Chromosome-level reference genome and resequencing of 322 accessions reveal evolution, genomic imprint and key agronomic traits in adzuki bean.

Adzuki bean (Vigna angularis) is an important legume crop cultivated in over 30 countries worldwide. We developed a high-quality chromosome-level reference genome of adzuki bean cultivar Jingnong6 by combining PacBio Sequel long-read sequencing with short-read and Hi-C technologies. The assembled genome covers 97.8% of the adzuki bean genome with a contig N50 of approximately 16 Mb and a total of 32 738 protein-coding genes. We also generated a comprehensive genome variation map of adzuki bean by whole-genome resequencing (WGRS) of 322 diverse adzuki beans accessions including both wild and cultivated. Furthermore, we have conducted comparative genomics and a genome-wide association study (GWAS) on key agricultural traits to investigate the evolution and domestication. GWAS identified several candidate genes, including VaCycA3;1, VaHB15, VaANR1 and VaBm, that exhibited significant associations with domestication traits. Furthermore, we conducted functional analyses on the roles of VaANR1 and VaBm in regulating seed coat colour. We provided evidence for the highest genetic diversity of wild adzuki (Vigna angularis var. nipponensis) in China with the presence of the most original wild adzuki bean, and the occurrence of domestication process facilitating transition from wild to cultigen. The present study elucidates the genetic basis of adzuki bean domestication traits and provides crucial genomic resources to support future breeding efforts in adzuki bean.

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.

Identification of Quantitative Trait Loci Controlling Root Morphological Traits in an Interspecific Soybean Population Using 2D Imagery Data.

Roots are the hidden and most important part of plants. They serve as stabilizers and channels for uptaking water and nutrients and play a crucial role in the growth and development of plants. Here, two-dimensional image data were used to identify quantitative trait loci (QTL) controlling root traits in an interspecific mapping population derived from a cross between wild soybean 'PI366121' and cultivar 'Williams 82'. A total of 2830 single-nucleotide polymorphisms were used for genotyping, constructing genetic linkage maps, and analyzing QTLs. Forty-two QTLs were identified on twelve chromosomes, twelve of which were identified as major QTLs, with a phenotypic variation range of 36.12% to 39.11% and a logarithm of odds value range of 12.01 to 17.35. Two significant QTL regions for the average diameter, root volume, and link average diameter root traits were detected on chromosomes 3 and 13, and both wild and cultivated soybeans contributed positive alleles. Six candidate genes, Glyma.03G027500 (transketolase/glycoaldehyde transferase), Glyma.03G014500 (dehydrogenases), Glyma.13G341500 (leucine-rich repeat receptor-like protein kinase), Glyma.13G341400 (AGC kinase family protein), Glyma.13G331900 (60S ribosomal protein), and Glyma.13G333100 (aquaporin transporter) showed higher expression in root tissues based on publicly available transcriptome data. These results will help breeders improve soybean genetic components and enhance soybean root morphological traits using desirable alleles from wild soybeans.

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-wide association study reveals novel loci and a candidate gene for resistance to frogeye leaf spot (Cercospora sojina) in soybean.

Frogeye leaf spot, caused by the fungus Cercospora sojina, is a threat to soybeans in the southeastern and midwestern United States that can be controlled by crop genetic resistance. Limited genetic resistance to the disease has been reported, and only three sources of resistance have been used in modern soybean breeding. To discover novel sources and identify the genomic locations of resistance that could be used in soybean breeding, a GWAS was conducted using a panel of 329 soybean accessions selected to maximize genetic diversity. Accessions were phenotyped using a 1-5 visual rating and by using image analysis to count lesion number and measure the percent of leaf area diseased. Eight novel loci on eight chromosomes were identified for three traits utilizing the FarmCPU or BLINK models, of which a locus on chromosome 11 was highly significant across all model-trait combinations. KASP markers were designed using the SoySNP50K Beadchip and variant information from 65 of the accessions that have been sequenced to target SNPs in the gene model Glyma.11g230400, a LEUCINE-RICH REPEAT RECEPTOR-LIKE PROTEIN KINASE. The association of a KASP marker, GSM990, designed to detect a missense mutation in the gene was the most significant with all three traits in a genome-wide association, and the marker may be useful to select for resistance to frogeye leaf spot in soybean breeding.

