Search

ABSTRACT Breeding programs are often constrained by the genetic diversity of the parental lines, even though these lines can be a rare source of unique alleles not found elsewhere. Therefore, identifying these rare alleles is crucial for keeping them in the breeding programs while introducing new genetic resources. The growing amount of whole genome sequenced data has made Genome‐wide Association Study (GWAS) dominant in investigations to find causal genes for all crops, including legumes. However, GWAS often fails to predict more than one causative mutation (CM) in multiple alleles of a single causal gene. Consequently, multiple alleles complicate breeding when not recognized by a single associated marker, which typically identifies only the most frequent CM and discriminates against the others. In this work, we focus on adopting recent applied genomics methods to identify multiple independent alleles and rare alleles in soybean as a model for other legumes. We predicted, identified, and confirmed a new and extremely rare CM for the loss of black pigmentation in the soybean seed coat and hilum color R gene, the Q25fs. The deletion of eight bases leads to a frameshift, a premature stop codon, and a truncated, nonfunctional protein. Our results also suggest a possibly new gene or an allele of the seed coat color inhibitor I gene. Using a soybean model, we demonstrate how applied genomics methods can accelerate pre‐breeding, and additionally, we discuss the potential for adopting these methods for application to other legumes.

Abstract Pod shattering is a major production constraint of soybean [Glycine max (L.)]. The objectives of this study were to (i) estimate heritability for pod shattering resistance, (ii) determine the frequency of the pod shattering resistance allele pdh1 in the International Institute for Tropical Agriculture (IITA) soybean germplasm and Zambian commercial varieties, and (iii) determine the effectiveness of the DNA marker for the pod shattering resistance allele pdh1. A total of 59 genotypes were evaluated for pod shattering in field trials conducted in Malawi and Zambia and genotyped with a marker for pdh1. TGx2002‐8FM and TGx2002‐9FM were the most resistant among genotypes in early and medium maturity classes and can be used for genetic enhancement of pod shattering resistance in these specific maturity classes. Narrow sense heritability estimates for pod shattering ranged from 0.27 to 0.80. Of the 59 genotypes, 57 (96.6%) carried the resistance allele pdh1 while only two genotypes (3.6%) carried the susceptible allele, suggesting near‐fixation of the resistance allele pdh1 in the IITA germplasm. The marker for pdh1 was highly effective in selecting resistant genotypes.

Genome-to-phenome research in agriculture aims to improve crops through in silico predictions. Genome-wide association study (GWAS) is potent in identifying genomic loci that underlie important traits. As a statistical method, increasing the sample quantity, data quality, or diversity of the GWAS dataset positively impacts GWAS power. For more precise breeding, concrete candidate genes with exact functional variants must be discovered. Many post-GWAS methods have been developed to narrow down the associated genomic regions and, ideally, to predict candidate genes and causative mutations (CMs). Historical natural selection and breeding-related artificial selection both act to change the frequencies of different alleles of genes that control phenotypes. With higher diversity and more extensive GWAS datasets, there is an increased chance of multiple alleles with independent CMs in a single causal gene. This can be caused by the presence of samples from geographically isolated regions that arose during natural or artificial selection. This simple fact is a complicating factor in GWAS-driven discoveries. Currently, none of the existing association methods address this issue and need to identify multiple alleles and, more specifically, the actual CMs. Therefore, we developed a tool that computes a score for a combination of variant positions in a single candidate gene and, based on the highest score, identifies the best number and combination of CMs. The tool is publicly available as a Python package on GitHub, and we further created a web-based Multiple Alleles discovery (MADis) tool that supports soybean and is hosted in SoyKB (https://soykb.org/SoybeanMADisTool/). We tested and validated the algorithm and presented the utilization of MADis in a pod pigmentation L1 gene case study with multiple CMs from natural or artificial selection. Finally, we identified a candidate gene for the pod color L2 locus and predicted the existence of multiple alleles that potentially cause loss of pod pigmentation. In this work, we show how a genomic analysis can be employed to explore the natural and artificial selection of multiple alleles and, thus, improve and accelerate crop breeding in agriculture.

