Construction of high resolution genetic linkage maps to improve the soybean genome sequence assembly Glyma1.01

Ability of Genomic Prediction to Bi-Parent-Derived Breeding Population Using Public Data for Soybean Oil and Protein Content

Genomic selection (GS) is a marker-based selection method used to improve the genetic gain of quantitative traits in plant breeding. A large number of breeding datasets are available in the soybean database, and the application of these public datasets in GS will improve breeding efficiency and reduce time and cost. However, the most important problem to be solved is how to improve the ability of across-population prediction. The objectives of this study were to perform genomic prediction (GP) and estimate the prediction ability (PA) for seed oil and protein contents in soybean using available public datasets to predict breeding populations in current, ongoing breeding programs. In this study, six public datasets of USDA GRIN soybean germplasm accessions with available phenotypic data of seed oil and protein contents from different experimental populations and their genotypic data of single-nucleotide polymorphisms (SNPs) were used to perform GP and to predict a bi-parent-derived breeding population in our experiment. The average PA was 0.55 and 0.50 for seed oil and protein contents within the bi-parents population according to the within-population prediction; and 0.45 for oil and 0.39 for protein content when the six USDA populations were combined and employed as training sets to predict the bi-parent-derived population. The results showed that four USDA-cultivated populations can be used as a training set individually or combined to predict oil and protein contents in GS when using 800 or more USDA germplasm accessions as a training set. The smaller the genetic distance between training population and testing population, the higher the PA. The PA increased as the population size increased. In across-population prediction, no significant difference was observed in PA for oil and protein content among different models. The PA increased as the SNP number increased until a marker set consisted of 10,000 SNPs. This study provides reasonable suggestions and methods for breeders to utilize public datasets for GS. It will aid breeders in developing GS-assisted breeding strategies to develop elite soybean cultivars with high oil and protein contents.

Genetic mapping reveals the complex genetic architecture controlling slow canopy wilting in soybean

In soybean [Glycine max (L.) Merr.], drought stress is the leading cause of yield loss from abiotic stress in rain-fed US growing areas. Only 10% of the US soybean production is irrigated; therefore, plants must possess physiological mechanisms to tolerate drought stress. Slow canopy wilting is a physiological trait that is observed in a few exotic plant introductions (PIs) and may lead to yield improvement under drought stress. Canopy wilting of 130 recombinant inbred lines (RILs) derived from Hutcheson × PI 471938 grown under drought stress was visually evaluated and genotyped with the SoySNP6K BeadChip. Over four years, field evaluations of canopy wilting were conducted under rainfed conditions at three locations across the US (Georgia, Kansas, and North Carolina). Due to the variation in weather among locations and years, the phenotypic data were collected from seven environments. Substantial variation in canopy wilting was observed among the genotypes in the RIL population across environments. Three QTLs were identified for canopy wilting from the RIL population using composite interval mapping on chromosomes (Chrs) 2, 8, and 9 based on combined environmental analyses. These QTLs inherited the favorable alleles from PI 471938 and accounted for 11, 10, and 14% of phenotypic variation, respectively. A list of 106 candidate genes were narrowed down for these three QTLs based on the published information. The QTLs identified through this research can be used as targets for further investigation to understand the mechanisms of slow canopy wilting. These QTLs could be deployed to improve drought tolerance through a targeted selection of the genomic regions from PI 471938.

High-density genetic linkage mapping in Sitka spruce advances the integration of genomic resources in conifers

In species with large and complex genomes such as conifers, dense linkage maps are a useful resource for supporting genome assembly and laying the genomic groundwork at the structural, populational, and functional levels. However, most of the 600+ extant conifer species still lack extensive genotyping resources, which hampers the development of high-density linkage maps. In this study, we developed a linkage map relying on 21,570 single nucleotide polymorphism (SNP) markers in Sitka spruce (Picea sitchensis [Bong.] Carr.), a long-lived conifer from western North America that is widely planted for productive forestry in the British Isles. We used a single-step mapping approach to efficiently combine RAD-seq and genotyping array SNP data for 528 individuals from 2 full-sib families. As expected for spruce taxa, the saturated map contained 12 linkages groups with a total length of 2,142 cM. The positioning of 5,414 unique gene coding sequences allowed us to compare our map with that of other Pinaceae species, which provided evidence for high levels of synteny and gene order conservation in this family. We then developed an integrated map for P. sitchensis and Picea glauca based on 27,052 markers and 11,609 gene sequences. Altogether, these 2 linkage maps, the accompanying catalog of 286,159 SNPs and the genotyping chip developed, herein, open new perspectives for a variety of fundamental and more applied research objectives, such as for the improvement of spruce genome assemblies, or for marker-assisted sustainable management of genetic resources in Sitka spruce and related species.

Unveiling synergistic QTLs associated with slow wilting in soybean (Glycine max [L.] Merr.)

KEY MESSAGE

A stable QTL qSW_Gm10 works with a novel locus, qSW_Gm01, in a synergistic manner for controlling slow-wilting traits at the early vegetative stage under drought stress in soybean. Drought is one of the major environmental factors which limits soybean yield. Slow wilting is a promising trait that can enhance drought resilience in soybean without additional production costs. Recently, a Korean soybean cultivar SS2-2 was reported to exhibit slow wilting at the early vegetative stages. To find genetic loci responsible for slow wilting, in this study, quantitative trait loci (QTL) analysis was conducted using a recombinant inbred line (RIL) population derived from crossing between Taekwangkong (fast-wilting) and SS2-2 (slow-wilting). Wilting score and leaf moisture content were evaluated at the early vegetative stages for three years. Using the ICIM-MET module, a novel QTL on Chr01, qSW_Gm01 was identified, together with a previously known QTL, qSW_Gm10. These two QTLs were found to work synergistically for slow wilting of the RILs under the water-restricted condition. Furthermore, the SNP markers from the SoySNP50K dataset, located within these QTLs, were associated with the wilting phenotype in 30 diverse soybean accessions. Two genes encoding protein kinase 1b and multidrug resistance-associated protein 4 were proposed as candidate genes for qSW_Gm01 and qSW_Gm10, respectively, based on a comprehensive examination of sequence variation and gene expression differences in the parental lines under drought conditions. These genes may play a role in slow wilting by optimally regulating stomatal aperture. Our findings provide promising genetic resources for improving drought resilience in soybean and give valuable insights into the genetic mechanisms governing slow wilting.

Genome-wide association study reveals GmFulb as candidate gene for maturity time and reproductive length in soybeans (Glycine max)

The ability of soybean [Glycine max (L.) Merr.] to adapt to different latitudes is attributed to genetic variation in major E genes and quantitative trait loci (QTLs) determining flowering time (R1), maturity (R8), and reproductive length (RL). Fully revealing the genetic basis of R1, R8, and RL in soybeans is necessary to enhance genetic gains in soybean yield improvement. Here, we performed a genome-wide association analysis (GWA) with 31,689 single nucleotide polymorphisms (SNPs) to detect novel loci for R1, R8, and RL using a soybean panel of 329 accessions with the same genotype for three major E genes (e1-as/E2/E3). The studied accessions were grown in nine environments and observed for R1, R8 and RL in all environments. This study identified two stable peaks on Chr 4, simultaneously controlling R8 and RL. In addition, we identified a third peak on Chr 10 controlling R1. Association peaks overlap with previously reported QTLs for R1, R8, and RL. Considering the alternative alleles, significant SNPs caused RL to be two days shorter, R1 two days later and R8 two days earlier, respectively. We identified association peaks acting independently over R1 and R8, suggesting that trait-specific minor effect loci are also involved in controlling R1 and R8. From the 111 genes highly associated with the three peaks detected in this study, we selected six candidate genes as the most likely cause of R1, R8, and RL variation. High correspondence was observed between a modifying variant SNP at position 04:39294836 in GmFulb and an association peak on Chr 4. Further studies using map-based cloning and fine mapping are necessary to elucidate the role of the candidates we identified for soybean maturity and adaptation to different latitudes and to be effectively used in the marker-assisted breeding of cultivars with optimal yield-related traits.

