Genomic blueprints of soybean (Glycine max) pathogen resistance: revealing the key genes for sustainable agriculture.

Soybean (Glycine max ) is an important oilseed, protein and biodiesel crop. It faces significant threats from bacterial, fungal and viral pathogens, which cause economic losses and jeopardises global food security. In this article, we explore the relationship between soybeans and these pathogens, focusing on the molecular responses that are crucial for soybeans defence mechanisms. Molecular responses involve small RNAs and specific genes, including resistance (R) genes that are pivotal in triggering immune responses. Functional genomics, which makes use of cutting-edge technologies, such as CRISPR Cas9 gene editing, allows us to identify genes that provide insights into the defence mechanisms of soybeans with the focus on using genomics to understand the mechanisms involved in host pathogen interactions and ultimately improve the resilience of soybeans. Genes like GmKR3 and GmVQ58 have demonstrated resistance against soybean mosaic virus and common cutworm, respectively. Genetic studies have identified quantitative trait loci (QTLs) including those linked with soybean cyst nematode, root-knot nematode and Phytophthora root and stem rot resistance. Additionally, resistance against Asian soybean rust and soybean cyst nematode involves specific genes and their variations in terms of different copy numbers. To address the challenges posed by evolving pathogens and meet the demands of a growing population, accelerated soybean breeding efforts leveraging functional genomics are imperative. Targeted breeding strategies based on a deeper understanding of soybean gene function and regulation will enhance disease resistance, ensuring sustainable agriculture and global food security. Collaborative research and continued technological advancements are crucial for securing a resilient and productive agricultural future.

Exploring the role of FBXL fbxl gene family in Soybean: Implications for plant height and seed size regulation.

F-box proteins constitute a significant family in eukaryotes and, as a component of the Skp1p-cullin-F-box complex, are considered critical for cellular protein degradation and other biological processes in plants. Despite their importance, the functions of F-box proteins, particularly those with C-terminal leucine-rich repeat (LRR) domains, remain largely unknown in plants. Therefore, the present study conducted genome-wide identification and in silico characterization of F-BOX proteins with C-terminal LRR domains in soybean (Glycine max L.) (GmFBXLs). A total of 45 GmFBXLs were identified. The phylogenetic analysis showed that GmFBXLs could be subdivided into ten subgroups and exhibited a close relationship with those from Arabidopsis thaliana, Cicer aretineum, and Medicago trunculata. It was observed that most cis-regulatory elements in the promoter regions of GmFBXLs are involved in hormone signalling, stress responses, and developmental stages. In silico transcriptome data illustrated diverse expression patterns of the identified GmFBXLs across various tissues, such as shoot apical meristem, flower, green pods, leaves, nodules, and roots. Overexpressing (OE) GmFBXL12 in Tianlong No.1 cultivar resulted in a significant difference in seed size, number of pods, and number of seeds per plant, indicated a potential increase in yield compared to wild type. This study offers valuable perspectives into the role of FBXLs in soybean, serving as a foundation for future research. Additionally, the identified OE lines represent valuable genetic resources for enhancing seed-related traits in soybean.

Molecular and genetic insights into secondary metabolic regulation underlying insect-pest resistance in legumes.

Insect pests pose a major threat to agricultural production, resulting in significant economic losses for countries. A high infestation of insects in any given area can severely reduce crop yield and quality. This review examines the existing resources for managing insect pests and highlights alternative eco-friendly techniques to enhance insect pest resistance in legumes. Recently, the application of plant secondary metabolites has gained popularity in controlling insect attacks. Plant secondary metabolites encompass a wide range of compounds such as alkaloids, flavonoids, and terpenoids, which are often synthesized through intricate biosynthetic pathways. Classical methods of metabolic engineering involve manipulating key enzymes and regulatory genes to enhance or redirect the production of secondary metabolites in plants. Additionally, the role of genetic approaches, such as quantitative trait loci mapping, genome-wide association (GWAS) mapping, and metabolome-based GWAS in insect pest management is discussed, also, the role of precision breeding, such as genome editing technologies and RNA interference for identifying pest resistance and manipulating the genome to develop insect-resistant cultivars are explored, highlighting the positive contribution of plant secondary metabolites engineering-based resistance against insect pests. It is suggested that by understanding the genes responsible for beneficial metabolite compositions, future research might hold immense potential to shed more light on the molecular regulation of secondary metabolite biosynthesis, leading to advancements in insect-resistant traits in crop plants. In the future, the utilization of metabolic engineering and biotechnological methods may serve as an alternative means of producing biologically active, economically valuable, and medically significant compounds found in plant secondary metabolites, thereby addressing the challenge of limited availability.

