Zenglu Li

SSR mapping and confirmation of the QTL from PI96354 conditioning soybean resistance to southern root-knot nematode

Abstract Root-knot nematodes (Meloidogyne spp.) can cause severe yield loss of soybean [Glycine max (L.) Merr.] in the southern production region of the USA. Planting root-knot nematode-resistant cultivars is the most effective method of preventing yield loss. DNA marker-assisted breeding may accelerate the development of root-knot nematode-resistant cultivars. RFLP markers have previously been used to identify quantitative trait loci (QTLs) conferring resistance to southern root-knot nematode [Meloidogyne incognita (Kofoid and White) Chitwood] (Mi) in a F2:3 soybean population created by crossing the resistant PI96354 and the susceptible ’Bossier.’ A major QTL on linkage group (LG) O conditioning 31% of the variation in Mi gall number and a minor QTL on LG-G conditioning 14% of the gall variation were reported. With the development of SSR markers for soybean improvement, a higher level of mapping resolution and semi-automated detection has become possible. The objectives of this research were: (1) to increase the marker density in the genomic regions of the QTLs for Mi resistance on LG-O and LG-G with SSR markers; and (2) to confirm the effect of the QTLs in a second population and a different genetic background. With SSR markers, the QTL on LG-O was flanked by Satt492 and Satt358, and on LG-G by Satt012 and Satt505. Utilizing SSR markers flanking the two QTLs, marker-assisted selection was performed in a second F2:3 population of PI96354× Bossier. Results confirmed the effectiveness of marker-assisted selection to predict the Mi phenotypes. By screening the BC2F2 population of Prichard (3)×G93–9009 we confirmed that selection for the minor QTL on LG-G with flanking SSR markers would enhance the resistance of lines containing the major QTL (which is most-likely Rmi1).

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.

SNP identification and marker assay development for high-throughput selection of soybean cyst nematode resistance

BackgroundSoybean cyst nematode (SCN) is the most economically devastating pathogen of soybean. Two resistance loci, Rhg1 and Rhg4 primarily contribute resistance to SCN race 3 in soybean. Peking and PI 88788 are the two major sources of SCN resistance with Peking requiring both Rhg1 and Rhg4 alleles and PI 88788 only the Rhg1 allele. Although simple sequence repeat (SSR) markers have been reported for both loci, they are linked markers and limited to be applied in breeding programs due to accuracy, throughput and cost of detection methods. The objectives of this study were to develop robust functional marker assays for high-throughput selection of SCN resistance and to differentiate the sources of resistance.ResultsBased on the genomic DNA sequences of 27 soybean lines with known SCN phenotypes, we have developed Kompetitive Allele Specific PCR (KASP) assays for two Single nucleotide polymorphisms (SNPs) from Glyma08g11490 for the selection of the Rhg4 resistance allele. Moreover, the genomic DNA of Glyma18g02590 at the Rhg1 locus from 11 soybean lines and cDNA of Forrest, Essex, Williams 82 and PI 88788 were fully sequenced. Pairwise sequence alignment revealed seven SNPs/insertion/deletions (InDels), five in the 6th exon and two in the last exon. Using the same 27 soybean lines, we identified one SNP that can be used to select the Rhg1 resistance allele and another SNP that can be employed to differentiate Peking and PI 88788-type resistance. These SNP markers have been validated and a strong correlation was observed between the SNP genotypes and reactions to SCN race 3 using a panel of 153 soybean lines, as well as a bi-parental population, F5–derived recombinant inbred lines (RILs) from G00-3213 x LG04-6000.ConclusionsThree functional SNP markers (two for Rhg1 locus and one for Rhg4 locus) were identified that could provide genotype information for the selection of SCN resistance and differentiate Peking from PI 88788 source for most germplasm lines. The robust KASP SNP marker assays were developed. In most contexts, use of one or two of these markers is sufficient for high-throughput marker-assisted selection of plants that will exhibit SCN resistance.

