Interactions Among Heterodera glycines, Macrophomina phaseolina, and Soybean Genotype.

Heterodera glycines, the soybean cyst nematode (SCN), and fungal pathogen Macrophomina phaseolina are economically important soybean pathogens that may coinfest fields. Resistance remains the most effective management tactic for SCN, and the rhg1-b resistance allele derived from plant introduction 88788 is most commonly deployed in the northern United States. The concomitant effects of SCN and M. phaseolina on soybean performance, as well as the effect of the rhg1-b allele in two different genetic backgrounds, were evaluated in three environments (during 2013 to 2015) and a greenhouse bioassay. Within two soybean populations, half of the lines had the rhg1-b allele, and the other half had the susceptible allele in the backgrounds of the cultivars IA3023 and LD00-3309. Significant interactions between soybean rhg1-b allele and M. phaseolina-infested plots were observed in 2014. In all experiments, initial SCN populations (Pi) and M. phaseolina in roots were associated with reduced soybean yield. SCN reproduction factor (RF = final population/Pi) was affected by SCN Pi, rhg1-b, and genetic background. A background-by-genotype interaction on yield was observed only in 2015, with a stronger rhg1-b effect in the LD00-3309 background, which suggested that the susceptible parent 'IA3023' is tolerant to SCN. SCN female index from greenhouse experiments was compared with field RF, and Lin's concordance and Pearson's correlation coefficients decreased with increasing field SCN Pi in soil. In this study, both SCN and M. phaseolina reduced soybean yield asymptomatically, and the impact of SCN rhg1-b resistance was dependent on SCN virulence but also population density.

Genotype imputation for soybean nested association mapping population to improve precision of QTL detection.

KEY MESSAGE: Software for high imputation accuracy in soybean was identified. Imputed dataset could significantly reduce the interval of genomic regions controlling traits, thus greatly improve the efficiency of candidate gene identification. Genotype imputation is a strategy to increase marker density of existing datasets without additional genotyping. We compared imputation performance of software BEAGLE 5.0, IMPUTE 5 and AlphaPlantImpute and tested software parameters that may help to improve imputation accuracy in soybean populations. Several factors including marker density, extent of linkage disequilibrium (LD), minor allele frequency (MAF), etc., were examined for their effects on imputation accuracy across different software. Our results showed that AlphaPlantImpute had a higher imputation accuracy than BEAGLE 5.0 or IMPUTE 5 tested in each soybean family, especially if the study progeny were genotyped with an extremely low number of markers. LD extent, MAF and reference panel size were positively correlated with imputation accuracy, a minimum number of 50 markers per chromosome and MAF of SNPs > 0.2 in soybean line were required to avoid a significant loss of imputation accuracy. Using the software, we imputed 5176 soybean lines in the soybean nested mapping population (NAM) with high-density markers of the 40 parents. The dataset containing 423,419 markers for 5176 lines and 40 parents was deposited at the Soybase. The imputed NAM dataset was further examined for the improvement of mapping quantitative trait loci (QTL) controlling soybean seed protein content. Most of the QTL identified were at identical or at similar position based on initial and imputed datasets; however, QTL intervals were greatly narrowed. The resulting genotypic dataset of NAM population will facilitate QTL mapping of traits and downstream applications. The information will also help to improve genotyping imputation accuracy in self-pollinated crops.

An atypical N-ethylmaleimide sensitive factor enables the viability of nematode-resistant Rhg1 soybeans.

