A genome-wide association study of seed protein and oil content in soybean

The Slow Pandemic: Emergence of Antimicrobial Resistance in the Postadvent of SARS-CoV-2 Pandemic

Background: The unprecedented outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has dramatically changed the global approach to public health, emphasizing the importance of measures to control and prevent infections. In response to the COVID-19 crisis, stringent hygiene practices and surface disinfection have become the norm, with an unprecedented surge in the use of disinfectants and antiseptics (DAs). Main Text: While these measures have been crucial in curbing the spread of the virus, an emerging concern has taken center stage: the potential impact of the prolonged and widespread use of antimicrobial compounds in these products on the development of antibiotic resistance. Antimicrobial resistance (AMR) has long been recognized as one of the most pressing global health threats. Quaternary ammonium compounds (QAC) such as benzalkonium chloride, benzethonium chloride, and cetylpyridinium chloride, which are extensively used in DAs formulations, have gained less attention in the context of AMR. Conclusion: A high abundance of QACs was detected in wastewater, and certain bacteria such as Pseudomonas aeruginosa, Acinetobacter baumannii, and Enterococcus species developed resistance to these compounds over time. We analyzed the available evidence from the scientific literature, examining the presence and concentrations of QACs in different water sources, and their resistance mechanisms. This review aimed to shed light on the multifaceted challenges that arise from the dual battle against the COVID-19 pandemic and the ongoing global fight against AMR.

Soybean genome‑wide association study of seed weight, protein, and oil content in the southeastern USA

Soybean is a globally significant legume crop, providing essential protein and oil for human and livestock nutrition. Improving oil and protein content simultaneously without compromising yield has been challenging due to the quantitative nature of these traits and their interrelationships. This study aims to deepen our understanding of the molecular basis soybean of seed weight, protein, and oil content to facilitate marker-assisted breeding to enhance these traits. In this research, a Genome-Wide Association Study (GWAS) was conducted utilizing 285 diverse soybean accessions from maturity group V, employing genotyping through the SoySNP50K platform. These accessions were tested in three environmental conditions of the southeast US for three traits: 100-seed weight, protein, and oil content. The study identified 18, 23, and 26 SNPs significantly associated with 100-seed weight, seed oil, and protein content. Colocalized protein and oil content regions were discovered on chromosomes 15, 16, and 20. Chromosomes 15 and 20 are well documented to have pleiotropic but opposite effects on oil and protein content, but both regions contain genes that affect individual traits, such as FAD2-1 and nodulin MtN21. A 1.92 Mb region on chromosome 11 exhibits a target region to improve oil and seed weight without affecting protein content. This study highlights key genomic regions and candidate genes influencing seed weight, protein, and oil content, with some regions affecting multiple traits. Hence, these findings provide a valuable foundation for marker-assisted selection to optimize seed weight and simultaneously enhance oil and protein content in soybean breeding programs.

Genome-wide DNA methylation patterns in Daphnia magna are not significantly associated with age

BACKGROUND

DNA methylation plays a crucial role in gene regulation and epigenetic inheritance across diverse organisms. Daphnia magna, a model organism in ecological and evolutionary research, has been widely used to study environmental responses, pharmaceutical toxicity, and developmental plasticity. However, its DNA methylation landscape and age-related epigenetic changes remain incompletely understood.

RESULTS

In this study, we characterized DNA methyltransferases (DNMTs) and mapped DNA methylation across the D. magna genome using whole-genome bisulfite sequencing. Our analysis identified three DNMTs: a highly expressed but nonfunctional de novo methyltransferase (DNMT3.1), alongside lowly expressed yet functional de novo methyltransferase (DNMT3.2) and maintenance methyltransferase (DNMT1). D. magna exhibits overall low DNA methylation, targeting primarily CpG dinucleotides. Methylation is sparse at promoters but elevated in the first exons downstream of transcription start sites, with these exons showing hypermethylation relative to adjacent introns. To examine age-associated DNA methylation changes, we analyzed D. magna individuals across multiple life stages. Our results showed no significant global differences in DNA methylation levels between young, mature, and old individuals, nor any age-related clustering in dimensionality reduction analyses. Attempts to construct an epigenetic clock using machine learning models did not yield accurate age predictions, likely due to the overall low DNA methylation levels and lack of robust age-associated methylation changes.

CONCLUSIONS

This study provides a comprehensive characterization of D. magna's DNA methylation landscape and DNMT enzymes, highlighting a distinct pattern of exon-biased CpG methylation. Contrary to prior studies, we found no strong evidence supporting age-associated epigenetic changes, suggesting that DNA methylation may have a limited role in aging in D. magna. These findings enhance our understanding of invertebrate epigenetics and emphasize the need for further research into the interplay between DNA methylation, environmental factors, and gene regulation in D. magna.

Detection of genes associated with soybean protein content using a genome-wide association study

The protein content in soybean seeds serves as a crucial measure of soybean quality. Breeding high-protein varieties remains the most cost-effective and efficient approach to increasing soybean protein levels. Nevertheless, limited research has focused on identifying the genes responsible for high protein content among the diverse soybean cultivars. To address this gap, a genome-wide association study (GWAS) was conducted on 455 soybean varieties with varying protein content to predict and validate novel genes involved in regulating protein levels in soybean seeds. Protein content data were obtained from three distinct environments, along with three environmental variables derived from oil content, which is closely related to protein levels. Genotyping was performed using the SoySNP180k BeadChip, yielding genotype data for 63,306 non-redundant single nucleotide polymorphisms (SNPs). Five multi-locus GWAS methods were employed, resulting in the identification of 81 significant quantitative trait nucleotides (QTNs), of which 37 QTNs detected across different methods and environments were further analyzed. Moreover, the simulation platform Blib was used to conduct single-crossing simulation breeding on 81 QTN loci for actual breeding prediction. Haplotype analysis based on re-sequencing data confirmed 2 genes closely linked to protein synthesis, providing a theoretical basis for breeding high-protein soybean varieties and developing molecular breeding strategies.

Characterization of a G. max × G. soja nested association mapping population and identification of loci controlling seed composition traits from wild soybean

Wild soybean (Glycine soja Siebold & Zucc.) has valuable genetic diversity for improved disease resistance, stress tolerance, seed protein content and seed sulfur-containing amino acid concentrations. Many studies have reported loci controlling seed composition traits based on cultivated soybean populations, but wild soybean has been largely overlooked. In this study, a nested association mapping (NAM) population consisting of 10 families and 1107 recombinant inbred lines was developed by crossing 10 wild accessions with the common cultivar NC-Raleigh. Seed composition of the F6 generation grown at two locations was phenotyped, and genetic markers were identified for each line. The average number of recombination events in the wild soybean-derived population was significantly higher than that in the cultivated soybean-derived population, which resulted in a higher resolution for QTL mapping. Segregation bias in almost all NAM families was significantly biased toward the alleles of the wild soybean parent. Through single-family linkage mapping and association analysis of the entire NAM population, new QTLs with positive allele effects were identified from wild parents, including 5, 6, 18, 9, 16, 17 and 20 for protein content, oil content, total protein and oil content, methionine content, cysteine content, lysine content and threonine content, respectively. Candidate genes associated with these traits were identified based on gene annotations and gene expression levels in different tissues. This is the first study to reveal the genetic characteristics of wild soybean-derived populations, landscapes and the extent of effects of QTLs and candidate genes controlling traits from different wild soybean parents.

