A SNP-Based Genetic Linkage Map of Soybean Using the SoySNP6K Illumina Infinium BeadChip Genotyping Array

This study reports a high density genetic linkage map based on the ‘Maryland 96-5722’ by ‘Spencer’ recombinant inbred line (RIL) population of soybean [Glycine max (L.) Merr.] and constructed exclusively with single nucleotide polymorphism (SNP) markers. The Illumina Infinium SoySNP6K BeadChip genotyping array produced 5,376 SNPs in the mapping population, with a 96.75% success rate. Significant level of goodness-of-fit for each locus was tested based on the observed vs. expected ratio (1:1). Out of 5,376 markers, 1,465 SNPs fit the 1:1 segregation rate having ≤20% missing data plus heterozygosity among the RILs. Among this 1,456 just 657 were polymorphic between the parents DNAs tested. These 657 SNPs were mapped using the JoinMap 4.0 software and 550 SNPs were distributed on 16 linkage groups (LGs) among the 20 chromosomes of the soybean genome. The total map length was just 201.57 centiMorgans (cM) with an average marker density of 0.37 cM. This is one of the high density SNP-based genetic linkage maps of soybean that will be used by the scientific community to map quantitative trait loci (QTL) and identify candidate genes for important agronomic traits in soybean.

Resistance to Soybean Cyst Nematode: Rhg1

The genes underlying rhg1 lie at a sometimes dominant sometimes co-dominant locus, necessary for resistance to all Hg types of the soybean (Glycine max (L.) Merr.) cyst nematode (Heterodera glycines). Genomic research identified; nucleotide changes within a candidate gene encoding a receptor like kinase (RLK) that were capable of altering root development and thereby part of the resistance to Hg types 0 (race 3); changes in a laccase that are capable of altering cyst development; and genes underlying changes in membrane biology. This set of three genes are subject to co-selection with a modifier locus on another linkage block. Root development is slowed in the resistant seedling and results in end of season yield loss when SCN is not present. However, in the presence of SCN resistant seedling roots grow just as vigorously as the now slower growing parasitized susceptible roots and therefore show little loss to SCN parasitism. In some genotypes but not others the RLK can act alone to confer resistance. Functional paralogs of the three gene cluster have been found on other linkage groups including A1, B1, G, and O and these can be functional in different sources of resistance like G. soja, PI 437654 and PI438489B. At rhg1 the allele differences change the structure, interacting partners and activity of the LRR protein and the laccase. The changes between the alleles result in about 30 other proteins (judged by 2 Dgels), 112 metabolites (by FTICRMS) and 8 metabolites (by GCMS) to increase in abundance in roots during SCN infection in the resistant NILs. Understanding the basis of root stunting by resistance alleles will be used to improve methods for developing new nematode resistant soybean cultivars that do not suffer from the yield suppression and low seed germination rates of existing cultivars.

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, Biochemical, and Morphological Diversity of the Legume Biofuel Tree Pongamia pinnata

Pongamia pinnata is regarded as a sustainable biofuel feedstock of the future because of its abundant production of oil-rich seeds, tolerance to abiotic stress, and ability to undergo biological nitrogen fixation (minimizing nitrogen inputs). However, it needs extensive domestication through selection and genetic improvement. Owing to its outcrossing nature, Pongamia displays large phenotypic diversity, which is advantageous for selection of desirable phenotypes but problematic for plantation management. In this study, variation was evaluated for seed mass, oil content, and oil composition. To evaluate genetic diversity and to lay the basis for a molecular breeding approach we developed second generation sequencing (2GS)-derived ISSR markers (Pongamia Inter-Simple Sequence Repeats; PISSR). The special feature of PISSRs is that the number of nucleotide repeats and the 5’ and 3’ nucleotide extensions were not arbitrarily chosen, but were based on Pongamia genomic sequences obtained from a NGS (Illumina®) database. Amplification products were resolved by polyacrylamide gel electrophoresis and silver staining or automated capillary electrophoresis to yield distinct and reproducible profiles. Polymorphic bands were excised from polyacrylamide gels and sequenced to reveal similarity to DNA sequences from other legumes. We demonstrated: 1) an abundance of nucleotide core repeats in the Pongamia genome, 2) large genetic and phenotypic diversity among randomly sampled Pongamia trees, 3) restricted diversity in progeny derived from a single mature tree; 4) stability of PISSR markers in Pongamia clones; and 5) genomic DNA sequences within PISSR markers. PISSRs provide a valuable biotechnology tool for assessment of genetic diversity, gene tagging and molecular breeding in Pongamia pinnata.