N-ethylmaleimide sensitive factor (NSF) and α-soluble NSF attachment protein (α-SNAP) are essential eukaryotic housekeeping proteins that cooperatively function to sustain vesicular trafficking. The "resistance to Heterodera glycines 1" (Rhg1) locus of soybean (Glycine max) confers resistance to soybean cyst nematode, a highly damaging soybean pest. Rhg1 loci encode repeat copies of atypical α-SNAP proteins that are defective in promoting NSF function and are cytotoxic in certain contexts. Here, we discovered an unusual NSF allele (Rhg1-associated NSF on chromosome 07; NSFRAN07 ) in Rhg1+ germplasm. NSFRAN07 protein modeling to mammalian NSF/α-SNAP complex structures indicated that at least three of the five NSFRAN07 polymorphisms reside adjacent to the α-SNAP binding interface. NSFRAN07 exhibited stronger in vitro binding with Rhg1 resistance-type α-SNAPs. NSFRAN07 coexpression in planta was more protective against Rhg1 α-SNAP cytotoxicity, relative to WT NSFCh07 Investigation of a previously reported segregation distortion between chromosome 18 Rhg1 and a chromosome 07 interval now known to contain the Glyma.07G195900 NSF gene revealed 100% coinheritance of the NSFRAN07 allele with disease resistance Rhg1 alleles, across 855 soybean accessions and in all examined Rhg1+ progeny from biparental crosses. Additionally, we show that some Rhg1-mediated resistance is associated with depletion of WT α-SNAP abundance via selective loss of WT α-SNAP loci. Hence atypical coevolution of the soybean SNARE-recycling machinery has balanced the acquisition of an otherwise disruptive housekeeping protein, enabling a valuable disease resistance trait. Our findings further indicate that successful engineering of Rhg1-related resistance in plants will require a compatible NSF partner for the resistance-conferring α-SNAP.

Field evaluation of three sources of genetic resistance to sudden death syndrome of soybean.

KEY MESSAGE: Despite numerous challenges, field testing of three sources of genetic resistance to sudden death syndrome of soybean provides information to more effectively improve resistance to this disease in cultivars. Sudden death syndrome (SDS) of soybean [Glycine max (L.) Merrill] is a disease that causes yield loss in soybean growing regions across the USA and worldwide. While several quantitative trait loci (QTL) for SDS resistance have been mapped, studies to further evaluate these QTL are limited. The objective of our research was to map SDS resistance QTL and to test the effect of mapped resistance QTL on foliar symptoms when incorporated into elite soybean backgrounds. We mapped a QTL from Ripley to chromosome 10 (CHR10) and a QTL from PI507531 to chromosomes 1 and 18 (CHR1 and 18). Six populations were then developed to test the following QTL: cqSDS-001, with resistance originating from PI567374, CHR10, CHR1, and CHR18. The populations which segregated for resistant and susceptible QTL alleles were field tested in multiple environments and evaluated for SDS foliar symptoms. While foliar disease development was variable across environments and populations, a significant effect of each QTL on disease was detected within at least one environment. This includes the detection of cqSDS-001 in three genetic backgrounds. The QTL allele from the resistant parents was associated with greater resistance than the susceptible alleles for all QTL and backgrounds with the exception of the allele for CHR18, where the opposite occurred. This study highlights the importance and difficulties of evaluating QTL and the need for multi-year SDS field testing. The information presented in this study can aid breeders in making decisions to improve resistance to SDS.

QTL mapping and epistatic interaction analysis of field resistance to sudden death syndrome (Fusarium virguliforme) in soybean.

KEY MESSAGE: Two interactive quantitative trait loci (QTLs) controlled the field resistance to sudden death syndrome (SDS) in soybean. The interaction between them was confirmed. Sudden death syndrome (SDS), caused by Fusarium virguliforme, is a major disease of soybean [Glycine max (L.) Merr.] in the United States. Breeding for soybean resistance to SDS is the most cost-effective method to manage the disease. The objective of this study was to identify and characterize quantitative trait loci (QTLs) underlying field resistance to SDS in a recombinant inbred line population from the cross GD2422 × LD01-5907. This population was genotyped with 1786 polymorphic single nucleotide polymorphisms (SNPs) using SoySNP6 K iSelect BeadChip and evaluated for SDS resistance in a naturally infested field. Four SDS resistance QTLs were mapped on Chromosomes 4, 8, 12 and 18. The resistant parent, LD01-5907, contributed the resistance alleles for the QTLs on Chromosomes 8 and 18 (qSDS-8 and qSDS-18), while the other parent, GD2422, provided the resistance alleles for the QTLs on Chromosomes 4 and 12 (qSDS-4 and qSDS-12). The minor QTL on Chromosome 12 (qSDS-12) is novel. The QTL on Chromosomes 8 and 18 (qSDS-8 and qSDS-18) overlapped with two soybean cyst nematode resistance-related loci, Rhg4 and Rhg1, respectively. A significant interaction between qSDS-8 and qSDS-18 was detected by disease incidence. Individual effects together with the interaction effect explained around 70% of the phenotypic variance. The epistatic interaction of qSDS-8 and qSDS-18 was confirmed by the field performance across multiple years. Furthermore, the resistance alleles at qSDS-8 and qSDS-18 were demonstrated to be recessive. The SNP markers linked to these QTLs will be useful for marker-assisted breeding to enhance the SDS resistance.