Molecular, genetic, and genomic basis of seed size and yield characteristics in soybean

Soybean (Glycine max L. Merr.) is a crucial oilseed cash crop grown worldwide and consumed as oil, protein, and food by humans and feed by animals. Comparatively, soybean seed yield is lower than cereal crops, such as maize, rice, and wheat, and the demand for soybean production does not keep up with the increasing consumption level. Therefore, increasing soybean yield per unit area is the most crucial breeding objective and is challenging for the scientific community. Moreover, yield and associated traits are extensively researched in cereal crops, but little is known about soybeans' genetics, genomics, and molecular regulation of yield traits. Soybean seed yield is a complex quantitative trait governed by multiple genes. Understanding the genetic and molecular processes governing closely related attributes to seed yield is crucial to increasing soybean yield. Advances in sequencing technologies have made it possible to conduct functional genomic research to understand yield traits' genetic and molecular underpinnings. Here, we provide an overview of recent progress in the genetic regulation of seed size in soybean, molecular, genetics, and genomic bases of yield, and related key seed yield traits. In addition, phytohormones, such as auxin, gibberellins, cytokinins, and abscisic acid, regulate seed size and yield. Hence, we also highlight the implications of these factors, challenges in soybean yield, and seed trait improvement. The information reviewed in this study will help expand the knowledge base and may provide the way forward for developing high-yielding soybean cultivars for future food demands.

SoyDBean: a database for SNPs reconciliation by multiple versions of soybean reference genomes

Due to the development of sequence technology and decreased cost, many whole genome sequences have been obtained. As a result, extensive genetic variations have been discovered from many populations and germplasms to understand the genetic diversity of soybean (Glycine max [L.] Merr.). However, assessing the quality of variation is essential because the published variants were collected using different bioinformatic methods and parameters. Furthermore, despite the enhanced genome contiguity and more efficient filling of "N" stretches in the new reference genome, there remains a dearth of endeavors to verify the caliber of variations present in it. The primary goal of this research was to discern a dependable set of SNPs that can withstand reconciliation across multiple reference genomes. Additionally, the investigation aimed to reconfirm the variations through the utilization of numerous whole genome sequencing data obtained from publicly available databases. Based on the result, we created datasets that comprised the thoroughly verified SNP coordinates between the reference assemblies. The resulting "SoyDBean" database is now publicly accessible through the following URL: http://soydbean.plantprofile.net/ .

Genetic variation and genetic complexity of nodule occupancy in soybean inoculated with USDA110 and USDA123 rhizobium strains

BACKGROUND

Symbiotic nitrogen fixation differs among Bradyrhizobium japonicum strains. Soybean inoculated with USDA123 has a lower yield than strains known to have high nitrogen fixation efficiency, such as USDA110. In the main soybean-producing area in the Midwest of the United States, USDA123 has a high nodule incidence in field-grown soybean and is competitive but inefficient in nitrogen fixation. In this study, a high-throughput system was developed to characterize nodule number among 1,321 Glycine max and 69 Glycine soja accessions single inoculated with USDA110 and USDA123.

RESULTS

Seventy-three G. max accessions with significantly different nodule number of USDA110 and USDA123 were identified. After double inoculating 35 of the 73 accessions, it was observed that PI189939, PI317335, PI324187B, PI548461, PI562373, and PI628961 were occupied by USDA110 and double-strain nodules but not by USDA123 nodules alone. PI567624 was only occupied by USDA110 nodules, and PI507429 restricted all strains. Analysis showed that 35 loci were associated with nodule number in G. max when inoculated with strain USDA110 and 35 loci with USDA123. Twenty-three loci were identified in G. soja when inoculated with strain USDA110 and 34 with USDA123. Only four loci were common across two treatments, and each locus could only explain 0.8 to 1.5% of phenotypic variation.

CONCLUSIONS

High-throughput phenotyping systems to characterize nodule number and occupancy were developed, and soybean germplasm restricting rhizobium strain USDA123 but preferring USDA110 was identified. The larger number of minor effects and a small few common loci controlling the nodule number indicated trait genetic complexity and strain-dependent nodulation restriction. The information from the present study will add to the development of cultivars that limit USDA123, thereby increasing nitrogen fixation efficiency and productivity.

Genome resequencing reveals genetic loci and genes conferring resistance to SMV-SC8 in soybean

KEY MESSAGE

A soybean natural population genotyped by resequencing and another RIL population genotyped by SoySNP6K were used to explore consistent genetic loci and genes under greenhouse- and field-conditions for SMV-SC8 resistance. Soybean mosaic virus (SMV) is a member of the genus Potyvirus that occurs in all soybean-growing areas of the world and causes serious losses of yield and seed quality. In this study, a natural population composed of 209 accessions resequenced at an average depth of 18.44 × and another RIL population containing 193 lines were used to explore genetic loci and genes conferring resistance to SMV-SC8. There were 3030 SNPs significantly associated with resistance to SC8 on chromosome 13 in the natural population, among which 327 SNPs were located within an ~ 0.14 Mb region (from 28.46 to 28.60 Mb) of the major QTL qRsc8F in the RIL population. Two genes among 21 candidate genes, GmMACPF1 and GmRad60, were identified in the region of consistent linkage and association. Compared to the mock control, the changes in the expression of these two genes after inoculation with SC8 differed between resistant and susceptible accessions. More importantly, GmMACPF1 was shown to confer resistance to SC8 by significantly decreasing virus content in soybean hairy roots overexpressing this gene. A functional marker, FMSC8, was developed based on the allelic variation of GmMACPF1, and a high coincidence rate of 80.19% between the disease index and marker genotype was identified in the 419 soybean accessions. The results provide valuable resources for studies on the molecular mechanism of SMV resistance and genetic improvement in soybean.

Genome-Wide Identification and Comparative Analysis of RALF Gene Family in Legume and Non-Legume Species

Rapid alkalinization factor (RALF) are small secreted peptide hormones that can induce rapid alkalinization in a medium. They act as signaling molecules in plants, playing a critical role in plant development and growth, especially in plant immunity. Although the function of RALF peptides has been comprehensively analyzed, the evolutionary mechanism of RALFs in symbiosis has not been studied. In this study, 41, 24, 17 and 12 RALFs were identified in Arabidopsis, soybean, Lotus and Medicago, respectively. A comparative analysis including the molecular characteristics and conserved motifs suggested that the RALF pre-peptides in soybean represented a higher value of isoelectric point and more conservative motifs/residues composition than other species. All 94 RALFs were divided into two clades according to the phylogenetic analysis. Chromosome distribution and synteny analysis suggested that the expansion of the RALF gene family in Arabidopsis mainly depended on tandem duplication, while segment duplication played a dominant role in legume species. The expression levels of most RALFs in soybean were significantly affected by the treatment of rhizobia. Seven GmRALFs are potentially involved in the release of rhizobia in the cortex cells. Overall, our research provides novel insights into the understanding of the role of the RALF gene family in nodule symbiosis.

Development of SNP marker panels for genotyping by target sequencing (GBTS) and its application in soybean

A high-throughput genotyping platform with customized flexibility, high genotyping accuracy, and low cost is critical for marker-assisted selection and genetic mapping in soybean. Three assay panels were selected from the SoySNP50K, 40K, 20K, and 10K arrays, containing 41,541, 20,748, and 9670 SNP markers, respectively, for genotyping by target sequencing (GBTS). Fifteen representative accessions were used to assess the accuracy and consistency of the SNP alleles identified by the SNP panels and sequencing platform. The SNP alleles were 99.87% identical between technical replicates and 98.86% identical between the 40K SNP GBTS panel and 10× resequencing analysis. The GBTS method was also accurate in the sense that the genotypic dataset of the 15 representative accessions correctly revealed the pedigree of the accessions, and the biparental progeny datasets correctly constructed the linkage maps of the SNPs. The 10K panel was also used to genotype two parent-derived populations and analyze QTLs controlling 100-seed weight, resulting in the identification of the stable associated genetic locus Locus_OSW_06 on chromosome 06. The markers flanking the QTL explained 7.05% and 9.83% of the phenotypic variation, respectively. Compared with GBS and DNA chips, the 40K, 20K, and 10K panels reduced costs by 5.07% and 58.28%, 21.44% and 65.48%, and 35.74% and 71.76%, respectively. Low-cost genotyping panels could facilitate soybean germplasm assessment, genetic linkage map construction, QTL identification, and genomic selection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01372-6.