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.

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.

Genome-Wide Detection of Quantitative Trait Loci and Prediction of Candidate Genes for Seed Sugar Composition in Early Mature Soybean.

Seed sugar composition, mainly including fructose, glucose, sucrose, raffinose, and stachyose, is an important indicator of soybean [Glycine max (L.) Merr.] seed quality. However, research on soybean sugar composition is limited. To better understand the genetic architecture underlying the sugar composition in soybean seeds, we conducted a genome-wide association study (GWAS) using a population of 323 soybean germplasm accessions which were grown and evaluated under three different environments. A total of 31,245 single-nucleotide polymorphisms (SNPs) with minor allele frequencies (MAFs) ≥ 5% and missing data ≤ 10% were selected and used in the GWAS. The analysis identified 72 quantitative trait loci (QTLs) associated with individual sugars and 14 with total sugar. Ten candidate genes within the 100 Kb flanking regions of the lead SNPs across six chromosomes were significantly associated with sugar contents. According to GO and KEGG classification, eight genes were involved in the sugar metabolism in soybean and showed similar functions in Arabidopsis. The other two, located in known QTL regions associated with sugar composition, may play a role in sugar metabolism in soybean. This study advances our understanding of the genetic basis of soybean sugar composition and facilitates the identification of genes controlling this trait. The identified candidate genes will help improve seed sugar composition in soybean.

Development of a versatile resource for post-genomic research through consolidating and characterizing 1500 diverse wild and cultivated soybean genomes.

BACKGROUND: With advances in next-generation sequencing technologies, an unprecedented amount of soybean accessions has been sequenced by many individual studies and made available as raw sequencing reads for post-genomic research. RESULTS: To develop a consolidated and user-friendly genomic resource for post-genomic research, we consolidated the raw resequencing data of 1465 soybean genomes available in the public and 91 highly diverse wild soybean genomes newly sequenced. These altogether provided a collection of 1556 sequenced genomes of 1501 diverse accessions (1.5 K). The collection comprises of wild, landraces and elite cultivars of soybean that were grown in East Asia or major soybean cultivating areas around the world. Our extensive sequence analysis discovered 32 million single nucleotide polymorphisms (32mSNPs) and revealed a SNP density of 30 SNPs/kb and 12 non-synonymous SNPs/gene reflecting a high structural and functional genomic diversity of the new collection. Each SNP was annotated with 30 categories of structural and/or functional information. We further identified paired accessions between the 1.5 K and 20,087 (20 K) accessions in US collection as genomic "equivalent" accessions sharing the highest genomic identity for minimizing the barriers in soybean germplasm exchange between countries. We also exemplified the utility of 32mSNPs in enhancing post-genomics research through in-silico genotyping, high-resolution GWAS, discovering and/or characterizing genes and alleles/mutations, identifying germplasms containing beneficial alleles that are potentially experiencing artificial selection. CONCLUSION: The comprehensive analysis of publicly available large-scale genome sequencing data of diverse cultivated accessions and the newly in-house sequenced wild accessions greatly increased the soybean genome-wide variation resolution. This could facilitate a variety of genetic and molecular-level analyses in soybean. The 32mSNPs and 1.5 K accessions with their comprehensive annotation have been made available at the SoyBase and Ag Data Commons. The dataset could further serve as a versatile and expandable core resource for exploring the exponentially increasing genome sequencing data for a variety of post-genomic research.

Impact of multiple selective breeding programs on genetic diversity in soybean germplasm.