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.

Abstract Background The advancement of sequencing technologies today has made a plethora of whole-genome re-sequenced (WGRS) data publicly available. However, research utilizing the WGRS data without further configuration is nearly impossible. To solve this problem, our research group has developed an interactive Allele Catalog Tool to enable researchers to explore the coding region allelic variation present in over 1,000 re-sequenced accessions each for soybean, Arabidopsis, and maize. Results The Allele Catalog Tool was designed originally with soybean genomic data and resources. The Allele Catalog datasets were generated using our variant calling pipeline (SnakyVC) and the Allele Catalog pipeline (AlleleCatalog). The variant calling pipeline is developed to parallelly process raw sequencing reads to generate the Variant Call Format (VCF) files, and the Allele Catalog pipeline takes VCF files to perform imputations, functional effect predictions, and assemble alleles for each gene to generate curated Allele Catalog datasets. Both pipelines were utilized to generate the data panels (VCF files and Allele Catalog files) in which the accessions of the WGRS datasets were collected from various sources, currently representing over 1,000 diverse accessions for soybean, Arabidopsis, and maize individually. The main features of the Allele Catalog Tool include data query, visualization of results, categorical filtering, and download functions. Queries are performed from user input, and results are a tabular format of summary results by categorical description and genotype results of the alleles for each gene. The categorical information is specific to each species; additionally, available detailed meta-information is provided in modal popups. The genotypic information contains the variant positions, reference or alternate genotypes, the functional effect classes, and the amino-acid changes of each accession. Besides that, the results can also be downloaded for other research purposes. Conclusions The Allele Catalog Tool is a web-based tool that currently supports three species: soybean, Arabidopsis, and maize. The Soybean Allele Catalog Tool is hosted on the SoyKB website ( https://soykb.org/SoybeanAlleleCatalogTool/ ), while the Allele Catalog Tool for Arabidopsis and maize is hosted on the KBCommons website ( https://kbcommons.org/system/tools/AlleleCatalogTool/Zmays and https://kbcommons.org/system/tools/AlleleCatalogTool/Athaliana ). Researchers can use this tool to connect variant alleles of genes with meta-information of species.

The rapid growth of sequencing technology and its increasing popularity in biology-related research over the years has made whole genome re-sequencing (WGRS) data become widely available. A large amount of WGRS data can unlock the knowledge gap between genomics and phenomics through gaining an understanding of the genomic variations that can lead to phenotype changes. These genomic variations are usually comprised of allele and structural changes in DNA, and these changes can affect the regulatory mechanisms causing changes in gene expression and altering the phenotypes of organisms. In this research work, we created the GenVarX toolset, that is backed by transcription factor binding sequence data in promoter regions, the copy number variations data, SNPs and Indels data, and phenotypes data which can potentially provide insights about phenotypic differences and solve compelling questions in plant research. Analytics-wise, we have developed strategies to better utilize the WGRS data and mine the data using efficient data processing scripts, libraries, tools, and frameworks to create the interactive and visualization-enhanced GenVarX toolset that encompasses both promoter regions and copy number variation analysis components. The main capabilities of the GenVarX toolset are to provide easy-to-use interfaces for users to perform queries, visualize data, and interact with the data. Based on different input windows on the user interface, users can provide inputs corresponding to each field and submit the information as a query. The data returned on the results page is usually displayed in a tabular fashion. In addition, interactive figures are also included in the toolset to facilitate the visualization of statistical results or tool outputs. Currently, the GenVarX toolset supports soybean, rice, and Arabidopsis. The researchers can access the soybean GenVarX toolset from SoyKB via https://soykb.org/SoybeanGenVarX/, rice GenVarX toolset, and Arabidopsis GenVarX toolset from KBCommons web portal with links https://kbcommons.org/system/tools/GenVarX/Osativa and https://kbcommons.org/system/tools/GenVarX/Athaliana, respectively.