A comparison of genotyping-by-sequencing analysis methods on low-coverage crop datasets shows advantages of a new workflow, GB-eaSy.

BACKGROUND: Genotyping-by-sequencing (GBS), a method to identify genetic variants and quickly genotype samples, reduces genome complexity by using restriction enzymes to divide the genome into fragments whose ends are sequenced on short-read sequencing platforms. While cost-effective, this method produces extensive missing data and requires complex bioinformatics analysis. GBS is most commonly used on crop plant genomes, and because crop plants have highly variable ploidy and repeat content, the performance of GBS analysis software can vary by target organism. Here we focus our analysis on soybean, a polyploid crop with a highly duplicated genome, relatively little public GBS data and few dedicated tools. RESULTS: We compared the performance of five GBS pipelines using low-coverage Illumina sequence data from three soybean populations. To address issues identified with existing methods, we developed GB-eaSy, a GBS bioinformatics workflow that incorporates widely used genomics tools, parallelization and automation to increase the accuracy and accessibility of GBS data analysis. Compared to other GBS pipelines, GB-eaSy rapidly and accurately identified the greatest number of SNPs, with SNP calls closely concordant with whole-genome sequencing of selected lines. Across all five GBS analysis platforms, SNP calls showed unexpectedly low convergence but generally high accuracy, indicating that the workflows arrived at largely complementary sets of valid SNP calls on the low-coverage data analyzed. CONCLUSIONS: We show that GB-eaSy is approximately as good as, or better than, other leading software solutions in the accuracy, yield and missing data fraction of variant calling, as tested on low-coverage genomic data from soybean. It also performs well relative to other solutions in terms of the run time and disk space required. In addition, GB-eaSy is built from existing open-source, modular software packages that are regularly updated and commonly used, making it straightforward to install and maintain. While GB-eaSy outperformed other individual methods on the datasets analyzed, our findings suggest that a comprehensive approach integrating the results from multiple GBS bioinformatics pipelines may be the optimal strategy to obtain the largest, most highly accurate SNP yield possible from low-coverage polyploid sequence data.

An efficient method for measuring copy number variation applied to improvement of nematode resistance in soybean.

Copy number variation (CNV) is implicated in important traits in multiple crop plants, but can be challenging to genotype using conventional methods. The Rhg1 locus of soybean, which confers resistance to soybean cyst nematode (SCN), is a CNV of multiple 31.2-kb genomic units each containing four genes. Reliable, high-throughput methods to quantify Rhg1 and other CNVs for selective breeding were developed. The CNV genotyping assay described here uses a homeologous gene copy within the paleopolyploid soybean genome to provide the internal control for a single-tube TaqMan copy number assay. Using this assay, CNV in breeding populations can be tracked with high precision. We also show that extensive CNV exists within Fayette, a released, inbred SCN-resistant soybean cultivar with a high copy number at Rhg1 derived from a single donor parent. Copy number at Rhg1 is therefore unstable within a released variety over a relatively small number of generations. Using this assay to select for individuals with altered copy number, plants were obtained with both increased copy number and increased SCN resistance relative to control plants. Thus, CNV genotyping technologies can be used as a new type of marker-assisted selection to select for desirable traits in breeding populations, and to control for undesirable variation within cultivars.

Impact of seed protein alleles from three soybean sources on seed composition and agronomic traits.

KEY MESSAGE: Evaluation of seed protein alleles in soybean populations showed that an increase in protein concentration is generally associated with a decrease in oil concentration and yield. Soybean [Glycine max (L.) Merrill] meal is one of the most important plant-based protein sources in the world. Developing cultivars high in seed protein concentration and seed yield is a difficult task because the traits have an inverse relationship. Over two decades ago, a protein quantitative trait loci (QTL) was mapped on chromosome (chr) 20, and this QTL has been mapped to the same position in several studies and given the confirmed QTL designation cqSeed protein-003. In addition, the wp allele on chr 2, which confers pink flower color, has also been associated with increased protein concentration. The objective of our study was to evaluate the effect of cqSeed protein-003 and the wp locus on seed composition and agronomic traits in elite soybean backgrounds adapted to the Midwestern USA. Segregating populations of isogenic lines were developed to test the wp allele and the chr 20 high protein QTL alleles from Danbaekkong (PI619083) and Glycine soja PI468916 at cqSeed protein-003. An increase in protein concentration and decrease in yield were generally coupled with the high protein alleles at cqSeed protein-003 across populations, whereas the effects of wp on protein concentration and yield were variable. These results not only demonstrate the difficulty in developing cultivars with increased protein and yield but also provide information for breeding programs seeking to improve seed composition and agronomic traits simultaneously.