KEY MESSAGE: Independent soybean breeding programs shape genetic diversity from unimproved germplasm to modern cultivars in similar ways, but distinct breeding populations retain unique genetic variation, preserving additional diversity. From the domestication of wild soybean (Glycine soja Sieb. & Zucc.), over 3,000 years ago, to the modern soybean (Glycine max L. Merr) cultivars that provide much of the world's oil and protein, soybean populations have undergone fundamental changes. We evaluated the molecular impact of breeding and selection using 391 soybean accessions including US cultivars and their progenitors from the USDA Soybean Germplasm Collection (CGP), plus two new populations specifically developed to increase genetic diversity and high yield in two alternative gene pools: one derived from exotic G. max germplasm (AGP) and one derived from G. soja (SGP). Reduction in nucleotide genetic diversity (π) was observed with selection within gene pools, but artificial selection in the AGP maintained more diversity than in the CGP. The highest FST levels were seen between ancestral and elite lines in all gene pools, but specific nucleotide-level patterns varied between gene pools. Population structure analyses support that independent selection resulted in high-yielding elite lines with similar allelic compositions in the AGP and CGP. SGP, however, produced elite progeny that were well differentiated from, but lower yielding than, CGP elites. Both the AGP and SGP retained a significant number of private alleles that are absent in CGP. We conclude that the genomic diversity shaped by multiple selective breeding programs can result in gene pools of highly productive elite lines with similar allelic compositions in a genome-wide perspective. Breeding programs with different ancestral lines, however, can retain private alleles representing unique genetic diversity.

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.

Epistatic interaction between Rhg1-a and Rhg2 in PI 90763 confers resistance to virulent soybean cyst nematode populations.

KEY MESSAGE: An epistatic interaction between SCN resistance loci rhg1-a and rhg2 in PI 90763 imparts resistance against virulent SCN populations which can be employed to diversify SCN resistance in soybean cultivars. With more than 95% of the $46.1B soybean market dominated by a single type of genetic resistance, breeding for soybean cyst nematode (SCN)-resistant soybean that can effectively combat the widespread increase in virulent SCN populations presents a significant challenge. Rhg genes (for Resistance to Heterodera glycines) play a key role in resistance to SCN; however, their deployment beyond the use of the rhg1-b allele has been limited. In this study, quantitative trait loci (QTL) were mapped using PI 90763 through two biparental F3:4 recombinant inbred line (RIL) populations segregating for rhg1-a and rhg1-b alleles against a SCN HG type 1.2.5.7 (Race 2) population. QTL located on chromosome 18 (rhg1-a) and chromosome 11 (rhg2) were determined to confer SCN resistance in PI 90763. The rhg2 gene was fine-mapped to a 169-Kbp region pinpointing GmSNAP11 as the strongest candidate gene. We demonstrated a unique epistatic interaction between rhg1-a and rhg2 loci that not only confers resistance to multiple virulent SCN populations. Further, we showed that pyramiding rhg2 with the conventional mode of resistance, rhg1-b, is ineffective against these virulent SCN populations. This highlights the importance of pyramiding rhg1-a and rhg2 to maximize the impact of gene pyramiding strategies toward management of SCN populations virulent on rhg1-b sources of resistance. Our results lay the foundation for the next generation of soybean resistance breeding to combat the number one pathogen of soybean.

Genetic Insight into Disease Resistance Gene Clusters by Using Sequencing-Based Fine Mapping in Sunflower (Helianthus annuus L.).

Rust and downy mildew (DM) are two important sunflower diseases that lead to significant yield losses globally. The use of resistant hybrids to control rust and DM in sunflower has a long history. The rust resistance genes, R13a and R16, were previously mapped to a 3.4 Mb region at the lower end of sunflower chromosome 13, while the DM resistance gene, Pl33, was previously mapped to a 4.2 Mb region located at the upper end of chromosome 4. High-resolution fine mapping was conducted using whole genome sequencing of HA-R6 (R13a) and TX16R (R16 and Pl33) and large segregated populations. R13a and R16 were fine mapped to a 0.48 cM region in chromosome 13 corresponding to a 790 kb physical interval on the XRQr1.0 genome assembly. Four disease defense-related genes with nucleotide-binding leucine-rich repeat (NLR) motifs were found in this region from XRQr1.0 gene annotation as candidate genes for R13a and R16. Pl33 was fine mapped to a 0.04 cM region in chromosome 4 corresponding to a 63 kb physical interval. One NLR gene, HanXRQChr04g0095641, was predicted as the candidate gene for Pl33. The diagnostic SNP markers developed for each gene in the current study will facilitate marker-assisted selections of resistance genes in sunflower breeding programs.

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.

Comparative analysis of mitochondrial genomes of soybean cytoplasmic male-sterile lines and their maintainer lines.