The changing landscape of agriculture: role of precision breeding in developing smart crops.

Food plants play a crucial role in human survival, providing them essential nutrients. However, traditional breeding methods have not been able to keep up with the demands of the growing population. The improvement of food plants aims to increase yield, quality, and resistance to biotic and abiotic stresses. With CRISPR/Cas9, researchers can identify and edit key genes conferring desirable qualities in agricultural plants, including increased yield, enhanced product quality attributes, and increased tolerance to biotic and abiotic challenges. These modifications have enabled the creation of "smart crops" that exhibit rapid climatic adaptation, resistance to extreme weather conditions and high yield and quality. The use of CRISPR/Cas9 combined with viral vectors or growth regulators has made it possible to produce more efficient modified plants with certain conventional breeding methods. However, ethical and regulatory aspects of this technology must be carefully considered. Proper regulation and application of genome editing technology can bring immense benefits to agriculture and food security. This article provides an overview of genetically modified genes and conventional as well as emerging tools, including CRISPR/Cas9, that have been utilized to enhance the quality of plants/fruits and their products. The review also discusses the challenges and prospects associated with these techniques.

Unraveling the Diverse Roles of Neglected Genes Containing Domains of Unknown Function (DUFs): Progress and Perspective.

Domain of unknown function (DUF) is a general term for many uncharacterized domains with two distinct features: relatively conservative amino acid sequence and unknown function of the domain. In the Pfam 35.0 database, 4795 (24%) gene families belong to the DUF type, yet, their functions remain to be explored. This review summarizes the characteristics of the DUF protein families and their functions in regulating plant growth and development, generating responses to biotic and abiotic stress, and other regulatory roles in plant life. Though very limited information is available about these proteins yet, by taking advantage of emerging omics and bioinformatic tools, functional studies of DUF proteins could be utilized in future molecular studies.

CRISPR-Cas9 based stress tolerance: New hope for abiotic stress tolerance in chickpea (Cicer arietinum).

Plants are subjected to biotic and abiotic stresses regularly, which irreparably harm agricultural production. Eco-friendly and sustainable technology to deal with this challenge is to breed abiotic stress tolerant cultivars. To generate crop plants conferring resistance against stresses, conventional breeding was used in the past, but because of the complex heredity of abiotic stress tolerance traits, such techniques remain insufficient in making greater enhancement. Genome-engineering based on CRISPR-Cas9 (clustered regularly interspaced short palindromic repeats-CRISPR associated protein9) has shown enormous potential in developing climate-resilient cultivars. Likewise, the development of chickpea transgenic lines by knockout of 4CL and REV7 genes exhibits drought tolerance which establishes a foundation for future studies in chickpea. In addition, the CRISPR-Cas9 system can boost yield potential under abiotic stress situations by producing non-transgenic plants having the required characteristics. This review article discusses the validation of gene function based on the CRISPR-Cas9 for the development of abiotic stress-tolerant crop plants, emphasizing the chickpea to open the new ventures of generating abiotic stress-tolerant chickpea varieties.

Characterizing stomatal attributes and photosynthetic induction in relation to biochemical changes in Coriandrum sativum L. by foliar-applied zinc oxide nanoparticles under drought conditions.

