Cicer super-pangenome provides insights into species evolution and agronomic trait loci for crop improvement in chickpea.

Chickpea (Cicer arietinum L.)-an important legume crop cultivated in arid and semiarid regions-has limited genetic diversity. Efforts are being undertaken to broaden its diversity by utilizing its wild relatives, which remain largely unexplored. Here, we present the Cicer super-pangenome based on the de novo genome assemblies of eight annual Cicer wild species. We identified 24,827 gene families, including 14,748 core, 2,958 softcore, 6,212 dispensable and 909 species-specific gene families. The dispensable genome was enriched for genes related to key agronomic traits. Structural variations between cultivated and wild genomes were used to construct a graph-based genome, revealing variations in genes affecting traits such as flowering time, vernalization and disease resistance. These variations will facilitate the transfer of valuable traits from wild Cicer species into elite chickpea varieties through marker-assisted selection or gene-editing. This study offers valuable insights into the genetic diversity and potential avenues for crop improvement in chickpea.

The era of panomics-driven gene discovery in plants.

Panomics is an approach to integrate multiple 'omics' datasets, generated using different individuals or natural variations. Considering their diverse phenotypic spectrum, the phenome is inherently associated with panomics-based science, which is further combined with genomics, transcriptomics, metabolomics, and other omics techniques, either independently or collectively. Panomics has been accelerated through recent technological advancements in the field of genomics that enable the detection of population-wide structural variations (SVs) and hence offer unprecedented insights into the genetic variations contributing to important agronomic traits. The present review provides the recent trends of panomics-driven gene discovery toward various traits related to plant development, stress tolerance, accumulation of specialized metabolites, and domestication/dedomestication. In addition, the success stories are highlighted in the broader context of enhancing crop productivity.

Quantitative trait loci and genomic prediction for grain sugar and mineral concentrations of cowpea [Vigna unguiculata (L.) Walp.].

Development of high yielding cowpea varieties coupled with good taste and rich in essential minerals can promote consumption and thus nutrition and profitability. The sweet taste of cowpea grain is determined by its sugar content, which comprises mainly sucrose and galacto-oligosaccharides (GOS) including raffinose and stachyose. However, GOS are indigestible and their fermentation in the colon can produce excess intestinal gas, causing undesirable bloating and flatulence. In this study, we aimed to examine variation in grain sugar and mineral concentrations, then map quantitative trait loci (QTLs) and estimate genomic-prediction (GP) accuracies for possible application in breeding. Grain samples were collected from a multi-parent advanced generation intercross (MAGIC) population grown in California during 2016-2017. Grain sugars were assayed using high-performance liquid chromatography. Grain minerals were determined by inductively coupled plasma-optical emission spectrometry and combustion. Considerable variation was observed for sucrose (0.6-6.9%) and stachyose (2.3-8.4%). Major QTLs for sucrose (QSuc.vu-1.1), stachyose (QSta.vu-7.1), copper (QCu.vu-1.1) and manganese (QMn.vu-5.1) were identified. Allelic effects of major sugar QTLs were validated using the MAGIC grain samples grown in West Africa in 2017. GP accuracies for minerals were moderate (0.4-0.58). These findings help guide future breeding efforts to develop mineral-rich cowpea varieties with desirable sugar content.

A novel natural variation in the promoter of GmCHX1 regulates conditional gene expression to improve salt tolerance in soybean.

Identification and characterization of soybean germplasm and gene(s)/allele(s) for salt tolerance is an effective way to develop improved varieties for saline soils. Previous studies identified GmCHX1 (Glyma03g32900) as a major salt tolerance gene in soybean, and two main functional variations were found in the promoter region (148/150 bp insertion) and the third exon with a retrotransposon insertion (3.78 kb). In the current study, we identified four salt-tolerant soybean lines, including PI 483460B (Glycine soja), carrying the previously identified salt-sensitive variations at GmCHX1, suggesting new gene(s) or new functional allele(s) of GmCHX1 in these soybean lines. Subsequently, we conducted quantitative trait locus (QTL) mapping in a recombinant-inbred line population (Williams 82 (salt-sensitive) × PI 483460B) to identify the new salt tolerance loci/alleles. A new locus, qSalt_Gm18, was mapped on chromosome 18 associated with leaf scorch score. Another major QTL, qSalt_Gm03, was identified to be associated with chlorophyll content ratio and leaf scorch score in the same chromosomal region of GmCHX1 on chromosome 3. Novel variations in a STRE (stress response element) cis-element in the promoter region of GmCHX1 were found to regulate the salt-inducible expression of the gene in these four newly identified salt-tolerant lines including PI 483460B. This new allele of GmCHX1 with salt-inducible expression pattern provides an energy cost efficient (conditional gene expression) strategy to protect soybean yield in saline soils without yield penalty under non-stress conditions. Our results suggest that there might be no other major salt tolerance locus similar to GmCHX1 in soybean germplasm, and further improvement of salt tolerance in soybean may rely on gene-editing techniques instead of looking for natural variations.

