PI 438489B Research Articles

Development of SNP molecular markers associated with resistance to reniform nematode in soybean using KASP genotyping

Reniform nematode (Rotylenchulus reniformis, Linford and Oliveira) is a sedentary, semi-endoparasite that infects a wide range of plant hosts and is one of the top three nematode pathogens affecting soybean in the southeastern United States. Previous studies have linked resistance to reniform nematode in soybean to two quantitative trait loci on chromosomes 11 and 18. A Kompetitive Allele-Specific PCR (KASP) assay was designed using SNP markers within these two regions to distinguish reniform nematode-resistant soybean based on genotype. A collection of 44 soybean plant introductions with resistant phenotype to reniform nematode and 40 susceptible soybean lines were genotyped at the two target loci to validate the KASP assay design. Of the 44 observed resistant lines, two carried the susceptible genotype; PI 438489B at the locus on chromosome 18 and PI 495017C on chromosome 11. Of the 40 observed susceptible soybean lines, only 25 had the expected susceptible genotype at the loci on chromosome 18 and 13 on chromosome 11. Our KASP assay was 68% accurate in predicting the phenotype of 84 soybean accessions based on their genotype at the SNP marker on chromosome 18 and 83% accurate at chromosome 11. These results indicate a moderate correlation of soybean SNP markers GlyREN18_46 and GlyREN11_190 with reniform nematode resistance. Further research is required to improve the accuracy of KASP assays to predict soybean response to reniform nematode, particularly host susceptibility.

Dissecting nematode resistance regions in soybean revealed pleiotropic effect of soybean cyst and reniform nematode resistance genes.

Reniform nematode (RN, Rotylenchulus reniformis Linford & Oliveira) has emerged as one of the most important plant parasitic nematodes of soybean [Glycine max (L.) Merr.]. Planting resistant varieties is the most effective strategy for nematode management. The objective of this study was to identify quantitative trait loci (QTL) for RN resistance in an exotic soybean line, PI 438489B, using two linkage maps constructed from the Universal Soybean Linkage Panel (USLP 1.0) and next-generation whole-genome resequencing (WGRS) technology. Two QTL controlling RN resistance were identified-the soybean cyst nematode (SCN, Heterodera glycines) resistance gene GmSNAP18 at the rhg1 locus and its paralog GmSNAP11. Strong association between resistant phenotype and haplotypes of the GmSNAP11 and GmSNAP18 was observed. The results indicated that GmSNAP11 possibly could have epistatic effect on GmSNAP18, or vice versa, with the presence of a significant correlation in RN resistance of rhg1-a GmSNAP18 vs. rhg1-b GmSNAP18. Most importantly, our preliminary data suggested that GmSNAP18 and GmSNAP11 proteins physically interact in planta, suggesting that they belong to the same pathway for resistance. Unlike GmSNAP18, no indication of GmSNAP11 copy number variation was found. Moreover, gene-based single nucleotide polymorphism (SNP) markers were developed for rapid detection of RN or SCN resistance at these loci. Our analysis substantiates synergic interaction between GmSNAP11 and GmSNAP18 genes and confirms their roles in RN as well as SCN resistance. These results could contribute to a better understanding of evolution and subfunctionalization of genes conferring resistance to multiple nematode species and provide a framework for further investigations.

Molecular characterization of genomic regions for resistance to Pythium ultimum var. ultimum in the soybean cultivar Magellan.