Accelerating Ligand Discovery for Insect Odorant Receptors

Odorant receptors (ORs) are main actors of the insects peripheral olfactory system, making them prime targets for pest control through olfactory disruption. Traditional methods employed in the context of chemical ecology for identifying OR ligands rely on analyzing compounds present in the insect's environment or screening molecules with structures similar to known ligands. However, these approaches can be time-consuming and constrained by the limited chemical space they explore. Recent advances in OR structural understanding, coupled with scientific breakthroughs in protein structure prediction, have facilitated the application of Structure-Based Virtual Screening (SBVS) techniques for accelerated ligand discovery. Here, we report the first successful application of SBVS to insect ORs. We developed a unique workflow that combines molecular docking predictions, in vivo validation and behavioral assays to identify new behaviorally active volatiles for non-pheromonal receptors. This work serves as a proof of concept, laying the groundwork for future studies and highlighting the need for improved computational approaches. Finally, we propose a simple model for predicting receptor response spectra based on the hypothesis that the binding pocket properties partially encode this information, as suggested by our results on Spodoptera littoralis ORs.

OsLOX1 positively regulates seed vigor and drought tolerance in rice

The lipoxygenase (LOX) gene family is widely distributed in plants, and its activity is closely associated with seed viability and stress tolerance. In this study, we cloned the rice(Oryza sativa)lipoxygenase gene OsLOX1, a key participant in the 13-lipoxygenase metabolic pathway. Our primary focus was to investigate its role in mediating responses to drought stress and seed germination in rice. Histochemical staining and qPCR analysis indicated that the expression level of OsLOX1 was relatively high in leaves and early germinating seeds. Our findings revealed that mutant lines with CRISPR/Cas9-induced knockout of OsLOX1 exhibited reduced tolerance to drought stress compared with the wild-type. This was accompanied by elevated levels of H2O2 and malondialdehyde, and a decrease in the expression levels of genes associated with antioxidant enzymes. Furthermore, knockout of OsLOX1 reduced the longevity of rice seeds increased H2O2 and MDA levels, and decreased the activities of the antioxidant enzymes superoxide dismutase and catalase, compared with the wild-type. These findings demonstrated that OsLOX1 positively regulated rice seed vigor and drought stress.

Multiscale molecular modeling of chromatin with MultiMM: From nucleosomes to the whole genome

Motivation: We present a user-friendly 3D chromatin simulation model for the human genome based on OpenMM, addressing the challenges posed by existing models with use-specific implementations. Our approach employs a multi-scale energy minimization strategy, capturing chromatin's hierarchical structure. Initiating with a Hilbert curve-based structure, users can input files specifying nucleosome positioning, loops, compartments, or subcompartments. Results: The model utilizes an energy minimization approach with a large choice of numerical integrators, providing the entire genome's structure within minutes. Output files include the generated structures for each chromosome, offering a versatile and accessible tool for chromatin simulation in bioinformatics studies. Furthermore, MultiMM is capable of producing nucleosome-resolution structures by making simplistic geometric assumptions about the structure and the density of nucleosomes on the DNA. Code availability: Open-source software and the manual are freely available on https://github.com/SFGLab/MultiMM or via pip https://pypi.org/project/MultiMM/.

Identification of QTL-allele systems of seed size and oil content for simultaneous genomic improvement in Northeast China soybeans

Northeast China (NEC) is the major production area for soybeans in China, whereas its soybean germplasm has played key roles in world soybean production, especially in the Americas. For plant breeding, genomic selection involves two stages, cross design and progeny selection, with the former determining the latter's potential. In NEC, one of the major breeding purposes is for 100-seed weight (100SW) and seed oil content (SOC). A diverse sample with 361 NEC soybean germplasm accessions was evaluated for their 100SW and SOC in Tieling, Liaoning, China. Both traits exhibited significant phenotypic, genotypic, and G × E variation, with a trait heritability of 82.38% and 86.26%, respectively. A restricted two-stage multi-locus genome-wide association study (RTM-GWAS) with 15,501 SNPLDB (SNP linkage disequilibrium block) markers identified 80 and 92 QTLs with 230 and 299 alleles for 100SW and SOC, respectively. Corresponding to some increase of the two traits, almost all the alleles in the early maturity groups (MG 0 + 00 + 000) were inherited from the late MGs (MG I+II+III), indicating that genetic recombination was the major motivator in addition to a few allele emergence and some allele exclusion fluctuations among early MGs. Using the 95th percentile as indicator, the prediction of recombination potentials showed that 30.43 g 100SW and 27.73% SOC might be achieved, respectively. Three strategies of simultaneous genomic improvement of both traits in designing optimal crosses, namely, 100SW-first, SOC-first, and 100SW-SOC-balance, were proved to be efficient. Thus, the optimal cross design could be extended to multiple traits based on a relatively thorough identification of the QTL-alleles using RTM-GWAS.

Advances in Soybean Genetic Improvement

The soybean (Glycine max) is a globally important crop due to its high protein and oil content, which serves as a key resource for human and animal nutrition, as well as bioenergy production. This review assesses recent advancements in soybean genetic improvement by conducting an extensive literature analysis focusing on enhancing resistance to biotic and abiotic stresses, improving nutritional profiles, and optimizing yield. We also describe the progress in breeding techniques, including traditional approaches, marker-assisted selection, and biotechnological innovations such as genetic engineering and genome editing. The development of transgenic soybean cultivars through Agrobacterium-mediated transformation and biolistic methods aims to introduce traits such as herbicide resistance, pest tolerance, and improved oil composition. However, challenges remain, particularly with respect to genotype recalcitrance to transformation, plant regeneration, and regulatory hurdles. In addition, we examined how wild soybean germplasm and polyploidy contribute to expanding genetic diversity as well as the influence of epigenetic processes and microbiome on stress tolerance. These genetic innovations are crucial for addressing the increasing global demand for soybeans, while mitigating the effects of climate change and environmental stressors. The integration of molecular breeding strategies with sustainable agricultural practices offers a pathway for developing more resilient and productive soybean varieties, thereby contributing to global food security and agricultural sustainability.

A Dominance Hypothesis Argument for Historical Genetic Gains and the Fixation of Heterosis in Octoploid Strawberry

Heterosis was the catalyst for the domestication of cultivated strawberry (Fragaria × ananassa), an interspecific hybrid species that originated in the 1700s. The hybrid origin was discovered because the phenotypes of spontaneous hybrids transgressed those of their parent species. The transgressions included fruit yield increases and other genetic gains in the twentieth century that sparked the global expansion of strawberry production. The importance of heterosis to the agricultural success of the hybrid species, however, has remained a mystery. Here we show that heterosis has disappeared (become fixed) among improved hybrids within a population (the California population) that has been under long-term selection for increased fruit yield, weight, and firmness. We found that the highest yielding hybrids are among the most highly inbred (59-79%), which seems counterintuitive for a highly heterozygous, outbreeder carrying heavy genetic loads. Although faint remnants of heterosis were discovered, the between-parent allele frequency differences and dispersed favorable dominant alleles necessary for heterosis have decreased nearly genome-wide within the California population. Conversely, heterosis was prevalent and significant among wide hybrids, especially for fruit count, a significant driver of genetic gains for fruit yield. We attributed the disappearance (fixation) of heterosis within the California population to increased homozygosity of favorable dominant alleles and inbreeding associated with selection, random genetic drift, and selective sweeps. Despite historical inbreeding, the highest yielding hybrids reported to-date are estimated to be heterozygous for 20,370-44,280 of 97,000-108,000 genes in the octoploid genome, the equivalent of an entire diploid genome or more.

Consanguinity and Occurrence of Monogenic Diseases in a Single Tertiary Centre in Riyadh, Saudi Arabia: A 2 Years Cross-Sectional Study

Background

Consanguinity, or the practice of marrying close relatives, is a common cultural tradition in Saudi Arabia, with rates among the highest in the world. This practice has significant implications for the prevalence and distribution of major single genetic defects and chromosomal abnormalities within the Saudi population.

Methods

Herein, using the BESTCare electronic medical record system (designed to streamline hospital operations, enhance patient care, and improve the overall efficiency of healthcare services; bestcare.ezcaretech.com) in a single tertiary centre, King Abdullah Specialized Children Hospital (KASCH) in Riyadh, Saudi Arabia, we performed a cross-sectional study for all patients referred to the hospital from the 1st January 2020 until 1st January 2022.

