in a fixed environment, because their synthesis and accumulation are affected by many biotic and abiotic factors. Due to this complexity, isoflavone QTL mapping has often produced conflicting results especially with variable growing conditions. Herein, we comparatively mapped soybean seed isoflavones genistein, daidzein, and glycitein by using several of the most commonly used mapping approaches: interval mapping, composite interval mapping, multiple interval mapping and a mixed-model based composite interval mapping. In total, 26 QTLs, including many novel regions, were found bearing additive main effects in a population of RILs derived from the cross between Essex and PI 437654. Our comparative approach demonstrates that statistical mapping methodologies are crucial for QTL discovery in complex traits. Despite a previous understanding of the influence of additive QTL on isoflavone production, the role of epistasis is not well established. Results indicate that epistasis, although largely dependent on the environment, is a very important genetic component underlying seed isoflavone content, and suggest epistasis as a key factor causing the observed phenotypic variability of these traits in diverse environments.

Polygenic inheritance of canopy wilting in soybean [Glycine max (L.) Merr.]

As water demand for agriculture exceeds water availability, cropping systems need to become more efficient in water usage, such as deployment of cultivars that sustain yield under drought conditions. Soybean cultivars differ in how quickly they wilt during water-deficit stress, and this trait may lead to yield improvement during drought. The objective of this study was to determine the genetic mechanism of canopy wilting in soybean using a mapping population of recombinant inbred lines (RILs) derived from a cross between KS4895 and Jackson. Canopy wilting was rated in three environments using a rating scale of 0 (no wilting) to 100 (severe wilting and plant death). Transgressive segregation was observed for the RIL population with the parents expressing intermediate wilting scores. Using multiple-loci analysis, four quantitative trait loci (QTLs) on molecular linkage groups (MLGs) A2, B2, D2, and F were detected (P Collapse

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MESH Headings

• Analysis of Variance
• Chromosome Mapping
• Crosses, Genetic
• Genetic Markers
• Inbreeding
• Multifactorial Inheritance/genetics
• Phenotype
• Plant Leaves/genetics
• Plant Leaves/physiology
• Quantitative Trait Loci/genetics
• Glycine max/genetics
• Glycine max/physiology

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Grants Collapse

Affiliation(s)

Dirk V Charlson Department of Crop, Soil, and Environmental Science, University of Arkansas, Fayetteville, AR 72704, USA
Sandeep Bhatnagar
C Andy King
Jeffery D Ray
Clay H Sneller
Thomas E Carter
Larry C Purcell

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QTL in mega-environments: II. Agronomic trait QTL co-localized with seed yield QTL detected in a population derived from a cross of high-yielding adapted x high-yielding exotic soybean lines

Seed yield mega-environment-universal and specific QTL (QTL(U) and QTL(SP), respectively) linked to Satt100, Satt130, Satt162, Satt194, Satt259 Satt277 and Sat_126, have been identified in a population derived from a cross between a Chinese and a Canadian soybean [Glycine max (L.) Merrill] elite line. The variation observed in yield could be the consequence of the variation of agronomic traits. Yield-component traits have been reported in the literature, but a better understanding of their impact at the molecular level is still lacking. Therefore, the objectives of this study were to identify traits correlated with yield and to determine if the yield QTL(U) and QTL(SP) were co-localized with QTL(U) and QTL(SP) associated with an agronomic trait. A recombinant inbred line (RIL) population was developed from a cross between a high-yielding adapted Canadian and a high-yielding exotic Chinese soybean elite line. The RIL were evaluated in multiple environments in China and Canada during the period from 2004 to 2006. Four yield QTL(U,) tagged by markers Satt100, Satt277, Satt162 and Sat_126, were co-localized with a QTL associated with an agronomic trait, behaving as either QTL(U) or QTL(SP) for the agronomic trait. For example, the yield QTL(U,) tagged by marker Satt100 was associated also with 100 seed weight, pods per plant, pods per node, plant height, R1, R5, R8, oil content and protein content in all Canadian environments, but only with pods per plant, pods per node, plant height, R1, R5, R8 and oil content in two or more Chinese environments. No agronomic traits QTL were co-localized with the yield QTL(U) tagged by the marker Satt139 or the yield QTL(SP) tagged by Satt259, suggesting a physiological basis of the yield in these QTL. The results suggest that a successful introgression of crop productivity alleles from plant introductions into an adapted germplasm could be facilitated by the use of both the QTL(U) and QTL(SP) because each type of QTL contributed either directly or indirectly through yield-component traits to seed yield of RILs.