Genome-wide survey identified superior and rare haplotypes for plant height in the north-eastern soybean germplasm of China

The proper and efficient utilization of natural genetic diversity can significantly impact crop improvements. Plant height is a quantitative trait governing the plant type as well as the yield and quality of soybean. Here, we used a combined approach including a genome-wide association study (GWAS) and haplotype and candidate gene analyses to explore the genetic basis of plant height in diverse natural soybean populations. For the GWAS analysis, we used the whole-genome resequencing data of 196 diverse soybean cultivars collected from different accumulated temperature zones of north-eastern China to detect the significant single-nucleotide polymorphisms (SNPs) associated with plant height across three environments (E1, E2, and E3). A total of 33 SNPs distributed on four chromosomes, viz., Chr.02, Chr.04, Chr.06, and Chr.19, were identified to be significantly associated with plant height across the three environments. Among them, 23 were consistently detected in two or more environments and the remaining 10 were identified in only one environment. Interestingly, all the significant SNPs detected on the respective chromosomes fell within the physical interval of linkage disequilibrium (LD) decay (± 38.9 kb). Hence, these genomic regions were considered to be four quantitative trait loci (QTLs), viz., qPH2, qPH4, qPH6, and qPH19, regulating plant height. Moreover, the genomic region flanking all significant SNPs on four chromosomes exhibited strong LD. These significant SNPs thus formed four haplotype blocks, viz., Hap-2, Hap-4, Hap-6, and Hap-19. The number of haplotype alleles underlying each block varied from four to six, and these alleles regulate the different phenotypes of plant height ranging from dwarf to extra-tall heights. Nine candidate genes were identified within the four haplotype blocks, and these genes were considered putative candidates regulating soybean plant height. Hence, these stable QTLs, superior haplotypes, and candidate genes (after proper validation) can be deployed for the development of soybean cultivars with desirable plant heights.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01363-7.

N. Lopes I, Abdelnoor RV, Marcelino-Guimarães FC. Mapping of a soybean rust resistance in PI 594756 at the Rpp1 locus

Asian soybean rust (ASR), caused by the fungus Phakopsora pachyrhizi, is the main disease affecting soybean in Brazil. This study aimed at investigating and mapping the resistance of the PI 594756 to P. pachyrhizi, by using Bulked Segregant Analysis (BSA). The PI 594756 and the susceptible PI 594891 were crossed and the resulting F2 and F2:3 populations (208 and 1770 plants, respectively) were tested against ASR. Also, these PIs and differential varieties were tested against a panel of monosporic isolates. Plants presenting tan lesions were classified as susceptible (S) while plants presenting reddish-brown (RB) lesions were classified as resistant. DNA bulks were genotyped with Infinium BeadChips and the genomic region identified was further analyzed in the F2 individuals with target GBS (tGBS). PI 594,56 presented a unique resistance profile compared to the differential varieties. The resistance was monogenic dominant; however, it was classified as incompletely dominant when quantitatively studied. Genetic and QTL mapping placed the PI 594756 gene between the genomic region located at 55,863,741 and 56,123,516 bp of chromosome 18. This position is slightly upstream mapping positions of Rpp1 (PI 200492) and Rpp1-b (PI 594538A). Finally, we performed a haplotype analysis in a whole genomic sequencing-SNP database composed of Brazilian historical germplasm and sources of Rpp genes. We found SNPs that successfully differentiated the new PI 594756 allele from Rpp1 and Rpp1-b sources. The haplotype identified can be used as a tool for marker-assisted selection (MAS).

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01358-4.

QTL Mapping of Palmitic Acid Content Using Specific-Locus Amplified Fragment Sequencing (SLAF-Seq) Genotyping in Soybeans (Glycine max L.)

Soybeans are essential crops that supply protein and oil. The composition and contents of soybean fatty acids are relevant to human health and have a significant relationship with soybean oil processing and applications. Identifying quantitative trait locus (QTL) genes related to palmitic acid could facilitate the development of a range of nutritive soybean cultivars using molecular marker-assisted selection. In this study, we used a cultivar with higher palmitic acid content, ‘Dongnong42’, and a lower palmitic acid content cultivar, ‘Hobbit’, to establish F2:6 recombinant inbred lines. A high-density genetic map containing 9980 SLAF markers was constructed and distributed across 20 soybean chromosomes. The genetic map contained a total genetic distance of 2602.58 cM and an average genetic distance of 0.39 cM between adjacent markers. Two QTLs related to palmitic acid content were mapped using inclusive composite interval mapping, explaining 4.2–10.1% of the phenotypic variance in three different years and environments, including the QTL included in seed palmitic 7-3, which was validated by developing SSR markers. Based on the SNP/Indel and significant differential expression analyses of Dongnong42 and Hobbit, two genes, Glyma.15g119700 and Glyma.15g119800, were selected as candidate genes. The high-density genetic map, QTLs, and molecular markers will be helpful for the map-based cloning of palmitic acid content genes. These could be used to accelerate breeding for high nutritive value cultivars via molecular marker-assisted breeding.

The construction of a high-density consensus genetic map for soybean based on SNP markers derived from genotyping-by-sequencing

Genetic linkage maps are used to localize markers on the genome based on the recombination frequency. Most often, these maps are based on the segregation observed within a single biparental population of limited size (n < 300) where relatively few recombination events are sampled and in which some genomic regions are monomorphic because both parents carry the same alleles. Together, these two limitations affect both the resolution and extent of genome coverage of such maps. Consensus genetic maps overcome the limitations of individual genetic maps by merging the information from multiple segregating populations derived from a greater diversity of parental combinations, thus increasing the number of recombination events and reducing the number of monomorphic regions. The aim of this study was to construct a high-density consensus genetic map for single nucleotide polymorphism (SNP) markers obtained through a genotyping-by-sequencing (GBS) approach. Individual genetic maps were generated from six F4:5 mapping populations (n = 278-365), totaling 1857 individuals. The six linkage maps were then merged to produce a consensus map comprising a total of 16 311 mapped SNPs that jointly cover 99.5% of the soybean genome with only two gaps larger than 10 cM. Compared to previous soybean consensus maps, it offers a more extensive and uniform coverage.

SoyMAGIC: An Unprecedented Platform for Genetic Studies and Breeding Activities in Soybean

Multi-Parent Advanced Generation Inter-Cross (MAGIC) populations are emerging genetic platforms for high-resolution and fine mapping of quantitative traits, such as agronomic and seed composition traits in soybean (Glycine max L.). We have established an eight-parent MAGIC population, comprising 721 recombinant inbred lines (RILs), through conical inter-mating of eight soybean lines. The parental lines were genetically diverse elite cultivars carrying different agronomic and seed composition characteristics, including amino acids and fatty acids, as well as oil and protein concentrations. This study aimed to introduce soybean MAGIC (SoyMAGIC) population as an unprecedented platform for genotypic and phenotypic investigation of agronomic and seed quality traits in soybean. The RILs were evaluated for important seed composition traits using replicated field trials during 2020 and 2021. To measure the seed composition traits, near-infrared reflectance (NIR) was employed. The RILs were genotyped using genotyping-by-sequencing (GBS) method to decipher the genome and discover single-nucleotide polymorphic (SNP) markers among the RILs. A high-density linkage map was constructed through inclusive composite interval mapping (ICIM). The linkage map was 3,770.75 cM in length and contained 12,007 SNP markers. Chromosomes 11 and 18 were recorded as the shortest and longest linkage groups with 71.01 and 341.15 cM in length, respectively. Observed transgressive segregation of the selected traits and higher recombination frequency across the genome confirmed the capability of MAGIC population in reshuffling the diversity in the soybean genome among the RILs. The assessment of haplotype blocks indicated an uneven distribution of the parents' genomes in RILs, suggesting cryptic influence against or in favor of certain parental genomes. The SoyMAGIC population is a recombined genetic material that will accelerate further genomic studies and the development of soybean cultivars with improved seed quality traits through the development and implementation of reliable molecular-based toolkits.

Mapping and identification of QTL in 5601T × U99-310255 RIL population using SNP genotyping: soybean seed quality traits

BACKGROUND

Molecular markers have played and will continue to play a major role in the genetic characterization and improvement of soybeans. They have helped identify major loci for tolerance to abiotic stressors, disease resistance, herbicide resistance, soybean seed quality traits, and yield. However, most yield quantitative trait loci (QTL) are specific to a certain population, and the genetic variation found in the specific bi-parental population is not always shared in other populations. A major objective in soybean breeding is to develop high yielding cultivars. Unfortunately, soybean seed yield, as well as protein and oil content, are complex quantitative traits to characterize from the phenotypic and genotypic perspectives. The objectives of this study are to detect soybean genomic regions that increase protein content, while maintaining oil content and seed yield and to successfully identify soybean QTL associated with these seed quality traits.

METHODS AND RESULTS

To achieve these objectives, data from the 138 recombinant inbred lines grown in six environments were used to perform QTL detection analyses in search of significant genomic regions affecting soybean seed protein, oil, and yield.

CONCLUSIONS

A total of 21 QTL were successfully identified for yield, protein, oil, methionine, threonine, lodging, maturity, and meal. Knowledge of their locations and flanking markers will aid in marker assisted selection for plant breeders. This will lead to a more valuable soybean for farmers, processors, and animal nutritionists.