Results

The present study, which included 1100 individuals, found a high prevalence of consanguinity (64%) and a significant proportion of third-degree relatives (69%). The mean age of participants was 12.24 years, and the diagnostic rate using advanced molecular genetics techniques was 45%, with whole exome sequencing (WES) being the most common method (43%). The study also noted a significant delay in diagnosis for more than a year in 16% of cases, with a common neurodevelopmental phenotype (18%).

Conclusion

In conclusion, we revealed the prevalence of consanguineous marriages in the KASCH hospital in Riyadh, Saudi Arabia. We also highlighted the most frequently referred phenotype. These findings are consistent with previous research on the prevalence and impact of consanguinity on rare genetic disorders.

A sucrose-binding protein and β-conglycinins regulate soybean seed protein content and control multiple seed traits

Expanded agriculture production is required to support the world's population but can impose substantial environmental and climate change costs, particularly with intensifying animal production and protein demand. Shifting from an animal- to a plant-based protein diet has numerous health benefits. Soybean (Glycine max [L.] Merr.) is a major source of protein for human food and animal feed; improved soybean protein content and amino acid composition could provide high-quality soymeal for animal feed, healthier human foods, and a reduced carbon footprint. Nonetheless, during the soybean genome evolution, a balance was established between the amount of seed protein, oil, and carbohydrate content, burdening the development of soybean cultivars with high proteins (HPs). We isolated 2 high-seed protein soybean mutants, HP1 and HP2, with improved seed amino acid composition and stachyose content, pointing to their involvement in controlling seed rebalancing phenomenon. HP1 encodes β-conglycinin (GmCG-1) and HP2 encodes sucrose-binding protein (GmSBP-1), which are both highly expressed in soybean seeds. Mutations in GmSBP-1, GmCG-1, and the paralog GmCG-2 resulted in increased protein levels, confirming their role as general regulators of seed protein content, amino acid seed composition, and seed vigor. Biodiversity analysis of GmCG and GmSBP across 108 soybean accessions revealed haplotypes correlated with protein and seed carbohydrate content. Furthermore, our data revealed an unprecedented role of GmCG and GmSBP proteins in improving seed vigor, crude protein, and amino acid digestibility. Since GmSBP and GmCG are present in most seed plants analyzed, these genes could be targeted to improve multiple seed traits.

Genome-Wide Association Studies and QTL Mapping Reveal a New Locus Associated with Resistance to Bacterial Pustule Caused by Xanthomonas citri pv. glycines in Soybean

Bacterial pustule (BP), caused by Xanthomonas citri pv. glycines, is an important disease that, under favorable conditions, can drastically affect soybean production. We performed a genome-wide association study (GWAS) with a panel containing Brazilian and American cultivars, which were screened qualitatively and quantitatively against two Brazilian X. citri isolates (IBS 333 and IBS 327). The panel was genotyped using a genotyping by sequencing (GBS) approach, and we identified two main new regions in soybeans associated with X. citri resistance on chromosomes 6 (IBS 333) and 18 (IBS 327), different from the traditional rxp gene located on chromosome 17. The region on chromosome 6 was also detected by QTL mapping using a biparental cross between Williams 82 (R) and PI 416937 (S), showing that Williams 82 has another recessive resistance gene besides rxp, which was also detected in nine BP-resistant ancestors of the Brazilian cultivars (including CNS, S-100), based on haplotype analysis. Furthermore, we identified additional SNPs in strong LD (0.8) with peak SNPs by exploring variation available in WGS (whole genome sequencing) data among 31 soybean accessions. In these regions in strong LD, two candidate resistance genes were identified (Glyma.06g311000 and Glyma.18g025100) for chromosomes 6 and 18, respectively. Therefore, our results allowed the identification of new chromosomal regions in soybeans associated with BP disease, which could be useful for marker-assisted selection and will enable a reduction in time and cost for the development of resistant cultivars.

Agile Genetics: Single gene resolution without the fuss

Gene discovery reveals new biology, expands the utility of marker-assisted selection, and enables targeted mutagenesis. Still, such discoveries can take over a decade. We present a general strategy, "Agile Genetics," that uses nested, structured populations to overcome common limits on gene resolution. Extensive simulation work on realistic genetic architectures shows that, at population sizes of >5000 samples, single gene-resolution can be achieved using bulk segregant pools. At this scale, read depth and technical replication become major drivers of resolution. Emerging enrichment methods to address coverage are on the horizon; we describe one possibility - iterative depth sequencing (ID-seq). In addition, graph-based pangenomics in experimental populations will continue to maximize accuracy and improve interpretation. Based on this merger of agronomic scale with molecular and bioinformatic innovation, we predict a new age of rapid gene discovery.

Glycine rich proteins of ticks: more than a cement component

Glycine-rich proteins (GRPs) are arbitrarily defined as those containing 20% or more glycine residues and constitute a superfamily divided into subfamilies based on their structure and/or function. GRPs have been identified in a diverse array of organisms and have been shown to possess a number of distinctive biological characteristics, including nucleic acid binding, adhesive glue-like properties, antimicrobial activity, involvement in the stress response and in the formation of cuticle components. In ticks, their expression has been described and studied mainly in the salivary glands, and their primary function is usually associated with cement formation and/or structure. Conversely, several GRPs are present in all tick developmental stages, and the expression of many GRP genes is modulated by physiological processes and immune challenges, such as feeding and pathogen infection. Considering that some tick GRPs appear to play essential roles in the tick life cycle, they have been evaluated as immune targets, with a focus on their potential application in vaccine development. This review highlights the roles that tick GRPs may perform beyond the formation and maintenance of the cement scaffold, including structural characterization, locations and functional relevance, hypothetical functions, and their potential use in anti-tick vaccine development.

Across-environment seed protein stability and genetic architecture of seed components in soybean

The recent surge in the plant-based protein market has resulted in high demands for soybean genotypes with improved grain yield, seed protein and oil content, and essential amino acids (EAAs). Given the quantitative nature of these traits, complex interactions among seed components, as well as between seed components and environmental factors and management practices, add complexity to the development of desired genotypes. In this study, the across-environment seed protein stability of 449 genetically diverse plant introductions was assessed, revealing that genotypes may display varying sensitivities to such environmental stimuli. The EAAs valine, phenylalanine, and threonine showed the highest variable importance toward the variation in stability, while both seed protein and oil contents were among the explanatory variables with the lowest importance. In addition, 56 single nucleotide polymorphism (SNP) markers were significantly associated with various seed components. Despite the strong phenotypic Pearson's correlation observed among most seed components, many independent genomic regions associated with one or few seed components were identified. These findings provide insights for improving the seed concentration of specific EAAs and reducing the negative correlation between seed protein and oil contents.

Polyphenols as Therapeutics in Respiratory Diseases: Moving from Preclinical Evidence to Potential Clinical Applications

Respiratory diseases are the most common and severe health complication and a leading cause of death worldwide. Despite breakthroughs in diagnosis and treatment, few safe and effective therapeutics have been reported. Phytochemicals are gaining popularity due to their beneficial effects and low toxicity. Polyphenols are secondary metabolites with high molecular weights found at high levels in natural food sources such as fruits, vegetables, grains, and citrus seeds. Over recent decades, polyphenols and their beneficial effects on human health have been the subject of intense research, with notable successes in preventing major chronic non-communicable diseases. Many respiratory syndromes can be treated effectively with polyphenolic supplements, including acute lung damage, pulmonary fibrosis, asthma, pulmonary hypertension, and lung cancer. This review summarizes the role of polyphenols in respiratory conditions with sufficient experimental data, highlights polyphenols with beneficial effects for each, and identifies those with therapeutic potential and their underlying mechanisms. Moreover, clinical studies and future research opportunities in this area are discussed.