Two novel QTL for resistance to Pythium ultimum var. ultimum were identified in soybean using an Illumina SNP Chip and whole genome re-sequencing. Pythium ultimum var. ultimum is one of numerous Pythium spp. that causes severe pre- and post-emergence damping-off of seedlings and root rot of soybean [Glycine max (L.) Merr.]. The objective of this research was to identify quantitative trait loci (QTL) for resistance to P. ultimum var. ultimum in a recombinant inbred line population derived from a cross of 'Magellan' (moderately resistant) and PI 438489B (susceptible). Two different mapping approaches were utilized: the universal soybean linkage panel (USLP 1.0) and the bin map constructed from whole genome re-sequencing (WGRS) technology. Two genomic regions associated with variation in three disease-related parameters were detected using both approaches, with the bin map providing higher resolution. Using WGRS, the first QTL were mapped within a 350-kbp region on Chr. 6 and explained 7.5-13.5% of the phenotypic variance. The second QTL were positioned in a 260-kbp confidence interval on Chr. 8 and explained 6.3-16.8% of the phenotypic variation. Candidate genes potentially associated with disease resistance were proposed. High-resolution genetic linkage maps with a number of significant SNP markers could benefit marker-assisted breeding and dissection of the molecular mechanisms underlying soybean resistance to Pythium damping-off in 'Magellan.' Additionally, the outputs of this study may encourage more screening of diverse soybean germplasm and utilization of genome-wide association studies to understand the genetic basis of quantitative disease resistance.

The ‘PI 438489B’ by ‘Hamilton’ SNP-Based Genetic Linkage Map of Soybean [Glycine max (L.) Merr.] Identified Quantitative Trait Loci that Underlie Seedling SDS Resistance

Soybeans [Glycine max (L.) Merr.] are susceptible to many diseases including fungal diseases such as soybean sudden death syndrome (SDS). Several studies reported SDS resistance quantitative trait loci (QTL) on the soybean genome using different recombinant inbred line (RIL) populations and low density genetic linkage maps. High density exclusively single nucleotide polymorphisms-based (SNP-based) maps were not yet reported in soybean. The objectives of this study were (1) to construct a high density SNP-based genetic linkage map of soybean using the ‘PI438489B’ by ‘Hamilton’ (PIxH, n=50) recombinant inbred line population, and (2) to map QTL for SDS resistance using this high-density reliable genetic SNP-based map. The PI438489B by Hamilton high-density SNP-based genetic map was a high density map composed of 31 LGs, 648 SNPs, and covered 1,524.7 cM with an average of 2.37 cM between two adjacent SNP markers. Fourteen significant QTL were identified for SDS resistance using interval mapping (IM) and composite interval mapping (CIM) with LOD scores that ranged between 2.6 and 5.0. Twelve QTL were identified for foliar disease severity (FDS) and three QTL for root rot severity (RRS) of which one QTL underlain both FDS and RRS. The fourteen QTL were mapped onto ten separate chromosomes of the soybean genome. Seven of the intervals encompassing the QTL had been identified previously (on LGs C1, C2, D1b, G, L, N and O) associated with resistance to SDS but seven were novel (LGs A2 (2), B1, C2, D1a, D1b and O). We constructed the first PI438489B by Hamilton exclusively SNP-Based map and identified fourteen QTL that underlie SDS resistance including both resistances to foliar and root rot symptoms caused by Fusarium virguliforme infection. The QTL discovered here for SDS resistance could be useful to include in breeding programs in developing soybean cultivars resistant to SDS.

Genetic Analysis of Relative Water Content (RWC) in Two Recombinant Inbred Line Populations of Soybean [Glycine max (L.) Merr.

Drought affects soybean [Glycine max (L.) Merr.] and other crops productivity in the US and other parts of the world. Relative water content (RWC) is an important indicator for plant water deficit tolerance (WDT). The objective of this study is to map quantitative trait loci (QTL) for RWC and several other leaf traits such as leaf dry weight (LDW), leaf fresh weight (LFW), and leaf turgid weight (LTW) in two soybean recombinant inbred line (RIL) populations, one derived from a cross of ‘Essex’ and ‘Forrest’ (ExF, n=94) and the other is derived from a cross of ‘PI 438489B’ and ‘Hamilton’ (PIxH, n=50). In the PIxH RIL population, eight QTL were identified and mapped on 6 different linkage groups (LGs) of the soybean genome. No QTL for LFW were identified in this population. In the ExF RIL population, 10 QTL were identified and mapped on 5 different LGs of soybean. Chromosome 18 (LG G) contains clusters of QTL for LFW, LTW, and RWC in the ExF RIL population. This same chromosome contains a QTL for RWC in the PIxH RIL population. The QTL found here are important to be included in breeding programs for soybean water deficit tolerance (WDT).