Identification of superior haplotypes in a diverse natural population for breeding desirable plant height in soybean

KEY MESSAGE

Plant height of soybean is associated with a haplotype block on chromosome 19, which classified 211 soybean accessions into five distinct groups showing significant differences for the target trait. Genetic variation is pivotal for crop improvement. Natural populations are precious genetic resources. However, efficient strategies for the targeted utilization of these resources for quantitative traits, such as plant height (PH), are scarce. Being an important agronomic trait associated with soybean yield and quality, it is imperative to unravel the genetic mechanisms underlying PH in soybean. Here, a genome-wide association study (GWAS) was performed to identify single nucleotide polymorphisms (SNPs) significantly associated with PH in a natural population of 211 cultivated soybeans, which was genotyped with NJAU 355 K Soy SNP Array and evaluated across six environments. A total of 128 SNPs distributed across 17 chromosomes were found to be significantly associated with PH across six environments and a combined environment. Three significant SNPs were consistently identified in at least three environments on Chr.02 (AX-93958260), Chr.17 (AX-94154834), and Chr.19 (AX-93897200). Genomic regions of ~ 130 kb flanking these three consistent SNPs were considered as stable QTLs, which included 169 genes. Of these, 22 genes (including Dt1) were prioritized and defined as putative candidates controlling PH. The genomic region flanking 12 most significant SNPs was in strong linkage disequilibrium (LD). These SNPs formed a single haplotype block containing five haplotypes for PH, namely Hap-A, Hap-B, Hap-C, Hap-D, and Hap-E. Deployment of such superior haplotypes in breeding programs will enable development of improved soybean varieties with desirable plant height.

POWR1 is a domestication gene pleiotropically regulating seed quality and yield in soybean

Seed protein, oil content and yield are highly correlated agronomically important traits that essentially account for the economic value of soybean. The underlying molecular mechanisms and selection of these correlated seed traits during soybean domestication are, however, less known. Here, we demonstrate that a CCT gene, POWR1, underlies a large-effect protein/oil QTL. A causative TE insertion truncates its CCT domain and substantially increases seed oil content, weight, and yield while decreasing protein content. POWR1 pleiotropically controls these traits likely through regulating seed nutrient transport and lipid metabolism genes. POWR1 is also a domestication gene. We hypothesize that the TE insertion allele is exclusively fixed in cultivated soybean due to selection for larger seeds during domestication, which significantly contributes to shaping soybean with increased yield/seed weight/oil but reduced protein content. This study provides insights into soybean domestication and is significant in improving seed quality and yield in soybean and other crop species.

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.

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.

Physiological breeding for yield improvement in soybean: solar radiation interception-conversion, and harvest index

KEY MESSAGE

Efficiency of light interception, Radiation use efficiency and harvest index can be used as targets to improve grain yield potential in soybean. Grain yield (GY) production can be expressed as the result of three main efficiencies: light interception (Ei), radiation use (RUE), and harvest index (HI). Although dissecting GY through these three efficiencies is not entirely new, there is a lack of knowledge about the phenotypic variation, the genetic architecture, and the relative contribution of these three efficiencies on GY in soybean. This knowledge gap coupled with laborious phenotyping prevents the active consideration of these efficiencies into breeding programs. This study aims to reveal the phenotypic variation, heritability, genetic relationships, genetic architecture, and genomic prediction for Ei, RUE, and HI in soybean. We evaluated a maturity control panel of 383 Recombinant Inbred Lines (RILs) selected from the soybean nested association mapping (SoyNAM) population. Dry matter ground measured along with canopy coverage (CC) from UAS imagery were collected in three environments. Light interception was modeled through a logistic curve using CC as a proxy. The total above-ground biomass collected during the growing season and its respective cumulative light intercepted were used to derive RUE through linear models fitting. Additive-genetic correlations, genome-wide association (GWA) and whole-genome regressions (WGR) were performed to evaluate the relationship between traits, their association with genomic regions, and the feasibility of predicting these efficiencies with genomic information. Correlation analyses considered three groups: the entire data set, and the high- and low-yielding RILs to determine association as a function of the GY. Our results revealed moderate to high phenotypic variation for Ei, RUE, and HI with ranges of 8.5%, 1.1 g MJ-1, and 0.2, respectively. Additive-genetic correlation revealed a strong relationship of GY with HI and moderate with RUE and Ei when whole data set was considered, but negligible contribution of HI on GY when just the top 100 was analyzed. The GWA analyses showed that Ei is associated with three SNPs; two of them located on chromosome 7 and one on chromosome 11 with no previous quantitative trait loci (QTLs) reported for these regions. RUE is associated with four SNPs on chromosomes 1, 7, 11, and 18. Some of these QTLs are novel, while others are previously documented for plant architecture and chlorophyll content. Two SNPs positioned on chromosome 13 and 15 with previous QTLs reported for plant height and seed set, weight and abortion were associated with HI. WGR showed high predictive ability for Ei, RUE, and HI with maximum correlation ranging between 0.75 and 0.80. Future improvements in GY can be expected through strategies prioritizing Ei for short-term results when using high yielding germplasm and RUE for medium- and long-term outcomes. This work is a pioneer attempt to integrate traditional physiological traits into the breeding process in the context of physiological breeding.

Genetic and Genomic Resources for Soybean Breeding Research

Soybean (Glycine max) is a legume species of significant economic and nutritional value. The yield of soybean continues to increase with the breeding of improved varieties, and this is likely to continue with the application of advanced genetic and genomic approaches for breeding. Genome technologies continue to advance rapidly, with an increasing number of high-quality genome assemblies becoming available. With accumulating data from marker arrays and whole-genome resequencing, studying variations between individuals and populations is becoming increasingly accessible. Furthermore, the recent development of soybean pangenomes has highlighted the significant structural variation between individuals, together with knowledge of what has been selected for or lost during domestication and breeding, information that can be applied for the breeding of improved cultivars. Because of this, resources such as genome assemblies, SNP datasets, pangenomes and associated databases are becoming increasingly important for research underlying soybean crop improvement.

Integrating omics approaches to discover and prioritize candidate genes involved in oil biosynthesis in soybean

Soybean is a major source of edible protein and oil. Oil content is a quantitative trait that is significantly determined by genetic and environmental factors. Over the past 30 years, a large volume of soybean genetic, genomic, and transcriptomic data have been accumulated. Nevertheless, integrative analyses of such data remain scarce, in spite of their importance for crop improvement. We hypothesized that the co-occurrence of genomic regions for oil-related traits in different studies may reveal more stable regions encompassing important genetic determinants of oil content and quality in soybean. We integrated publicly available data, obtained with distinct techniques, to discover and prioritize candidate genes involved in oil biosynthesis and regulation in soybean. We detected key fatty acid biosynthesis genes (e.g., BCCP2 and ACCase, FADs, KAS family proteins) and several transcription factors, which are likely regulators of oil biosynthesis. In addition, we identified new candidates for seed oil accumulation and quality, such as Glyma.03G213300 and Glyma.19G160700, which encode a translocator protein homolog and a histone acetyltransferase, respectively. Further, oil and protein genomic hotspots are strongly associated with breeding and not with domestication, suggesting that soybean domestication prioritized other traits. The genes identified here are promising targets for breeding programs and for the development of soybean lines with increased oil content and quality.

Assemblies of the genomes of parasitic wasps using meta-assembly and scaffolding with genetic linkage

Safe, effective biological-control introductions against invasive pests depend on narrowly host-specific natural enemies with the ability to adapt to a changing environment. As part of a project on the genetic architectures of these traits, we assembled and annotated the genomes of two aphid parasitoids, Aphelinus atriplicis and Aphelinus certus. We report here several assemblies of A. atriplicis made with Illumina and PacBio data, which we combined into a meta-assembly. We scaffolded the meta-assembly with markers from a genetic map of hybrids between A. atriplicis and A. certus. We used this genetic-linkage scaffolded (GLS) assembly of A. atriplicis to scaffold a de novo assembly of A. certus. The de novo assemblies of A. atriplicis differed in contiguity, and the meta-assembly of these assemblies was more contiguous than the best de novo assembly. Scaffolding with genetic-linkage data allowed chromosomal-level assembly of the A. atriplicis genome and scaffolding a de novo assembly of A. certus with this GLS assembly, greatly increased the contiguity of the A. certus assembly to the point where it was also at the chromosomal-level. However, completeness of the A. atriplicis assembly, as measured by percent complete, single-copy BUSCO hymenopteran genes, varied little among de novo assemblies and was not increased by meta-assembly or genetic scaffolding. Furthermore, the greater contiguity of the meta-assembly and GLS assembly had little or no effect on the numbers of genes identified, the proportions with homologs or functional annotations. Increased contiguity of the A. certus assembly provided modest improvement in assembly completeness, as measured by percent complete, single-copy BUSCO hymenopteran genes. The total genic sequence increased, and while the number of genes declined, gene length increased, which together suggest greater accuracy of gene models. More contiguous assemblies provide uses other than gene annotation, for example, identifying the genes associated with quantitative trait loci and understanding of chromosomal rearrangements associated with speciation.

