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.

Shoulder and Neck Balance in Adolescent Idiopathic Scoliosis: Which Radiographic Indices are Reliable and Practical?

Introduction

Deformities of the spine and thorax in adolescent idiopathic scoliosis affect appearance. They are a cause of inferiority, affecting psychological well-being and the social life of the patients. To contribute to curve evaluation, planning in curve correction, and improving the post-operative aesthetics, many studies on the correlation between appearance and radiography in the assessment of shoulder and neck balance have been reported recently. In general, these studies did not clarify which indices are required to evaluate shoulder and neck balance. This study aimed to learn about indices to assess shoulder and neck balance in adolescent idiopathic scoliosis in correlation between clinical appearance and radiography.

Materials and methods

This observational study recruited 50 patients with adolescent idiopathic scoliosis who were 12 to 18 years of age with Cobb angle >10°. Based on Pearson correlation coefficient, radiographic parameters such as coracoid height difference (CHD), clavicle rib intersection distance (CRID), clavicle angle (CA), clavicle chest cage angle difference (CCAD), and T1 tilt angle were evaluated in correlation with clinical shoulder and neck balance by difference of inner shoulder height (SHi), difference of outer shoulder height (SHo), and neck tilt angle.

Results

SHi was moderately correlated with T1 tilt angle (r [hereafter] = 0.45), CA (0.47), and CHD (0.57), high-moderately correlated with CRID (0.64), very-highly correlated with CCAD (0.84). SHo was moderately correlated with T1 tilt angle (0.43), highly correlated with CHD (0.60), CA (0.63), and CRID (0.72), and very-highly correlated with CCAD (0.89). T1 tilt angle was high-moderately correlated with neck tilt angle (0.76). The correlation coefficients between clinical and radiographic shoulder and neck balance according to sex, BMI, type of main curve, severity of main curve did not change significantly.

Conclusion

There was a very high correlation between SHo (shoulder tilt) and CCAD (0.89); the correlation between SHo and CRID was high-moderate (0.72), but CRID is easier than CCAD to evaluate on radiographs. On the other hand, T1 tilt angle, which is the easiest radiographic parameter to evaluate, had a high-moderate correlation with neck tilt angle (0.76) but a moderate correlation with SHo (0.43).

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.

Mitigating microplastic pollution: A critical review on the effects, remediation, and utilization strategies of microplastics

Microplastics are found ubiquitous in the natural environment and are an increasing source of worry for global health. Rapid industrialization and inappropriate plastic waste management in our daily lives have resulted in an increase in the amount of microplastics in the ecosystem. Microplastics that are <150 μm in size could be easily ingested by living beings and cause considerable toxicity. Microplastics can aggregate in living organisms and cause acute, chronic, carcinogenic, developmental, and genotoxic damage. As a result, a sustainable approach to reducing, reusing, and recycling plastic waste is required to manage microplastic pollution in the environment. However, there is still a significant lack of effective methods for managing these pollutants. As a result, the purpose of this review is to convey information on microplastic toxicity and management practices that may aid in the reduction of microplastic pollution. This review further insights on how plastic trash could be converted as value-added products, reducing the load of accumulating plastic wastes in the environment, and leading to a beneficial endeavor for humanity.

Endocrine disruptors: Unravelling the link between chemical exposure and Women's reproductive health

An Endocrine Disrupting Chemical (EDC) is any compound that disrupts the function of the endocrine system in humans and is ubiquitous in the environment either as a result of natural events or through anthropogenic activities. Bisphenol A, phthalates, parabens, pesticides, triclosan, polychlorinated biphenyls, and heavy metals, which are frequently found in the pharmaceutical, cosmetic, and packaging sectors, are some of the major sources of EDC pollutants. EDCs have been identified to have a deteriorating effect on the female reproductive system, as evidenced by the increasing number of reproductive disorders such as endometriosis, uterine fibroids, polycystic ovary syndrome, premature ovarian failure, menstrual irregularity, menarche, and infertility. Studying EDCs in relation to women's health is essential for understanding the complex interactions between environmental factors and health outcomes. It enables the development of strategies to mitigate risks, protect reproductive and overall health, and inform public policy decisions to safeguard women's well-being. Healthcare professionals must know the possible dangers of EDC exposure and ask about environmental exposures while evaluating patients. This may result in more precise diagnosis and personalized treatment regimens. This review summarises the existing understanding of prevalent EDCs that impact women's health and involvement in female reproductive dysfunction and underscores the need for more research. Further insights on potential mechanisms of action of EDCs on female has been emphasized in the article. We also discuss the role of nutritional intervention in reducing the effect of EDCs on women's reproductive health. EDC pollution can be further reduced by adhering to strict regulations prohibiting the release of estrogenic substances into the environment.

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.

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.

Standards for clinical trials for treating TB

BACKGROUND: The value, speed of completion and robustness of the evidence generated by TB treatment trials could be improved by implementing standards for best practice.METHODS: A global panel of experts participated in a Delphi process, using a 7-point Likert scale to score and revise draft standards until consensus was reached.RESULTS: Eleven standards were defined: Standard 1, high quality data on TB regimens are essential to inform clinical and programmatic management; Standard 2, the research questions addressed by TB trials should be relevant to affected communities, who should be included in all trial stages; Standard 3, trials should make every effort to be as inclusive as possible; Standard 4, the most efficient trial designs should be considered to improve the evidence base as quickly and cost effectively as possible, without compromising quality; Standard 5, trial governance should be in line with accepted good clinical practice; Standard 6, trials should investigate and report strategies that promote optimal engagement in care; Standard 7, where possible, TB trials should include pharmacokinetic and pharmacodynamic components; Standard 8, outcomes should include frequency of disease recurrence and post-treatment sequelae; Standard 9, TB trials should aim to harmonise key outcomes and data structures across studies; Standard 10, TB trials should include biobanking; Standard 11, treatment trials should invest in capacity strengthening of local trial and TB programme staff.CONCLUSION: These standards should improve the efficiency and effectiveness of evidence generation, as well as the translation of research into policy and practice.