IMA Genome - F19 : A genome assembly and annotation guide to empower mycologists, including annotated draft genome sequences of Ceratocystis pirilliformis, Diaporthe australafricana, Fusarium ophioides, Paecilomyces lecythidis, and Sporothrix stenoceras

The pace at which Next Generation Sequence data is being produced continues to accelerate as technology improves. As a result, such data are increasingly becoming accessible to biologists outside of the field of bioinformatics. In contrast, access to training in the methods of genome assembly and annotation are not growing at a similar rate. In this issue, we report on a Genome Assembly Workshop for Mycologists that was held at the Forestry and Agricultural Biotechnology Institute (FABI) at the University of Pretoria, South Africa and make available the 12 draft genome sequences emanating from the event. With the aim of making the process of genome assembly and annotation more accessible to biologists, we provide a step-by-step guide to both genome assembly and annotation, intended to encourage and empower mycologists to use genome data in their research.

An updated view of bacterial endophytes as antimicrobial agents against plant and human pathogens

Bacterial endophytes are a crucial component of the phytomicrobiome, playing an essential role in agriculture and industries. Endophytes are a rich source of bioactive compounds, serving as natural antibiotics that can be effective in combating antibiotic resistance in pathogens. These bacteria interact with host plants through various processes such as quorum sensing, chemotaxis, antibiosis, and enzymatic activity. The current paper focuses on how plants benefit extensively from endophytic bacteria and their symbiotic relationship in which the microbes enhance plant growth, nitrogen fixation, increase nutrient uptake, improve defense mechanisms, and act as antimicrobial agents against pathogens. Moreover, it highlights some of the bioactive compounds produced by endophytes.

GWAS and WGCNA Analysis Uncover Candidate Genes Associated with Oil Content in Soybean

Soybean vegetable oil is an important source of the human diet. However, the analysis of the genetic mechanism leading to changes in soybean oil content is still incomplete. In this study, a total of 227 soybean materials were applied and analyzed by a genome-wide association study (GWAS). There are 44 quantitative trait nucleotides (QTNs) that were identified as associated with oil content. A total of six, four, and 34 significant QTN loci were identified in Xiangyang, Hulan, and Acheng, respectively. Of those, 26 QTNs overlapped with or were near the known oil content quantitative trait locus (QTL), and 18 new QTNs related to oil content were identified. A total of 594 genes were located near the peak single nucleotide polymorphism (SNP) from three tested environments. These candidate genes exhibited significant enrichment in tropane, piperidine, and pyridine alkaloid biosynthesiss (ko00960), ABC transporters (ko02010), photosynthesis-antenna proteins (ko00196), and betalain biosynthesis (ko00965). Combined with the GWAS and weighted gene co-expression network analysis (WGCNA), four candidate genes (Glyma.18G300100, Glyma.11G221100, Glyma.13G343300, and Glyma.02G166100) that may regulate oil content were identified. In addition, Glyma.18G300100 was divided into two main haplotypes in the studied accessions. The oil content of haplotype 1 is significantly lower than that of haplotype 2. Our research findings provide a theoretical basis for improving the regulatory mechanism of soybean oil content.

The impact of Elaeagnus angustifolia root exudates on Parafrankia soli NRRL B-16219 exoproteome

Root exudates from host plant species are known to play a critical role in the establishment and maintenance of symbiotic relationships with soil bacteria. In this study, we investigated the impact of root exudates from compatible host plant species; Elaeagnus angustifolia on the exoproteome of Parafrankia soli strain NRRL B-16219. A total of 565 proteins were evidenced as differentially abundant, with 32 upregulated and 533 downregulated in presence of the plant exudates. Analysis of the function of these proteins suggests that the bacterial strain is undergoing a complex metabolic reprogramming towards a new developmental phase elicited in presence of host plant root exudates. The upregulation of Type II/IV secretion system proteins among the differentially expressed proteins indicates their possible role in infecting the host plant, as shown for some rhizobia. Additionally, EF-Tu, proteins upregulated in this study, may function as an effector for the T4SSs and trigger plant defense responses. These findings suggest that Parafrankia soli may use EF-Tu to infect the actinorhizal host plant and pave the way for further investigations of the molecular mechanisms underlying the establishment of symbiotic relationships.

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

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

Genome-wide association study for yield-related traits in faba bean (Vicia faba L.)

Yield is the most complex trait to improve crop production, and identifying the genetic determinants for high yield is a major issue in breeding new varieties. In faba bean (Vicia faba L.), quantitative trait loci (QTLs) have previously been detected in studies of biparental mapping populations, but the genes controlling the main trait components remain largely unknown. In this study, we investigated for the first time the genetic control of six faba bean yield-related traits: shattering (SH), pods per plant (PP), seeds per pod (SP), seeds per plant (SPL), 100-seed weight (HSW), and plot yield (PY), using a genome-wide association study (GWAS) on a worldwide collection of 352 homozygous faba bean accessions with the aim of identifying markers associated with them. Phenotyping was carried out in field trials at three locations (Spain, United Kingdom, and Serbia) over 2 years. The faba bean panel was genotyped with the Affymetrix faba bean SNP-chip yielding 22,867 SNP markers. The GWAS analysis identified 112 marker-trait associations (MTAs) in 97 candidate genes, distributed over the six faba bean chromosomes. Eight MTAs were detected in at least two environments, and five were associated with multiple traits. The next step will be to validate these candidates in different genetic backgrounds to provide resources for marker-assisted breeding of faba bean yield.

A genome-wide study of the lipoxygenase gene families in Medicago truncatula and Medicago sativa reveals that MtLOX24 participates in the methyl jasmonate response

BACKGROUND

Lipoxygenase (LOX) is a multifunctional enzyme that is primarily related to plant organ growth and development, biotic and abiotic stress responses, and production of flavor-associated metabolites. In higher plants, the LOX family encompasses several isozymes with varying expression patterns between tissues and developmental stages. These affect processes including seed germination, seed storage, seedling growth, fruit ripening, and leaf senescence. LOX family genes have multiple functions in response to hormones such as methyl jasmonate (MeJA) and salicylic acid.

RESULTS

In this study, we identified 30 and 95 LOX homologs in Medicago truncatula and Medicago sativa, respectively. These genes were characterized with analyses of their basic physical and chemical properties, structures, chromosomal distributions, and phylogenetic relationships to understand structural variations and their physical locations. Phylogenetic analysis was conducted for members of the three LOX subfamilies (9-LOX, type I 13-LOX, and type II 13-LOX) in Arabidopsis thaliana, Glycine max, M. truncatula, and M. sativa. Analysis of predicted promoter elements revealed several relevant cis-acting elements in MtLOX and MsLOX genes, including abscisic acid (ABA) response elements (ABREs), MeJA response elements (CGTCA-motifs), and antioxidant response elements (AREs). Cis-element data combined with transcriptomic data demonstrated that LOX gene family members in these species were most likely related to abiotic stress responses, hormone responses, and plant development. Gene expression patterns were confirmed via quantitative reverse transcription PCR. Several MtLOX genes (namely MtLOX15, MtLOX16, MtLOX20, and MtLOX24) belonging to the type I 13-LOX subfamily and other LOX genes (MtLOX7, MtLOX11, MsLOX23, MsLOX87, MsLOX90, and MsLOX94) showed significantly different expression levels in the flower tissue, suggesting roles in reproductive growth. Type I 13-LOXs (MtLOX16, MtLOX20, MtLOX21, MtLOX24, MsLOX57, MsLOX84, MsLOX85, and MsLOX94) and type II 13-LOXs (MtLOX5, MtLOX6, MtLOX9, MtLOX10, MsLOX18, MsLOX23, and MsLOX30) were MeJA-inducible and were predicted to function in the jasmonic acid signaling pathway. Furthermore, exogenous MtLOX24 expression in Arabidopsis verified that MtLOX24 was involved in MeJA responses, which may be related to insect-induced abiotic stress.