Soybean genetics, genomics, and breeding for improving nutritional value and reducing antinutritional traits in food and feed.

Soybean [Glycine max (L.) Merr.] is a globally important crop due to its valuable seed composition, versatile feed, food, and industrial end-uses, and consistent genetic gain. Successful genetic gain in soybean has led to widespread adaptation and increased value for producers, processors, and consumers. Specific focus on the nutritional quality of soybean seed composition for food and feed has further elucidated genetic knowledge and bolstered breeding progress. Seed components are historical and current targets for soybean breeders seeking to improve nutritional quality of soybean. This article reviews genetic and genomic foundations for improvement of nutritionally important traits, such as protein and amino acids, oil and fatty acids, carbohydrates, and specific food-grade considerations; discusses the application of advanced breeding technology such as CRISPR/Cas9 in creating seed composition variations; and provides future directions and breeding recommendations regarding soybean seed composition traits.

Novel genetic resources associated with sucrose and stachyose content through genome-wide association study in soybean (Glycine max (L.) Merr.).

The nutritional value of soybean [Glycine max (L.) Merr.] for animals is influenced by soluble carbohydrates, such as sucrose and stachyose. Although sucrose is nutritionally desirable, stachyose is an antinutrient causing diarrhea and flatulence in non-ruminant animals. We conducted a genome-wide association study of 220 soybean accessions using 21,317 single nucleotide polymorphisms (SNPs) from the SoySNP50K iSelect Beadchip data to identify significant SNPs associated with sucrose and stachyose content. Seven significant SNPs were identified for sucrose content across chromosomes (Chrs.) 2, 8, 12, 17, and 20, while thirteen significant SNPs were identified for stachyose content across Chrs. 2, 5, 8, 9, 10, 13, 14, and 15. Among those significant SNPs, three sucrose-related SNPs on Chrs. 8 and 17 were novel, while twelve stachyose-related SNPs on Chrs. 2, 5, 8, 9, 10, 13, 14, and 15 were novel. Based on Phytozome, STRING, and GO annotation, 17 and 24 candidate genes for sucrose and stachyose content, respectively, were highly associated with the carbohydrate metabolic pathway. Among these, the publicly available RNA-seq Atlas database highlighted four candidate genes associated with sucrose (Glyma.08g361200 and Glyma.17g258100) and stachyose (Glyma.05g025300 and Glyma.13g077900) content, which had higher gene expression levels in developing seed and multiple parts of the soybean plant. The results of this study will extend knowledge of the molecular mechanism and genetic basis underlying sucrose and stachyose content in soybean seed. Furthermore, the novel candidate genes and SNPs can be valuable genetic resources that soybean breeders may utilize to modify carbohydrate profiles for animal and human usage.

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

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

Genetic Mapping for QTL Associated with Seed Nickel and Molybdenum Accumulation in the Soybean 'Forrest' by 'Williams 82' RIL Population.