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.

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.

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.

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.

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.

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.

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.

Application of an Improved 2-Dimensional High-Throughput Soybean Root Phenotyping Platform to Identify Novel Genetic Variants Regulating Root Architecture Traits

Nutrient-efficient root system architecture (RSA) is becoming an important breeding objective for generating crop varieties with improved nutrient and water acquisition efficiency. Genetic variants shaping soybean RSA is key in improving nutrient and water acquisition. Here, we report on the use of an improved 2-dimensional high-throughput root phenotyping platform that minimizes background noise by imaging pouch-grown root systems submerged in water. We also developed a background image cleaning Python pipeline that computationally removes images of small pieces of debris and filter paper fibers, which can be erroneously quantified as root tips. This platform was used to phenotype root traits in 286 soybean lines genotyped with 5.4 million single-nucleotide polymorphisms. There was a substantially higher correlation in manually counted number of root tips with computationally quantified root tips (95% correlation), when the background was cleaned of nonroot materials compared to root images without the background corrected (79%). Improvements in our RSA phenotyping pipeline significantly reduced overestimation of the root traits influenced by the number of root tips. Genome-wide association studies conducted on the root phenotypic data and quantitative gene expression analysis of candidate genes resulted in the identification of 3 putative positive regulators of root system depth, total root length and surface area, and root system volume and surface area of thicker roots (DOF1-like zinc finger transcription factor, protein of unknown function, and C2H2 zinc finger protein). We also identified a putative negative regulator (gibberellin 20 oxidase 3) of the total number of lateral roots.

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.

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.

Wildsoydb DataHub: a platform for accessing soybean multiomic datasets across multiple reference genomes

The Wildsoydb DataHub is an integrated interface for biologists and breeders to access soybean genomic resources easily, allowing them to fully utilize the results of genomic research.

Breeding for disease resistance in soybean: a global perspective

KEY MESSAGE

This review provides a comprehensive atlas of QTLs, genes, and alleles conferring resistance to 28 important diseases in all major soybean production regions in the world. Breeding disease-resistant soybean [Glycine max (L.) Merr.] varieties is a common goal for soybean breeding programs to ensure the sustainability and growth of soybean production worldwide. However, due to global climate change, soybean breeders are facing strong challenges to defeat diseases. Marker-assisted selection and genomic selection have been demonstrated to be successful methods in quickly integrating vertical resistance or horizontal resistance into improved soybean varieties, where vertical resistance refers to R genes and major effect QTLs, and horizontal resistance is a combination of major and minor effect genes or QTLs. This review summarized more than 800 resistant loci/alleles and their tightly linked markers for 28 soybean diseases worldwide, caused by nematodes, oomycetes, fungi, bacteria, and viruses. The major breakthroughs in the discovery of disease resistance gene atlas of soybean were also emphasized which include: (1) identification and characterization of vertical resistance genes reside rhg1 and Rhg4 for soybean cyst nematode, and exploration of the underlying regulation mechanisms through copy number variation and (2) map-based cloning and characterization of Rps11 conferring resistance to 80% isolates of Phytophthora sojae across the USA. In this review, we also highlight the validated QTLs in overlapping genomic regions from at least two studies and applied a consistent naming nomenclature for these QTLs. Our review provides a comprehensive summary of important resistant genes/QTLs and can be used as a toolbox for soybean improvement. Finally, the summarized genetic knowledge sheds light on future directions of accelerated soybean breeding and translational genomics studies.

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.

The Spatial Distribution and Genetic Diversity of the Soybean Cyst Nematode, Heterodera glycines, in China: It Is Time to Take Measures to Control Soybean Cyst Nematode

The continuous evolution and spread of virulent forms of the soybean cyst nematode (SCN) driven by the environment and anthropogenic intervention is a serious threat to the soybean production worldwide, including China. Especially in China, the implemented measures to control SCN are insufficient for sustainable agricultural development yet. We summarized our knowledge about the spread and spatial distribution of SCN in China and the virulence diversity in the main soybean growing areas. To reveal the genetic relatedness and diversity of SCN populations, we re-sequenced 53 SCN genomes from the Huang-Huai Valleys, one of the two main soybean growing areas in China. We identified spreading patterns linked to the local agroecosystems and topographies. Moreover, we disclosed the first evidence for the selection of complex virulence in the field even under low selection pressure in an example from North Shanxi. SCN is present in all soybean growing areas in China but SCN susceptible cultivars are still largely grown indicating that SCN-related damage and financial loss have not received the attention they deserve yet. To prevent increasing yield losses and to improve the acceptance of resistant cultivars by the growers, we emphasized that it is time to accelerate SCN resistance breeding, planting resistant cultivars to a larger extent, and to support farmers to implement a wider crop rotation for sustainable development of the soybean production in China.

Save the Mekong Delta from drowning

Policy must address drivers, not just symptoms, of subsidence.