CONCLUSIONS

We identified six and four LOX genes specifically expressed in the flowers of M. truncatula and M. sativa, respectively. Eight and seven LOX genes were induced by MeJA in M. truncatula and M. sativa, and the LOX genes identified were mainly distributed in the type I and type II 13-LOX subfamilies. MtLOX24 was up-regulated at 8 h after MeJA induction, and exogenous expression in Arabidopsis demonstrated that MtLOX24 promoted resistance to MeJA-induced stress. This study provides valuable new information regarding the evolutionary history and functions of LOX genes in the genus Medicago.

Identification of adult resistant genes to stripe rust in wheat from southwestern China based on GWAS and WGCNA analysis

KEY MESSAGE

In this study, genome-wide association studies combined with transcriptome data analysis were utilized to reveal potential candidate genes for stripe rust resistance in wheat, providing a basis for screening wheat varieties for stripe rust resistance. Wheat stripe rust, which is caused by the wheat stripe rust fungus (Puccinia striiformis f. sp. tritici, Pst) is one of the world's most devastating diseases of wheat. Genetic resistance is the most effective strategy for controlling diseases. Although wheat stripe rust resistance genes have been identified to date, only a few of them confer strong and broad-spectrum resistance. Here, the resistance of 335 wheat germplasm resources (mainly wheat landraces) from southwestern China to wheat stripe rust was evaluated at the adult stage. Combined genome-wide association study (GWAS) and weighted gene co-expression network analysis (WGCNA) based on RNA sequencing from stripe rust resistant accession Y0337 and susceptible accession Y0402, five candidate resistance genes to wheat stripe rust (TraesCS1B02G170200, TraesCS2D02G181000, TraesCS4B02G117200, TraesCS6A02G189300, and TraesCS3A02G122300) were identified. The transcription level analyses showed that these five genes were significantly differentially expressed between resistant and susceptible accessions post inoculation with Pst at different times. These candidate genes could be experimentally transformed to validate and manipulate fungal resistance, which is beneficial for the development of the wheat cultivars resistant to stripe rust.

Gene expression profile analysis of subregions of the adult female reproductive tract in the brown anole, Anolis sagrei

In brief

Modes of reproduction across limbed vertebrates are diverse, but the molecular mechanisms required for the development and maintenance of reproductive tract tissue architecture are poorly understood. This paper describes gene expression changes across the regions of the reproductive tract of the adult female brown anole, Anolis sagrei.

Abstract

The morphological diversity and functional role of the organs of the female reproductive system across tetrapods (limbed vertebrates) are relatively poorly understood. Although some features are morphologically similar, species-specific modification makes comparisons between species and inference about evolutionary origins challenging. In combination with the study of morphological changes, studying differences in gene expression in the adult reproductive system in diverse species can clarify the function of each organ. Here, we use the brown anole, Anolis sagrei, to study gene expression differences within the reproductive tract of the adult female. We generated gene expression profiles of four biological replicates of the three regions of the female reproductive tract, the infundibulum, glandular uterus, and nonglandular uterus, by RNA-sequencing. We aligned reads to the recently published A. sagrei genome and identified significantly differentially expressed genes between the regions using DESeq2. Each organ expressed approximately 14,600 genes, and comparison of gene expression profiles between organs revealed between 367 and 883 differentially expressed genes. We identify shared and region-specific transcriptional signatures for the three regions and compare gene expression in the brown anole reproductive tract to known gene expression patterns in other tetrapods. We find that genes in the Hox cluster have an anterior-posterior, collinear expression pattern as has been described in mammals. We also define a secretome for the glandular uterus. These data provide fundamental information for functional studies of the reproductive tract organs in the brown anole and an important phylogenetic anchor for comparative studies of the evolution of the female reproductive tract.

Transcriptomic Response of the Atlantic Surfclam (Spisula solidissima) to Acute Heat Stress

There is clear evidence that the oceans are warming due to anthropogenic climate change, and the northeastern coast of USA contains some of the fastest warming areas. This warming is projected to continue with serious biological and social ramifications for fisheries and aquaculture. One species particularly vulnerable to warming is the Atlantic surfclam (Spisula solidissima). The surfclam is a critically important species, linking marine food webs and supporting a productive, lucrative, and sustainable fishery. The surfclam is also emerging as an attractive candidate for aquaculture diversification, but the warming of shallow coastal farms threatens the expansion of surfclam aquaculture. Little is known about the adaptive potential of surfclams to cope with ocean warming. In this study, the surfclam transcriptome under heat stress was examined. Two groups of surfclams were subjected to heat stress to assess how artificial selection may alter gene expression. One group of clams had been selected for greater heat tolerance (HS) and the other was composed of random control clams (RC). After a 6-h exposure to 16 or 29 °C, gill transcriptome expression profiles of the four temperature/group combinations were determined by RNA sequencing and compared. When surfclams experienced heat stress, they exhibited upregulation of heat shock proteins (HSPs), inhibitors of apoptosis (IAPs), and other stress-response related genes. RC clams differentially expressed 1.7 times more genes than HS clams, yet HS clams had a stronger response of key stress response genes, including HSPs, IAPs, and genes involved with mitigating oxidative stress. The findings imply that the HS clams have a more effective response to heat stress after undergoing the initial selection event due to genetic differences created by the selection, epigenetic memory of the first heat shock, or both. This work provides insights into how surfclams adapt to heat stress and should inform future breeding programs that attempt to breed surfclam for greater heat tolerance, and ultimately bring greater resiliency to shellfish farms.

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

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

Improving fraud detection with semi-supervised topic modeling and keyword integration

Fraud detection through auditors' manual review of accounting and financial records has traditionally relied on human experience and intuition. However, replicating this task using technological tools has represented a challenge for information security researchers. Natural language processing techniques, such as topic modeling, have been explored to extract information and categorize large sets of documents. Topic modeling, such as latent Dirichlet allocation (LDA) or non-negative matrix factorization (NMF), has recently gained popularity for discovering thematic structures in text collections. However, unsupervised topic modeling may not always produce the best results for specific tasks, such as fraud detection. Therefore, in the present work, we propose to use semi-supervised topic modeling, which allows the incorporation of specific knowledge of the study domain through the use of keywords to learn latent topics related to fraud. By leveraging relevant keywords, our proposed approach aims to identify patterns related to the vertices of the fraud triangle theory, providing more consistent and interpretable results for fraud detection. The model's performance was evaluated by training with several datasets and testing it with another one that did not intervene in its training. The results showed efficient performance averages with a 7% increase in performance compared to a previous job. Overall, the study emphasizes the importance of deepening the analysis of fraud behaviors and proposing strategies to identify them proactively.

Favorable Loci Identified for Stripe Rust Resistance in Chinese Winter Wheat Accessions via Genome-Wide Association Study

Stripe rust (or yellow rust), caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most devastating diseases of wheat worldwide. Currently, the utilization of resistant cultivars is the most viable way to reduce yield losses. In this study, a panel of 188 wheat accessions from China was evaluated for stripe rust resistance, and genome-wide association studies were performed using high-quality Diversity Arrays Technology markers. According to the phenotype and genotype data, a total of 26 significant marker-trait associations were identified, representing 18 quantitative trait loci (QTLs) on chromosomes 1B, 2A, 2B, 3A, 3B, 5A, 5B, 6B, 7B, and 7D. Of the 18 QTLs, almost all were associated with adult plant resistance (APR) except QYr.nwsuaf-6B.2, which was associated with all-stage resistance (also known as seedling resistance). Three of the 18 QTLs were mapped far from previously identified Pst resistance genes and QTLs and were considered potentially new loci. The other 15 QTLs were mapped close to known resistance genes and QTLs. Subsequent haplotype analysis for QYr.nwsuaf-2A and QYr.nwsuaf-7B.3 revealed the degrees of resistance of the panel in the APR stage. In summary, the favorable alleles identified in this study may be useful in breeding for disease resistance to stripe rust.