Abstract Background Soybean is an economically important crop which flowers predominantly in response to photoperiod. Several major loci controlling the quantitative trait for reproductive timing have been identified, of which allelic combinations at three of these loci, E1, E2, and E3, are the dominant factors driving time to flower and reproductive period. However, functional genomics studies have identified additional loci which affect reproductive timing, many of which are less understood. A better characterization of these genes will enable fine-tuning of adaptation to various production environments. Two such genes, E1La and E1Lb, have been implicated in flowering by previous studies, but their effects have yet to be assessed under natural photoperiod regimes. Results Natural and induced variants of E1La and E1Lb were identified and introgressed into lines harboring either E1 or its early flowering variant, e1-as. Lines were evaluated for days to flower and maturity in a Maturity Group (MG) III production environment. These results revealed that variation in E1La and E1Lb promoted earlier flowering and maturity, with stronger effects in e1-as background than in an E1 background. The geographic distribution of E1La alleles among wild and cultivated soybean revealed that natural variation in E1La likely contributed to northern expansion of wild soybean, while breeding programs in North America exploited e1-as to develop cultivars adapted to northern latitudes. Conclusion This research identified novel alleles of the E1 paralogues, E1La and E1Lb, which promote flowering and maturity under natural photoperiods. These loci represent sources of genetic variation which have been under-utilized in North American breeding programs to control reproductive timing, and which can be valuable additions to a breeder’s molecular toolbox.

Optimization of plant architecture by modifying stem termination and timing of flowering and maturity of soybean is a promising strategy to improve its adaptability to specific production environments. Therefore, it is important to choose a proper stem termination type and to understand morphological differences between each stem termination type under various environmental conditions. Variations in abruptness of stem termination have been generally classified into three classical genetic types, indeterminate (Dt1), determinate (dt1), and semi-determinate (Dt2). However, an additional stem termination type, termed tall determinate, and its genetic symbol, dt1-t, were introduced about 25 years ago. The tall determinate soybean lines show delayed cessation of apical stem growth and about 50% taller plant heights than the typical determinate soybeans, even though the genetic control of the tall determinate phenotype was found to be allelic to dt1. Despite the potential agronomic merits of the alternative stem termination type, knowledge about the tall determinate soybean remains limited. We clarified the molecular basis of the tall determinate stem termination type and examined potential agronomic merits of the alternative stem type under three different production environments in the US. Sequence analysis of the classical tall determinate soybean lines revealed that the dt1-t allele responsible for tall determinate stem architecture is caused by two of the identified independent missense alleles of dt1, dt1-t1 (R130K), and dt1-t2 (R62S). Also, from the comparison among soybean accessions belonging to each of the genotype categories for stem termination types, soybean accessions with tall determinate alleles were found to have a high discrepancy rate in phenotyping. Newly developed tall determinate late-maturing soybean germplasm lines had taller plant heights and a greater number of nodes with a similar stem diameter and similar pod density at the apical stem compared to typical determinate soybeans having dt1 (R166W) alleles in Southern environments in the US. The phenotype of increased pod-bearing nodes with lodging resistance has the potential to improve yield, especially grown in high yield environments. This study suggests an alternative strategy to remodel the shape of soybean plants, which can possibly lead to yield improvement through the modification of soybean plant architecture.

Adaptation of soybean cultivars to the photoperiod in which they are grown is critical for optimizing plant yield. However, despite its importance, only the major loci conferring variation in flowering time and maturity of US soybean have been isolated. By contrast, over 200 genes contributing to floral induction in the model organism Arabidopsis thaliana have been described. In this work, putative alleles of a library of soybean orthologs of these Arabidopsis flowering genes were tested for their latitudinal distribution among elite US soybean lines developed in the United States. Furthermore, variants comprising the alleles of genes with significant differences in latitudinal distribution were assessed for amino acid conservation across disparate genera to infer their impact on gene function. From these efforts, several candidate genes from various biological pathways were identified that are likely being exploited toward adaptation of US soybean to various maturity groups.