Abiotic stress, particularly drought, will remain an alarming challenge for sustainable agriculture. New approaches have been opted, such as nanoparticles (NPs), to reduce the negative impact of drought stress and lessen the use of synthetic fertilizers and pesticides that are an inevitable problem these days. The application of zinc oxide nanoparticles (ZnO NPs) has been recognized as an effective strategy to enhance plant growth and crop production during abiotic stress. The aim of the current study was to investigate the role of ZnO NPs in drought stress management of drought-susceptible Coriandrum sativum L. (C. sativum) in two consecutive seasons. Drought regimes (moderate drought regime-MDR and intensive drought regime-IDR) were developed based on replenishment method with respect to 50% field capacity of fully irrigated (control) plants. The results showed that foliar application of 100 ppm ZnO NPs improved the net photosynthesis (Pn), stomatal conductance (C), and transpiration rate (E) and boosted up the photosynthetic capacity associated with photosynthetic active radiation in MDR. Similarly, 48% to 30% improvement of chlorophyll b content was observed in MDR and onefold to 41% in IDR during both seasons in ZnO NP-supplemented plants. The amount of abscisic acid in leaves showed a decreasing trend in MDR and IDR in the first season (40% and 30%) and the second season (49% and 33%) compared with untreated ZnO NP plants. The ZnO NP-treated plants showed an increment in total soluble sugars, total phenolic content, and total flavonoid content in both drought regimes, whereas the abaxial surface showed high stomatal density and stomatal index than the adaxial surface in foliar-supplied NP plants. Furthermore, ZnO NPs improve the magnitude of stomata ultrastructures like stomatal length, stomatal width, and pore length for better adaptation against drought. Principal component analysis revealed the efficacy of ZnO NPs in inducing drought tolerance in moderate and intensive stress regimes. These results suggest that 100 ppm ZnO NPs can be used to ameliorate drought tolerance in C. sativum plants.

Genome-wide association study uncovers major genetic loci associated with seed flooding tolerance in soybean.

BACKGROUND: Seed flooding stress is one of the threatening environmental stressors that adversely limits soybean at the germination stage across the globe. The knowledge on the genetic basis underlying seed-flooding tolerance is limited. Therefore, we performed a genome-wide association study (GWAS) using 34,718 single nucleotide polymorphism (SNPs) in a panel of 243 worldwide soybean collections to identify genetic loci linked to soybean seed flooding tolerance at the germination stage. RESULTS: In the present study, GWAS was performed with two contrasting models, Mixed Linear Model (MLM) and Multi-Locus Random-SNP-Effect Mixed Linear Model (mrMLM) to identify significant SNPs associated with electrical conductivity (EC), germination rate (GR), shoot length (ShL), and root length (RL) traits at germination stage in soybean. With MLM, a total of 20, 40, 4, and 9 SNPs associated with EC, GR, ShL and RL, respectively, whereas in the same order mrMLM detected 27, 17, 13, and 18 SNPs. Among these SNPs, two major SNPs, Gm_08_11971416, and Gm_08_46239716 were found to be consistently connected with seed-flooding tolerance related traits, namely EC and GR across two environments. We also detected two SNPs, Gm_05_1000479 and Gm_01_53535790 linked to ShL and RL, respectively. Based on Gene Ontology enrichment analysis, gene functional annotations, and protein-protein interaction network analysis, we predicted eight candidate genes and three hub genes within the regions of the four SNPs with Cis-elements in promoter regions which may be involved in seed-flooding tolerance in soybeans and these warrant further screening and functional validation. CONCLUSIONS: Our findings demonstrate that GWAS based on high-density SNP markers is an efficient approach to dissect the genetic basis of complex traits and identify candidate genes in soybean. The trait associated SNPs could be used for genetic improvement in soybean breeding programs. The candidate genes could help researchers better understand the molecular mechanisms underlying seed-flooding stress tolerance in soybean.

Identification and Validation of Major QTLs, Epistatic Interactions, and Candidate Genes for Soybean Seed Shape and Weight Using Two Related RIL Populations.

Understanding the genetic mechanism underlying seed size, shape, and weight is essential for enhancing soybean cultivars. High-density genetic maps of two recombinant inbred line (RIL) populations, LM6 and ZM6, were evaluated across multiple environments to identify and validate M-QTLs as well as identify candidate genes behind major and stable quantitative trait loci (QTLs). A total of 239 and 43 M-QTLs were mapped by composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM) approaches, from which 180 and 18, respectively, are novel QTLs. Twenty-two QTLs including four novel major QTLs were validated in the two RIL populations across multiple environments. Moreover, 18 QTLs showed significant AE effects, and 40 pairwise of the identified QTLs exhibited digenic epistatic effects. Thirty-four QTLs associated with seed flatness index (FI) were identified and reported here for the first time. Seven QTL clusters comprising several QTLs for seed size, shape, and weight on genomic regions of chromosomes 3, 4, 5, 7, 9, 17, and 19 were identified. Gene annotations, gene ontology (GO) enrichment, and RNA-seq analyses of the genomic regions of those seven QTL clusters identified 47 candidate genes for seed-related traits. These genes are highly expressed in seed-related tissues and nodules, which might be deemed as potential candidate genes regulating the seed size, weight, and shape traits in soybean. This study provides detailed information on the genetic basis of the studied traits and candidate genes that could be efficiently implemented by soybean breeders for fine mapping and gene cloning, and for marker-assisted selection (MAS) targeted at improving these traits individually or concurrently.