Genome assembly of the popular Korean soybean cultivar Hwangkeum

Massive resequencing efforts have been undertaken to catalog allelic variants in major crop species including soybean, but the scope of the information for genetic variation often depends on short sequence reads mapped to the extant reference genome. Additional de novo assembled genome sequences provide a unique opportunity to explore a dispensable genome fraction in the pan-genome of a species. Here, we report the de novo assembly and annotation of Hwangkeum, a popular soybean cultivar in Korea. The assembly was constructed using PromethION nanopore sequencing data and two genetic maps and was then error-corrected using Illumina short-reads and PacBio SMRT reads. The 933.12 Mb assembly was annotated as containing 79,870 transcripts for 58,550 genes using RNA-Seq data and the public soybean annotation set. Comparison of the Hwangkeum assembly with the Williams 82 soybean reference genome sequence (Wm82.a2.v1) revealed 1.8 million single-nucleotide polymorphisms, 0.5 million indels, and 25 thousand putative structural variants. However, there was no natural megabase-scale chromosomal rearrangement. Incidentally, by adding two novel subfamilies, we found that soybean contains four clearly separated subfamilies of centromeric satellite repeats. Analyses of satellite repeats and gene content suggested that the Hwangkeum assembly is a high-quality assembly. This was further supported by comparison of the marker arrangement of anthocyanin biosynthesis genes and of gene arrangement at the Rsv3 locus. Therefore, the results indicate that the de novo assembly of Hwangkeum is a valuable additional reference genome resource for characterizing traits for the improvement of this important crop species.

Multiplex CRISPR-Cas9 editing of DNA methyltransferases in rice uncovers a class of non-CG methylation specific for GC-rich regions

DNA methylation in the non-CG context is widespread in the plant kingdom and abundant in mammalian tissues such as the brain and pluripotent cells. Non-CG methylation in Arabidopsis thaliana is coordinately regulated by DOMAINS REARRANGED METHYLTRANSFERASE (DRM) and CHROMOMETHYLASE (CMT) proteins but has yet to be systematically studied in major crops due to difficulties in obtaining genetic materials. Here, utilizing the highly efficient multiplex CRISPR-Cas9 genome-editing system, we created single- and multiple-knockout mutants for all the nine DNA methyltransferases in rice (Oryza sativa) and profiled their whole-genome methylation status at single-nucleotide resolution. Surprisingly, the simultaneous loss of DRM2, CHROMOMETHYLASE3 (CMT2), and CMT3 functions, which completely erases all non-CG methylation in Arabidopsis, only partially reduced it in rice. The regions that remained heavily methylated in non-CG contexts in the rice Os-dcc (Osdrm2/cmt2/cmt3a) triple mutant had high GC contents. Furthermore, the residual non-CG methylation in the Os-dcc mutant was eliminated in the Os-ddccc (Osdrm2/drm3/cmt2/cmt3a/cmt3b) quintuple mutant but retained in the Os-ddcc (Osdrm2/drm3/cmt2/cmt3a) quadruple mutant, demonstrating that OsCMT3b maintains non-CG methylation in the absence of other major methyltransferases. Our results showed that OsCMT3b is subfunctionalized to accommodate a distinct cluster of non-CG-methylated sites at highly GC-rich regions in the rice genome.

Patterns of Genetic Variation in a Soybean Germplasm Collection as Characterized with Genotyping-by-Sequencing

Genomic characterization is playing an increasing role in plant germplasm conservation and utilization, as it can provide higher resolution with genome-wide SNP markers than before to identify and analyze genetic variation. A genotyping-by-sequencing technique was applied to genotype 541 soybean accessions conserved at Plant Gene Resources of Canada and 30 soybean cultivars and breeding lines developed by the Ottawa soybean breeding program of Agriculture and Agri-Food Canada. The sequencing generated an average of 952,074 raw sequence reads per sample. SNP calling identified 43,891 SNPs across 20 soybean chromosomes and 69 scaffolds with variable levels of missing values. Based on 19,898 SNPs with up to 50% missing values, three distinct genetic groups were found in the assayed samples. These groups were a mixture of the samples that originated from different countries and the samples of known maturity groups. The samples that originated from Canada were clustered into all three distinct groups, but 30 Ottawa breeding lines fell into two groups only. Based on the average pairwise dissimilarity estimates, 40 samples with the most genetic distinctness were identified from three genetic groups with diverse sample origin and known maturity. Additionally, 40 samples with the highest genetic redundancy were detected and they consisted of different sample origins and maturity groups, largely from one genetic group. Moreover, some genetically duplicated samples were identified, but the overall level of genetic duplication was relatively low in the collection. These findings are useful for soybean germplasm management and utilization.

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.

The patterns of deleterious mutations during the domestication of soybean

Globally, soybean is a major protein and oil crop. Enhancing our understanding of the soybean domestication and improvement process helps boost genomics-assisted breeding efforts. Here we present a genome-wide variation map of 10.6 million single-nucleotide polymorphisms and 1.4 million indels for 781 soybean individuals which includes 418 domesticated (Glycine max), 345 wild (Glycine soja), and 18 natural hybrid (G. max/G. soja) accessions. We describe the enhanced detection of 183 domestication-selective sweeps and the patterns of putative deleterious mutations during domestication and improvement. This predominantly selfing species shows 7.1% reduction of overall deleterious mutations in domesticated soybean relative to wild soybean and a further 1.4% reduction from landrace to improved accessions. The detected domestication-selective sweeps also show reduced levels of deleterious alleles. Importantly, genotype imputation with this resource increases the mapping resolution of genome-wide association studies for seed protein and oil traits in a soybean diversity panel.

Genome-wide association identifies several QTLs controlling cysteine and methionine content in soybean seed including some promising candidate genes

Soybean is an important source of protein, oil and carbohydrates, as well as other beneficial nutrients. A major function of proteins in nutrition is to supply adequate amounts of amino acids. Although they are essential for human nutrition, the sulfur-containing amino acids cysteine (Cys) and methionine (Met) are often limited and the genetic control of their content in soybean seeds is poorly characterized. This study aimed to characterize the phenotypic variation and identify quantitative trait loci (QTL) associated with Cys and Met content in a core set of 137 soybean lines, representative of the genetic diversity among Canadian short-season soybean, spanning maturity groups 000-II (MG000-II). Significant phenotypic differences were found among these lines for Cys, Met and Cys + Met content. Using both a mixed linear model and six multi-locus methods with a catalogue of 2.18 M SNPs, we report a total of nine QTLs and seventeen QTNs of which seven comprise promising candidate genes. This work allowed us to reproducibly detect multiple novel loci associated with sulfur-containing amino acid content. The markers and genes identified in this study may be useful for soybean genetic improvement aiming to increase Cys and Met content.

Selection of GmSWEET39 for oil and protein improvement in soybean

Soybean [Glycine max (L.) Merr.] was domesticated from wild soybean (G. soja Sieb. and Zucc.) and has been further improved as a dual-use seed crop to provide highly valuable oil and protein for food, feed, and industrial applications. However, the underlying genetic and molecular basis remains less understood. Having combined high-confidence bi-parental linkage mapping with high-resolution association analysis based on 631 whole sequenced genomes, we mapped major soybean protein and oil QTLs on chromosome15 to a sugar transporter gene (GmSWEET39). A two-nucleotide CC deletion truncating C-terminus of GmSWEET39 was strongly associated with high seed oil and low seed protein, suggesting its pleiotropic effect on protein and oil content. GmSWEET39 was predominantly expressed in parenchyma and integument of the seed coat, and likely regulates oil and protein accumulation by affecting sugar delivery from maternal seed coat to the filial embryo. We demonstrated that GmSWEET39 has a dual function for both oil and protein improvement and undergoes two different paths of artificial selection. A CC deletion (CC-) haplotype H1 has been intensively selected during domestication and extensively used in soybean improvement worldwide. H1 is fixed in North American soybean cultivars. The protein-favored (CC+) haplotype H3 still undergoes ongoing selection, reflecting its sustainable role for soybean protein improvement. The comprehensive knowledge on the molecular basis underlying the major QTL and GmSWEET39 haplotypes associated with soybean improvement would be valuable to design new strategies for soybean seed quality improvement using molecular breeding and biotechnological approaches.