Introgression of a Danbaekkong high-protein allele across different genetic backgrounds in soybean

Soybean meal is a major component of livestock feed due to its high content and quality of protein. Understanding the genetic control of protein is essential to develop new cultivars with improved meal protein. Previously, a genomic region on chromosome 20 significantly associated with elevated protein content was identified in the cultivar Danbaekkong. The present research aimed to introgress the Danbaekkong high-protein allele into elite lines with different genetic backgrounds by developing and deploying robust DNA markers. A multiparent population consisting of 10 F5-derived populations with a total of 1,115 recombinant inbred lines (RILs) was developed using "Benning HP" as the donor parent of the Danbaekkong high-protein allele. A new functional marker targeting the 321-bp insertion in the gene Glyma.20g085100 was developed and used to track the Danbaekkong high-protein allele across the different populations and enable assessment of its effect and stability. Across all populations, the high-protein allele consistently increased the content, with an increase of 3.3% in seed protein. A total of 103 RILs were selected from the multiparent population for yield testing in five environments to assess the impact of the high-protein allele on yield and to enable the selection of new breeding lines with high protein and high yield. The results indicated that the high-protein allele impacts yield negatively in general; however, it is possible to select high-yielding lines with high protein content. An analysis of inheritance of the Chr 20 high-protein allele in Danbaekkong indicated that it originated from a Glycine soja line (PI 163453) and is the same as other G. soja lines studied. A survey of the distribution of the allele across 79 G. soja accessions and 35 Glycine max ancestors of North American soybean cultivars showed that the high-protein allele is present in all G. soja lines evaluated but not in any of the 35 North American soybean ancestors. These results demonstrate that G. soja accessions are a valuable source of favorable alleles for improvement of protein composition.

Overexpression of PavbHLH28 from Prunus avium enhances tolerance to cold stress in transgenic Arabidopsis

BACKGROUND

The basic helix-loop-helix (bHLH) gene family is one of plants' largest transcription factor families. It plays an important role in regulating plant growth and abiotic stress response.

RESULTS

In this study, we determined that the PavbHLH28 gene participated in cold resistance. The PavbHLH28 gene was located in the nucleus and could be induced by low temperature. Under the treatment of ABA, PEG, and GA3, the transcript level of PavbHLH28 was affected. At low temperature, overexpression of the PavbHLH28 gene enhanced the cold resistance of plants with higher proline content, lower electrolyte leakage (EL) and malondialdehyde (MDA) content. Compared with the WT plants, the transgenic plants accumulated fewer reactive oxygen species (ROS), and the activity and expression levels of antioxidant enzymes were significantly increased. The expression of proline synthesis enzyme genes was up-regulated, and the transcripts levels of degradation genes were significantly down-regulated. The transcripts abundance of the cold stressed-related genes in the C-repeat binding factor (CBF) pathway was not significantly different between WT plants and transgenic plants after cold stress. Moreover, the PavbHLH28 could directly bind to the POD2 gene promoter and promote its gene expression.

CONCLUSIONS

Overall, PavbHLH28 enhanced the cold resistance of transgenic plants through a CBF-independent pathway, which may be partly related to ROS scavenging.

Antilisterial activity of raw sheep milk from two native Epirus breeds: Culture-dependent identification, bacteriocin gene detection and primary safety evaluation of the antagonistic LAB biota

Raw milk from native small ruminant breeds in Epirus, Greece, is a valuable natural source of autochthonous lactic acid bacteria (LAB) strains with superior biotechnological properties. In this study, two bulk milks (RM1, RM2) from two local sheep yards, intended for traditional Kefalotyri cheese production, were preselected for bacteriocin-like antilisterial activity by in vitro tests. Their antagonistic LAB biota was quantified followed by polyphasic (16S rRNA gene sequencing; IGS for Enterococcus; a multiplex-PCR for Leuconostoc) identification of 42 LAB (RM1/18; RM2/24) isolates further evaluated for bacteriocin encoding genes and primary safety traits. Representative isolates of the numerically dominant mesophilic LAB were Leuconostoc mesenteroides (10) in both RMs, Streptococcus parauberis (7) in RM2, and Lactococcus lactis (1) in RM1; the subdominant thermophilic LAB isolates were Enterococcus durans (8), E. faecium (6), E. faecalis (3), E. hirae (1), E. hermanniensis (1), Streptococcus lutetiensis (2), S. equinus (1) and S. gallolyticus (1). Based on their rpoB, araA, dsr and sorA profiles, six Ln. mesenteroides strains (8 isolates) were atypical lying between the subspecies mesenteroides and dextranicum, whereas two strains profiled with Ln. mesenteroides subsp. jonggajibkimchi that is first-time reported in Greek dairy food. Two RM1 E. faecium strain biotypes (3 isolates) showed strong, enterocin-mediated antilisterial activity due to entA/entB/entP possession. One E. durans from RM1 possessed entA and entP, while additional nine RM2 isolates of the E. faecium/durans group processed entA or entP singly. All showed direct (cell-associated) antilisterial activity only, as also both S. lutetiensis strains from RM2 did strongly. Desirably, no LAB isolate was β-hemolyrtic, or cytolysin-positive, or possessed vanA, vanB for vancomycin resistance, or agg, espA, hyl, and IS16 virulence genes. However, all three E. faecalis from RM2 possessed gelE and/or ace virulence genes. In conclusion, all Ln. mesenteroides strains, the two safe, enterocin A-B-P-producing E. faecium strains, and the two antilisterial S. lutetiensis strains should be validated further as potential costarter or adjunct cultures in Kefalotyri cheese. The prevalence of α-hemolytic pyogenic streptococci in raw milk, mainly S. parauberis in RM2, requires consideration in respect to subclinical mastitis in sheep and the farm hygiene overall.

Gamma-rays induced mutations increase soybean oil and protein contents

Mutation breeding is one of the effective techniques used for improving desired traits such as yield quality and quantity in economic crops. The present study aims to develop oil and protein contents in addition to high yield attributes in soybean using gamma rays as a mutagen. Seeds of the soybean genotypes Giza 21, Giza 22, Giza 82, Giza 83 and 117 were treated with gamma rays doses 50, 100, 200 and 300 Gy. Plants were then scored based on morphological parameters correlated with yield quantity including plant height, seed weight and valuable protein and oil contents. Mutant lines exhibiting the highest yield attributes were selected and used as parents for M2 generation. The M2 progeny was further assessed based on their ability to maintain their yield attributes. Twenty mutant lines were selected and used as M3 lines. The yield parameters inferred a positive effect of gamma irradiation on the collected M3 mutant lines compared to their parental genotypes. 100 Gy of gamma rays gave the highest effect on the number of pods, branches and seeds per plant in addition to protein content, while 200 Gy was more effective in increasing plant height, number of pods per plant, and oil content. Six mutant lines scored the highest yield parameters. Further assessment inferred an inverse relationship between oil and protein content in most of the tested cultivars with high agronomic features. However, four mutant lines recorded high content of oil and protein besides their high seed yield as well, which elect them as potential candidates for large-scale evaluation. The correlation among examined parameters was further confirmed via principal component analysis (PCA), which inferred a positive correlation between the number of pods, branches, seeds, and seed weight. Conversely, oil and protein content were inversely correlated in most of yielded mutant lines. Together, those findings introduce novel soybean lines with favorable agronomic traits for the market. In addition, our research sheds light on the value of using gamma rays treatment in enhancing genetic variability in soybean and improving oil, protein contents and seed yield.

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

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

Permanent draft genome sequence of Bradyrhizobium vignae, strain ISRA 400, an elite nitrogen-fixing bacterium, isolated from the groundnut growing area in Senegal

A new Bradyrhizobium vignae strain called ISRA400 was isolated from groundnut (Arachis hypogaea L.) root nodules obtained by trapping the bacteria from soil samples collected in the Senegalese groundnut basin. In this study, we present the draft genome sequence of this strain ISRA400, which spans approximatively 7.9 Mbp and exhibits a G+C content of 63.4%. The genome analysis revealed the presence of 48 tRNA genes and one rRNA operon (16S, 23S, and 5S). The nodulation test revealed that this strain ISRA400 significantly improves the nodulation parameters and chlorophyll content of the Arachis hypogaea variety Fleur11. These findings suggest the potential of Bradyrhizobium vignae strain ISRA400 as an effective symbiotic partner for improving the growth and productivity of groundnut crop.

