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-1-1_ZN and qSLT-20-1_K3N). 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-13-3_ZY, qSL-13-4_ZY, and qSW-13-4_ZY, 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).

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.

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.

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. 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. 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.

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-susceptibleCoriandrum sativumL. (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 inC. sativumplants.