Exploring Machine Learning Algorithms to Unveil Genomic Regions Associated With Resistance to Southern Root-Knot Nematode in Soybeans

Southern root-knot nematode [SRKN, Meloidogyne incognita (Kofold & White) Chitwood] is a plant-parasitic nematode challenging to control due to its short life cycle, a wide range of hosts, and limited management options, of which genetic resistance is the main option to efficiently control the damage caused by SRKN. To date, a major quantitative trait locus (QTL) mapped on chromosome (Chr.) 10 plays an essential role in resistance to SRKN in soybean varieties. The confidence of discovered trait-loci associations by traditional methods is often limited by the assumptions of individual single nucleotide polymorphisms (SNPs) always acting independently as well as the phenotype following a Gaussian distribution. Therefore, the objective of this study was to conduct machine learning (ML)-based genome-wide association studies (GWAS) utilizing Random Forest (RF) and Support Vector Machine (SVM) algorithms to unveil novel regions of the soybean genome associated with resistance to SRKN. A total of 717 breeding lines derived from 330 unique bi-parental populations were genotyped with the Illumina Infinium BARCSoySNP6K BeadChip and phenotyped for SRKN resistance in a greenhouse. A GWAS pipeline involving a supervised feature dimension reduction based on Variable Importance in Projection (VIP) and SNP detection based on classification accuracy was proposed. Minor effect SNPs were detected by the proposed ML-GWAS methodology but not identified using Bayesian-information and linkage-disequilibrium Iteratively Nested Keyway (BLINK), Fixed and Random Model Circulating Probability Unification (FarmCPU), and Enriched Compressed Mixed Linear Model (ECMLM) models. Besides the genomic region on Chr. 10 that can explain most of SRKN resistance variance, additional minor effects SNPs were also identified on Chrs. 10 and 11. The findings in this study demonstrated that overfitting in GWAS may lead to lower prediction accuracy, and the detection of significant SNPs based on classification accuracy limited false-positive associations. The expansion of the basis of the genetic resistance to SRKN can potentially reduce the selection pressure over the major QTL on Chr. 10 and achieve higher levels of resistance.

Machine learning models outperform deep learning models, provide interpretation and facilitate feature selection for soybean trait prediction

Recent growth in crop genomic and trait data have opened opportunities for the application of novel approaches to accelerate crop improvement. Machine learning and deep learning are at the forefront of prediction-based data analysis. However, few approaches for genotype to phenotype prediction compare machine learning with deep learning and further interpret the models that support the predictions. This study uses genome wide molecular markers and traits across 1110 soybean individuals to develop accurate prediction models. For 13/14 sets of predictions, XGBoost or random forest outperformed deep learning models in prediction performance. Top ranked SNPs by F-score were identified from XGBoost, and with further investigation found overlap with significantly associated loci identified from GWAS and previous literature. Feature importance rankings were used to reduce marker input by up to 90%, and subsequent models maintained or improved their prediction performance. These findings support interpretable machine learning as an approach for genomic based prediction of traits in soybean and other crops.

Haplotype mapping uncovers unexplored variation in wild and domesticated soybean at the major protein locus cqProt-003

KEY MESSAGE

The major soy protein QTL, cqProt-003, was analysed for haplotype diversity and global distribution, and results indicate 304 bp deletion and variable tandem repeats in protein coding regions are likely causal candidates. Here, we present association and linkage analysis of 985 wild, landrace and cultivar soybean accessions in a pan genomic dataset to characterize the major high-protein/low-oil associated locus cqProt-003 located on chromosome 20. A significant trait-associated region within a 173 kb linkage block was identified, and variants in the region were characterized, identifying 34 high confidence SNPs, 4 insertions, 1 deletion and a larger 304 bp structural variant in the high-protein haplotype. Trinucleotide tandem repeats of variable length present in the second exon of gene Glyma.20G085100 are strongly correlated with the high-protein phenotype and likely represent causal variation. Structural variation has previously been found in the same gene, for which we report the global distribution of the 304 bp deletion and have identified additional nested variation present in high-protein individuals. Mapping variation at the cqProt-003 locus across demographic groups suggests that the high-protein haplotype is common in wild accessions (94.7%), rare in landraces (10.6%) and near absent in cultivated breeding pools (4.1%), suggesting its decrease in frequency primarily correlates with domestication and continued during subsequent improvement. However, the variation that has persisted in under-utilized wild and landrace populations holds high breeding potential for breeders willing to forego seed oil to maximize protein content. The results of this study include the identification of distinct haplotype structures within the high-protein population, and a broad characterization of the genomic context and linkage patterns of cqProt-003 across global populations, supporting future functional characterization and modification.

Sequencing the USDA core soybean collection reveals gene loss during domestication and breeding

The gene content of plants varies between individuals of the same species due to gene presence/absence variation, and selection can alter the frequency of specific genes in a population. Selection during domestication and breeding will modify the genomic landscape, though the nature of these modifications is only understood for specific genes or on a more general level (e.g., by a loss of genetic diversity). Here we have assembled and analyzed a soybean (Glycine spp.) pangenome representing more than 1,000 soybean accessions derived from the USDA Soybean Germplasm Collection, including both wild and cultivated lineages, to assess genomewide changes in gene and allele frequency during domestication and breeding. We identified 3,765 genes that are absent from the Lee reference genome assembly and assessed the presence/absence of all genes across this population. In addition to a loss of genetic diversity, we found a significant reduction in the average number of protein-coding genes per individual during domestication and subsequent breeding, though with some genes and allelic variants increasing in frequency associated with selection for agronomic traits. This analysis provides a genomic perspective of domestication and breeding in this important oilseed crop.

