Development of SNP Genotyping Assays for Seed Composition Traits in Soybean

QTL mapping and multi-omics identify candidate genes for protein and oil in soybean

KEY MESSAGE

QTL mapping, BSA-seq, and RNA-seq revealed key QTL/genes of protein and oil, some of which were aligned with previous QTLs. EMS-mutations and SoyGVD were applied to validate function of candidate genes. Protein and oil are the two principal economic components of soybean seed. Although several related genes regulating soybean protein and oil accumulation have been reported, the regulatory mechanisms remain largely unknown. In this study, quantitative trait loci (QTL) mapping was employed using four generations derived from a cross between Changjiangchun 2 (high protein and oil content) and Yushuxian 2 (low protein and oil content), resulting in the detection of 37 QTLs, including 16 QTLs for protein content and 21 QTLs for oil content. BSA-seq was performed on two parents and two offspring extreme pools from F2 population individuals. Two QTLs, qOIL1.2 and qPRO14.1, were found to overlap with the BSA-seq mapping interval, in which eight genes exhibited single nucleotide polymorphisms (SNPs) or insertion/deletion (InDel) variations within their coding sequences (CDS). RNA-seq was performed on seeds collected at 20, 30, and 40 days after-pollination (DAP) from two extreme pools of F2:3 population individuals. A total of 199 deferentially expressed genes (DEGs) were obtained within the QTLs regions. In conjunction with previous research, 10 protein and four oil QTLs intervals were aligned with previously identified QTLs. Notably, based on EMS-induced mutation lines and SoyGVD database, 12 potential candidate genes were screened out and preliminary validated the function for oil and protein in soybeans. These findings lay the groundwork for further research into candidate genes and marker-assisted selection (MAS) in soybean breeding to enhance seed protein and oil content.

Genomic analysis and characterization of new loci associated with seed protein and oil content in soybeans

Breeding for increased protein without a reduction in oil content in soybeans [Glycine max (L.) Merr.] is a challenge for soybean breeders but an expected goal. Many efforts have been made to develop new soybean varieties with high yield in combination with desirable protein and/or oil traits. An elite line, R05-1415, was reported to be high yielding, high protein, and low oil. Several significant quantitative trait loci (QTL) for protein and oil were reported in this line, but many of them were unstable across environments or genetic backgrounds. Thus, a new study under multiple field environments using the Infinium BARCSoySNP6K BeadChips was conducted to detect and confirm stable genomic loci for these traits. Genetic analyses consistently detected a single major genomic locus conveying these two traits with remarkably high phenotypic variation explained (R2 ), varying between 24.2% and 43.5%. This new genomic locus is located between 25.0 and 26.7 Mb, distant from the previously reported QTL and did not overlap with other commonly reported QTL and the recently cloned gene Glyma.20G085100. Homolog analysis indicated that this QTL did not result from the paracentric chromosome inversion with an adjacent genomic fragment that harbors the reported QTL. The pleiotropic effect of this QTL could be a challenge for improving protein and oil simultaneously; however, a further study of four candidate genes with significant expressions in the seed developmental stages coupled with haplotype analysis may be able to pinpoint causative genes. The functionality and roles of these genes can be determined and characterized, which lay a solid foundation for the improvement of protein and oil content in soybeans.

A chromosome 16 deletion conferring a high sucrose phenotype in soybean

Sucrose in soybean seeds is desirable for many end-uses. Increased sucrose contents were discovered to associate with a chromosome 16 deletion resulting from fast neutron irradiation. Soybean is one of the most economically important crops in the United States. A primary end-use of soybean is for livestock feed. Therefore, genetic improvement of seed composition is one of the most important goals in soybean breeding programs. Sucrose is desired in animal feed due to its role as an easily digestible energy source. An elite soybean line was irradiated with fast neutrons and the seed from plants were screened for altered seed composition with near-infrared spectroscopy (NIR). One mutant line, G15FN-54, was found to have higher sucrose content (8-9%) than the parental line (5-6%). Comparative genomic hybridization (CGH) revealed three large deletions on chromosomes (Chrs) 10, 13, and 16 in the mutant, which were confirmed through whole genome sequencing (WGS). A bi-parental population derived from the mutant G15FN-54 and the cultivar Benning was developed to conduct a bulked segregant analysis (BSA) with SoySNP50K BeadChips, revealing that the deletion on Chr 16 might be responsible for the altered phenotype. The mapping result using the bi-parental population confirmed that the deletion on Chr 16 conferred elevated sucrose content and a total of 21 genes are located within this Chr 16 deletion. NIR and high-pressure liquid chromatography (HPLC) were used to confirm the stability of the phenotype across generations in the bi-parental population. The mutation will be useful to understand the genetic control of soybean seed sucrose content.