Introduction of High Throughput and Cost Effective SNP Genotyping Platforms in Soybean

We presented here the application of two in-plate SNP (single nucleotide polymorphism) genotyping platforms for soybean plants [Glycine max (L.) Merr.], KASP® (Kompetitive Allele Specific PCR genotyping, LGC Genomics) and TaqMan® (Life Technologies) respectively. These two systems offer us an ability to determine the genotypes of 384 individual samples accurately and efficiently by allele specific PCR in a single plate using typical PCR conditions. Both of the systems require small quantity of genomic DNA obtained from a simple DNA extraction. The genomic sequences containing target SNPs can easily be used as a basic blueprint to design the probes and primers of KASP® and TaqMan® assays whether the sequences are obtained from the genome sequence of soybean William 82 (Wm82.a2.v1), Illumina Soy50k SNPs, or parallel resequencing. Moreover, we listed the pros and cons of the two systems and explained the principles behind the platforms. The high call rate and clear clustering separation of the SNPs can be readily obtained from these platforms without conducting any assay optimization processes. These platforms can routinely be performed on 96/384-well plate format with or without an automation procedure. Therefore, these platforms are especially suitable for the SNP genotyping on a particular trait with a large sample size, gene fine mapping, and marker assisted selection. Further, they require little hands-on experience and achieve per-site and per-individual costs below that of current SSR, AFLP, RFLP, and SNP chip technologies. The platforms can be used for genotyping on a wide range of organisms due to their simplicity and flexibility of handling. Meanwhile, we also especially presented some of the advantages using KASP® SNP genotyping pipeline, which was cost effective in the selection of allele specific assay and therefore, efficiently facilitated the soybean genotyping across large numbers (thousands or more) of individual lines for a great range of markers (hundreds to thousands) in our laboratory.

New Approaches to Selecting Resistance or Tolerance to SDS and Fusarium Root Rot

Fusarial rots are a significant problem worldwide affecting roots (and sometimes fruits) of most major crops including soybean, maize and wheat. Cultivar variation in partial resistance or tolerance is widespread and significant. Different cultivars of the soybean [Glycine max (L.) Merr.] have both resistance/tolerance to the leaf scorch known as Sudden Death Syndrome (SDS) and to the infection and root rot by the causal organism, Fusarium virguliforme (ex. F. solani f. sp glycines) hence the syndrome is composed of two diseases (1-3). Thirteen loci have been identified from analysis of 7 different crosses (2). Using new strains and new methods resistance loci in ‘Hartwig’ and ‘Forrest’, resistant cultivars clearly showed two loci underlie root resistance (lower LG G and D2) and four to eleven loci underlie leaf scorch resistance, depending on the cross made(eg, C2, F, I and upper G in ExF). Transcript abundance analysis of roots in response to F. virguliforme shows an orthologous set of transcripts accumulate during infection of resistant soybean cultivars and Arabidopsis thaliana that include the pathways leading to phenylpropanoid metabolism and its control, guanyl cylase a common second messenger and several transcription factors. Guanyl cyclase is also implicated in resistance in maize. In root disease resistance the genes implicated were known to be stress related. Therefore, A. thaliana is partially resistant and can be used to test both transgenes and mutants in candidate genes. Trangenics show fine maps to BACs have isolated some genes. For example, by fine mapping in NILs candidate genes underlying the controlling loci programming root resistance was a multi-stress resistance protein (lower G; Rfs1). For leaf scorch (Rfs4) an ascorbate peroxidase (C2) has been targeted. Also, Rfs2, a receptor like kinase (G) has been used to generate stable transgenic soybeans. Identification of the genes and loci conferring SDS resistance has provided options to breed improved cultivars with resistance to SDS.