The Genetic Architecture of Seed Composition in Soybean Is Refined by Genome-Wide Association Scans Across Multiple Populations

Soybean oil and meal are major contributors to world-wide food production. Consequently, the genetic basis for soybean seed composition has been intensely studied using family-based mapping. Population-based mapping approaches, in the form of genome-wide association (GWA) scans, have been able to resolve loci controlling moderately complex quantitative traits (QTL) in numerous crop species. Yet, it is still unclear how soybean’s unique population history will affect GWA scans. Using one of the populations in this study, we simulated phenotypes resulting from a range of genetic architectures. We found that with a heritability of 0.5, ∼100% and ∼33% of the 4 and 20 simulated QTL can be recovered, respectively, with a false-positive rate of less than ∼6×10−5 per marker tested. Additionally, we demonstrated that combining information from multi-locus mixed models and compressed linear-mixed models improves QTL identification and interpretation. We applied these insights to exploring seed composition in soybean, refining the linkage group I (chromosome 20) protein QTL and identifying additional oil QTL that may allow some decoupling of highly correlated oil and protein phenotypes. Because the value of protein meal is closely related to its essential amino acid profile, we attempted to identify QTL underlying methionine, threonine, cysteine, and lysine content. Multiple QTL were found that have not been observed in family-based mapping studies, and each trait exhibited associations across multiple populations. Chromosomes 1 and 8 contain strong candidate alleles for essential amino acid increases. Overall, we present these and additional data that will be useful in determining breeding strategies for the continued improvement of soybean’s nutrient portfolio.

Transcriptomic changes due to water deficit define a general soybean response and accession-specific pathways for drought avoidance

BackgroundAmong abiotic stresses, drought is the most common reducer of crop yields. The slow-wilting soybean genotype PI 416937 is somewhat robust to water deficit and has been used previously to map the trait in a bi-parental population. Since drought stress response is a complex biological process, whole genome transcriptome analysis was performed to obtain a deeper understanding of the drought response in soybean.ResultsContrasting data from PI 416937 and the cultivar ‘Benning’, we developed a classification system to identify genes that were either responding to water-deficit in both genotypes or that had a genotype x environment (GxE) response. In spite of very different wilting phenotypes, 90% of classifiable genes had either constant expression in both genotypes (33%) or very similar response profiles (E genes, 57%). By further classifying E genes based on expression profiles, we were able to discern the functional specificity of transcriptional responses at particular stages of water-deficit, noting both the well-known reduction in photosynthesis genes as well as the less understood up-regulation of the protein transport pathway. Two percent of classifiable genes had a well-defined GxE response, many of which are located within slow-wilting QTLs. We consider these strong candidates for possible causal genes underlying PI 416937’s unique drought avoidance strategy.ConclusionsThere is a general and functionally significant transcriptional response to water deficit that involves not only known pathways, such as down-regulation of photosynthesis, but also up-regulation of protein transport and chromatin remodeling. Genes that show a genotypic difference are more likely to show an environmental response than genes that are constant between genotypes. In this study, at least five genes that clearly exhibited a genotype x environment response fell within known QTL and are very good candidates for further research into slow-wilting.

Identification of quantitative trait loci underlying resistance to southern root-knot and reniform nematodes in soybean accession PI 567516C

Abstract Soybean cyst nematode (SCN, Heterodera glycine Ichinohe), southern root-knot nematode [SRKN, Meloidogyne incognita (Kofoid and White) Chitwood] and reniform nematode (RN, Rotylenchulus reniformis Linford and Oliveira) are three important plant–parasitic pests in soybean. Previous study showed that plant introduction (PI) 567516C harbored novel quantitative trait loci (QTL) conferring SCN resistance to soybean. However, QTL underlying resistance to SRKN and RN in PI 567516C remain unknown. The objectives of this study were to identify QTL for resistance to SRKN and RN in PI 567516C. Two hundred and forty-seven F6:9 recombinant inbred lines, derived from a cross between cultivar Magellan and PI 567516C, were evaluated for resistance to SRKN and RN. Two hundred and thirty-eight simple sequence repeats and 687 single nucleotide polymorphism markers were used to construct a genetic linkage map. Three significant QTL associated with resistance to SRKN were mapped on chromosomes (Chrs.) 10, 13 and 17. Two significant QTL associated with resistance to RN were detected on Chrs. 11 and 18. Whole-genome resequencing revealed that there might be Peking-type Rhg1 in PI 567516C. Our study provides useful information to employ PI 567516C in soybean breeding in order to develop new cultivars with resistance to multiple nematodes.