Genetic mapping and functional genomics of soybean seed protein

Soybean is an utterly important crop for high-quality meal protein and vegetative oil. Soybean seed protein content has become a key factor in nutrients for livestock feed as well as human dietary consumption. Genetic improvement of soybean seed protein is highly desired to meet the demands of rapidly growing world population. Molecular mapping and genomic analysis in soybean have identified many quantitative trait loci (QTL) underlying seed protein content control. Exploring the mechanisms of seed storage protein regulation will be helpful to achieve the improvement of protein content. However, the practice of breeding higher protein soybean is challenging because soybean seed protein is negatively correlated with seed oil content and yield. To overcome the limitation of such inverse relationship, deeper insights into the property and genetic control of seed protein are required. Recent advances of soybean genomics have strongly enhanced the understandings for molecular mechanisms of soybean with better seed quality. Here, we review the research progress in the genetic characteristics of soybean storage protein, and up-to-date advances of molecular mappings and genomics of soybean protein. The key factors underlying the mechanisms of the negative correlation between protein and oil in soybean seeds are elaborated. We also briefly discuss the future prospects of breaking the bottleneck of the negative correlation to develop high protein soybean without penalty of oil and yield.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01373-5.

Incorporation of Soil-Derived Covariates in Progeny Testing and Line Selection to Enhance Genomic Prediction Accuracy in Soybean Breeding

The availability of high-dimensional molecular markers has allowed plant breeding programs to maximize their efficiency through the genomic prediction of a phenotype of interest. Yield is a complex quantitative trait whose expression is sensitive to environmental stimuli. In this research, we investigated the potential of incorporating soil texture information and its interaction with molecular markers via covariance structures for enhancing predictive ability across breeding scenarios. A total of 797 soybean lines derived from 367 unique bi-parental populations were genotyped using the Illumina BARCSoySNP6K and tested for yield during 5 years in Tiptonville silt loam, Sharkey clay, and Malden fine sand environments. Four statistical models were considered, including the GBLUP model (M1), the reaction norm model (M2) including the interaction between molecular markers and the environment (G×E), an extended version of M2 that also includes soil type (S), and the interaction between soil type and molecular markers (G×S) (M3), and a parsimonious version of M3 which discards the G×E term (M4). Four cross-validation scenarios simulating progeny testing and line selection of tested–untested genotypes (TG, UG) in observed–unobserved environments [OE, UE] were implemented (CV2 [TG, OE], CV1 [UG, OE], CV0 [TG, UE], and CV00 [UG, UE]). Across environments, the addition of G×S interaction in M3 decreased the amount of variability captured by the environment (−30.4%) and residual (−39.2%) terms as compared to M1. Within environments, the G×S term in M3 reduced the variability captured by the residual term by 60 and 30% when compared to M1 and M2, respectively. M3 outperformed all the other models in CV2 (0.577), CV1 (0.480), and CV0 (0.488). In addition to the Pearson correlation, other measures were considered to assess predictive ability and these showed that the addition of soil texture seems to structure/dissect the environmental term revealing its components that could enhance or hinder the predictability of a model, especially in the most complex prediction scenario (CV00). Hence, the availability of soil texture information before the growing season could be used to optimize the efficiency of a breeding program by allowing the reconsideration of field experimental design, allocation of resources, reduction of preliminary trials, and shortening of the breeding cycle.