Effect of Row Spacing on Seed Isoflavone Contents in Soybean [Glycine max (L.) Merr.

Soybean isoflavones compounds such as genistein, daidzein, and glycitein have numerous human health benefits including the reduction of risks of cardiovascular diseases, breast and prostate cancers, and menaupose symptoms in women. Understanding the genetic and environmental control of isoflavones accumulation is of great importance for developing new cultivars with high amounts of seed isoflavones. This study was conducted to analyze the effect of row spacing (25 cm vs. 50 cm) on seed isoflavones accumulation using a recombinant inbred line (RIL) population derived from the cross of PI 438489B and “Hamilton” (PIxH, n = 50). The two row spaces generated plant densities of 250,000 plants/ha and 90,000 plants/ha, respectively. Significant differences in soybean seed isoflavones (daidzein, genistein and glycitein) contents have been observed between plants grown in the two different plant densities. The mean daidzein content was 0.03458 μg·g-1 in plants grown in 50 cm row spaces (low plant density), which was significantly higher than its content (0.03019 μg·g-1) in plants grown in 25 cm row spaces (high plant density). Similarly, the mean glycitein content in plants grown in 50 cm row spaces (0.01905 μg·g-1) was significantly higher than its content in plants grown in 25 cm row spaces (0.00498 μg·g-1. Also, the mean genistein content in plants grown in 50 cm row spaces (0.01466 μg·g-1) was higher than its content in plants grown in 25 cm row spaces (0.00831 μg·g-1). These preliminary results are important in guiding farmers and breeders on choosing the best row spaces to grow soybean plants in order to optimize isoflavones contents. Further studies are needed to understand the correlation between seed isoflavones contents and other agronomic traits such as seed yield, protein, and oil contents.

Pinpointing genes underlying the quantitative trait loci for root-knot nematode resistance in palaeopolyploid soybean by whole genome resequencing

The objective of this study was to use next-generation sequencing technologies to dissect quantitative trait loci (QTL) for southern root-knot nematode (RKN) resistance into individual genes in soybean. Two hundred forty-six recombinant inbred lines (RIL) derived from a cross between Magellan (susceptible) and PI 438489B (resistant) were evaluated for RKN resistance in a greenhouse and sequenced at an average of 0.19× depth. A sequence analysis pipeline was developed to identify and validate single-nucleotide polymorphisms (SNPs), infer the parental source of each SNP allele, and genotype the RIL population. Based on 109,273 phased SNPs, recombination events in RILs were identified, and a total of 3,509 bins and 3,489 recombination intervals were defined. About 50.8% of bins contain 1 to 10 genes. A linkage map was subsequently constructed by using bins as molecular markers. Three QTL for RKN resistance were identified. Of these, one major QTL was mapped to bin 10 of chromosome 10, which is 29.7 kb in size and harbors three true genes and two pseudogenes. Based on sequence variations and gene-expression analysis, the candidate genes underlying the major QTL for RKN resistance were pinpointed. They are Glyma10g02150 and Glyma10g02160, encoding a pectin methylesterase inhibitor and a pectin methylesterase inhibitor -pectin methylesterase, respectively. This QTL mapping approach not only combines SNP discovery, SNP validation, and genotyping, but also solves the issues caused by genome duplication and repetitive sequences. Hence, it can be widely used in crops with a reference genome to enhance QTL mapping accuracy.