Soybean BARCSoySNP6K: An assay for soybean genetics and breeding research

The limited number of recombinant events in recombinant inbred lines suggests that for a biparental population with a limited number of recombinant inbred lines, it is unnecessary to genotype the lines with many markers. For genomic prediction and selection, previous studies have demonstrated that only 1000-2000 genome-wide common markers across all lines/accessions are needed to reach maximum efficiency of genomic prediction in populations. Evaluation of too many markers will not only increase the cost but also generate redundant information. We developed a soybean (Glycine max) assay, BARCSoySNP6K, containing 6000 markers, which were carefully chosen from the SoySNP50K assay based on their position in the soybean genome and haplotype block, polymorphism among accessions and genotyping quality. The assay includes 5000 single nucleotide polymorphisms (SNPs) from euchromatic and 1000 from heterochromatic regions. The percentage of SNPs with minor allele frequency >0.10 was 95% and 91% in the euchromatic and heterochromatic regions, respectively. Analysis of progeny from two large families genotyped with SoySNP50K versus BARCSoySNP6K showed that the position of the common markers and number of unique bins along linkage maps were consistent based on the SNPs genotyped with the two assays; however, the rate of redundant markers was dramatically reduced with the BARCSoySNP6K. The BARCSoySNP6K assay is proven as an excellent tool for detecting quantitative trait loci, genomic selection and assessing genetic relationships. The assay is commercialized by Illumina Inc. and being used by soybean breeders and geneticists and the list of SNPs in the assay is an ideal resource for SNP genotyping by targeted amplicon sequencing.

Next Generation Sequencing Based Forward Genetic Approaches for Identification and Mapping of Causal Mutations in Crop Plants: A Comprehensive Review

The recent advancements in forward genetics have expanded the applications of mutation techniques in advanced genetics and genomics, ahead of direct use in breeding programs. The advent of next-generation sequencing (NGS) has enabled easy identification and mapping of causal mutations within a short period and at relatively low cost. Identifying the genetic mutations and genes that underlie phenotypic changes is essential for understanding a wide variety of biological functions. To accelerate the mutation mapping for crop improvement, several high-throughput and novel NGS based forward genetic approaches have been developed and applied in various crops. These techniques are highly efficient in crop plants, as it is relatively easy to grow and screen thousands of individuals. These approaches have improved the resolution in quantitative trait loci (QTL) position/point mutations and assisted in determining the functional causative variations in genes. To be successful in the interpretation of NGS data, bioinformatics computational methods are critical elements in delivering accurate assembly, alignment, and variant detection. Numerous bioinformatics tools/pipelines have been developed for such analysis. This article intends to review the recent advances in NGS based forward genetic approaches to identify and map the causal mutations in the crop genomes. The article also highlights the available bioinformatics tools/pipelines for reducing the complexity of NGS data and delivering the concluding outcomes.

Identification of loci controlling mineral element concentration in soybean seeds

BACKGROUND

Mineral nutrients play a crucial role in the biochemical and physiological functions of biological systems. The enhancement of seed mineral content via genetic improvement is considered as the most promising and cost-effective approach compared alternative means for meeting the dietary needs. The overall objective of this study was to perform a GWAS of mineral content (Ca, K, P and S) in seeds of a core set of 137 soybean lines that are representative of the diversity of early maturing soybeans cultivated in Canada (maturity groups 000-II).

RESULTS

This panel of 137 soybean lines was grown in five environments (in total) and the seed mineral content was measured using a portable x-ray fluorescence (XRF) spectrometer. The association analyses were carried out using three statistical models and a set of 2.2 million SNPs obtained from a combined dataset of genotyping-by-sequencing and whole-genome sequencing. Eight QTLs significantly associated with the Ca, K, P and S content were identified by at least two of the three statistical models used (in two environments) contributing each from 17 to 31% of the phenotypic variation. A strong reproducibility of the effect of seven out these eight QTLs was observed in three other environments. In total, three candidate genes were identified involved in transport and assimilation of these mineral elements.

CONCLUSIONS

There have been very few GWAS studies to identify QTLs associated with the mineral element content of soybean seeds. In addition to being new, the QTLs identified in this study and candidate genes will be useful for the genetic improvement of soybean nutritional quality through marker-assisted selection. Moreover, this study also provides details on the range of phenotypic variation encountered within the Canadian soybean germplasm.

Characterization of genetic heterogeneity within accessions in the USDA soybean germplasm collection

Soybean breeding relies on the use of wild (Glycine soja Sieb. and Zucc.) and domesticated [Glycine max (L.) Merr.] germplasm for trait improvement. Soybeans are self-pollinating and accessions can be maintained as pure lines, however within-accession genetic variation has been observed in previous studies of some landraces and elite cultivars. The objective of this study was to characterize within-line variation in the accessions housed in the USDA Soybean Germplasm Collection. This collection includes over 20,000 accessions, each previously genotyped using the SoySNP50K Chip. Each SoySNP50K genotype was developed by pooling approximately three individuals per accession. Therefore, clusters of SNPs called as heterozygous within an accession can be inferred to represent putative regions of heterogeneity between the three individuals sampled. In this study, we found high-probability intervals of heterogeneity in 4% of the collection, representing 870 accessions. Heterogeneous loci were found on every chromosome and, collectively, covered 98.4% of the soybean genome and 99% of the gene models. Sanger sequencing confirmed regions of genomic heterogeneity among a subset of ten accessions. This dataset provides useful information and considerations for users of crop germplasm seed banks. Furthermore, the heterogeneous accessions and/or loci represent a unique genetic resource that is immediately available for forward and reverse genetics studies.

Nested association mapping of important agronomic traits in three interspecific soybean populations

KEY MESSAGE

Glycine soja germplasm can be used to successfully introduce new alleles with the potential to add valuable new genetic diversity to the current elite soybean gene pool. Given the demonstrated narrow genetic base of the US soybean production, it is essential to identify beneficial alleles from exotic germplasm, such as wild soybean, to enhance genetic gain for favorable traits. Nested association mapping (NAM) is an approach to population development that permits the comparison of allelic effects of the same QTL in multiple parents. Seed yield, plant maturity, plant height and plant lodging were evaluated in a NAM panel consisting of 392 recombinant inbred lines derived from three biparental interspecific soybean populations in eight environments during 2016 and 2017. Nested association mapping, combined with linkage mapping, identified three major QTL for plant maturity in chromosomes 6, 11 and 12 associated with alleles from wild soybean resulting in significant increases in days to maturity. A significant QTL for plant height was identified on chromosome 13 with the allele increasing plant height derived from wild soybean. A significant grain yield QTL was detected on chromosome 17, and the allele from Glycine soja had a positive effect of 166 kg ha-1; RIL's with the wild soybean allele yielded on average 6% more than the lines carrying the Glycine max allele. These findings demonstrate the usefulness and potential of alleles from wild soybean germplasm to enhance important agronomic traits in a soybean breeding program.

Chromosomal features revealed by comparison of genetic maps of Glycine max and Glycine soja

Recombination is a crucial component of evolution and breeding. New combinations of variation on chromosomes are shaped by recombination. Recombination is also involved in chromosomal rearrangements. However, recombination rates vary tremendously among chromosome segments. Genome-wide genetic maps are one of the best tools to study variation of recombination. Here, we describe high density genetic maps of Glycine max and Glycine soja constructed from four segregating populations. The maps were used to identify chromosomal rearrangements and find the highly predictable pattern of cross-overs on the broad scale in soybean. Markers on these genetic maps were used to evaluate assembly quality of the current soybean reference genome sequence. We find a strong inversion candidate larger than 3 Mb based on patterns of cross-overs. We also identify quantitative trait loci (QTL) that control number of cross-overs. This study provides fundamental insights relevant to practical strategy for breeding programs and for pan-genome researches.