Understanding the genetic basis of seed Ni and Mo is essential. Since soybean is a major crop in the world and a major source for nutrients, including Ni and Mo, the objective of the current research was to map genetic regions (quantitative trait loci, QTL) linked to Ni and Mo concentrations in soybean seed. A recombinant inbred line (RIL) population was derived from a cross between 'Forrest' and 'Williams 82' (F × W82). A total of 306 lines was used for genotyping using 5405 single nucleotides polymorphism (SNP) markers using Infinium SNP6K BeadChips. A two-year experiment was conducted and included the parents and the RIL population. One experiment was conducted in 2018 in North Carolina (NC), and the second experiment was conducted in Illinois in 2020 (IL). Logarithm of the odds (LOD) of ≥2.5 was set as a threshold to report identified QTL using the composite interval mapping (CIM) method. A wide range of Ni and Mo concentrations among RILs was observed. A total of four QTL (qNi-01, qNi-02, and qNi-03 on Chr 2, 8, and 9, respectively, in 2018, and qNi-01 on Chr 20 in 2020) was identified for seed Ni. All these QTL were significantly (LOD threshold > 2.5) associated with seed Ni, with LOD scores ranging between 2.71-3.44, and with phenotypic variance ranging from 4.48-6.97%. A total of three QTL for Mo (qMo-01, qMo-02, and qMo-03 on Chr 1, 3, 17, respectively) was identified in 2018, and four QTL (qMo-01, qMo-02, qMo-03, and qMo-04, on Chr 5, 11, 14, and 16, respectively) were identified in 2020. Some of the current QTL had high LOD and significantly contributed to the phenotypic variance for the trait. For example, in 2018, Mo QTL qMo-01 on Chr 1 had LOD of 7.8, explaining a phenotypic variance of 41.17%, and qMo-03 on Chr 17 had LOD of 5.33, with phenotypic variance explained of 41.49%. In addition, one Mo QTL (qMo-03 on Chr 14) had LOD of 9.77, explaining 51.57% of phenotypic variance related to the trait, and another Mo QTL (qMo-04 on Chr 16) had LOD of 7.62 and explained 49.95% of phenotypic variance. None of the QTL identified here were identified twice across locations/years. Based on a search of the available literature and of SoyBase, the four QTL for Ni, identified on Chr 2, 8, 9, and 20, and the five QTL associated with Mo, identified on Chr 1, 17, 11, 14, and 16, are novel and not previously reported. This research contributes new insights into the genetic mapping of Ni and Mo, and provides valuable QTL and molecular markers that can potentially assist in selecting Ni and Mo levels in soybean seeds.

The Late Embryogenesis Abundant Proteins in Soybean: Identification, Expression Analysis, and the Roles of GmLEA4_19 in Drought Stress.

Late embryogenesis abundant (LEA) proteins play important roles in regulating plant growth and responses to various abiotic stresses. In this research, a genome-wide survey was conducted to recognize the LEA genes in Glycine max. A total of 74 GmLEA was identified and classified into nine subfamilies based on their conserved domains and the phylogenetic analysis. Subcellular localization, the duplication of genes, gene structure, the conserved motif, and the prediction of cis-regulatory elements and tissue expression pattern were then conducted to characterize GmLEAs. The expression profile analysis indicated that the expression of several GmLEAs was a response to drought and salt stress. The co-expression-based gene network analysis suggested that soybean LEA proteins may exert regulatory effects through the metabolic pathways. We further explored GnLEA4_19 function in Arabidopsis and the results suggests that overexpressed GmLEA4_19 in Arabidopsis increased plant height under mild or serious drought stress. Moreover, the overexpressed GmLEA4_19 soybean also showed a drought tolerance phenotype. These results indicated that GmLEA4_19 plays an important role in the tolerance to drought and will contribute to the development of the soybean transgenic with enhanced drought tolerance and better yield. Taken together, this study provided insight for better understanding the biological roles of LEA genes in soybean.

Quantitative Trait Loci and Candidate Genes That Control Seed Sugars Contents in the Soybean 'Forrest' by 'Williams 82' Recombinant Inbred Line Population.

Soybean seed sugars are among the most abundant beneficial compounds for human and animal consumption in soybean seeds. Higher seed sugars such as sucrose are desirable as they contribute to taste and flavor in soy-based food. Therefore, the objectives of this study were to use the 'Forrest' by 'Williams 82' (F × W82) recombinant inbred line (RIL) soybean population (n = 309) to identify quantitative trait loci (QTLs) and candidate genes that control seed sugar (sucrose, stachyose, and raffinose) contents in two environments (North Carolina and Illinois) over two years (2018 and 2020). A total of 26 QTLs that control seed sugar contents were identified and mapped on 16 soybean chromosomes (chrs.). Interestingly, five QTL regions were identified in both locations, Illinois and North Carolina, in this study on chrs. 2, 5, 13, 17, and 20. Amongst 57 candidate genes identified in this study, 16 were located within 10 Megabase (MB) of the identified QTLs. Amongst them, a cluster of four genes involved in the sugars' pathway was collocated within 6 MB of two QTLs that were detected in this study on chr. 17. Further functional validation of the identified genes could be beneficial in breeding programs to produce soybean lines with high beneficial sucrose and low raffinose family oligosaccharides.