Has photosynthetic capacity increased with 80 years of soybean breeding? An examination of historical soybean cultivars.

Crop biomass production is a function of the efficiencies with which sunlight can be intercepted by the canopy and then converted into biomass. Conversion efficiency has been identified as a target for improvement to enhance crop biomass and yield. Greater conversion efficiency in modern soybean [Glycine max (L.) Merr.] cultivars was documented in recent field trials, and this study explored the physiological basis for this observation. In replicated field trials conducted over three successive years, diurnal leaf gas exchange and photosynthetic CO2 response curves were measured in 24 soybean cultivars with year of release dates (YOR) from 1923 to 2007. Maximum photosynthetic capacity, mesophyll conductance and nighttime respiration have not changed consistently with cultivar release date. However, daily carbon gain was periodically greater in more recently released cultivars compared with older cultivars. Our analysis suggests that this difference in daily carbon gain primarily occurred when stomatal conductance and soil water content were high. There was also evidence for greater chlorophyll content and greater sink capacity late in the growing season in more recently released soybean varieties. Better understanding of the mechanisms that have improved conversion efficiency in the past may help identify new, promising targets for the future.

Impact of Rhg1 copy number, type, and interaction with Rhg4 on resistance to Heterodera glycines in soybean.

KEY MESSAGE: Evaluations of soybean populations showed that both Rhg1 copy number and type were important in determining soybean cyst nematode resistance with higher copy number within Rhg1 type conferring greater resistance. Rhg1 and Rhg4 are important loci conferring resistance to soybean cyst nematode (SCN; Heterodera glycines). Alleles at Rhg1 have been shown to vary for copy number and type and the importance of this variation in conferring resistance is not well defined. The repeat number ranges from one to 10 and there are three variant repeat sequence types [plant introduction (PI) 88788-'Fayette' type (F), 'Peking' type (P) and Williams 82 type (W)] across diverse soybean germplasm. We developed populations segregating for Rhg1 copy number and type and Rhg4 allele type to investigate the effect of these factors and their interaction on SCN resistance. F2 plants from each cross were evaluated for the segregation of Rhg1 and Rhg4 alleles and for SCN reproduction after infesting plants with HG type 2.5.7 and HG type 7 populations. Within repeat types, an increase in repeat number was associated with greater resistance. The P type Rhg1 showed an advantage over F + W type for SCN population HG type 2.5.7 but this was not observed for SCN HG type 7. While plants with P type Rhg1 required Rhg4 to achieve full resistance, Rhg4 did not increase resistance in the background of F + W type Rhg1 repeat. This study demonstrates the importance of both Rhg1 copy number and type in determining resistance and can assist soybean breeders in determining what alleles would best fit their breeding goals.

Evolution and selection of Rhg1, a copy-number variant nematode-resistance locus.

The soybean cyst nematode (SCN) resistance locus Rhg1 is a tandem repeat of a 31.2 kb unit of the soybean genome. Each 31.2-kb unit contains four genes. One allele of Rhg1, Rhg1-b, is responsible for protecting most US soybean production from SCN. Whole-genome sequencing was performed, and PCR assays were developed to investigate allelic variation in sequence and copy number of the Rhg1 locus across a population of soybean germplasm accessions. Four distinct sequences of the 31.2-kb repeat unit were identified, and some Rhg1 alleles carry up to three different types of repeat unit. The total number of copies of the repeat varies from 1 to 10 per haploid genome. Both copy number and sequence of the repeat correlate with the resistance phenotype, and the Rhg1 locus shows strong signatures of selection. Significant linkage disequilibrium in the genome outside the boundaries of the repeat allowed the Rhg1 genotype to be inferred using high-density single nucleotide polymorphism genotyping of 15 996 accessions. Over 860 germplasm accessions were found likely to possess Rhg1 alleles. The regions surrounding the repeat show indications of non-neutral evolution and high genetic variability in populations from different geographic locations, but without evidence of fixation of the resistant genotype. A compelling explanation of these results is that balancing selection is in operation at Rhg1.