Using A Minimum Tile Path For Plant Transformations Encompassing the Entire Soybean Genome

Genomes like Glycine max (soybean) that have been highly conserved following increases in ploidy represent a frontier for genome analysis. Many soybean QTL analyzed to date have been composed of gene clusters each with contributing a portion of the trait rather than alleles of single genes. At the Soybean Genome Database (SoyGD) http://soybeangenome.siu.edu the genome browser that integrates and served the publicly available soybean physical map, BAC fingerprint database and genetic map associated genomic data shows a minimum tile of transformation ready BIBAC-like clones in pCLD04541 (pV41; oriV; tra; bom). Sequence resources made available through the DOE genome sequencing project have allowed the minimum tile to be revised and new functional analyses to be made. There are 3,840 MTP clones that appeared to encompass 90% of the genome (see http://soybeangenome.siu.edu/cgi-bin/gbrowse/BES_scaffolds). The BIBAC-like clones (tetR) from E. coli DH10 B were transferred en masse to Agrobacterium tumefaciens by triparental matings with EHA105 (rifR) mediated by pRK2013 (oriP) in DH10B (kanR) in 384 well plates. Although not necessary the extra helper plasmid boosted efficiency 10 fold. Individual A. tumefaciens rifampicin and tetracyclin resistant strains were used for transformation of Arabidopsis thaliana flowers in 384 well arrays. Initially kanamycin selection was used to isolate transgenic plants. Because the BACs were already tetR the recA mutants of A. tumefaciens could not be used (Tn3 insertions). Consequent to this and partial transconjugation events only some inserts are transferred completely while other transformed lines contain a substitution series of deleted inserts anchored on the Ti-left border (LB). These are maintained as kanR mixtures of seed. Phenotypes found for lines transgenic for particular BACs that were repeated include seed composition (protein, oil), development (growth, senescence) and disease resistance (suddean death syndrome (SDS) and soybean cyst nematode (SCN).

Genetic Analysis of Root and Shoot Traits in the ‘Essex’ By ‘Forrest’ Recombinant Inbred Line (RIL) Population of Soybean [Glycine max (L.) Merr.]

Crop productivity is severely reduced by water deficit and drought in many plant species including soybean. Improved root and shoot traits can contribute to drought tolerance ability of the plant. This research was conducted to identify QTL that underlie several root and shoot traits in the ‘Essex’ by ‘Forrest’ (ExF RILs, n=94) recombinant inbred line (RIL) soybean population. Field collected samples were used for gathering phenotypic data of basal root thickness (BRT), lateral root number (LRN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW), shoot fresh weight (SFW), shoot dry weight (SDW), and calculating RFW/SFW, and RDW/SDW ratios. All traits and ratios were compared against DNA markers using the composite interval mapping (CIM). A total of 12 QTL: 3 for MRL, 1 QTL for LRN, 1 QTL for BRT, 2 QTL for RFW, 2 QTL for RDW, 4 QTL for SFW, 3 QTL for SDW, and 3 QTL for SFW/SDW were identified and mapped on different linkage groups (LGs) A2, B2, C2, D1a, F, G, and N. The LOD scores of these QTL ranged from 2.5 to 6.0. No QTL were associated with RFW/RDW. The root and shoot trait QTL of this study may benefit breeding programs for producing cultivars tolerant to water deficit and high yield. Preliminary analyses of genes the QTL regions using GO annotation gave insight into genes that may underlie some of these QTLs.

Selective Genotyping for Marker Assisted Selection Strategies for Soybean Yield Improvement

Using molecular markers in soybean [Glycine max (L.) Merr.] has lead to the identification of major loci controlling quantitative and qualitative traits that include: disease resistance, insect resistance and tolerance to abiotic stresses. Yield has been considered as one of the most important quantitative traits in soybean breeding. Unfortunately, yield is a very complex trait and most yield quantitative trait loci (QTL) that have been identified have had only limited success for marker assisted selection (MAS). The objective of this study was to identify QTL associated with soybean seed yield in preliminary yield trials grown in different environments and to evaluate their effective use for MAS using a yield prediction model (YPM), which included epistasis. To achieve this objective, 875 F5:9 recombinant inbred lines (RIL) from a population developed from a cross between two prominent ancestors of the North American soybean (Essex and Williams 82) were used. The 875 RIL and check cultivars were divided into four groups based on maturity and each group was grown in Knoxville, TN and one other location that had an environment in which the maturity group (MG) was adapted to be grown. Each RIL was genotyped with >50,000 single nucleotide polymorphic markers (SNPs) of which 17,232 were polymorphic across the population. Yield QTL were detected using a single factor (SF) analysis of variance (ANOVA) and composite interval mapping (CIM). Based on CIM, 23 yield QTL were identified. Twenty-one additional QTL were detected using SF ANOVA. Individually, these QTL explained from 4.5% to 11.9% of the phenotypic variation for yield. QTL were identified on all 20 chromosomes and five of the 46 QTL have not been previously reported. This study provides new information concerning yield QTL in soybean and may offer important insights into MAS strategies for soybean.

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).