Genetic architecture of soybean tolerance to off-target dicamba.

The adoption of dicamba-tolerant (DT) soybean in the United States resulted in extensive off-target dicamba damage to non-DT vegetation across soybean-producing states. Although soybeans are highly sensitive to dicamba, the intensity of observed symptoms and yield losses are affected by the genetic background of genotypes. Thus, the objective of this study was to detect novel marker-trait associations and expand on previously identified genomic regions related to soybean response to off-target dicamba. A total of 551 non-DT advanced breeding lines derived from 232 unique bi-parental populations were phenotyped for off-target dicamba across nine environments for three years. Breeding lines were genotyped using the Illumina Infinium BARCSoySNP6K BeadChip. Filtered SNPs were included as predictors in Random Forest (RF) and Support Vector Machine (SVM) models in a forward stepwise selection loop to identify the combination of SNPs yielding the highest classification accuracy. Both RF and SVM models yielded high classification accuracies (0.76 and 0.79, respectively) with minor extreme misclassifications (observed tolerant predicted as susceptible, and vice-versa). Eight genomic regions associated with off-target dicamba tolerance were identified on chromosomes 6 [Linkage Group (LG) C2], 8 (LG A2), 9 (LG K), 10 (LG O), and 19 (LG L). Although the genetic architecture of tolerance is complex, high classification accuracies were obtained when including the major effect SNP identified on chromosome 6 as the sole predictor. In addition, candidate genes with annotated functions associated with phases II (conjugation of hydroxylated herbicides to endogenous sugar molecules) and III (transportation of herbicide conjugates into the vacuole) of herbicide detoxification in plants were co-localized with significant markers within each genomic region. Genomic prediction models, as reported in this study, can greatly facilitate the identification of genotypes with superior tolerance to off-target dicamba.

Near-gapless genome assemblies of Williams 82 and Lee cultivars for accelerating global soybean research.

Complete, gapless telomere-to-telomere chromosome assemblies are a prerequisite for comprehensively investigating the architecture of complex regions, like centromeres or telomeres and removing uncertainties in the order, spacing, and orientation of genes. Using complementary genomics technologies and assembly algorithms, we developed highly contiguous, nearly gapless, genome assemblies for two economically important soybean [Glycine max (L.) Merr] cultivars (Williams 82 and Lee). The centromeres were distinctly annotated on all the chromosomes of both assemblies. We further found that the canonical telomeric repeats were present at the telomeres of all chromosomes of both Williams 82 and Lee genomes. A total of 10 chromosomes in Williams 82 and eight in Lee were entirely reconstructed in single contigs without any gap. Using the combination of ab initio prediction, protein homology, and transcriptome evidence, we identified 58,287 and 56,725 protein-coding genes in Williams 82 and Lee, respectively. The genome assemblies and annotations will serve as a valuable resource for studying soybean genomics and genetics and accelerating soybean improvement.

Prospects for developing allergen-depleted food crops.

In addition to the challenge of meeting global demand for food production, there are increasing concerns about food safety and the need to protect consumer health from the negative effects of foodborne allergies. Certain bio-molecules (usually proteins) present in food can act as allergens that trigger unusual immunological reactions, with potentially life-threatening consequences. The relentless working lifestyles of the modern era often incorporate poor eating habits that include readymade prepackaged and processed foods, which contain additives such as peanuts, tree nuts, wheat, and soy-based products, rather than traditional home cooking. Of the predominant allergenic foods (soybean, wheat, fish, peanut, shellfish, tree nuts, eggs, and milk), peanuts (Arachis hypogaea) are the best characterized source of allergens, followed by tree nuts (Juglans regia, Prunus amygdalus, Corylus avellana, Carya illinoinensis, Anacardium occidentale, Pistacia vera, Bertholletia excels), wheat (Triticum aestivum), soybeans (Glycine max), and kidney beans (Phaseolus vulgaris). The prevalence of food allergies has risen significantly in recent years including chance of accidental exposure to such foods. In contrast, the standards of detection, diagnosis, and cure have not kept pace and unfortunately are often suboptimal. In this review, we mainly focus on the prevalence of allergies associated with peanut, tree nuts, wheat, soybean, and kidney bean, highlighting their physiological properties and functions as well as considering research directions for tailoring allergen gene expression. In particular, we discuss how recent advances in molecular breeding, genetic engineering, and genome editing can be used to develop potential low allergen food crops that protect consumer health.