Genome-Wide Association Study and QTL Meta-Analysis Identified Novel Genomic Loci Controlling Potassium Use Efficiency and Agronomic Traits in Bread Wheat

Potassium use efficiency, a complex trait, directly impacts the yield potential of crop plants. Low potassium efficiency leads to a high use of fertilizers, which is not only farmer unfriendly but also deteriorates the environment. Genome-wide association studies (GWAS) are widely used to dissect complex traits. However, most studies use single-locus one-dimensional GWAS models which do not provide true information about complex traits that are controlled by multiple loci. Here, both single-locus GWAS (MLM) and multi-locus GWAS (pLARmEB, FASTmrMLM, mrMLM, FASTmrEMMA) models were used with genotyping from 90 K Infinium SNP array and phenotype derived from four normal and potassium-stress environments, which identified 534 significant marker-trait associations (MTA) for agronomic and potassium related traits: pLARmEB = 279, FASTmrMLM = 213, mrMLM = 35, MLM = 6, FASTmrEMMA = 1. Further screening of these MTA led to the detection of eleven stable loci: q1A, q1D, q2B-1, q2B-2, q2D, q4D, q5B-1, q5B-2, q5B-3, q6D, and q7A. Moreover, Meta-QTL (MQTL) analysis of four independent QTL studies for potassium deficiency in bread wheat located 16 MQTL on 13 chromosomes. One locus identified in this study (q5B-1) colocalized with an MQTL (MQTL_{_11} ), while the other ten loci were novel associations. Gene ontology of these loci identified 20 putative candidate genes encoding functional proteins involved in key pathways related to stress tolerance, sugar metabolism, and nutrient transport. These findings provide potential targets for breeding potassium stress resistant wheat cultivars and advocate the advantages of multi-locus GWAS models for studying complex traits.

Construction and comparison of three reference-quality genome assemblies for soybean

We report reference-quality genome assemblies and annotations for two accessions of soybean (Glycine max) and for one accession of Glycine soja, the closest wild relative of G. max. The G. max assemblies provided are for widely used US cultivars: the northern line Williams 82 (Wm82) and the southern line Lee. The Wm82 assembly improves the prior published assembly, and the Lee and G. soja assemblies are new for these accessions. Comparisons among the three accessions show generally high structural conservation, but nucleotide difference of 1.7 single-nucleotide polymorphisms (snps) per kb between Wm82 and Lee, and 4.7 snps per kb between these lines and G. soja. snp distributions and comparisons with genotypes of the Lee and Wm82 parents highlight patterns of introgression and haplotype structure. Comparisons against the US germplasm collection show placement of the sequenced accessions relative to global soybean diversity. Analysis of a pan-gene collection shows generally high conservation, with variation occurring primarily in genomically clustered gene families. We found approximately 40-42 inversions per chromosome between either Lee or Wm82v4 and G. soja, and approximately 32 inversions per chromosome between Wm82 and Lee. We also investigated five domestication loci. For each locus, we found two different alleles with functional differences between G. soja and the two domesticated accessions. The genome assemblies for multiple cultivated accessions and for the closest wild ancestor of soybean provides a valuable set of resources for identifying causal variants that underlie traits for the domestication and improvement of soybean, serving as a basis for future research and crop improvement efforts for this important crop species.

Identification and characterization of a fast-neutron-induced mutant with elevated seed protein content in soybean

KEY MESSAGE

Protein content of soybean is critical for utility of soybean meal. A fast-neutron-induced deletion on chromosome 12 was found to be associated with increased protein content. Soybean seed composition affects the utility of soybean, and improving seed composition is an essential breeding goal. Fast neutron radiation introduces genomic mutations resulting in novel variation for traits of interest. Two elite soybean lines were irradiated with fast neutrons and screened for altered seed composition. Twenty-three lines with altered protein, oil, or sucrose content were selected based on near-infrared spectroscopy data from five environments and yield tested at five locations. Mutants with significantly increased protein averaged 19.1-36.8 g kg-1 more protein than the parents across 10 environments. Comparative genomic hybridization (CGH) identified putative mutations in a mutant, G15FN-12, that has 36.8 g kg-1 higher protein than the parent genotype, and whole genome sequencing (WGS) of the mutant has confirmed these mutations. An F2:3 population was developed from G15FN-12 to determine association between genomic changes and increased protein content. Bulked segregant analysis of the population using the SoySNP50K BeadChip identified a CGH- and WGS-confirmed deletion on chromosome 12 to be responsible for elevated protein content. The population was genotyped using a KASP marker designed at the mutation region, and significant association (P < 0.0001) between the deletion on chromosome 12 and elevated protein content was observed and confirmed in the F3:4 generation. The F2 segregants homozygous for the deletion averaged 27 g kg-1 higher seed protein and 8 g kg-1 lower oil than homozygous wild-type segregants. Mutants with altered seed composition are a new resource for gene function studies and provide elite materials for genetic improvement of seed composition.

Genome-wide genetic diversity is maintained through decades of soybean breeding in Canada

KEY MESSAGE

Genetic diversity in Canadian soybean is maintained over decades of selection in two public breeding programs. Breeders have used a portion of the genetic diversity available in germplasm collections. Both public and private breeding efforts have been critical for the development of soybean cultivars grown around the world. Global genetic diversity of soybean has been well characterized; however, this diversity is not well studied at the breeding program scale. The objective of this study was to characterize genetic diversity over decades of breeding in two public soybean breeding programs at the University of Guelph, Canada. To address this objective, a pedigree-related panel combining 296 soybean accessions from the Ridgetown and Guelph Campus breeding programs was studied. The accessions were genotyped using genotyping-by-sequencing, imputed using the GmHapMap reference genotypes resulting in more than 3.8M SNPs, further filtered to 77k SNPs. Population structure analysis did not identify structure between the breeding programs and historical germplasm. The linkage disequilibrium decay ranged from 400 to 600 kb on average in euchromatic regions. Nucleotide diversity over decades of breeding shows that historical accessions had the highest nucleotide diversity, with significant decreases corresponding to the initial breeding activity in Canada; however, genetic diversity has increased in the last 20 years in both breeding programs. Maturity gene E2 was nearly fixed for e2 in Ridgetown accessions, while unfixed in Guelph accessions. Comparison of the breeding programs to the USDA germplasm collection reveals that breeders have only used a portion of the available genetic diversity, allowing future breeders to exploit this untapped resource. The approach used in this study may be of interest to other breeding programs for evaluating changes in genetic diversity resulting from breeding activities.

Effect of marker segregation distortion on high density linkage map construction and QTL mapping in Soybean (Glycine max L.)

Marker segregation distortion is a natural phenomenon. Severely distorted markers are usually excluded in the construction of linkage maps. We investigated the effect of marker segregation distortion on linkage map construction and quantitative trait locus (QTL) mapping. A total of 519 recombinant inbred lines of soybean from orthogonal and reciprocal crosses between LSZZH and NN493-1 were genotyped by specific length amplified fragment markers and seed linoleic acid content was measured in three environments. As a result, twenty linkage groups were constructed with 11,846 markers, including 1513 (12.77%) significantly distorted markers, on 20 chromosomes, and the map length was 2475.86 cM with an average marker-interval of 0.21 cM. The inclusion of distorted markers in the analysis was shown to not only improve the grouping of the markers from the same chromosomes, and the consistency of linkage maps with genome, but also increase genome coverage by markers. Combining genotypic data from both orthogonal and reciprocal crosses decreased the proportion of distorted markers and then improved the quality of linkage maps. Validation of the linkage maps was confirmed by the high collinearity between positions of markers in the soybean reference genome and in linkage maps and by the high consistency of 24 QTL regions in this study compared with the previously reported QTLs and lipid metabolism related genes. Additionally, linkage maps that include distorted markers could add more information to the outputs from QTL mapping. These results provide important information for linkage mapping, gene cloning and marker-assisted selection in soybean.

Functional analysis and development of a CRISPR/Cas9 allelic series for a CPR5 ortholog necessary for proper growth of soybean trichomes

Developments in genomic and genome editing technologies have facilitated the mapping, cloning, and validation of genetic variants underlying trait variation. This study combined bulked-segregant analysis, array comparative genomic hybridization, and CRISPR/Cas9 methodologies to identify a CPR5 ortholog essential for proper trichome growth in soybean (Glycine max). A fast neutron mutant line exhibited short trichomes with smaller trichome nuclei compared to its parent line. A fast neutron-induced deletion was identified within an interval on chromosome 6 that co-segregated with the trichome phenotype. The deletion encompassed six gene models including an ortholog of Arabidopsis thaliana CPR5. CRISPR/Cas9 was used to mutate the CPR5 ortholog, resulting in five plants harboring a total of four different putative knockout alleles and two in-frame alleles. Phenotypic analysis of the mutants validated the candidate gene, and included intermediate phenotypes that co-segregated with the in-frame alleles. These findings demonstrate that the CPR5 ortholog is essential for proper growth and development of soybean trichomes, similar to observations in A. thaliana. Furthermore, this work demonstrates the value of using CRISPR/Cas9 to generate an allelic series and intermediate phenotypes for functional analysis of candidate genes and/or the development of novel traits.