Mapping of partial resistance to Phytophthora sojae in soybean PIs using whole-genome sequencing reveals a major QTL

In the last decade, more than 70 quantitative trait loci (QTL) related to soybean [Glycine max (L.) Merr.] partial resistance (PR) against Phytophthora sojae have been identified by genome-wide association studies (GWAS). However, most of them have either a minor effect on the resistance level or are specific to a single phenotypic variable or one isolate, thereby limiting their use in breeding programs. In this study, we have used an analytical approach combining (a) the phenotypic characterization of a diverse panel of 357 soybean accessions for resistance to P. sojae captured through a single variable, corrected dry weight; (b) a new hydroponic assay allowing the inoculation of a combination of P. sojae isolates covering the spectrum of commercially relevant Rps genes; and (c) exhaustive genotyping through whole-genome resequencing (WGS). This led to the identification of a novel P. sojae resistance QTL with a relatively major effect compared with the previously reported QTL. The QTL interval, spanning ∼500 kb on chromosome (Chr) 15, does not colocalize with previously reported QTL for P. sojae resistance. Plants carrying the favorable allele at this QTL were 60% more resistant. Eight genes were found to reside in the linkage disequilibrium (LD) block containing the peak single-nucleotide polymorphism (SNP) including Glyma.15G217100, which encodes a major latex protein (MLP)-like protein, with a functional annotation related to pathogen resistance. Expression analysis of Glyma.15G217100 indicated that it was nearly eight times more highly expressed in a group of plant introductions (PIs) carrying the resistant (R) allele compared with those carrying the susceptible (S) allele within a short period after inoculation. These results offer new and valuable options to develop improved soybean cultivars with broad resistance to P. sojae through marker-assisted selection.

Pangenomics in crop improvement-from coding structural variations to finding regulatory variants with pangenome graphs

Since the first reported crop pangenome in 2014, advances in high-throughput and cost-effective DNA sequencing technologies facilitated multiple such studies including the pangenomes of oilseed rape (Brassica napus L.), soybean [Glycine max (L.) Merr.], rice (Oryza sativa L.), wheat (Triticum aestivum L.), and barley (Hordeum vulgare L.). Compared with single-reference genomes, pangenomes provide a more accurate representation of the genetic variation present in a species. By combining the genomic data of multiple accessions, pangenomes allow for the detection and annotation of complex DNA polymorphisms such as structural variations (SVs), one of the major determinants of genetic diversity within a species. In this review we summarize the current literature on crop pangenomics, focusing on their application to find candidate SVs involved in traits of agronomic interest. We then highlight the potential of pangenomes in the discovery and functional characterization of noncoding regulatory sequences and their variations. We conclude with a summary and outlook on innovative data structures representing the complete content of plant pangenomes including annotations of coding and noncoding elements and outcomes of transcriptomic and epigenomic experiments.

Classification Methods and Identification of Reniform Nematode Resistance in Known Soybean Cyst Nematode-Resistant Soybean Genotypes

Plant parasitic nematodes are a major yield-limiting factor of soybean in the United States and Canada. It has been indicated that soybean cyst nematode (SCN; Heterodera glycines Ichinohe) and reniform nematode (RN; Rotylenchulus reniformis Linford and Oliveira) resistance could be genetically related. For many years, fragmentary data have shown this relationship. This report evaluates RN reproduction on 418 plant introductions (PIs) selected from the U.S. Department of Agriculture Soybean Germplasm Collection with reported SCN resistance. The germplasm was divided into two tests of 214 PIs reported as resistant and 204 PIs reported as moderately resistant to SCN. The defining and reporting of RN resistance changed several times in the last 30 years, causing inconsistencies in RN resistance classification among multiple experiments. Comparison of four RN resistance classification methods was performed: (i) ≤10% as compared with the susceptible check, (ii) using normalized reproduction index (RI) values, and using (iii) transformed data log10(x), and (iv) transformed data log10(x + 1) in an optimal univariate k-means clustering analysis. The method of transformed data log10(x) was selected as the most accurate for classification of RN resistance. Among 418 PIs with reported SCN resistance, the log10(x) method grouped 59 PIs (15%) as resistant and 130 PIs (31%) as moderately resistant to RN. Genotyping of a subset of the most resistant PIs to both nematode species revealed their strong correlation with rhg1-a allele. This research identified genotypes with resistance to two nematode species and potential new sources of RN resistance that could be valuable to breeders in developing resistant cultivars.

Characterization of Root System Architecture Traits in Diverse Soybean Genotypes Using a Semi-Hydroponic System

Phenotypic variation and correlations among root traits form the basis for selecting and breeding soybean varieties with efficient access to water and nutrients and better adaptation to abiotic stresses. Therefore, it is important to develop a simple and consistent system to study root traits in soybean. In this study, we adopted the semi-hydroponic system to investigate the variability in root morphological traits of 171 soybean genotypes popularized in the Yangtze and Huaihe River regions, eastern China. Highly diverse phenotypes were observed: shoot height (18.7-86.7 cm per plant with a median of 52.3 cm); total root length (208-1663 cm per plant with a median of 885 cm); and root mass (dry weight) (19.4-251 mg per plant with a median of 124 mg). Both total root length and root mass exhibited significant positive correlation with shoot mass (p ≤ 0.05), indicating their relationship with plant growth and adaptation strategies. The nine selected traits contributed to one of the two principal components (eigenvalues > 1), accounting for 78.9% of the total genotypic variation. Agglomerative hierarchical clustering analysis separated the 171 genotypes into five major groups based on these root traits. Three selected genotypes with contrasting root systems were validated in soil-filled rhizoboxes (1.5 m deep) until maturity. Consistent ranking of the genotypes in some important root traits at various growth stages between the two experiments indicates the reliability of the semi-hydroponic system in phenotyping root trait variability at the early growth stage in soybean germplasms.