Abstract Background Soybean is native to the temperate zones of East Asia. Poor yields of soybean in West African countries may be partially attributed to inadequate adaptation of soybean to tropical environments. Adaptation will require knowledge of the effects of allelic combinations of major maturity genes (E1, E2, and E3) and stem architecture. The long juvenile trait (J) influences soybean flowering time in short, ~ 12 h days, which characterize tropical latitudes. Soybean plant architecture includes determinate or indeterminate stem phenotypes controlled by the Dt1 gene. Understanding the influence of these genetic components on plant development and adaptation is key to optimize phenology and improve soybean yield potential in tropical environments. Results Soybean lines from five recombinant inbred populations were developed that varied in their combinations of targeted genes. The soybean lines were field tested in multiple environments and characterized for days to flowering (DTF), days to maturity (DTM), and plant height in locations throughout northern Ghana, and allelic combinations were determined for each line for associating genotype with phenotype. The results revealed significant differences based on genotype for DTF and DTM and allowed the comparison of different variant alleles of those genes. The mutant alleles of J and E1 had significant impact on DTF and DTM, and alleles of those genes interacted with each other for DTF but not DTM. The Dt1 gene significantly influenced plant height but not DTF or DTM. Conclusions This research identified major and minor effect alleles of soybean genes that can be combined to control DTF, DTM, and plant height in short day tropical environments in Ghana. These phenotypes contribute to adaptation to a low latitude environment that can be optimized in a soybean breeding program with targeted selection of desired allele combinations. The knowledge of the genetic control of these traits will enhance molecular breeding to produce optimally adapted soybean varieties targeted to tropical environments.

Abstract Background Achieving appropriate maturity in a target environment is essential to maximizing crop yield potential. In soybean [Glycine max (L.) Merr.], the time to maturity is largely dependent on developmental response to dark periods. Once the critical photoperiod is reached, flowering is initiated and reproductive development proceeds. Therefore, soybean adaptation has been attributed to genetic changes and natural or artificial selection to optimize plant development in specific, narrow latitudinal ranges. In North America, these regions have been classified into twelve maturity groups (MG), with lower MG being shorter season than higher MG. Growing soybean lines not adapted to a particular environment typically results in poor growth and significant yield reductions. The objective of this study was to develop a molecular model for soybean maturity based on the alleles underlying the major maturity loci: E1, E2, and E3. Results We determined the allelic variation and diversity of the E maturity genes in a large collection of soybean landraces, North American ancestors, Chinese cultivars, North American cultivars or expired Plant Variety Protection lines, and private-company lines. The E gene status of accessions in the USDA Soybean Germplasm Collection with SoySNP50K Beadchip data was also predicted. We determined the E allelic combinations needed to adapt soybean to different MGs in the United States (US) and discovered a strong signal of selection for E genotypes released in North America, particularly the US and Canada. Conclusions The E gene maturity model proposed will enable plant breeders to more effectively transfer traits into different MGs and increase the overall efficiency of soybean breeding in the US and Canada. The powerful yet simple selection strategy for increasing soybean breeding efficiency can be used alone or to directly enhance genomic prediction/selection schemes. The results also revealed previously unrecognized aspects of artificial selection in soybean imposed by soybean breeders based on geography that highlights the need for plant breeding that is optimized for specific environments.