Mapping QTL for Adult-Plant Resistance to Stripe Rust in a Chinese Wheat Landrace

Wheat stripe (yellow) rust is a worldwide disease that seriously reduces wheat grain yield and quality. Adult-plant resistance (APR) to stripe rust is generally more durable but usually controlled by multiple genes with partial resistance. In this study, a recombinant inbred line population was developed from a cross between a Chinese wheat landrace, Tutoumai, with APR to stripe rust, and a highly susceptible wheat cultivar, Siyang 936. The population was genotyped by genotyping-by-sequencing and phenotyped for APR to stripe rust in four consecutive field experiments. Three QTLs, QYr.sdau-1BL, QYr.sdau-5BL, and QYr.sdau-6BL, were identified for APR to stripe rust, and explained 8.0–21.2%, 10.1–22.7%, and 11.6–18.0% of the phenotypic variation, respectively. QYr.sdau-1BL was further mapped to a 21.6 Mb region using KASP markers derived from SNPs identified by RNA-seq of the two parents. In the QYr.sdau-1BL region, 13 disease-resistance-related genes were differently expressed between the two parents, and therefore were considered as the putative candidates of QYr.sdau-1BL. This study provides favorable gene/QTL and high-throughput markers to breeding programs for marker-assisted selection of the wheat stripe rust APR genes.

Introgression of Maize Lethal Necrosis Resistance Quantitative Trait Loci Into Susceptible Maize Populations and Validation of the Resistance Under Field Conditions in Naivasha, Kenya

Maize lethal necrosis (MLN), resulting from co-infection by maize chlorotic mottle virus (MCMV) and sugarcane mosaic virus (SCMV) can cause up to 100% yield losses in maize in Africa under serious disease conditions. Maize improvement through conventional backcross (BC) takes many generations but can significantly be shortened when molecular tools are utilized in the breeding process. We used a donor parent (KS23-6) to transfer quantitative trait loci (QTL) for resistance to MLN into nine adapted but MLN susceptible lines. Nurseries were established in Kiboko, Kenya during 2015-2017 seasons and BC₃F₂ progeny were developed using marker assisted backcrossing (MABC) approach. Six single nucleotide polymorphism (SNP) markers linked to QTL for resistance to MLN were used to genotype 2,400 BC₃F₂ lines using Kompetitive Allele Specific PCR (KASP) platform. We detected that two of the six QTL had major effects for resistance to MLN under artificial inoculation field conditions in 56 candidate BC₃F₂ lines. To confirm whether these two QTL are reproducible under different field conditions, the 56 BC₃F₂ lines including their parents were evaluated in replicated trials for two seasons under artificial MLN inoculations in Naivasha, Kenya in 2018. Strong association of genotype with phenotype was detected. Consequently, 19 superior BC₃F₂ lines with favorable alleles and showing improved levels of resistance to MLN under artificial field inoculation were identified. These elite lines represent superior genetic resources for improvement of maize hybrids for resistance to MLN. However, 20 BC₃F₂ lines were fixed for both KASP markers but were susceptible to MLN under field conditions, which could suggest weak linkage between the KASP markers and target genes. The validated two major QTL can be utilized to speed up the breeding process but additional loci need to be identified between the KASP markers and the resistance genes to strengthen the linkage.

Development of Breeder-Friendly KASP Markers for Low Concentration of Kunitz Trypsin Inhibitor in Soybean Seeds

Trypsin inhibitors (TI), a common anti-nutritional factor in soybean, prevent animals' protein digestibility reducing animal growth performance. No commercial soybean cultivars with low or null concentration of TI are available. The availability of a high throughput genotyping assay will be beneficial to incorporate the low TI trait into elite breeding lines. The aim of this study is to develop and validate a breeder friendly Kompetitive Allele Specific PCR (KASP) assay linked to low Kunitz trypsin inhibitor (KTI) in soybean seeds. A total of 200 F3:5 lines derived from PI 547656 (low KTI) X Glenn (normal KTI) were genotyped using the BARCSoySNP6K_v2 Beadchip. F3:4 and F3:5 lines were grown in Blacksburg and Orange, Virginia in three years, respectively, and were measured for KTI content using a quantitative HPLC method. We identified three SNP markers tightly linked to the major QTL associated to low KTI in the mapping population. Based on these SNPs, we developed and validated the KASP assays in a set of 93 diverse germplasm accessions. The marker Gm08_44814503 has 86% selection efficiency for the accessions with low KTI and could be used in marker assisted breeding to facilitate the incorporation of low KTI content in soybean seeds.