Direct Infusion Metabolomics of the Photosystem and Chlorophyll Related Metabolites within a Drought Tolerant Plant Introduction of Glycine max

Drought is the most prolific form of abiotic stress that legumes and cereal plants alike can endure, and the planting of an improper cultivar at the beginning of a season can cause unexpected losses up to fifty percent under water deficient conditions. Herein, a plant introduction (PI) of an exotic cultivar of soybean (Glycine max), PI 567731, which demonstrates a slow wilting (SW) canopy phenotype in maturity group III, was profiled under drought conditions in field trials in Missouri against a drought susceptible check cultivar, Pana. Metabolomic profiling was carried out on samples of leaves from each of these cultivars at V5 and R2 growth stages both while irrigated and while under drought stress for three weeks. PI 567731 was observed to have differential phytochemical content, and enhanced levels of chlorophyll (Chl) a/b and pheophytin (Pheo) were profiled by direct infusion electrospray Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Indicating drought induced changes of the photosystem and photosynthetic capabilities alongside water preservation strategies are important within the SW phenotype drought response. Subsequent multivariate analysis was able to form predictive models, encompassing the variance of growth and drought stress of the cultivar. Moreover, the existence of unique Chl-related metabolites (CRM) (m/z > 900) were confirmed through tandem mass spectrometry. The resultant coordination of fatty acids to the core of the porphyrin ring was observed and played an unknown role in the proliferation of the photosynthesis. However, the relative ratio of the most abundant CRM is undisturbed by drought stress in PI 567731, in contrast to the drought susceptible cultivar. These results provide key insights into drought related metabolic mechanisms.

Dietary soluble non-starch polysaccharide level and xylanase influence the gastrointestinal environment and nutrient utilisation in laying hens

1. The objective of this study was to examine the influence of dietary soluble non-starch polysaccharide (sNSP) level and xylanase supplementation on productive performance, viscosity and pH along the gastrointestinal tract in laying hens. Excreta moisture content, ileal and caecal microbiota and short chain fatty acid (SCFA) composition and apparent total tract nutrient utilisation was measured.2. Hyline Brown laying hens (n=144) were housed individually at 25 weeks of age and allocated to one of four wheat-based dietary treatments in a 2 × 2 factorial arrangement, consisting of two levels of sNSP (High 13.40 g/kg or Low 11.22 g/kg), with or without xylanase (0 or 12,000 BXU/kg). Birds were fed the dietary treatments for 56 days.3. Increasing dietary sNSP increased jejunum viscosity, degradability of total NSP, total tract flow of insoluble arabinose, and succinic acid concentration in the caeca (P<0.05). Feeding high sNSP decreased excreta moisture content, total tract energy retention and free oligosaccharide, total tract flow of soluble and insoluble galactose and insoluble rhamnose and fucose, and ileal acetic and lactic acid concentrations (P<0.05), and tended to reduce egg production (P=0.058).4. Supplementation with xylanase resulted in reduced jejunum and ileum viscosity, caecal pH, excreta moisture, flow of soluble arabinose and glucose and insoluble arabinose and xylose, caecal concentration of Lactobacillus sp. and isobutyric and succinic acid, and ileal concentration of Bacillus sp. and total anaerobic bacteria (P<0.05). Xylanase application also increased energy retention and insoluble and total NSP degradation, and caecal abundance of Bifidobacteria sp. and valeric acid (P<0.05).6. These results reiterated the ability of xylanase to improve nutrient digestibility and reduce excreta moisture content in laying hens, and highlighted the importance of considering dietary sNSP level in laying hen diets.

Genome-wide identification and analysis of soybean acyl-ACP thioesterase gene family reveals the role of GmFAT to improve fatty acid composition in soybean seed

KEY MESSAGE

Soybean acyl-ACP thioesterase gene family have been characterized; GmFATA1A mutants were discovered to confer high oleic acid, while GmFATB mutants presented low palmitic and high oleic acid seed content. Soybean oil stability and quality are primarily determined by the relative proportions of saturated versus unsaturated fatty acids. Commodity soybean typically contains 11% palmitic acid, as the primary saturated fatty acids. Reducing palmitic acid content is the principal approach to minimize the levels of saturated fatty acids in soybean. Though high palmitic acid enhances oxidative stability of soybean oil, it is negatively correlated with oil and oleic acid content and can cause coronary heart diseases for humans. For plants, acyl-acyl carrier protein (ACP) thioesterases (TEs) are a group of enzymes to hydrolyze acyl group and release free fatty acid from plastid. Among them, GmFATB1A has become the main target to genetically reduce the palmitic acid content in soybean. However, the role of members in soybean acyl-ACP thioesterase gene family is largely unknown. In this study, we characterized two classes of TEs, GmFATA, and GmFATB in soybean. We also denominated two GmFATA members and discovered six additional members that belong to GmFATB gene family through phylogenetic, syntenic, and in silico analysis. Using TILLING-by-Sequencing+, we identified an allelic series of mutations in five soybean acyl-ACP thioesterase genes, including GmFATA1A, GmFATB1A, GmFATB1B, GmFATB2A, and GmFATB2B. Additionally, we discovered mutations at GmFATA1A to confer high oleic acid (up to 34.5%) content, while mutations at GmFATB presented low palmitic acid (as low as 5.6%) and high oleic acid (up to 36.5%) phenotypes. The obtained soybean mutants with altered fatty acid content can be used in soybean breeding program for improving soybean oil composition traits.

Association of body mass index with non-achievement of target low-density lipoprotein level in older patients at very high cardiovascular risk: a multicentre study

Introduction

Low-density lipoprotein cholesterol (LDL-c) is a well-established risk factor for atherosclerotic cardiovascular disease. Nonetheless, the association of body mass index (BMI) with non-achievement of target LDL-c level in older patients with type 2 diabetes (T2D) at very high cardiovascular risk is unknown.