Genetic Mapping and Confirmation of Quantitative Trait Loci for Seed Protein and Oil Contents and Seed Weight in Soybean

ABSTRACTDemand for soybean [Glycine max (L.) Merr.] meal has increased worldwide and soybean importers often offer premiums for soybean containing higher contents of protein and oil. Objectives were to detect quantitative trait loci (QTL) associated with soybean seed protein, oil, and seed weight in a soybean mapping population and confirm detected QTL across genetic backgrounds and environments. Two populations of 216 and 156 recombinant inbred lines were developed from Magellan × PI 438489B and Magellan × PI 567516C crosses, respectively, and grown in two Missouri environments in 2008. More than 900 simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers were used for mapping in each population. Across environments and genetic backgrounds, we have identified seven QTL for protein, six for oil, and four for seed weight. Two QTL were detected in common for protein and oil, one on chromosome (Chr.) 5 and another on Chr. 6. Additionally, we have detected one new seed weight QTL on Chr. 6, in the same region of protein and oil QTL. Confirmed protein and oil QTL on Chrs. 5 and 6 may be important targets to find candidate genes involved in modification of protein and oil contents and seed weight using genetic and genomic approaches. Also, SSR and SNP markers closely associated with these QTL can be useful for marker‐assisted selection.

Quantitative Trait Loci Associated with Moisture, Protein, and Oil Content in Soybean [Glycine max (L.) Merr.

The objectives of this study were to detect quantitative trait loci (QTL) for moisture, protein, and oil content in soybean grown in two plant density environments. Soybean recombinant inbred lines (RIL), obtained from a cross between cultivars PI 438489B and Hamilton, were used. Thirty one linkage groups were obtained from high density genetic linkage maps constructed by 1,536 Universal Soy Linkage Panel 1.0 of single nucleotide polymorphisms (SNP) markers. For the lines cultivated in higher plant density (25 cm row space), ten QTLs were mapped in A2, B2, C2, D1a, M and O linkage groups for moisture, protein, and oil. Two QTLs for moisture, two QTLs for protein and six QTLs for oil explained 0.09, 15.36 and 3.54% of the phenotypic variation of moisture, protein, and oil respectively. For the lines cultivated in lower density (50 cm row space), three QTLs for each of moisture and protein were mapped in linkage groups A2, C1, D1b, L and O; QTLs for moisture and protein explained 0.96 and 10.63% of the phenotypic variation respectively. These QTL will facilitate the implementation of MAS for moisture, protein and oil content in soybean-breeding programs.

Genetic Analysis of Yield Components in the PI 438489B by ‘Hamilton’ Recombinant Inbred Line (RIL) Population of Soybean [Glycine max (L.) Merr.

Yield is a multi-factorial trait determined by several genetic traits and highly correlated with important agronomic traits in many crops including soybean. [Glycine max (L.)]. Plant height, seed and pod numbers, and seed weight are all components of yield and polygenic in nature. The objective of this study was to identify quantitative trait loci (QTL) for days to germination, days to flowering, plant height, pod number, seed number, 100-seed weight, and total seed weight in soybean using the using the PI 438489B by ‘Hamilton’ recombinant inbred line (RIL) population (PIxH, n=50). A total of 18 QTL were found on 10 different chromosomes. Three QTL for days to germination (qDG001-qDG003) have been identified on chromosomes 5b, 6, and 13b. Two QTL (qDF001 and qDF002) have been identified on chromosomes 9 and 13b, respectively. On QTL for plant height (qPH001) have been identified on chromosome 6. Four QTL for pod number (qPN001-qPN004) had been identified on chromosomes 2, 6, and 8 (2 QTL), respectively. Two QTL for seed number (qSN001 and qSN002) have been identified on chromosomes 5b and 11b, respectively. Five QTL for 100-seed weight (qSW001 to qSW005) have been identified on chromosomes 5a, 6, 8, 9, and 11c, respectively. Two QTL for total seed weight (qTSW001 and qTSW002) have been identified on chromosomes 5b and 17c, respectively. The QTL identified here may be introduced in breeding programs to develop soybean cultivars with high yield potential.

Genetic Analysis of Relative Water Content (RWC) in Two Recombinant Inbred Line Populations of Soybean [Glycine max (L.) Merr.