QTL in mega-environments: I. Universal and specific seed yield QTL detected in a population derived from a cross of high-yielding adapted x high-yielding exotic soybean lines

Modern soybean [(Glycine max (L.) Merrill] breeding programs rely primarily on the use of elite x elite line crosses to develop high-yielding cultivars. Favorable alleles for traits of interest have been found in exotic germplasm but the successful introduction of such alleles has been hampered by the lack of adaptation of the exotic parent to local mega-environment and difficulties in identifying superior progeny from elite x exotic crosses. The objective of this study was to use a population derived from a cross between an adapted and an exotic elite line to understand the genetic causes underlying adaptation to two mega-environments (China and Canada). A cross between a high-yielding Canadian cultivar 'OAC Millennium' and an elite Chinese cultivar 'Heinong 38' was performed to develop a recombinant inbred line (RIL) population. The RIL population was evaluated in China and Canada in multiple environments from 2004 to 2006. Significant variation for seed yield was observed among the RILs in both the Chinese and Canadian environment. Individual RILs performed differently between the Chinese and Canadian environments suggesting differential adaptation to intercontinental mega-environments. Seven seed yield quantitative trait loci (QTL) were identified of which five were mega-environment universal QTL (linked to markers Satt100, Satt162, Satt277, Sat_126, and the interval of Satt139-Sat_042) and two were mega-environment-specific QTL (at marker intervals, Satt194-SOYGPA and Satt259-Satt576). Seed yield QTL located near Satt277 has been confirmed and new QTL have been identified explaining between 9 and 37% of the phenotypic variation in seed yield. The QTL located near Satt100 explained the greatest amount of variation ranging from 18 to 37% per environment. Broad sense heritability ranged from 89 to 64% among environments. Epistatic effects have been identified in both mega-environments with pairs of markers explaining between 9 and 14% of the phenotypic variation in seed yield. An improved understanding of the type of QTL action as either universal or mega-environment-specific QTL as well as their interaction may facilitate the development of strategies to introgress specific high-yielding alleles from Chinese to North American germplasm and vice versa to sustain efforts in breeding of high-yielding soybean cultivars.

Identification of QTL underlying isoflavone contents in soybean seeds among multiple environments

Soybean isoflavones are valued in certain medicines, cosmetics, foods and feeds. Selection for high-isoflavone content in seeds along with agronomic traits is a goal of many soybean breeders. The aim of the study was to identify the quantitative trait loci (QTL) underlying seed isoflavone content in soybean among seven environments in China. A cross was made between 'Zhongdou 27', a soybean cultivar with higher mean isoflavone content in the seven environments (daidzein, DZ, 1,865 microg g(-1); genistein, GT, 1,614 microg g(-1); glycitein, GC, 311 microg g(-1) and total isoflavone, TI, 3,791 microg g(-1)) and 'Jiunong 20', a soybean cultivar with lower isoflavone content (DZ, 844 microg g(-1); GT, 1,046 microg g(-1); GC, 193 microg g(-1) and TI, 2,061 microg g(-1)). Through single-seed-descent, 130 F(5)-derived F(6) recombinant inbred lines were advanced. A total of 99 simple-sequence repeat markers were used to construct a genetic linkage map. Seed isoflavone contents were analyzed using high-performance liquid chromatography for multiple years and locations (Harbin in 2005, 2006 and 2007, Hulan in 2006 and 2007, and Suihua in 2006 and 2007). Three QTL were associated with DZ content, four with GT content, three with GC content, and five with TI content. For all QTL detected the beneficial allele was from Zhongdou 27. QTL were located on three (DZ), three (GC), four (GT) and five (TI) molecular linkage groups (LG). A novel QTL was detected with marker Satt144 on LG F that was associated with DZ (0.0014 > P > 0.0001, 5% < R (2) < 11%; 254 < DZ < 552 microg g(-1)), GT (0.0027 > P > 0.0001; 4% < R (2) < 9%; 262 < GT < 391 microg g(-1)), and TI (0.0011 > P > 0.0001; 4% < R (2) < 15%; 195 < TI < 871 microg g(-1)) across the various environments. A previously reported QTL on LG M detected by Satt540 was associated with TI across four environments and TI mean (0.0022 > P > 0.0001; 3% < R (2) < 8%; 182 < TI < 334 microg g(-1)) in China. Because both beneficial alleles were from Zhongdou 27, it was concluded that these two QTL would have the greatest potential value for marker-assisted selection for high-isoflavone content in soybean seed in China.