An extended KASP-SNP resource for molecular breeding in Chinese cabbage(Brassica rapa L. ssp. pekinensis)

Kompetitive allele-specific PCR (KASP) is a cost-effective single-step SNP genotyping technology, With an objective to enhance the marker repertoire and develop high efficient KASP-SNP markers in Chinese cabbage, we re-sequenced four Chinese cabbage doubled haploid (DH) lines, Y177-47, Y635-10, Y510-1 and Y510-9, and generated a total of more than 38.5 billion clean base pairs. A total of 827,720 SNP loci were identified with an estimated density of 3,217 SNPs/Mb. Further, a total of 387,354 SNPs with at least 30 bp to the next most adjacent SNPs on either side were selected as resource for KASP markers. From this resource, 258 (96.27%) of 268 SNP loci were successfully transformed into KASP-SNP markers using a Roche LightCycler 480-II instrument. Among these markers, 221 (85.66%) were co-dominant markers, 220 (85.27%) were non-synonymous SNPs, and 257 (99.6%) were newly developed markers. In addition, 53 markers were applied for genotyping of 34 Brassica rapa accessions. Cluster analysis separated these 34 accessions into three clusters based on heading types. The millions of SNP loci, a large set of resource for KASP markers, as well as the newly developed KASP markers in this study may facilitate further genetic and molecular breeding studies in Brassica rapa.

High-density genetic map using whole-genome resequencing for fine mapping and candidate gene discovery for disease resistance in peanut

Whole-genome resequencing (WGRS) of mapping populations has facilitated development of high-density genetic maps essential for fine mapping and candidate gene discovery for traits of interest in crop species. Leaf spots, including early leaf spot (ELS) and late leaf spot (LLS), and Tomato spotted wilt virus (TSWV) are devastating diseases in peanut causing significant yield loss. We generated WGRS data on a recombinant inbred line population, developed a SNP-based high-density genetic map, and conducted fine mapping, candidate gene discovery and marker validation for ELS, LLS and TSWV. The first sequence-based high-density map was constructed with 8869 SNPs assigned to 20 linkage groups, representing 20 chromosomes, for the 'T' population (Tifrunner × GT-C20) with a map length of 3120 cM and an average distance of 1.45 cM. The quantitative trait locus (QTL) analysis using high-density genetic map and multiple season phenotyping data identified 35 main-effect QTLs with phenotypic variation explained (PVE) from 6.32% to 47.63%. Among major-effect QTLs mapped, there were two QTLs for ELS on B05 with 47.42% PVE and B03 with 47.38% PVE, two QTLs for LLS on A05 with 47.63% and B03 with 34.03% PVE and one QTL for TSWV on B09 with 40.71% PVE. The epistasis and environment interaction analyses identified significant environmental effects on these traits. The identified QTL regions had disease resistance genes including R-genes and transcription factors. KASP markers were developed for major QTLs and validated in the population and are ready for further deployment in genomics-assisted breeding in peanut.

Dissecting genomic hotspots underlying seed protein, oil, and sucrose content in an interspecific mapping population of soybean using high-density linkage mapping

The cultivated [Glycine max (L) Merr.] and wild [Glycine soja Siebold & Zucc.] soybean species comprise wide variation in seed composition traits. Compared to wild soybean, cultivated soybean contains low protein, high oil, and high sucrose. In this study, an interspecific population was derived from a cross between G. max (Williams 82) and G. soja (PI 483460B). This recombinant inbred line (RIL) population of 188 lines was sequenced at 0.3× depth. Based on 91 342 single nucleotide polymorphisms (SNPs), recombination events in RILs were defined, and a high-resolution bin map was developed (4070 bins). In addition to bin mapping, quantitative trait loci (QTL) analysis for protein, oil, and sucrose was performed using 3343 polymorphic SNPs (3K-SNP), derived from Illumina Infinium BeadChip sequencing platform. The QTL regions from both platforms were compared, and a significant concordance was observed between bin and 3K-SNP markers. Importantly, the bin map derived from next-generation sequencing technology enhanced mapping resolution (from 1325 to 50 Kb). A total of five, nine, and four QTLs were identified for protein, oil, and sucrose content, respectively, and some of the QTLs coincided with soybean domestication-related genomic loci. The major QTL for protein and oil were mapped on Chr. 20 (qPro_20) and suggested negative correlation between oil and protein. In terms of sucrose content, a novel and major QTL were identified on Chr. 8 (qSuc_08) and harbours putative genes involved in sugar transport. In addition, genome-wide association using 91 342 SNPs confirmed the genomic loci derived from QTL mapping. A QTL-based haplotype using whole-genome resequencing of 106 diverse soybean lines identified unique allelic variation in wild soybean that could be utilized to widen the genetic base in cultivated soybean.