Drought affects soybean [Glycine max (L.) Merr.] and other crops productivity in the US and other parts of the world. Relative water content (RWC) is an important indicator for plant water deficit tolerance (WDT). The objective of this study is to map quantitative trait loci (QTL) for RWC and several other leaf traits such as leaf dry weight (LDW), leaf fresh weight (LFW), and leaf turgid weight (LTW) in two soybean recombinant inbred line (RIL) populations, one derived from a cross of ‘Essex’ and ‘Forrest’ (ExF, n=94) and the other is derived from a cross of ‘PI 438489B’ and ‘Hamilton’ (PIxH, n=50). In the PIxH RIL population, eight QTL were identified and mapped on 6 different linkage groups (LGs) of the soybean genome. No QTL for LFW were identified in this population. In the ExF RIL population, 10 QTL were identified and mapped on 5 different LGs of soybean. Chromosome 18 (LG G) contains clusters of QTL for LFW, LTW, and RWC in the ExF RIL population. This same chromosome contains a QTL for RWC in the PIxH RIL population. The QTL found here are important to be included in breeding programs for soybean water deficit tolerance (WDT).

The ‘PI 438489B’ by ‘Hamilton’ SNP-Based Genetic Linkage Map of Soybean [Glycine max (L.) Merr.] Identified Quantitative Trait Loci that Underlie Seedling SDS Resistance

Soybeans [Glycine max (L.) Merr.] are susceptible to many diseases including fungal diseases such as soybean sudden death syndrome (SDS). Several studies reported SDS resistance quantitative trait loci (QTL) on the soybean genome using different recombinant inbred line (RIL) populations and low density genetic linkage maps. High density exclusively single nucleotide polymorphisms-based (SNP-based) maps were not yet reported in soybean. The objectives of this study were (1) to construct a high density SNP-based genetic linkage map of soybean using the ‘PI438489B’ by ‘Hamilton’ (PIxH, n=50) recombinant inbred line population, and (2) to map QTL for SDS resistance using this high-density reliable genetic SNP-based map. The PI438489B by Hamilton high-density SNP-based genetic map was a high density map composed of 31 LGs, 648 SNPs, and covered 1,524.7 cM with an average of 2.37 cM between two adjacent SNP markers. Fourteen significant QTL were identified for SDS resistance using interval mapping (IM) and composite interval mapping (CIM) with LOD scores that ranged between 2.6 and 5.0. Twelve QTL were identified for foliar disease severity (FDS) and three QTL for root rot severity (RRS) of which one QTL underlain both FDS and RRS. The fourteen QTL were mapped onto ten separate chromosomes of the soybean genome. Seven of the intervals encompassing the QTL had been identified previously (on LGs C1, C2, D1b, G, L, N and O) associated with resistance to SDS but seven were novel (LGs A2 (2), B1, C2, D1a, D1b and O). We constructed the first PI438489B by Hamilton exclusively SNP-Based map and identified fourteen QTL that underlie SDS resistance including both resistances to foliar and root rot symptoms caused by Fusarium virguliforme infection. The QTL discovered here for SDS resistance could be useful to include in breeding programs in developing soybean cultivars resistant to SDS.

Genetic analysis of resistance to soybean cyst nematode in PI 438489B.

Soybean (Glycine max L. Merr.) plant introduction PI 438489B is a unique source that has resistance to all known populations of soybean cyst nematode (Heterodera glycines Ichinohe, SCN). This PI line also has many desirable agronomic characteristics, which makes it an attractive source of SCN resistance for use in a soybean breeding program. However, characterization of SCN resistance genes in this PI line have not been fully researched. In this study, we investigated the inheritance of resistance to populations of SCN races 1, 2, 3, 5, and 14 in PI 438489B. PI 438489B was crossed to the susceptible cultivar ‘Hamilton’ to generate F1 hybrids. The random F2 plants and F3 lines were evaluated in the greenhouse for reaction to these five populations of SCN races. Resistance to SCN races 1, 3, and 5 were mostly conditioned by three genes (Rhg Rhg rhg). Resistance to race 2 was controlled by four genes (Rhg rhg rgh rgh). Three recessive genes were most likely involved in giving resistance to race 14. We further concluded that resistance to different populations of SCN races may share some common genes or pleiotropic effects may be involved.