Fine mapping of the Asian soybean rust resistance gene Rpp2 from soybean PI 230970.

KEY MESSAGE: Asian soybean rust (ASR) resistance gene Rpp2 has been fine mapped into a 188.1 kb interval on Glyma.Wm82.a2, which contains a series of plant resistance ( R ) genes. Asian soybean rust (ASR), caused by the fungus Phakopsora pachyrihizi Syd. & P. Syd., is a serious disease in major soybean [Glycine max (L.) Merr.] production countries worldwide and causes yield losses up to 75 %. Defining the exact chromosomal position of ASR resistance genes is critical for improving the effectiveness of marker-assisted selection (MAS) for resistance and for cloning these genes. The objective of this study was to fine map the ASR resistance gene Rpp2 from the plant introduction (PI) 230970. Rpp2 was previously mapped within a 12.9-cM interval on soybean chromosome 16. The fine mapping was initiated by identifying recombination events in F2 and F3 plants using simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers that flank the gene. Seventeen recombinant plants were identified and then tested with additional genetic markers saturating the gene region to localize the positions of each recombination. The progeny of these selected plants were tested for resistance to ASR and with SSR markers resulting in the mapping of Rpp2 to a 188.1 kb interval on the Williams 82 reference genome (Glyma.Wm82.a2). Twelve genes including ten toll/interleukin-1 receptor (TIR)-nucleotide-binding site (NBS)-leucine-rich repeat (LRR) genes were predicted to exist in this interval on the Glyma.Wm82.a2.v1 gene model map. Eight of these ten genes were homologous to the Arabidopsis TIR-NBS-LRR gene AT5G17680.1. The identified SSR and SNP markers close to Rpp2 and the candidate gene information presented in this study will be significant resources for MAS and gene cloning research.

Historical gains in soybean (Glycine max Merr.) seed yield are driven by linear increases in light interception, energy conversion, and partitioning efficiencies.

Soybean (Glycine max Merr.) is the world's most widely grown leguminous crop and an important source of protein and oil for food and feed. Soybean yields have increased substantially throughout the past century, with yield gains widely attributed to genetic advances and improved cultivars as well as advances in farming technology and practice. Yet, the physiological mechanisms underlying the historical improvements in soybean yield have not been studied rigorously. In this 2-year experiment, 24 soybean cultivars released between 1923 and 2007 were grown in field trials. Physiological improvements in the efficiencies by which soybean canopies intercepted light (εi), converted light energy into biomass (εc), and partitioned biomass into seed (εp) were examined. Seed yield increased by 26.5kg ha(-1) year(-1), and the increase in seed yield was driven by improvements in all three efficiencies. Although the time to canopy closure did not change in historical soybean cultivars, extended growing seasons and decreased lodging in more modern lines drove improvements in εi. Greater biomass production per unit of absorbed light resulted in improvements in εc. Over 84 years of breeding, soybean seed biomass increased at a rate greater than total aboveground biomass, resulting in an increase in εp. A better understanding of the physiological basis for yield gains will help to identify targets for soybean improvement in the future.

Identification and molecular mapping of two soybean aphid resistance genes in soybean PI 587732.

Soybean [Glycine max (L.) Merr.] continues to be plagued by the soybean aphid (Aphis glycines Matsumura: SA) in North America. New soybean resistance sources are needed to combat the four identified SA biotypes. The objectives of this study were to determine the inheritance of SA resistance in PI 587732 and to map resistance gene(s). For this study, 323 F2 and 214 F3 plants developed from crossing PI 587732 to two susceptible genotypes were challenged with three SA biotypes and evaluated with genetic markers. Choice tests showed that resistance to SA Biotype 1 in the first F2 population was controlled by a gene in the Rag1 region on chromosome 7, while resistance to SA Biotype 2 in the second population was controlled by a gene in the Rag2 region on chromosome 13. When 134 F3 plants segregating in both the Rag1 and Rag2 regions were tested with a 1:1 mixture of SA Biotypes 1 and 2, the Rag2 region and an interaction between the Rag1 and Rag2 regions were significantly associated with the resistance. Based on the results of the non-choice tests, the resistance gene in the Rag1 region in PI 587732 may be a different allele or gene from Rag1 from Dowling because the PI 587732 gene showed antibiosis type resistance to SA Biotype 2 while Rag1 from Dowling did not. The two SA resistance loci and genetic marker information from this study will be useful in increasing diversity of SA resistance sources and marker-assisted selection for soybean breeding programs.