Legume genetic resources and transcriptome dynamics under abiotic stress conditions

Grain legumes are an important source of nutrition and income for billions of consumers and farmers around the world. However, the low productivity of new legume varieties, due to the limited genetic diversity available for legume breeding programmes and poor policymaker support, combined with an increasingly unpredictable global climate is resulting in a large gap between current yields and the increasing demand for legumes as food. Hence, there is a need for novel approaches to develop new high-yielding legume cultivars that are able to cope with a range of environmental stressors. Next-generation technologies are providing the tools that could enable the more rapid and cost-effective genomic and transcriptomic studies for most major crops, allowing the identification of key functional and regulatory genes involved in abiotic stress resistance. In this review, we provide an overview of the recent achievements regarding abiotic stress resistance in a wide range of legume crops and highlight the transcriptomic and miRNA approaches that have been used. In addition, we critically evaluate the availability and importance of legume genetic resources with desirable abiotic stress resistance traits.

Leaf Amino Acid Supply Affects Photosynthetic and Plant Nitrogen Use Efficiency under Nitrogen Stress

The coordinated distribution of nitrogen to source leaves and sinks is essential for supporting leaf metabolism while also supplying sufficient nitrogen to seeds for development. This study aimed to understand how regulated amino acid allocation to leaves affects photosynthesis and overall plant nitrogen use efficiency in Arabidopsis (Arabidopsis thaliana) and how soil nitrogen availability influences these processes. Arabidopsis plants with a knockout of AAP2, encoding an amino acid permease involved in xylem-to-phloem transfer of root-derived amino acids, were grown in low-, moderate-, and high-nitrogen environments. We analyzed nitrogen allocation to shoot tissues, photosynthesis, and photosynthetic and plant nitrogen use efficiency in these knockout plants. Our results demonstrate that, independent of nitrogen conditions, aap2 plants allocate more nitrogen to leaves than wild-type plants. Increased leaf nitrogen supply positively affected chlorophyll and Rubisco levels, photosynthetic nitrogen use efficiency, and carbon assimilation and transport to sinks. The aap2 plants outperformed wild-type plants with respect to growth, seed yield and carbon storage pools, and nitrogen use efficiency in both high and deficient nitrogen environments. Overall, this study demonstrates that increasing nitrogen allocation to leaves represents an effective strategy for improving carbon fixation and photosynthetic nitrogen use efficiency. The results indicate that an optimized coordination of nitrogen and carbon partitioning processes is critical for high oilseed production in Arabidopsis, including in plants exposed to limiting nitrogen conditions.

Molecular elucidation of a new allelic variation at the Sg-5 gene associated with the absence of group A saponins in wild soybean