Purpose

To investigate whether BMI is associated with non-achievement of target LDL-c level in older patients with T2D at very high cardiovascular risk.

Methods

From December 2019 to June 2020, in this multicentre prospective cross-sectional study, we enrolled 733 consecutive outpatients aged ≥60 years with T2D at very high cardiovascular risk in whom LDL-c levels could be measured after any stable lipid-lowering therapy for ≥6 months. Achievement of target lipid level was assessed based on the 2019 guidelines of the European Society of Cardiology for dyslipidaemia. Factors associated with non-achievement of target LDL-c level were determined using logistic regression analysis.

Results

Of the total cases (age, 68.6±7.2 years; men, 51.3%), 654 patients (89.2%) did not achieve an aggressive target LDL-c level of &lt;1.4 mmol/L. Target non-high-density lipoprotein cholesterol level of &lt;2.2 mmol/L and triglyceride level of &lt;1.7 mmol/L were not achieved in 87.9% and 56.2% of the patients, respectively. In the multivariate model, BMI was the only factor associated with failure to achieve target LDL-c level, but not other factors such as age, sex, education level, smoking, and comorbidities. The adjusted odds ratio were 0.88 (95% confidence interval [95% CI], 0.24–3.21; P=0.84) for underweight, 1.57 (95% CI, 0.87–2.81; P=0.13) for overweight, and 2.63 (95% CI, 1.43–4.83; P=0.002) for obesity (normal weight was set as reference) status.

Conclusions

Non-achievement of target LDL-c level is highly prevalent in older patients with T2D at very high cardiovascular risk. Obesity, defined by BMI, can be a factor associated with non-achievement of the target. The findings highlight the importance of management of lipid levels in older patients with T2D.

Funding Acknowledgement

Type of funding sources: None. Figure 1

Improved Constraints on Primordial Gravitational Waves using Planck, WMAP, and BICEP/Keck Observations through the 2018 Observing Season

We present results from an analysis of all data taken by the BICEP2, Keck Array, and BICEP3 CMB polarization experiments up to and including the 2018 observing season. We add additional Keck Array observations at 220 GHz and BICEP3 observations at 95 GHz to the previous 95/150/220  GHz dataset. The Q/U maps now reach depths of 2.8, 2.8, and 8.8  μK_{CMB} arcmin at 95, 150, and 220 GHz, respectively, over an effective area of ≈600 square degrees at 95 GHz and ≈400 square degrees at 150 and 220 GHz. The 220 GHz maps now achieve a signal-to-noise ratio on polarized dust emission exceeding that of Planck at 353 GHz. We take auto- and cross-spectra between these maps and publicly available WMAP and Planck maps at frequencies from 23 to 353 GHz and evaluate the joint likelihood of the spectra versus a multicomponent model of lensed ΛCDM+r+dust+synchrotron+noise. The foreground model has seven parameters, and no longer requires a prior on the frequency spectral index of the dust emission taken from measurements on other regions of the sky. This model is an adequate description of the data at the current noise levels. The likelihood analysis yields the constraint r_{0.05}<0.036 at 95% confidence. Running maximum likelihood search on simulations we obtain unbiased results and find that σ(r)=0.009. These are the strongest constraints to date on primordial gravitational waves.

Identification of genomic loci conferring broad-spectrum resistance to multiple nematode species in exotic soybean accession PI 567305

KEY MESSAGE

Genetic analysis identified a unique combination of major QTL for resistance to important soybean nematodes concurrently present in a single soybean accession, which has not been reported earlier. An exotic soybean [Glycine max (L.) Merr.] accession, PI 567305, was reported to be highly resistant to three important nematode species, soybean cyst (SCN), root-knot (RKN), and reniform (RN) nematodes. However, genetic basis controlling broad-spectrum resistance in this germplasm has not been investigated. We report results of genetic analysis to identify genomic loci conferring resistance to these nematode species. A bi-parental population consisting of 242 F8-derived recombinant inbred lines (RILs) was developed from a cross of a nematode susceptible cultivar, Magellan, and resistant accession, PI 567305. The RILs were phenotyped for nematode resistance to three SCN HG types. They were genotyped using the Infinium SoySNP6K BeadChips and genotype-by-sequencing (GBS) methods in an attempt to evaluate the cost-effectiveness and efficiency of these two genotyping platforms. Genetic analysis confirmed the major QTL on chromosomes (Chrs) 10 and 18 with broad-spectrum resistance to the three nematodes present in this germplasm. Haplotype and copy number variation analyses of SCN resistance QTL indicated that PI 567305 has a different haplotype, which is associated with likely a unique SCN resistance mechanism different from Peking- or PI 88788-type resistance. The evaluations of both Infinium Beadchip- and GBS-based genotyping technologies provided comprehensive insights for researchers to choose a cost-effective and efficient platform for QTL mapping and for other genomic studies in soybeans.