Selection of atrazine tolerant soybean calli and expression of that tolerance in regenerated plants

Lines of soybean [Glycine max (L.)] tolerant of atrazine were developed by an in vitro and in vivo atrazine challenge. Cotyledonary node plus epicotyl explants from mature germinated seed of soybean introduction PI 438489B were cultured on RV-5 medium containing 48 mg active ingredient (a.i.)/l atrazine for one month. Most of the explants (66%) on medium containing atrazine, and 10% on medium without atrazine died. Explants surviving exposure to atrazine callused and organogenically regenerated shoots developed. Soil around R0 plants regenerated from atrazine tolerant shoots and nonatrazine challenged shoots (controls) were subsequently tested in vivo for atrazine tolerance. All controls died. Seeds were collected from atrazine tolerant R0 plants. Two weeks after planting, emerged R1 seedlings were tested in vivo for atrazine tolerance as the R0 plants were. This procedure was repeated on the R2 plants. All nonatrazine selected control plants died when exposed to this herbicide. Atrazine tolerant R2 plants were maintained in atrazine amended soil and appeared as healthy and vigorous as the control growing in atrazine free soil.

Somaclonal variation in soybean plants regenerated from tissue culture

Callus cultures of soybean (Glycine max (L.) Merr.) genotypes PI 88788, PI 438489B, and cultivar Bedford were initiated in vitro from seedling explants consisting of the cotyledonary node plus epicotyl from germinated mature seed. Plants were regenerated from these callus cultures and subsequently evaluated for qualitative variation in three to four subsequent generations. Variant phenotypes observed that have not been previously reported from tissue culture include lanceolate leaves, leaf variegation (chimeral variegated plants), pod variegation on otherwise normal plants, and change in growth habit from indeterminate to determinate. The lanceolate leaf, chimeral variegated plant, and change from indeterminate to determinate growth habit characters were inherited through at least three generations (R0-R2), and segregation occurred in each generation. Pod variegation was inherited through the two generations tested thus far and segregation occurred in each generation. No variation was observed in control plants derived from normal seed. Variants appeared more frequently in regenerants from PI 88788 and PI 438489B than from Bedford. These results confirm and extend the finding that certain tissue culture techniques may be used to induce novel plant formation from somatic tissue of soybean.

Genetic Relationships among Soybean Plant Introductions for Resistance to Race 3 of Soybean Cyst Nematode

Soybean cyst nematode (SCN), Heterodera glycines Ichinohe, is a major pest of soybean, Glycine max L. Merr. Several plant introductions resistant to Race 3 have been identified, however the genetic relationships for resistance among them are not known. The F2 plants and F3 families from seven different crosses involving resistant parents were evaluated in the greenhouse to determine if the genes for resistance were identical or different from the genes in ‘Peking’ and/or PI 90763. Each seedling was inoculated with 1000 eggs and juveniles of SCN Race 3. Plant roots were washed after 30 d and white females enumerated. Based on the index of parasitism (IP) F2 plants and F3 families were categorized into resistant, segregating, or susceptible. The Chi‐square test was applied to determine goodness of fit between the observed and expected genetic ratios. Peking was found to have genes in common with PI 90763 and PI 438489B; whereas PI 90763 has genes in common with PI 438489BP, PI 404166, and PI 404198A. The cross between Peking and PI 88788 indicated segregation for one dominant and one recessive gene, and segregation in the cross PI 88788 × PI 438496B suggested two independent dominant genes. This information will assist soybean breeders in choosing additional resistant sources to SCN Race 3 in commercial cultivar development, thus providing a broader genetic base.