Inheritance of soybean aphid resistance in 21 soybean plant introductions.

KEY MESSAGE: The Rag2 region was frequently identified among 21 F 2 populations evaluated for soybean aphid resistance, and dominant gene action and single-gene resistance were also commonly identified. The soybean aphid [Aphis glycines Matsumura (Hemiptera: Aphididae)] is one of the most important insect pests of soybean [Glycine max (L.) Merr] in the northern USA and southern Canada, and four resistance loci (Rag1-rag4) have been discovered since the pest was identified in the USA in 2000. The objective of this research was to determine whether resistance expression in recently identified soybean aphid-resistant plant introductions (PIs) was associated with the four Rag loci using a collection of 21 F2 populations. The F2 populations were phenotyped with soybean aphid biotype 1, which is avirulent on plants having any of the currently identified Rag genes, using choice tests in the greenhouse and were tested with genetic markers linked to the four Rag loci. The phenotyping results indicate that soybean aphid resistance is controlled by a single dominant gene in 14 PIs, by two genes in three PIs, and four PIs had no clear Mendelian inheritance patterns. Genetic markers flanking Rag2 were significantly associated with aphid resistance in 20 PIs, the Rag1 region was significantly identified in five PIs, and the Rag3 region was identified in one PI. These results show that single dominant gene action at the Rag2 region may be a major source for aphid resistance in the USDA soybean germplasm collection.

Genetic architecture of protein and oil content in soybean seed and meal.

Soybean is grown primarily for the protein and oil extracted from its seed and its value is influenced by these components. The objective of this study was to map marker-trait associations (MTAs) for the concentration of seed protein, oil, and meal protein using the soybean nested association mapping (SoyNAM) population. The composition traits were evaluated on seed harvested from over 5000 inbred lines of the SoyNAM population grown in 10 field locations across 3 years. Estimated heritabilities were at least 0.85 for all three traits. The genotyping of lines with single nucleotide polymorphism markers resulted in the identification of 107 MTAs for the three traits. When MTAs for the three traits that mapped within 5 cM intervals were binned together, the MTAs were mapped to 64 intervals on 19 of the 20 soybean chromosomes. The majority of the MTA effects were small and of the 107 MTAs, 37 were for protein content, 39 for meal protein, and 31 for oil content. For cases where a protein and oil MTAs mapped to the same interval, most (94%) significant effects were opposite for the two traits, consistent with the negative correlation between these traits. A coexpression analysis identified candidate genes linked to MTAs and 18 candidate genes were identified. The large number of small effect MTAs for the composition traits suggest that genomic prediction would be more effective in improving these traits than marker-assisted selection.

Molecular mapping of soybean rust resistance in soybean accession PI 561356 and SNP haplotype analysis of the Rpp1 region in diverse germplasm.

Soybean rust (SBR), caused by Phakopsora pachyrhizi Sydow, is one of the most economically important and destructive diseases of soybean [Glycine max (L.) Merr.] and the discovery of novel SBR resistance genes is needed because of virulence diversity in the pathogen. The objectives of this research were to map SBR resistance in plant introduction (PI) 561356 and to identify single nucleotide polymorphism (SNP) haplotypes within the region on soybean chromosome 18 where the SBR resistance gene Rpp1 maps. One-hundred F(2:3) lines derived from a cross between PI 561356 and the susceptible experimental line LD02-4485 were genotyped with genetic markers and phenotyped for resistance to P. pachyrhizi isolate ZM01-1. The segregation ratio of reddish brown versus tan lesion type in the population supported that resistance was controlled by a single dominant gene. The gene was mapped to a 1-cM region on soybean chromosome 18 corresponding to the same interval as Rpp1. A haplotype analysis of diverse germplasm across a 213-kb interval that included Rpp1 revealed 21 distinct haplotypes of which 4 were present among 5 SBR resistance sources that have a resistance gene in the Rpp1 region. Four major North American soybean ancestors belong to the same SNP haplotype as PI 561356 and seven belong to the same haplotype as PI 594538A, the Rpp1-b source. There were no North American soybean ancestors belonging to the SNP haplotypes found in PI 200492, the source of Rpp1, or PI 587886 and PI 587880A, additional sources with SBR resistance mapping to the Rpp1 region.