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.

QTLs and Candidate Genes for Seed Protein Content in Two Recombinant Inbred Line Populations of Soybean

This study aimed to discover the quantitative trait loci (QTL) associated with a high seed protein content in soybean and unravel the potential candidate genes. We developed two recombinant inbred line populations: YS and SI, by crossing Saedanbaek (high protein) with YS2035-B-91-1-B-1 (low protein) and Saedanbaek with Ilmi (low protein), respectively, and evaluated the protein content for three consecutive years. Using single-nucleotide polymorphism (SNP)-marker-based linkage maps, four QTLs were located on chromosomes 15, 18, and 20 with high logarithm of odds values (5.9-55.0), contributing 5.5-66.0% phenotypic variance. In all three experimental years, qPSD20-1 and qPSD20-2 were stable and identified in overlapping positions in the YS and SI populations, respectively. Additionally, novel QTLs were identified on chromosomes 15 and 18. Considering the allelic sequence variation between parental lines, 28 annotated genes related to soybean seed protein-including starch, lipid, and fatty acid biosynthesis-related genes-were identified within the QTL regions. These genes could potentially affect protein accumulation during seed development, as well as sucrose and oil metabolism. Overall, this study offers insights into the genetic mechanisms underlying a high soybean protein content. The identified potential candidate genes can aid marker-assisted selection for developing soybean lines with an increased protein content.

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.

Genome-wide association study and high-quality gene mining related to soybean protein and fat

BACKGROUND

Soybean is one of the most important oil crops in the world, and its protein and fat are the primary sources of edible oil and vegetable protein. The effective components in soybean protein and fat have positive effects on improving human immunity, anti-tumor, and regulating blood lipids and metabolism. Therefore, increasing the contents of protein and fat in soybeans is essential for improving the quality of soybeans.

RESULTS

This study selected 292 soybean lines from different regions as experimental materials, based on SLAF-seq sequencing technology, and performed genome-wide association study (GWAS) on the phenotype data from 2019-2021 Planted at the experimental base of Jilin Agricultural University, such as the contents of protein and fat of soybeans. Through the GLM model and MLM model, four SNP sites (Gm09_39012959, Gm12_35492373, Gm16_9297124, and Gm20_24678362) that were significantly related to soybean fat content were associated for three consecutive years, and two SNP sites (Gm09_39012959 and Gm20_24678362) that were significantly related to soybean protein content were associated. By the annotation and enrichment of genes within the 100 Kb region of SNP loci flanking, two genes (Glyma.09G158100 and Glyma.09G158200) related to soybean protein synthesis and one gene (Glyma.12G180200) related to lipid metabolism were selected. By the preliminary verification of expression levels of genes with qPCR, it is found that during the periods of R6 and R7 of the accumulation of soybean protein and fat, Glyma.09G158100 and Glyma.09G158200 are positive regulatory genes that promote protein synthesis and accumulation, while Glyma.12G180200 is the negative regulatory gene that inhibits fat accumulation.

CONCLUSIONS

These results lay the basis for further verifying the gene function and studying the molecular mechanisms regulating the accumulation of protein and fat in soybean seeds.

miRNA mediated regulation of nitrogen response and nitrogen use efficiency of plants: the case of wheat

Nitrogen (N) is needed for plant growth and development and is the major limiting nutrient due to its higher demand in agricultural production globally. The use of N fertilizers has increased considerably in recent years to achieve higher cereal yields. High N inputs coupled with declining N use efficiency (NUE) result in the degradation of the environment. Plants have developed multidimensional strategies in response to changes in N availability in soil. These strategies include N stress-induced responses such as changes in gene expression patterns. Several N stress-induced genes and other regulatory factors, such as microRNAs (miRNAs), have been identified in different plant species, opening a new avenue of research in plant biology. This review presents a general overview of miRNA-mediated regulation of N response and NUE. Further, the in-silico target predictions and the predicted miRNA-gene network for nutrient metabolism/homeostasis in wheat provide novel insights. The information on N-regulated miRNAs and the differentially expressed target transcripts are necessary resources for genetic improvement of NUE by genome editing.

Deciphering the genetic architecture of resistance to Corynespora cassiicola in soybean (Glycine max L.) by integrating genome-wide association mapping and RNA-Seq analysis

Target spot caused by Corynespora cassiicola is a problematic disease in tropical and subtropical soybean (Glycine max) growing regions. Although resistant soybean genotypes have been identified, the genetic mechanisms underlying target spot resistance has not yet been studied. To address this knowledge gap, this is the first genome-wide association study (GWAS) conducted using the SoySNP50K array on a panel of 246 soybean accessions, aiming to unravel the genetic architecture of resistance. The results revealed significant associations of 14 and 33 loci with resistance to LIM01 and SSTA C. cassiicola isolates, respectively, with six loci demonstrating consistent associations across both isolates. To identify potential candidate genes within GWAS-identified loci, dynamic transcriptome profiling was conducted through RNA-Seq analysis. The analysis involved comparing gene expression patterns between resistant and susceptible genotypes, utilizing leaf tissue collected at different time points after inoculation. Integrating results of GWAS and RNA-Seq analyses identified 238 differentially expressed genes within a 200 kb region encompassing significant quantitative trait loci (QTLs) for disease severity ratings. These genes were involved in defense response to pathogen, innate immune response, chitinase activity, histone H3-K9 methylation, salicylic acid mediated signaling pathway, kinase activity, and biosynthesis of flavonoid, jasmonic acid, phenylpropanoid, and wax. In addition, when combining results from this study with previous GWAS research, 11 colocalized regions associated with disease resistance were identified for biotic and abiotic stress. This finding provides valuable insight into the genetic resources that can be harnessed for future breeding programs aiming to enhance soybean resistance against target spot and other diseases simultaneously.

Analysis of genetic diversity and genome-wide association study for drought tolerance related traits in Iranian bread wheat

BACKGROUND

Drought is most likely the most significant abiotic stress affecting wheat yield. The discovery of drought-tolerant genotypes is a promising strategy for dealing with the world's rapidly diminishing water resources and growing population. A genome-wide association study (GWAS) was conducted on 298 Iranian bread wheat landraces and cultivars to investigate the genetic basis of yield, yield components, and drought tolerance indices in two cropping seasons (2018-2019 and 2019-2020) under rainfed and well-watered environments.

RESULTS

A heatmap display of hierarchical clustering divided cultivars and landraces into four categories, with high-yielding and drought-tolerant genotypes clustering in the same group. The results of the principal component analysis (PCA) demonstrated that selecting genotypes based on the mean productivity (MP), geometric mean productivity (GMP), harmonic mean (HM), and stress tolerance index (STI) can help achieve high-yield genotypes in the environment. Genome B had the highest number of significant marker pairs in linkage disequilibrium (LD) for both landraces (427,017) and cultivars (370,359). Similar to cultivars, marker pairs on chromosome 4A represented the strongest LD (r2 = 0.32). However, the genomes D, A, and B have the highest LD, respectively. The single-locus mixed linear model (MLM) and multi-locus random-SNP-effect mixed linear model (mrMLM) identified 1711 and 1254 significant marker-trait association (MTAs) (-log10 P > 3) for all traits, respectively. A total of 874 common quantitative trait nucleotides (QTNs) were simultaneously discovered by both MLM and mrMLM methods. Gene ontology revealed that 11, 18, 6, and 11 MTAs were found in protein-coding regions (PCRs) for spike weight (SW), thousand kernel weight (TKW), grain number per spike (GN), and grain yield (GY), respectively.