Genome-Wide Identification and Analysis of the Hsp40/J-Protein Family Reveals Its Role in Soybean (Glycine max) Growth and Development.

The J-protein family comprises molecular chaperones involved in plant growth, development, and stress responses. Little is known about this gene family in soybean. Hence, we characterized J-protein genes in soybean, with the most highly expressed and responsive during flower and seed development. We also revealed their phylogeny, structure, motif analysis, chromosome location, and expression. Based on their evolutionary links, we divided the 111 potential soybean J-proteins into 12 main clades (I-XII). Gene-structure estimation revealed that each clade had an exon-intron structure resembling or comparable to others. Most soybean J-protein genes lacked introns in Clades I, III, and XII. Moreover, transcriptome data obtained from a publicly accessible soybean database and RT-qPCR were used to examine the differential expression of DnaJ genes in various soybean tissues and organs. The expression level of DnaJ genes indicated that, among 14 tissues, at least one tissue expressed the 91 soybean genes. The findings suggest that J-protein genes could be involved in the soybean growth period and offer a baseline for further functional research into J-proteins' role in soybean. One important application is the identification of J-proteins that are highly expressed and responsive during flower and seed development in soybean. These genes likely play crucial roles in these processes, and their identification can contribute to breeding programs to improve soybean yield and quality.

Diversity of fatty acid biosynthesis genes across the soybean pangenome.

Soybean (Glycine max) is a major crop that contributes more than half of global oilseed production. Much research has been directed towards improvement of the fatty acid profile of soybean seeds through marker assisted breeding. Recently published soybean pangenomes, based on thousands of soybean lines, provide an opportunity to identify new alleles that may be involved in fatty acid biosynthesis. In this study, we identify fatty acid biosynthesis genes in soybean pangenomes based on sequence identity with known genes and examine their sequence diversity across diverse soybean collections. We find three possible instances of a gene missing in wild soybean, including FAD8 and FAD2-2D, which may be involved in oleic and linoleic acid desaturation, respectively, although we recommend follow-up research to verify the absence of these genes. More than half of the 53 fatty acid biosynthesis genes identified contained missense variants, including one linked with a previously identified QTL for oil quality. These variants were present in multiple studies based on either short read mappings or alignment of reference grade genomes. Missense variants were found in previously characterized genes including FAD2-1A and FAD2-1B, both of which are involved in desaturation of oleic acid, as well as uncharacterized candidate fatty acid biosynthesis genes. We find that the frequency of missense alleles in fatty acid biosynthesis genes has been reduced significantly more than the global average frequency of missense mutations during domestication, and missense variation in some genes is near absent in modern cultivars. This could be due to the selection for fatty acid profiles in seed, though future work should be conducted towards understanding the phenotypic impacts of these variants.

Identification of genomic regions associated with soybean responses to off-target dicamba exposure.

The widespread adoption of genetically modified (GM) dicamba-tolerant (DT) soybean was followed by numerous reports of off-target dicamba damage and yield losses across most soybean-producing states. In this study, a subset of the USDA Soybean Germplasm Collection consisting of 382 genetically diverse soybean accessions originating from 15 countries was used to identify genomic regions associated with soybean response to off-target dicamba exposure. Accessions were genotyped with the SoySNP50K BeadChip and visually screened for damage in environments with prolonged exposure to off-target dicamba. Two models were implemented to detect significant marker-trait associations: the Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) and a model that allows the inclusion of population structure in interaction with the environment (G×E) to account for variable patterns of genotype responses in different environments. Most accessions (84%) showed a moderate response, either moderately tolerant or moderately susceptible, with approximately 8% showing tolerance and susceptibility. No differences in off-target dicamba damage were observed across maturity groups and centers of origin. Both models identified significant associations in regions of chromosomes 10 and 19. The BLINK model identified additional significant marker-trait associations on chromosomes 11, 14, and 18, while the G×E model identified another significant marker-trait association on chromosome 15. The significant SNPs identified by both models are located within candidate genes possessing annotated functions involving different phases of herbicide detoxification in plants. These results entertain the possibility of developing non-GM soybean cultivars with improved tolerance to off-target dicamba exposure and potentially other synthetic auxin herbicides. Identification of genetic sources of tolerance and genomic regions conferring higher tolerance to off-target dicamba may sustain and improve the production of other non-DT herbicide soybean production systems, including the growing niche markets of organic and conventional soybean.