Establishment of a soybean (Glycine max Merr. L) transposon-based mutagenesis repository

Soybean is a major crop species providing valuable feedstock for food, feed and biofuel. In recent years, considerable progress has been made in developing genomic resources for soybean, including on-going efforts to sequence the genome. These efforts have identified a large number of soybean genes, most with unknown function. Therefore, a major research priority is determining the function of these genes, especially those involved in agronomic performance and seed traits. One means to study gene function is through mutagenesis and the study of the resulting phenotypes. Transposon-tagging has been used successfully in both model and crop plants to support studies of gene function. In this report, we describe efforts to generate a transposon-based mutant collection of soybean. The Ds transposon system was used to create activation-tagging, gene and enhancer trap elements. Currently, the repository houses approximately 900 soybean events, with flanking sequence data derived from 200 of these events. Analysis of the insertions revealed approximately 70% disrupted known genes, with the majority matching sequences derived from either Glycine max or Medicago truncatula sequences. Among the mutants generated, one resulted in male-sterility and was shown to disrupt the strictosidine synthase gene. This example clearly demonstrates that it is possible to disrupt soybean gene function by insertional mutagenesis and to derive useful mutants by this approach in spite of the tetraploid nature of the soybean genome.

Re-annotation of the physical map of Glycine max for polyploid-like regions by BAC end sequence driven whole genome shotgun read assembly

BACKGROUND

Many of the world's most important food crops have either polyploid genomes or homeologous regions derived from segmental shuffling following polyploid formation. The soybean (Glycine max) genome has been shown to be composed of approximately four thousand short interspersed homeologous regions with 1, 2 or 4 copies per haploid genome by RFLP analysis, microsatellite anchors to BACs and by contigs formed from BAC fingerprints. Despite these similar regions,, the genome has been sequenced by whole genome shotgun sequence (WGS). Here the aim was to use BAC end sequences (BES) derived from three minimum tile paths (MTP) to examine the extent and homogeneity of polyploid-like regions within contigs and the extent of correlation between the polyploid-like regions inferred from fingerprinting and the polyploid-like sequences inferred from WGS matches.

RESULTS

Results show that when sequence divergence was 1-10%, the copy number of homeologous regions could be identified from sequence variation in WGS reads overlapping BES. Homeolog sequence variants (HSVs) were single nucleotide polymorphisms (SNPs; 89%) and single nucleotide indels (SNIs 10%). Larger indels were rare but present (1%). Simulations that had predicted fingerprints of homeologous regions could be separated when divergence exceeded 2% were shown to be false. We show that a 5-10% sequence divergence is necessary to separate homeologs by fingerprinting. BES compared to WGS traces showed polyploid-like regions with less than 1% sequence divergence exist at 2.3% of the locations assayed.

CONCLUSION

The use of HSVs like SNPs and SNIs to characterize BACs wil improve contig building methods. The implications for bioinformatic and functional annotation of polyploid and paleopolyploid genomes show that a combined approach of BAC fingerprint based physical maps, WGS sequence and HSV-based partitioning of BAC clones from homeologous regions to separate contigs will allow reliable de-convolution and positioning of sequence scaffolds (see BES_scaffolds section of SoyGD). This approach will assist genome annotation for paleopolyploid and true polyploid genomes such as soybean and many important cereal and fruit crops.