Detection of rare nematode resistance Rhg1 haplotypes in Glycine soja and a novel Rhg1 α-SNAP.

This study pursued the hypothesis that wild plant germplasm accessions carrying alleles of interest can be identified using available single nucleotide polymorphism (SNP) genotypes for particular alleles of other (unlinked) genes that contribute to the trait of interest. The soybean cyst nematode (SCN, Heterodera glycines [HG]) resistance locus Rhg1 is widely used in farmed soybean [Glycine max (L.) Merr.]. The two known resistance-conferring haplotypes, rhg1-a and rhg1-b, typically contain three or seven to 10 tandemly duplicated Rhg1 segments, respectively. Each Rhg1 repeat carries four genes, including Glyma.18G022500, which encodes unusual isoforms of the vesicle-trafficking chaperone α-SNAP. Using SoySNP50K data for NSFRAN07 allele presence, we discovered a new Rhg1 haplotype, rhg1-ds, in six accessions of wild soybean, Glycine soja Siebold & Zucc. (0.5% of the ∼1,100 G. soja accessions in the USDA collection). The α-SNAP encoded by rhg1-ds is unique at an important site of amino acid variation and shares with the rhg1-a and rhg1-b α-SNAP proteins the traits of cytotoxicity and altered N-ethylmaleimide sensitive factor (NSF) protein interaction. Copy number assays indicate three repeats of rhg1-ds. G. soja PI 507613 and PI 507623 exhibit resistance to HG type 2.5.7 SCN populations, in part because of contributions from other loci. In a segregating F2 population, rhg1-b and rhg1-ds made statistically indistinguishable contributions to resistance to a partially virulent HG type 2.5.7 SCN population. Hence, the unusual multigene copy number variation Rhg1 haplotype was present but rare in ancestral G. soja and was present in accessions that offer multiple traits for SCN resistance breeding. The accessions were initially identified for study based on an unlinked SNP.

High-throughput characterization, correlation, and mapping of leaf photosynthetic and functional traits in the soybean (Glycine max) nested association mapping population.

Photosynthesis is a key target to improve crop production in many species including soybean [Glycine max (L.) Merr.]. A challenge is that phenotyping photosynthetic traits by traditional approaches is slow and destructive. There is proof-of-concept for leaf hyperspectral reflectance as a rapid method to model photosynthetic traits. However, the crucial step of demonstrating that hyperspectral approaches can be used to advance understanding of the genetic architecture of photosynthetic traits is untested. To address this challenge, we used full-range (500-2,400 nm) leaf reflectance spectroscopy to build partial least squares regression models to estimate leaf traits, including the rate-limiting processes of photosynthesis, maximum Rubisco carboxylation rate, and maximum electron transport. In total, 11 models were produced from a diverse population of soybean sampled over multiple field seasons to estimate photosynthetic parameters, chlorophyll content, leaf carbon and leaf nitrogen percentage, and specific leaf area (with R2 from 0.56 to 0.96 and root mean square error approximately <10% of the range of calibration data). We explore the utility of these models by applying them to the soybean nested association mapping population, which showed variability in photosynthetic and leaf traits. Genetic mapping provided insights into the underlying genetic architecture of photosynthetic traits and potential improvement in soybean. Notably, the maximum Rubisco carboxylation rate mapped to a region of chromosome 19 containing genes encoding multiple small subunits of Rubisco. We also mapped the maximum electron transport rate to a region of chromosome 10 containing a fructose 1,6-bisphosphatase gene, encoding an important enzyme in the regeneration of ribulose 1,5-bisphosphate and the sucrose biosynthetic pathway. The estimated rate-limiting steps of photosynthesis were low or negatively correlated with yield suggesting that these traits are not influenced by the same genetic mechanisms and are not limiting yield in the soybean NAM population. Leaf carbon percentage, leaf nitrogen percentage, and specific leaf area showed strong correlations with yield and may be of interest in breeding programs as a proxy for yield. This work is among the first to use hyperspectral reflectance to model and map the genetic architecture of the rate-limiting steps of photosynthesis.