Application of a high-resolution genetic map for chromosome-scale genome assembly and fine QTLs mapping of seed size and weight traits in castor bean

Castor bean (Ricinus communis L., Euphorbiaceae) is a critical biodiesel crop and its seed derivatives have important industrial applications. Due to lack of a high-density genetic map, the breeding and genetic improvement of castor bean has been largely restricted. In this study, based on a recombinant inbred line (RIL) population consisting of 200 individuals, we generated 8,896 high-quality genomic SNP markers and constructed a high-resolution genetic map with 10 linkage groups (LGs), spanning 1,852.33 centiMorgan (cM). Based on the genetic map, 996 scaffolds from the draft reference genome were anchored onto 10 pseudo-chromosomes, covering 84.43% of the castor bean genome. Furthermore, the quality of the pseudo-chromosome scale assembly genome was confirmed via genome collinearity analysis within the castor bean genome as well as between castor bean and cassava. Our results provide new evidence that the phylogenetic position of castor bean is relatively solitary from other taxa in the Euphorbiaceae family. Based on the genetic map, we identified 16 QTLs that control seed size and weight (covering 851 candidate genes). The findings will be helpful for further research into potential new mechanisms controlling seed size and weight in castor bean. The genetic map and improved pseudo-chromosome scale genome provide crucial foundations for marker-assisted selection (MAS) of QTL governing important agronomic traits, as well as the accelerated molecular breeding of castor bean in a cost-effective pattern.

Screening populations for copy number variation using genotyping-by-sequencing: a proof of concept using soybean fast neutron mutants

BACKGROUND

The effective use of mutant populations for reverse genetic screens relies on the population-wide characterization of the induced mutations. Genome- and population-wide characterization of the mutations found in fast neutron populations has been hindered, however, by the wide range of mutations generated and the lack of affordable technologies to detect DNA sequence changes. In this study, we therefore aimed to test whether genotyping-by-sequencing (GBS) technology could be used to characterize copy number variation (CNV) induced by fast neutrons in a soybean mutant population.

RESULTS

We called CNVs from GBS data in 79 soybean mutants and assessed the sensitivity and precision of this approach by validating our results against array comparative genomic hybridization (aCGH) data for 19 of these mutants as well as targeted PCR and ddPCR assays for a representative subset of the smallest events detected by GBS. Our GBS pipeline detected 55 of the 96 events found by aCGH, with approximate detection thresholds of 60 kb, 500 kb and 1 Mb for homozygous deletions, hemizygous deletions and duplications, respectively. Among the whole set of 79 mutants, the GBS data revealed 105 homozygous deletions, 32 hemizygous deletions and 19 duplications. This included several extremely large events, exhibiting maximum sizes of ~ 11.2 Mb for a homozygous deletion, ~ 11.6 Mb for a hemizygous deletion, and ~ 50 Mb for a duplication.

CONCLUSIONS

This study provides a proof of concept that GBS can be used as an affordable high-throughput method for assessing CNVs in fast neutron mutants. The modularity of this GBS approach allows combining as many different libraries or sequencing runs as is necessary for reaching the goals of a particular study. This method should enable the low-cost genome-wide characterization of hundreds to thousands of individuals in fast neutron mutant populations or any population with large genomic deletions and duplications.

Construction of Genetic Linkage Maps in Multiparental Populations

Construction of genetic linkage maps has become a routine step for mapping quantitative trait loci (QTL), particularly in animal and plant breeding populations. Many multiparental populations have recently been produced to increase genetic diversity and QTL mapping resolution. However, few software packages are available for map construction in these populations. In this paper, we build a general framework for the construction of genetic linkage maps from genotypic data in diploid populations, including bi- and multiparental populations, cross-pollinated (CP) populations, and breeding pedigrees. The framework is implemented as an automatic pipeline called magicMap, where the maximum multilocus likelihood approach utilizes genotypic information efficiently. We evaluate magicMap by extensive simulations and eight real datasets: one biparental, one CP, four multiparent advanced generation intercross (MAGIC), and two nested association mapping (NAM) populations, the number of markers ranging from a few hundred to tens of thousands. Not only is magicMap the only software capable of accommodating all of these designs, it is more accurate and robust to missing genotypes and genotyping errors than commonly used packages.

Whole-genome re-sequencing reveals the impact of the interaction of copy number variants of the rhg1 and Rhg4 genes on broad-based resistance to soybean cyst nematode

Soybean cyst nematode (SCN) is the most devastating plant-parasitic nematode. Most commercial soybean varieties with SCN resistance are derived from PI88788. Resistance derived from PI88788 is breaking down due to narrow genetic background and SCN population shift. PI88788 requires mainly the rhg1-b locus, while 'Peking' requires rhg1-a and Rhg4 for SCN resistance. In the present study, whole genome re-sequencing of 106 soybean lines was used to define the Rhg haplotypes and investigate their responses to the SCN HG-Types. The analysis showed a comprehensive profile of SNPs and copy number variations (CNV) at these loci. CNV of rhg1 (GmSNAP18) only contributed towards resistance in lines derived from PI88788 and 'Cloud'. At least 5.6 copies of the PI88788-type rhg1 were required to confer SCN resistance, regardless of the Rhg4 (GmSHMT08) haplotype. However, when the GmSNAP18 copies dropped below 5.6, a 'Peking'-type GmSHMT08 haplotype was required to ensure SCN resistance. This points to a novel mechanism of epistasis between GmSNAP18 and GmSHMT08 involving minimum requirements for copy number. The presence of more Rhg4 copies confers resistance to multiple SCN races. Moreover, transcript abundance of the GmSHMT08 in root tissue correlates with more copies of the Rhg4 locus, reinforcing SCN resistance. Finally, haplotype analysis of the GmSHMT08 and GmSNAP18 promoters inferred additional levels of the resistance mechanism. This is the first report revealing the genetic basis of broad-based resistance to SCN and providing new insight into epistasis, haplotype-compatibility, CNV, promoter variation and its impact on broad-based disease resistance in plants.

Genomic Selection for Yield and Seed Composition Traits Within an Applied Soybean Breeding Program

Genomic selection (GS) has become viable for selection of quantitative traits for which marker-assisted selection has often proven less effective. The potential of GS for soybean was characterized using 483 elite breeding lines, genotyped with BARCSoySNP6K iSelect BeadChips. Cross validation was performed using RR-BLUP and predictive abilities (rMP) of 0.81, 0.71, and 0.26 for protein, oil, and yield, were achieved at the largest tested training set size. Minimal differences were observed when comparing different marker densities and there appeared to be inflation in rMP due to population structure. For comparison purposes, two additional methods to predict breeding values for lines of four bi-parental populations within the GS dataset were tested. The first method predicted within each bi-parental population (WP method) and utilized a training set of full-sibs of the validation set. The second method utilized a training set of all remaining breeding lines except for full-sibs of the validation set to predict across populations (AP method). The AP method is more practical as the WP method would likely delay the breeding cycle and leverage smaller training sets. Averaging across populations for protein and oil content, rMP for the AP method (0.55, 0.30) approached rMP for the WP method (0.60, 0.52). Though comparable, rMP for yield was low for both AP and WP methods (0.12, 0.13). Based on increases in rMP as training sets increased and the effectiveness of WP vs. AP method, the AP method could potentially improve with larger training sets and increased relatedness between training and validation sets.

Phenotypic Variation and Genetic Architecture for Photosynthesis and Water Use Efficiency in Soybean (Glycine max L. Merr)

Photosynthesis (A) and intrinsic water use efficiency (WUE) are physiological traits directly influencing biomass production, conversion efficiency, and grain yield. Though the influence of physiological process on yield is widely known, studies assessing improvement strategies are rare due to laborious phenotyping and specialized equipment needs. This is one of the first studies to assess the genetic architecture underlying A and intrinsic WUE, as well as to evaluate the feasibility of implementing genomic prediction. A panel of 383 soybean recombinant inbred lines were evaluated in a multi-environment yield trial that included measurements of A and intrinsic WUE, using an infrared gas analyzer during R4-R5 growth stages. Genetic variability was found to support the possibility of genetic improvement through breeding. High genetic correlation between grain yield (GY) and A (0.80) was observed, suggesting increases in GY can be achieved through the improvement of A. Genome-wide association analysis revealed quantitative trait loci (QTLs) for these physiological traits. Cross-validation studies indicated high predictive ability (>0.65) for the implementation of genomic prediction as a viable strategy to improve physiological efficiency while reducing field phenotyping. This work provides core knowledge to develop new soybean cultivars with enhanced photosynthesis and water use efficiency through conventional breeding and genomic techniques.