In soybean, triterpenoid saponin is one of the major secondary metabolites and is further classified into group A and DDMP saponins. Although they have known health benefits for humans and animals, acetylation of group A saponins causes bitterness and gives an astringent taste to soy products. Therefore, several studies are being conducted to eliminate acetylated group A saponins. Previous studies have isolated and characterized the Sg-5 (Glyma.15g243300) gene, which encodes the cytochrome P450 72A69 enzyme and is responsible for soyasapogenol A biosynthesis. In this study, we elucidated the molecular identity of a novel mutant of Glycine soja, 'CWS5095'. Phenotypic analysis using TLC and LC-PDA/MS/MS showed that the mutant 'CWS5095' did not produce any group A saponins. Segregation analysis showed that the absence of group A saponins is controlled by a single recessive allele. The locus was mapped on chromosome 15 (4.3 Mb) between Affx-89193969 and Affx-89134397 where the previously identified Glyma.15g243300 gene is positioned. Sequence analysis of the coding region for the Glyma.15g243300 gene revealed the presence of four SNPs in 'CWS5095' compared to the control lines. One of these four SNPs (G1127A) leads to the amino acid change Arg376Lys in the EXXR motif, which is invariably conserved among the CYP450 superfamily proteins. Co-segregation analysis showed that the missense mutation (Arg376Lys) was tightly linked with the absence of group A saponins in 'CWS5095'. Even though Arg and Lys have similar chemical features, the 3D modelled protein structure indicates that the replacement of Arg with Lys may cause a loss-of-function of the Sg-5 protein by inhibiting the stable binding of a heme cofactor to the CYP72A69 apoenzyme.

Accelerating public sector rice breeding with high-density KASP markers derived from whole genome sequencing of indica rice

Few public sector rice breeders have the capacity to use NGS-derived markers in their breeding programmes despite rapidly expanding repositories of rice genome sequence data. They rely on > 18,000 mapped microsatellites (SSRs) for marker-assisted selection (MAS) using gel analysis. Lack of knowledge about target SNP and InDel variant loci has hampered the uptake by many breeders of Kompetitive allele-specific PCR (KASP), a proprietary technology of LGC genomics that can distinguish alleles at variant loci. KASP is a cost-effective single-step genotyping technology, cheaper than SSRs and more flexible than genotyping by sequencing (GBS) or array-based genotyping when used in selection programmes. Before this study, there were 2015 rice KASP marker loci in the public domain, mainly identified by array-based screening, leaving large proportions of the rice genome with no KASP coverage. Here we have addressed the urgent need for a wide choice of appropriate rice KASP assays and demonstrated that NGS can detect many more KASP to give full genome coverage. Through re-sequencing of nine indica rice breeding lines or released varieties, this study has identified 2.5 million variant sites. Stringent filtering of variants generated 1.3 million potential KASP assay designs, including 92,500 potential functional markers. This strategy delivers a 650-fold increase in potential selectable KASP markers at a density of 3.1 per 1 kb in the indica crosses analysed and 377,178 polymorphic KASP design sites on average per cross. This knowledge is available to breeders and has been utilised to improve the efficiency of public sector breeding in Nepal, enabling identification of polymorphic KASP at any region or quantitative trait loci in relevant crosses. Validation of 39 new KASP was carried out by genotyping progeny from a range of crosses to show that they detected segregating alleles. The new KASP have replaced SSRs to aid trait selection during marker-assisted backcrossing in these crosses, where target traits include rice blast and BLB resistance loci. Furthermore, we provide the software for plant breeders to generate KASP designs from their own datasets.

Molecular mapping and genomics of soybean seed protein: a review and perspective for the future

KEY MESSAGE

Genetic improvement of soybean protein meal is a complex process because of negative correlation with oil, yield, and temperature. This review describes the progress in mapping and genomics, identifies knowledge gaps, and highlights the need of integrated approaches. Meal protein derived from soybean [Glycine max (L) Merr.] seed is the primary source of protein in poultry and livestock feed. Protein is a key factor that determines the nutritional and economical value of soybean. Genetic improvement of soybean seed protein content is highly desirable, and major quantitative trait loci (QTL) for soybean protein have been detected and repeatedly mapped on chromosomes (Chr.) 20 (LG-I), and 15 (LG-E). However, practical breeding progress is challenging because of seed protein content's negative genetic correlation with seed yield, other seed components such as oil and sucrose, and interaction with environmental effects such as temperature during seed development. In this review, we discuss rate-limiting factors related to soybean protein content and nutritional quality, and potential control factors regulating seed storage protein. In addition, we describe advances in next-generation sequencing technologies for precise detection of natural variants and their integration with conventional and high-throughput genotyping technologies. A syntenic analysis of QTL on Chr. 15 and 20 was performed. Finally, we discuss comprehensive approaches for integrating protein and amino acid QTL, genome-wide association studies, whole-genome resequencing, and transcriptome data to accelerate identification of genomic hot spots for allele introgression and soybean meal protein improvement.