Soybeans (Glycine max (L.) Merr.) with black seed coats and green cotyledons are rich in anthocyanins and chlorophylls known as functional nutrients, antioxidants and compounds with anticarcinogenic properties. Understanding the genetic diversity of germplasm is important to determine effective strategies for improving the economic traits of these soybeans. We aimed to analyze the genetic diversity of 470 soybean accessions by 6K single nucleotide polymorphic loci to determine genetic architecture of the soybeans with black seed coats and green cotyledons. We found soybeans with black seed coats and green cotyledons showed narrow genetic variability in South Korea. The genotypic frequency of the d1d2 and psbM variants for green cotyledon indicated that soybean collections from Korea were intermingled with soybean accessions from Japan and China. Regarding the chlorophyll content, the nuclear gene variant pair d1d2 produced significantly higher chlorophyll a content than that of chloroplast genome psbM variants. Among the soybean accessions in this study, flower color plays an important role in the anthocyanin composition of seed coats. We provide 36 accessions as a core collection representing 99.5% of the genetic diversity from the total accessions used in this study to show potential as useful breeding materials for cultivars with black seed coats and green cotyledons.

The value of soybean [ (L.) Merr.] is determined in part by functionality of major seed components, extractable oil and high protein meal. Soybean meal is an important protein source for animal feeds, and use of soybean meal by the food industry is increasing. Food allergens have negative impacts for both foods and feeds. The major soybean allergen, Gly m Bd 30K, was identified as the P34 protein, a low abundance but highly conserved seed protein. Recently, two soybean germplasm accessions (PI 567476 and PI 603570A) were identified as having reduced P34 content without other collateral changes in seed protein composition. In order to develop molecular markers to enhance breeding for low P34, our objective was to characterize the P34 gene region in wild-type and low-P34 soybean lines and exploit any sequence differences to allow direct selection for mutant P34 alleles. The results indicated the two low-P34 germplasm accessions contain a four-basepair insertion at the P34 start codon. The mutant allele may inhibit efficient translation initiation of the P34 protein. Inheritance of the mutant P34 alleles completely associated with the low-P34 phenotype. Molecular markers were developed that were based on the mutant allele of the P34 gene.

Plant seeds accumulate phosphorus in the form of -inositol-1,2,3,4,5,6-hexa-phosphate, commonly referred to as phytic acid. Phytic acid is found complexed with cationic mineral species in the form of phytate, which is not well digested or absorbed by monogastric species such as humans, poultry, and swine. As a result, soybean [ (L.) Merr.] has an effective deficiency of phosphorus and other minerals, despite high levels of minerals and phosphorus in the seed. Excreted phytate can also contribute to phosphorus contamination of groundwater and eutrophication of freshwater lakes and streams. In maize ( L. ssp. ), a recessive mutation in a conserved region within the () gene is responsible for the low phytic acid phenotype. We have identified recessive mutations in two soybean homologs of the maize gene in soybean line CX1834, a mutagenized line with a low phytic acid phenotype. In three populations analyzed, we identified complete association between homozygosity for mutant alleles of the two homologs and the low phytic acid phenotype in soybean. Molecular marker assays were designed that can be used to directly select for the mutant alleles that control the phenotype.

In the past decade, RNA silencing has gained significant attention because of its success in genomic scale research and also in the genetic improvement of crop plants. However, little is known about the molecular basis of siRNA processing in association with its target transcript. To reveal this process for improving hpRNA-mediated gene silencing in crop plants, the soybean GmFAD3 gene family was chosen as a test model. We analyzed RNAi mutant soybean lines in which three members of the GmFAD3 gene family were silenced. The silencing levels of FAD3A, FAD3B and FAD3C were correlated with the degrees of sequence homology between the inverted repeat of hpRNA and the GmFAD3 transcripts in the RNAi lines. Strikingly, transgenes in two of the three RNAi lines were heavily methylated, leading to a dramatic reduction of hpRNA-derived siRNAs. Small RNAs corresponding to the loop portion of the hairpin transcript were detected while much lower levels of siRNAs were found outside of the target region. siRNAs generated from the 318-bp inverted repeat were found to be diced much more frequently at stem sequences close to the loop and associated with the inferred cleavage sites on the target transcripts, manifesting "hot spots". The top candidate hpRNA-derived siRNA share certain sequence features with mature miRNA. This is the first comprehensive and detailed study revealing the siRNA-mediated gene silencing mechanism in crop plants using gene family GmFAD3 as a test model.