Chromosome-length genome assemblies of six legume species provide insights into genome organization, evolution, and agronomic traits for crop improvement.

INTRODUCTION: Legume crops are an important source of protein and oil for human health and in fixing atmospheric N2 for soil enrichment. With an objective to accelerate much-needed genetic analyses and breeding applications, draft genome assemblies were generated in several legume crops; many of them are not high quality because they are mainly based on short reads. However, the superior quality of genome assembly is crucial for a detailed understanding of genomic architecture, genome evolution, and crop improvement. OBJECTIVES: Present study was undertaken with an objective of developing improved chromosome-length genome assemblies in six different legumes followed by their systematic investigation to unravel different aspects of genome organization and legume evolution. METHODS: We employed in situ Hi-C data to improve the existing draft genomes and performed different evolutionary and comparative analyses using improved genome assemblies. RESULTS: We have developed chromosome-length genome assemblies in chickpea, pigeonpea, soybean, subterranean clover, and two wild progenitor species of cultivated groundnut (A. duranensis and A. ipaensis). A comprehensive comparative analysis of these genome assemblies offered improved insights into various evolutionary events that shaped the present-day legume species. We highlighted the expansion of gene families contributing to unique traits such as nodulation in legumes, gravitropism in groundnut, and oil biosynthesis in oilseed legume crops such as groundnut and soybean. As examples, we have demonstrated the utility of improved genome assemblies for enhancing the resolution of "QTL-hotspot" identification for drought tolerance in chickpea and marker-trait associations for agronomic traits in pigeonpea through genome-wide association study. Genomic resources developed in this study are publicly available through an online repository, 'Legumepedia'. CONCLUSION: This study reports chromosome-length genome assemblies of six legume species and demonstrates the utility of these assemblies in crop improvement. The genomic resources developed here will have significant role in accelerating genetic improvement applications of legume crops.

Genome-wide association analysis identified consistent QTL for seed yield in a soybean diversity panel tested across multiple environments.

Improving seed yield is one of the main targets of soybean [Glycine max (L.) Merr.] breeding. Identification of loci that influence productivity and understanding their genetic mechanism will help marker-assisted trait introgression. The present study evaluated a diverse panel of 541 soybean genotypes consisting of three maturity groups (MGs III-V) in four environments in Kansas, U.S. Data on seed yield, seed weight, shattering resistance, days to maturity, and plant height showed significant genotype, environmental, and genotype × environment interaction variations. Seed yield and shattering had moderate broad-sense heritability (<85%), while the rest of the traits showed high broad-sense heritability (>90%). The SoySNP50K iSelect BeadChip dataset was used to identify significantly associated loci via genome-wide association studies (GWAS). A total of 19 single-nucleotide polymorphisms (SNPs) were significantly associated with seed yield. Particularly, two stable seed yield quantitative trait loci (QTL) on chromosomes 9 and 17 were consistently detected in at least three out of four environments. Candidate gene analysis surrounding seed yield QTL on chromosome 9 showed that Glyma.09G048900, an oxygen binding protein, was the closest to the QTL peak. Similarly, Glyma.17G090200 and Glyma.17G090400 were within 20-kb region of the seed yield QTL on chromosome 17. The candidate genes warrant further analysis to determine their functional mechanisms and develop markers for seed yield improvement.

Differentially reset transcriptomes and genome bias response orchestrate wheat response to phosphate deficiency.

Phosphorus (P) is an essential macronutrient for all organisms. Phosphate (Pi) deficiency reduces grain yield and quality in wheat. Understanding how wheat responds to Pi deficiency at the global transcriptional level remains limited. We revisited the available RNA-seq transcriptome from Pi-starved wheat roots and shoots subjected to Pi starvation. Genome-wide transcriptome resetting was observed under Pi starvation, with a total of 917 and 2338 genes being differentially expressed in roots and shoots, respectively. Chromosomal distribution analysis of the gene triplets and differentially expressed genes (DEGs) revealed that the D genome displayed genome induction bias and, specifically, the chromosome 2D might be a key contributor to Pi-limiting triggered gene expression response. Alterations in multiple metabolic pathways pertaining to secondary metabolites, transcription factors and Pi uptake-related genes were evidenced. This study provides genomic insight and the dynamic landscape of the transcriptional changes contributing to the hexaploid wheat during Pi starvation. The outcomes of this study and the follow-up experiments have the potential to assist the development of Pi-efficient wheat cultivars.