The Soybean High Density 'Forrest' by 'Williams 82' SNP-Based Genetic Linkage Map Identifies QTL and Candidate Genes for Seed Isoflavone Content

Isoflavones are secondary metabolites that are abundant in soybean and other legume seeds providing health and nutrition benefits for both humans and animals. The objectives of this study were to construct a single nucleotide polymorphism (SNP)-based genetic linkage map using the ‘Forrest’ by ‘Williams 82’ (F×W82) recombinant inbred line (RIL) population (n = 306); map quantitative trait loci (QTL) for seed daidzein, genistein, glycitein, and total isoflavone contents in two environments over two years (NC-2018 and IL-2020); identify candidate genes for seed isoflavone. The FXW82 SNP-based map was composed of 2075 SNPs and covered 4029.9 cM. A total of 27 QTL that control various seed isoflavone traits have been identified and mapped on chromosomes (Chrs.) 2, 4, 5, 6, 10, 12, 15, 19, and 20 in both NC-2018 (13 QTL) and IL-2020 (14 QTL). The six QTL regions on Chrs. 2, 4, 5, 12, 15, and 19 are novel regions while the other 21 QTL have been identified by other studies using different biparental mapping populations or genome-wide association studies (GWAS). A total of 130 candidate genes involved in isoflavone biosynthetic pathways have been identified on all 20 Chrs. And among them 16 have been identified and located within or close to the QTL identified in this study. Moreover, transcripts from four genes (Glyma.10G058200, Glyma.06G143000, Glyma.06G137100, and Glyma.06G137300) were highly abundant in Forrest and Williams 82 seeds. The identified QTL and four candidate genes will be useful in breeding programs to develop soybean cultivars with high beneficial isoflavone contents.

Odderon Exchange from Elastic Scattering Differences between pp and pp[over ¯] Data at 1.96 TeV and from pp Forward Scattering Measurements

We describe an analysis comparing the pp[over ¯] elastic cross section as measured by the D0 Collaboration at a center-of-mass energy of 1.96 TeV to that in pp collisions as measured by the TOTEM Collaboration at 2.76, 7, 8, and 13 TeV using a model-independent approach. The TOTEM cross sections, extrapolated to a center-of-mass energy of sqrt[s]=1.96  TeV, are compared with the D0 measurement in the region of the diffractive minimum and the second maximum of the pp cross section. The two data sets disagree at the 3.4σ level and thus provide evidence for the t-channel exchange of a colorless, C-odd gluonic compound, also known as the odderon. We combine these results with a TOTEM analysis of the same C-odd exchange based on the total cross section and the ratio of the real to imaginary parts of the forward elastic strong interaction scattering amplitude in pp scattering for which the significance is between 3.4σ and 4.6σ. The combined significance is larger than 5σ and is interpreted as the first observation of the exchange of a colorless, C-odd gluonic compound.

Interferon γ neutralization reduces blood pressure, uterine artery resistance index, and placental oxidative stress in placental ischemic rats

Preeclampsia (PE) is characterized by maternal hypertension, intrauterine growth restriction, and increased cytolytic natural killer cells (cNKs), which secrete interferon γ (IFNγ). However, the precise role of IFNγ in contributing to PE pathophysiology remains unclear. Using the reduced uterine perfusion pressure (RUPP) rat model of placental ischemia, we tested the hypothesis that neutralization of IFNγ in RUPPs will decrease placental reactive oxygen species (ROS) and improve vascular function resulting in decreased MAP and improved fetal growth. On gestation day (GD) 14, the RUPP procedure was performed and on GDs 15 and 18, a subset of normal pregnant rats (NP) and RUPP rats were injected with 10 μg/kg of an anti-rat IFNγ monoclonal antibody. On GD 18, uterine artery resistance index (UARI) was measured via Doppler ultrasound and on GD 19, mean arterial pressure (MAP) was measured, animals were euthanized, and blood and tissues were collected for analysis. Increased MAP was observed in RUPP rats compared with NP and was reduced in RUPP + anti-IFNγ. Placental ROS was also increased in RUPP rats compared with NP rats and was normalized in RUPP + anti-IFNγ. Fetal and placental weights were reduced in RUPP rats, but were not improved following anti-IFNγ treatment. However, UARI was elevated in RUPP compared with NP rats and was reduced in RUPP + anti-IFNγ. In conclusion, we observed that IFNγ neutralization reduced MAP, UARI, and placental ROS in RUPP recipients. These data suggest that IFNγ is a potential mechanism by which cNKs contribute to PE pathophysiology and may represent a therapeutic target to improve maternal outcomes in PE.

Dissecting nematode resistance regions in soybean revealed pleiotropic effect of soybean cyst and reniform nematode resistance genes

Reniform nematode (RN, Rotylenchulus reniformis Linford & Oliveira) has emerged as one of the most important plant parasitic nematodes of soybean [Glycine max (L.) Merr.]. Planting resistant varieties is the most effective strategy for nematode management. The objective of this study was to identify quantitative trait loci (QTL) for RN resistance in an exotic soybean line, PI 438489B, using two linkage maps constructed from the Universal Soybean Linkage Panel (USLP 1.0) and next-generation whole-genome resequencing (WGRS) technology. Two QTL controlling RN resistance were identified-the soybean cyst nematode (SCN, Heterodera glycines) resistance gene GmSNAP18 at the rhg1 locus and its paralog GmSNAP11. Strong association between resistant phenotype and haplotypes of the GmSNAP11 and GmSNAP18 was observed. The results indicated that GmSNAP11 possibly could have epistatic effect on GmSNAP18, or vice versa, with the presence of a significant correlation in RN resistance of rhg1-a GmSNAP18 vs. rhg1-b GmSNAP18. Most importantly, our preliminary data suggested that GmSNAP18 and GmSNAP11 proteins physically interact in planta, suggesting that they belong to the same pathway for resistance. Unlike GmSNAP18, no indication of GmSNAP11 copy number variation was found. Moreover, gene-based single nucleotide polymorphism (SNP) markers were developed for rapid detection of RN or SCN resistance at these loci. Our analysis substantiates synergic interaction between GmSNAP11 and GmSNAP18 genes and confirms their roles in RN as well as SCN resistance. These results could contribute to a better understanding of evolution and subfunctionalization of genes conferring resistance to multiple nematode species and provide a framework for further investigations.