In soybean, only one mitochondrial genome of cultispecies has been completely obtained. To explore the effect of mitochondrial genome on soybean cytoplasmic male sterility (CMS), two CMS lines and three maintainer lines were used for sequencing. Comparative analysis showed that mitochondrial genome of the CMS line was more compact than that of its maintainer line, but genes were highly conserved. Conserved and unique sequence coexisted in the genomes. Mitochondrial genomes contained different sequence lengths and copy numbers of repeats between CMS line and maintainer line. Large and short repeats mediated intramolecular and intermolecular recombination in mitochondria. Unique sequences and genes were also involved in recombination process and constituted a complex network. orf178 and orf261 were identified as CMS-associated candidate genes. They had sequence characteristics of reported CMS genes in other crops and could be transcribed in CMS lines but not in maintainer lines. This report reveals mitochondrial genome of soybean CMS lines and compares complete mitochondrial sequence between CMS lines and their maintainer lines. The information will be helpful in further understanding the characteristics of soybean mitochondrial genome and the mechanism underlying CMS.

Genome-wide association mapping reveals new loci associated with light-colored seed coat at harvest and slow darkening in carioca beans.

BACKGROUND: Common bean (Phaseolus vulgaris L.) is a legume whose grain can be stored for months, a common practice among Brazilian growers. Over time, seed coats become darker and harder to cook, traits that are undesirable to consumers, who associate darker-colored beans with greater age. Like commercial pinto and cranberry bean varieties, carioca beans that have darker seeds at harvest time and after storage are subject to decreased market values. RESULTS: The goal of our study was to identify the genetic control associated with lightness of seed coat color at harvest (HL) and with tolerance to post-harvest seed coat darkening (PHD) by a genome-wide association study. For that purpose, a carioca diversity panel previously validated for association mapping studies was used with 138 genotypes and 1,516 high-quality SNPs. The panel was evaluated in two environments using a colorimeter and the CIELAB scale. Shelf storage for 30 days had the most expressive results and the L* (luminosity) parameter led to the greatest discrimination of genotypes. Three QTL were identified for HL, two on chromosome Pv04 and one on Pv10. Regarding PHD, results showed that genetic control differs for L* after 30 days and for the ΔL* (final L*-initial L*); only ΔL* was able to properly express the PHD trait. Four phenotypic classes were proposed, and five QTL were identified through six significant SNPs. CONCLUSIONS: Lightness of seed coat color at harvest showed an oligogenic inheritance corroborated by moderate broad-sense heritability and high genotypic correlation among the experiments. Only three QTL were significant for this trait - two were mapped on Pv04 and one on Pv10. Considering the ΔL, six QTL were mapped on four different chromosomes for PHD. The same HL QTL at the beginning of Pv10 was also associated with ΔL* and could be used as a tool in marker-assisted selection. Several candidate genes were identified and may be useful to accelerate the genetic breeding process.

Identification and characterization of novel QTL conferring internal detoxification of aluminium in soybean.

Aluminium (Al) toxicity inhibits soybean root growth, leading to insufficient water and nutrient uptake. Two soybean lines ('Magellan' and PI 567731) were identified differing in Al tolerance, as determined by primary root length ratio, total root length ratio, and root tip number ratio under Al stress. Serious root necrosis was observed in PI 567731, but not in Magellan under Al stress. An F8 recombinant inbred line population derived from a cross between Magellan and PI 567731 was used to map the quantitative trait loci (QTL) for Al tolerance. Three QTL on chromosomes 3, 13, and 20, with tolerant alleles from Magellan, were identified. qAl_Gm13 and qAl_Gm20 explained large phenotypic variations (13-27%) and helped maintain root elongation and initiation under Al stress. In addition, qAl_Gm13 and qAl_Gm20 were confirmed in near-isogenic backgrounds and were identified to epistatically regulate Al tolerance via internal detoxification instead of Al3+ exclusion. Phylogenetic and pedigree analysis identified the tolerant alleles of both loci derived from the US ancestral line, A.K.[FC30761], originally from China. Our results provide novel genetic resources for breeding Al-tolerant soybean and suggest that internal detoxification contributes to soybean tolerance to excessive soil Al.

Different loci control resistance to different isolates of the same race of Colletotrichum lindemuthianum in common bean.