High-Resolution Mapping in Two RIL Populations Refines Major "QTL Hotspot" Regions for Seed Size and Shape in Soybean (Glycine max L.).

Seed size and shape are important traits determining yield and quality in soybean. However, the genetic mechanism and genes underlying these traits remain largely unexplored. In this regard, this study used two related recombinant inbred line (RIL) populations (ZY and K3N) evaluated in multiple environments to identify main and epistatic-effect quantitative trait loci (QTLs) for six seed size and shape traits in soybean. A total of 88 and 48 QTLs were detected through composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM), respectively, and 15 QTLs were common among both methods; two of them were major (R2 > 10%) and novel QTLs (viz., qSW-1-1ZN and qSLT-20-1K3N). Additionally, 51 and 27 QTLs were identified for the first time through CIM and MCIM methods, respectively. Colocalization of QTLs occurred in four major QTL hotspots/clusters, viz., "QTL Hotspot A", "QTL Hotspot B", "QTL Hotspot C", and "QTL Hotspot D" located on Chr06, Chr10, Chr13, and Chr20, respectively. Based on gene annotation, gene ontology (GO) enrichment, and RNA-Seq analysis, 23 genes within four "QTL Hotspots" were predicted as possible candidates, regulating soybean seed size and shape. Network analyses demonstrated that 15 QTLs showed significant additive x environment (AE) effects, and 16 pairs of QTLs showing epistatic effects were also detected. However, except three epistatic QTLs, viz., qSL-13-3ZY, qSL-13-4ZY, and qSW-13-4ZY, all the remaining QTLs depicted no main effects. Hence, the present study is a detailed and comprehensive investigation uncovering the genetic basis of seed size and shape in soybeans. The use of a high-density map identified new genomic regions providing valuable information and could be the primary target for further fine mapping, candidate gene identification, and marker-assisted breeding (MAB).

Whole-genome mapping identified novel "QTL hotspots regions" for seed storability in soybean (Glycine max L.).

BACKGROUND: Seed aging in soybean is a serious challenge for agronomic production and germplasm preservation. However, its genetic basis remains largely unclear in soybean. Unraveling the genetic mechanism involved in seed aging, and enhancing seed storability is an imperative goal for soybean breeding. The aim of this study is to identify quantitative trait loci (QTLs) using high-density genetic linkage maps of soybean for seed storability. In this regard, two recombinant inbred line (RIL) populations derived from Zhengyanghuangdou × Meng 8206 (ZM6) and Linhefenqingdou × Meng 8206 (LM6) crosses were evaluated for three seed-germination related traits viz., germination rate (GR), normal seedling length (SL) and normal seedling fresh weight (FW) under natural and artificial aging conditions to map QTLs for seed storability. RESULTS: A total of 34 QTLs, including 13 QTLs for GR, 11 QTLs for SL and 10 QTLs for FW, were identified on 11 chromosomes with the phenotypic variation ranged from 7.30 to 23.16% under both aging conditions. All these QTLs were novel, and 21 of these QTLs were clustered in five QTL-rich regions on four different chromosomes viz., Chr3, Chr5, Chr17 &Chr18, among them the highest concentration of seven and six QTLs were found in "QTL hotspot A" (Chr17) and "QTL hotspot B" (Chr5), respectively. Furthermore, QTLs within all the five QTL clusters are linked to at least two studied traits, which is also supported by highly significant correlation between the three germination-related traits. QTLs for seed-germination related traits in "QTL hotspot B" were found in both RIL populations and aging conditions, and also QTLs underlying "QTL hotspot A" are identified in both RIL populations under artificial aging condition. These are the stable genomic regions governing the inheritance of seed storability in soybean, and will be the main focus for soybean breeders. CONCLUSION: This study uncovers the genetic basis of seed storability in soybean. The newly identified QTLs provides valuable information, and will be main targets for fine mapping, candidate gene identification and marker-assisted breeding. Hence, the present study is the first report for the comprehensive and detailed investigation of genetic architecture of seed storability in soybean.