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.

Dragendorff's reagent: Historical perspectives and current status of a versatile reagent introduced over 150 years ago at the University of Dorpat, Tartu, Estonia

The well-known Dragendorff's reagent (DR) was introduced by an Estonian-German Professor Johann Georg Noel Dragendorff (1836-1898) in the middle of the 19th century (1866). Dragendorff, who was a full-time professor in pharmacy at the university of Dorpat (Tartu) used his reagent originally for the rapid screening of herbal products to find traces of alkaloids. DR is a solution of potassium bismuth iodide composing of basic bismuth nitrate (Bi(NO₃)₃), tartaric acid, and potassium iodide (KI), and when contact with alkaloids DR produces an orange or orange red precipitate. In this review article, we make a short historical overview on the biography and scientific research work of Professor Dragendorff at the University of Dorpat. The chemistry, method of preparation, mechanism of action, and practical uses of DR in various disciplines in various European countries including the Baltic countries (Estonia, Latvia, Lithuania), Finland, Ukraine, Moldova, and in Asia (Vietnam), are also discussed. Over several decades, DR and its modifications have found uses in many new applications and disciplines, and a number of commercial DRs are also currently available on the market. Today, DR is used for example in the production of surfactants, where non-ionic surfactant is precipitated in water solution with modified DR (KBiI₄+BaCl₂+glacial acetic acid). Total six different potassium iodobismuthate (DR) solutions are also presented in the European Pharmacopoeia. In conclusion, DR (after more than 150 years of its invention in Estonia) has still an important role in pharmaceutical and related sciences all over the world.

TILLING-by-Sequencing+ Reveals the Role of Novel Fatty Acid Desaturases (GmFAD2-2s) in Increasing Soybean Seed Oleic Acid Content

Soybean is the second largest source of oil worldwide. Developing soybean varieties with high levels of oleic acid is a primary goal of the soybean breeders and industry. Edible oils containing high level of oleic acid and low level of linoleic acid are considered with higher oxidative stability and can be used as a natural antioxidant in food stability. All developed high oleic acid soybeans carry two alleles; GmFAD2-1A and GmFAD2-1B. However, when planted in cold soil, a possible reduction in seed germination was reported when high seed oleic acid derived from GmFAD2-1 alleles were used. Besides the soybean fatty acid desaturase (GmFAD2-1) subfamily, the GmFAD2-2 subfamily is composed of five members, including GmFAD2-2A, GmFAD2-2B, GmFAD2-2C, GmFAD2-2D, and GmFAD2-2E. Segmental duplication of GmFAD2-1A/GmFAD2-1B, GmFAD2-2A/GmFAD2-2C, GmFAD2-2A/GmFAD2-2D, and GmFAD2-2D/GmFAD2-2C have occurred about 10.65, 27.04, 100.81, and 106.55 Mya, respectively. Using TILLING-by-Sequencing+ technology, we successfully identified 12, 8, 10, 9, and 19 EMS mutants at the GmFAD2-2A, GmFAD2-2B, GmFAD2-2C, GmFAD2-2D, and GmFAD2-2E genes, respectively. Functional analyses of newly identified mutants revealed unprecedented role of the five GmFAD2-2A, GmFAD2-2B, GmFAD2-2C, GmFAD2-2D, and GmFAD2-2E members in controlling the seed oleic acid content. Most importantly, unlike GmFAD2-1 members, subcellular localization revealed that members of the GmFAD2-2 subfamily showed a cytoplasmic localization, which may suggest the presence of an alternative fatty acid desaturase pathway in soybean for converting oleic acid content without substantially altering the traditional plastidial/ER fatty acid production.

Tumor Necrosis Factor-alpha Blockade Improves Uterine Artery Resistance, Maternal Blood Pressure, and Fetal Growth in Placental Ischemic Rats

We recently reported that adoptive transfer of cytolytic Natural Killer cells (cNKs) from the Reduced Uterine Perfusion Pressure (RUPP) rat induces a preeclampsia (PE)-like phenotype in pregnant rats, accompanied by increased TNF-α. The purpose of this study was to investigate a role for increased TNF-α to induce oxidative stress (ROS), decrease nitric oxide (NO) bioavailability, and induce vascular dysfunction as mechanisms of hypertension (HTN) and intrauterine growth restriction (IUGR) in RUPPs. Pregnant Sprague Dawley rats underwent the RUPP or a Sham procedure on gestation day (GD) 14. On GDs 15 and 18, a subset of Sham and RUPP rats received i.p.injections of vehicle or 0.4 mg/kg of Etanercept (ETA), a soluble TNF-α receptor (n = 10/group). On GD18, Uterine Artery Resistance Index (UARI) was measured, and on GD19, mean arterial pressure (MAP), fetal and placental weights were measured, and blood and tissues were processed for analysis. TNF-α blockade normalized the elevated MAP observed RUPP. Additionally, both fetal and placental weights were decreased in RUPP compared to Sham, and were normalized in RUPP + ETA. Placental ROS was also increased in RUPP rats compared to Sham, and remained elevated in RUPP + ETA. Compared to Sham, UARI was elevated in RUPPs while plasma total nitrate was reduced, and these were normalized in ETA treated RUPPs. In conclusion, TNF-α blockade in RUPPs reduced MAP and UARI, improved fetal growth, and increased NO bioavailability. These data suggest that TNF-α regulation of NO bioavailability is a potential mechanism that contributes to PE pathophysiology and may represent a therapeutic target to improve maternal outcomes and fetal growth.