KEY MESSAGE: Linkage and genome-wide association analyses using high-throughput SNP genotyping revealed different loci controlling resistance to different isolates of race 65 of Colletotrichum lindemuthianum in common bean. Development of varieties with durable resistance to anthracnose is a major challenge in common bean breeding programs because of the extensive virulence diversity of Colletotrichum lindemuthianum fungus. We used linkage and genome-wide association analyses to tap the genomic regions associated with resistance to different isolates of race 65. Linkage mapping was done using an F2 population derived from the cross between the Mesoamerican common beans BRS Estilo x Ouro Vermelho, inoculated with two different isolates of race 65. Association genetics relied on a diversity common bean panel containing 189 common bean accessions inoculated with five different isolates of race 65 as an attempt to validate the linkage analysis findings and, eventually, identify other genomic regions associated with resistance to race 65. The F2 population and diversity panel were genotyped with the BARCBean6K_3 Illumina BeadChip containing 5398 SNP markers. Both linkage and genome-wide association analyses identified different loci controlling resistance to different isolates of race 65 on linkage group Pv04. Genome-wide association analysis also detected loci on Pv05, Pv10 and Pv11 associated with resistance to race 65. These findings indicate that resistance to race 65 can be overcome by the virulence diversity among different isolates of the same race and could lead to the loss of resistance after cultivar release. We identified 25 resistant common bean cultivars to all five isolates of race 65 in the diversity panel. The accessions should be useful to develop cultivars combining different resistance genes that favor durable resistance to anthracnose in common bean.

Mining QTLs for elevated protein and other major seed composition traits from diverse soybean germplasm.

Soybean is the world's largest source of protein for animal feed and the second largest source of vegetable oil. Improving the seed protein of soybean without negatively affecting yield and oil content is an important goal for soybean breeders. A population consisting of 132 recombinant inbred lines (RILs) was developed by crossing an elite breeding line, G00-3213 with a plant introduction, PI 594458A, with elevated protein content. In 2016 and 2017, each of the RILs was grown as a single row in Watkinsville, GA, while in 2018, the population was grown at two locations. The seed composition of RILs was analyzed with near-infrared (NIR) spectroscopy. The RIL population was genotyped using the SoySNP6k BeadChip for quantitative trait locus (QTL) mapping. Significant genotype × environment interaction was observed. QTL analyses in and across four environments identified 16, 10, 10, 16, and 5 QTLs for protein, oil, sucrose, and normalized cysteine and methionine contents, respectively. QTLs for protein content identified on chromosomes (Chrs) 3, 6, 13, and 20 were detected in multiple environments. Eight genomic regions on Chrs 3, 6, 8, 10, 13, 17, and 20 were detected that influenced two to four traits, indicating that pleiotropic or linkage effects of these loci may influence multiple seed composition traits. The results of this research provide additional genomic resources for genetic improvement of seed composition and help breeders to better understand the environmental impacts on these QTLs. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01242-z.

Genomic prediction using training population design in interspecific soybean populations.

Agronomically important traits generally have complex genetic architecture, where many genes have a small and largely additive effect. Genomic prediction has been demonstrated to increase genetic gain and efficiency in plant breeding programs beyond marker-assisted selection and phenotypic selection. The objective of this study was to evaluate the impact of allelic origin, marker density, training population size, and cross-validation schemes on the accuracy of genomic prediction models in an interspecific soybean nested association mapping (NAM) panel. Three cross-validation schemes were used: (a) Within-Family (WF): training population and predictions are made exclusively within each family; (b) Across All families (AF): all the individuals from the three families were randomly assigned to either the training or validation set; (c) Leave one Family out (LFO): each family is predicted using a training set that contains the other two families. Predictive abilities increased with training population size up to 350 individuals, but no significant gains were noted beyond 250 individuals in the training population. The number of markers had a limited impact on the observed predictive ability across traits; increasing markers used in the model above 1000 revealed no significant increases in prediction accuracy. Predictive abilities for AF were not significantly different from the WF method, and predictive abilities across populations for the WF method had a range of 0.58 to 0.70 for maturity, protein, meal, and oil. Our results also showed encouraging prediction accuracies for grain yield (0.58-0.69) using the WF method. Partitioning genomic prediction between G. max and G. soja alleles revealed useful information to select material with a larger allele contribution from both parents and could accelerate allele introgression from exotic germplasm into the elite soybean gene pool. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01203-6.