CONCLUSION

The results identified rich regions of quantitative trait loci (QTL) on Ch. 4A and 5A suggest that these chromosomes are important for drought tolerance and could be used in wheat breeding programs. Furthermore, the findings indicated that landraces studied in Iranian bread wheat germplasm possess valuable alleles, that are responsive to water-limited conditions. This GWAS experiment is one of the few types of research conducted on drought tolerance that can be exploited in the genome-mediated development of novel varieties of wheat.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

Genome-wide association study as a powerful tool for dissecting competitive traits in legumes

Legumes are extremely valuable because of their high protein content and several other nutritional components. The major challenge lies in maintaining the quantity and quality of protein and other nutritional compounds in view of climate change conditions. The global need for plant-based proteins has increased the demand for seeds with a high protein content that includes essential amino acids. Genome-wide association studies (GWAS) have evolved as a standard approach in agricultural genetics for examining such intricate characters. Recent development in machine learning methods shows promising applications for dimensionality reduction, which is a major challenge in GWAS. With the advancement in biotechnology, sequencing, and bioinformatics tools, estimation of linkage disequilibrium (LD) based associations between a genome-wide collection of single-nucleotide polymorphisms (SNPs) and desired phenotypic traits has become accessible. The markers from GWAS could be utilized for genomic selection (GS) to predict superior lines by calculating genomic estimated breeding values (GEBVs). For prediction accuracy, an assortment of statistical models could be utilized, such as ridge regression best linear unbiased prediction (rrBLUP), genomic best linear unbiased predictor (gBLUP), Bayesian, and random forest (RF). Both naturally diverse germplasm panels and family-based breeding populations can be used for association mapping based on the nature of the breeding system (inbred or outbred) in the plant species. MAGIC, MCILs, RIAILs, NAM, and ROAM are being used for association mapping in several crops. Several modifications of NAM, such as doubled haploid NAM (DH-NAM), backcross NAM (BC-NAM), and advanced backcross NAM (AB-NAM), have also been used in crops like rice, wheat, maize, barley mustard, etc. for reliable marker-trait associations (MTAs), phenotyping accuracy is equally important as genotyping. Highthroughput genotyping, phenomics, and computational techniques have advanced during the past few years, making it possible to explore such enormous datasets. Each population has unique virtues and flaws at the genomics and phenomics levels, which will be covered in more detail in this review study. The current investigation includes utilizing elite breeding lines as association mapping population, optimizing the choice of GWAS selection, population size, and hurdles in phenotyping, and statistical methods which will analyze competitive traits in legume breeding.

Characterizing the circadian connectome of Ocimum tenuiflorum using an integrated network theoretic framework

Across the three domains of life, circadian clock is known to regulate vital physiological processes, like, growth, development, defence etc. by anticipating environmental cues. In this work, we report an integrated network theoretic methodology comprising of random walk with restart and graphlet degree vectors to characterize genome wide core circadian clock and clock associated raw candidate proteins in a plant for which protein interaction information is available. As a case study, we have implemented this framework in Ocimum tenuiflorum (Tulsi); one of the most valuable medicinal plants that has been utilized since ancient times in the management of a large number of diseases. For that, 24 core clock (CC) proteins were mined in 56 template plant genomes to build their hidden Markov models (HMMs). These HMMs were then used to identify 24 core clock proteins in O. tenuiflorum. The local topology of the interologous Tulsi protein interaction network was explored to predict the CC associated raw candidate proteins. Statistical and biological significance of the raw candidates was determined using permutation and enrichment tests. A total of 66 putative CC associated proteins were identified and their functional annotation was performed.

A Genome-Wide Association Study Reveals Region Associated with Seed Protein Content in Cowpea

Cowpea (Vigna unguiculata L. Walp., 2n = 2x = 22) is a protein-rich crop that complements staple cereals for humans and serves as fodder for livestock. It is widely grown in Africa and other developing countries as the primary source of protein in the diet; therefore, it is necessary to identify the protein-related loci to improve cowpea breeding. In the current study, we conducted a genome-wide association study (GWAS) on 161 cowpea accessions (151 USDA germplasm plus 10 Arkansas breeding lines) with a wide range of seed protein contents (21.8~28.9%) with 110,155 high-quality whole-genome single-nucleotide polymorphisms (SNPs) to identify markers associated with protein content, then performed genomic prediction (GP) for future breeding. A total of seven significant SNP markers were identified using five GWAS models (single-marker regression (SMR), the general linear model (GLM), Mixed Linear Model (MLM), Fixed and Random Model Circulating Probability Unification (FarmCPU), and Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK), which are located at the same locus on chromosome 8 for seed protein content. This locus was associated with the gene Vigun08g039200, which was annotated as the protein of the thioredoxin superfamily, playing a critical function for protein content increase and nutritional quality improvement. In this study, a genomic prediction (GP) approach was employed to assess the accuracy of predicting seed protein content in cowpea. The GP was conducted using cross-prediction with five models, namely ridge regression best linear unbiased prediction (rrBLUP), Bayesian ridge regression (BRR), Bayesian A (BA), Bayesian B (BB), and Bayesian least absolute shrinkage and selection operator (BL), applied to seven random whole genome marker sets with different densities (10 k, 5 k, 2 k, 1 k, 500, 200, and 7), as well as significant markers identified through GWAS. The accuracies of the GP varied between 42.9% and 52.1% across the seven SNPs considered, depending on the model used. These findings not only have the potential to expedite the breeding cycle through early prediction of individual performance prior to phenotyping, but also offer practical implications for cowpea breeding programs striving to enhance seed protein content and nutritional quality.

Cystic echinococcosis microRNAs as potential noninvasive biomarkers: current insights and upcoming perspective

INTRODUCTION

Echinococcosis, also known as hydatidosis, is a zoonotic foodborne disease occurred by infection with the larvae of Echinococcus spp. which can lead to the development of hydatid cysts in various organs of the host. The diagnosis of echinococcosis remains challenging due to limited diagnostic tools.

AREAS COVERED

In recent years, microRNAs (miRNAs) have emerged as a promising biomarker for various infectious diseases, including those caused by helminths. Recent studies have identified several novel miRNAs in Echinococcus spp. shedding light on their essential roles in hydatid cyst host-parasite interactions. In this regard, several studies have shown that Echinococcus-derived miRNAs are present in biofluids such as serum and plasma of infected hosts. The detection of these miRNAs in the early stages of infection can serve as an early prognostic and diagnostic biomarker for echinococcosis.

EXPERT OPINION

The miRNAs specific to Echinococcus spp. show great potential as early diagnostic biomarkers for echinococcosis and can also provide insights into the pathogenesis of this disease. This review attempts to provide a comprehensive overview of Echinococcus-specific miRNAs, their use as early diagnostic biomarkers, and their function in host-parasite interactions.

Identification of quantitative trait loci controlling soybean seed protein and oil content

Soybean is a major source of seed protein and oil globally with an average composition of 40% protein and 20% oil in the seed. The goal of this study was to identify quantitative trait loci (QTL) conferring seed protein and oil content utilizing a population constructed by crossing an above average protein content line, PI 399084 to another line that had a low protein content value, PI 507429, both from the USDA soybean germplasm collection. The recombinant inbred line (RIL) population, PI 507429 x PI 399084, was evaluated in two replications over four years (2018-2021); the seeds were analyzed for seed protein and oil content using near-infrared reflectance spectroscopy. The recombinant inbred lines and the two parents were re-sequenced using genotyping by sequencing. A total of 12,761 molecular markers, which came from genotyping by sequencing, the SoySNP6k BeadChip and selected simple sequence repeat (SSR) markers from known protein QTL chromosomal regions were used for mapping. One QTL was identified on chromosome 2 explaining up to 56.8% of the variation for seed protein content and up to 43% for seed oil content. Another QTL identified on chromosome 15 explained up to 27.2% of the variation for seed protein and up to 41% of the variation for seed oil content. The protein and oil QTLs of this study and their associated molecular markers will be useful in breeding to improve nutritional quality in soybean.