In this Genomics Era, vast amounts of next-generation sequencing data have become publicly available for multiple genomes across hundreds of species. Analyses of these large-scale datasets can become cumbersome, especially when comparing nucleotide polymorphisms across many samples within a dataset and among different datasets or organisms. To facilitate the exploration of allelic variation and diversity, we have developed and deployed an in-house computer software to categorize and visualize these haplotypes. The SNPViz software enables users to analyze region-specific haplotypes from single nucleotide polymorphism (SNP) datasets for different sequenced genomes. The examination of allelic variation and diversity of important soybean [Glycine max (L.) Merr.] flowering time and maturity genes may provide additional insight into flowering time regulation and enhance researchers' ability to target soybean breeding for particular environments. For this study, we utilized two available soybean genomic datasets for a total of 72 soybean genotypes encompassing cultivars, landraces, and the wild species Glycine soja. The major soybean maturity genes E1, E2, E3, and E4 along with the Dt1 gene for plant growth architecture were analyzed in an effort to determine the number of major haplotypes for each gene, to evaluate the consistency of the haplotypes with characterized variant alleles, and to identify evidence of artificial selection. The results indicated classification of a small number of predominant haplogroups for each gene and important insights into possible allelic diversity for each gene within the context of known causative mutations. The software has both a stand-alone and web-based version and can be used to analyze other genes, examine additional soybean datasets, and view similar genome sequence and SNP datasets from other species.

Seed phytate is a repository of P and minerals in soybean [ (L.) Merr.] seeds that limits P and mineral bioavailability for monogastric animals (e.g., humans, swine [], and poultry [especially chicken, ]) due to insufficient digestive tract phytase activity. We previously identified epistatic recessive mutations affecting two paralogous adenosine triphosphate-binding cassette phytic acid transporter genes (one a nonsense mutation in and the other a missense mutation in ) as the molecular genetic basis in the ethyl methanesulfonate (EMS)-induced mutant low phytate soybean line M153. An additional mutant low phytate line, M766, contained one single nucleotide polymorphism within the ninth intron of the locus as well as a nonsense mutation in . The objectives of this research were to clarify the genetics underlying the low phytate phenotype in line M766 and to determine P partitioning in new combinations of mutant alleles from M766 and M153. Inheritance of nonsense alleles affecting both () genes (one from M153 and one from M766) led to the production of viable seeds that contained transgressive reductions in total seed phytate and significantly higher levels of inorganic phosphate than has been reported for nontransgenic soybean material and will allow efficient molecular selection of soybeans with even greater reductions of phytate for improved quality soybean meal.

Abstract  RNA interference (RNAi) has been recently employed as an effective experimental tool for both basic and applied biological studies in various organisms including plants. RNAi deploys small RNAs, mainly small interfering RNAs (siRNAs), to mediate the degradation of mRNA for regulating gene expression in plants. Here we report an efficient siRNA-mediated gene silencing of the omega-3 fatty acid desaturase (FAD3) gene family in a complex genome, the soybean (Glycine max). The FAD3 enzyme is responsible for the synthesis of α-linolenic acids (18:3) in the polyunsaturated fatty acid pathway. It is this fatty acid that contributes mostly to the instability of soybean and other seed oils. Therefore, a significant reduction of this fatty acid will increase the stability of the seed oil, enhancing the seed agronomical value. A conserved nucleotide sequence, 318-nt in length, common to the three gene family members was used as an inverted repeat for RNA interference. The RNAi expression cassette was driven by a seed-specific promoter. We show that the transgene-produced siRNA caused silencing of FAD3 that was comparable to the fad3 mutant phenotype and, furthermore, that such a silencing is stably inherited in engineered soybean lines. Since the pool size of the α-linolenic acids is small relative to the other polyunsaturated fatty acids in soybean, the significant reduction of this fatty acid suggests a role and great potential for the siRNA strategy in silencing gene families in a complex genome. [ABSTRACT FROM AUTHOR]