Advancements in breeding, genetics, and genomics for resistance to three nematode species in soybean

Key messageIntegration of genetic analysis, molecular biology, and genomic approaches drastically enhanced our understanding of genetic control of nematode resistance and provided effective breeding strategies in soybeans.AbstractThree nematode species, including soybean cyst (SCN, Heterodera glycine), root-knot (RKN, Meloidogyne incognita), and reniform (RN, Rotylenchulus reniformis), are the most destructive pests and have spread to soybean growing areas worldwide. Host plant resistance has played an important role in their control. This review focuses on genetic, genomic studies, and breeding efforts over the past two decades to identify and improve host resistance to these three nematode species. Advancements in genetics, genomics, and bioinformatics have improved our understanding of the molecular and genetic mechanisms of nematode resistance and enabled researchers to generate large-scale genomic resources and marker-trait associations. Whole-genome resequencing, genotyping-by-sequencing, genome-wide association studies, and haplotype analyses have been employed to map and dissect genomic locations for nematode resistance. Recently, two major SCN-resistant loci, Rhg1 and Rhg4, were cloned and other novel resistance quantitative trait loci (QTL) have been discovered. Based on these discoveries, gene-specific DNA markers have been developed for both Rhg1 and Rhg4 loci, which were useful for marker-assisted selection. With RKN resistance QTL being mapped, candidate genes responsible for RKN resistance were identified, leading to the development of functional single nucleotide polymorphism markers. So far, three resistances QTL have been genetically mapped for RN resistance. With nematode species overcoming the host plant resistance, continuous efforts in the identification and deployment of new resistance genes are required to support the development of soybean cultivars with multiple and durable resistance to these pests.

Genomic Signatures of North American Soybean Improvement Inform Diversity Enrichment Strategies and Clarify the Impact of Hybridization

Crop improvement represents a long-running experiment in artificial selection on a complex trait, namely yield. How such selection relates to natural populations is unclear, but the analysis of domesticated populations could offer insights into the relative role of selection, drift, and recombination in all species facing major shifts in selective regimes. Because of the extreme autogamy exhibited by soybean (Glycine max), many “immortalized” genotypes of elite varieties spanning the last century have been preserved and characterized using ∼50,000 single nucleotide polymorphic (SNP) markers. Also due to autogamy, the history of North American soybean breeding can be roughly divided into pre- and posthybridization eras, allowing for direct interrogation of the role of recombination in improvement and selection. Here, we report on genome-wide characterization of the structure and history of North American soybean populations and the signature of selection in these populations. Supporting previous work, we find that maturity defines population structure. Though the diversity of North American ancestors is comparable to available landraces, prehybridization line selections resulted in a clonal structure that dominated early breeding and explains many of the reductions in diversity found in the initial generations of soybean hybridization. The rate of allele frequency change does not deviate sharply from neutral expectation, yet some regions bare hallmarks of strong selection, suggesting a highly variable range of selection strengths biased toward weak effects. We also discuss the importance of haplotypes as units of analysis when complex traits fall under novel selection regimes.

An R package for SNP marker-based parent-offspring tests

BackgroundWith the advancement of genotyping technologies, whole genome and high-density SNP markers have been widely used for genotyping of mapping populations and for characterization of germplasm lines in many crops. Before conducting SNP data analysis, it is necessary to check the individuals to ensure the integrity of lines for further data analysis.ResultsWe have developed an R package to conduct a parent-offspring test of individuals which are genotyped with a fixed set of SNP markers for further genetic studies. The program uses monomorphic SNP loci between parents and their progeny genotypes to calculate the similarity between each offspring and their parents. Based on the similarity of parents and individual offspring, the users can determine the threshold level for the individuals to be included for further data analysis. We used an F5-derived soybean population of ‘5601T’ x PI 157440 that was genotyped with 1,536 SNPs to illustrate the procedure and its application.ConclusionsThe R package ‘ParentOffspring’ coupled with the available SNP genotyping platforms could be used to detect the possible variants in a specific cross, as well as the potential errors in sample handling and genotyping processes. It can be used in any crop which is genotyped with a fixed set of SNP markers.

Impact of Genomic Research on Soybean Breeding

Soybean (Glycine max L. Merrill) is the leading oilseed crop in the world and a primary source of vegetable oil for human consumption and protein meal for animal feed. The USA is the world’s largest soybean producer followed closely by Brazil and Argentina. Soybean breeding has been successful in developing soybean varieties with high yield, enhanced seed composition, and disease and pest resistance using conventional breeding approaches. The main challenge faced by soybean researchers has been continuously increasing genetic gain, yet increases in genetic gain have been observed over the past 80 years. Genomic technologies and DNA markers have been successfully developed and utilized in soybean over the past two decades to identify quantitative trait loci (QTL)/genes for traits of economic importance. These technologies have subsequently been utilized to introgress and select for these traits, enabling breeders to accelerate the breeding cycle and develop productive soybean cultivars. In this chapter, first we briefly review DNA marker technologies and how they have been used to characterize soybean germplasm. Then, we present examples of how genomic tools have been used for QTL discovery for traits of importance and conducting molecular breeding. To conclude, we provide our perspectives on the future of soybean breeding using DNA markers and next-generation sequencing.