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.

Genetic Dissection of Extreme Seed-Flooding Tolerance in a Wild Soybean PI342618B by Linkage Mapping and Candidate Gene Analysis.

Seed-flooding stress is one of major abiotic constraints that adversely affects soybean production worldwide. Identifying tolerant germplasms and revealing the genetic basis of seed-flooding tolerance are imperative goals for soybean breeding. In the present study, high-density linkage maps of two inter-specific recombinant inbred line (RIL) populations, named NJIRNP and NJIR4P, were utilized to identify major quantitative trait loci (QTLs) for seed-flooding tolerance using three parameters viz., germination rate (GR), normal seedling rate (NSR), and electrical conductivity (EC). A total of 25 and 18 QTLs were detected by composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM), respectively, and 12 common QTLs were identified through both methods. All favorable alleles for the tolerance are notably from the wild soybean parent. Moreover, four digenic epistatic QTL pairs were identified, and three of them showed no main effects. In addition, the pigmented soybean genotypes exhibited high seed-flooding tolerance compared with yellow seed coat genotypes in both populations. Moreover, out of five identified QTLs, one major region containing multiple QTLs associated with all three traits was identified on Chromosome 8, and most of the QTLs within this hotspot were major loci (R2 > 10) and detectable in both populations and multiple environments. Based on the gene expression and functional annotation information, 10 candidate genes from QTL "hotspot 8-2" were screened for further analysis. Furthermore, the results of qRT-PCR and sequence analysis revealed that only one gene, GmDREB2 (Glyma.08G137600), was significantly induced under flooding stress and displayed a TTC tribasic insertion mutation of the nucleotide sequence in the tolerant wild parent (PI342618B). GmDREB2 encodes an ERF transcription factor, and the subcellular localization analysis using green fluorescent protein (GFP) revealed that GmDREB2 protein was localized in the nucleus and plasma membrane. Furthermore, overexpression of GmDREB2 significantly promoted the growth of soybean hairy roots, which might indicate its critical role in seed-flooding stress. Thus, GmDREB2 was considered as the most possible candidate gene for seed-flooding tolerance.

Dysfunction of GmVPS8a causes compact plant architecture in soybean.

Vacuolar Protein Sorting 8 (Vps8) protein is a specific subunit of the class C core vacuole/endosome tethering (CORVET) complex that plays a key role in endosomal trafficking in yeast (Saccharomyces cerevisiae). However, its functions remain largely unclear in plant vegetative growth. Here, we identified a soybean (Glycine max) T4219 mutant characterized with compact plant architecture. Map-based cloning targeted to a candidate gene GmVPS8a (Glyma.07g049700) and further found that two nucleotides deletion in the first exon of GmVPS8a causes a premature termination of the encoded protein in the T4219 mutant. Its functions were validated by CRISPR/Cas9-engineered mutation in the GmVPS8a gene that recapitulated the T4219 mutant phenotypes. Furthermore, NbVPS8a-silenced tobacco (Nicotiana benthamiana) plants exhibited similar phenotypes to the T4219 mutant, suggesting its conserved roles in plant growth. The GmVPS8a is widely expressed in multiple organs and its protein interacts with GmAra6a and GmRab5a. Combined analysis of transcriptomic and proteomic data revealed that dysfunction of GmVPS8a mainly affects pathways on auxin signal transduction, sugar transport and metabolism, and lipid metabolism. Collectively, our work reveals the function of GmVPS8a in plant architecture, which may extend a new way for genetic improvement of ideal plant-architecture breeding in soybean and other crops.

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.

Exploring genetic architecture for pod-related traits in soybean using image-based phenotyping.

Mature pod color (PC) and pod size (PS) served as important characteristics are used in the soybean breeding programs. However, manual phenotyping of such complex traits is time-consuming, laborious, and expensive for breeders. Here, we collected pod images from two different populations, namely, a soybean association panel (SAP) consisting of 187 accessions and an inter-specific recombinant inbred line (RIL) population containing 284 RILs. An image-based phenotyping method was developed and used to extract the pod color- and size-related parameters from images. Genome-wide association study (GWAS) and linkage mapping were performed to decipher the genetic control of pod color- and size-related traits across 2 successive years. Both populations exhibited wide phenotypic variations and continuous distribution in pod color- and size-related traits, indicating quantitative polygenic inheritance of these traits. GWAS and linkage mapping approaches identified the two major quantitative trait loci (QTL) underlying the pod color parameters, i.e., qPC3 and qPC19, located to chromosomes 3 and 19, respectively, and 12 stable QTLs for pod size-related traits across nine chromosomes. Several genes residing within the genomic region of stable QTL were identified as potential candidates underlying these pod-related traits based on the gene annotation and expression profiling data. Our results provide the useful information for fine-mapping/map-based cloning of QTL and marker-assisted selection of elite varieties with desirable pod traits. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01223-2.

GmNAC8 acts as a positive regulator in soybean drought stress.

NAC proteins represent one of the largest transcription factor (TF) families involved in the regulation of plant development and the response to abiotic stress. In the present study, we elucidated the detailed role of GmNAC8 in the regulation of drought stress tolerance in soybean. The GmNAC8 protein was localized in the nucleus, and expression of the GmNAC8 gene was significantly induced in response to drought, abscisic acid (ABA), ethylene (ETH) and salicylic acid (SA) treatments. Thus, we generated GmNAC8 overexpression (OE1 and OE2) and GmNAC8 knockout (KO1 and KO2) lines to determine the role of GmNAC8 in drought stress tolerance. Our results revealed that, compared with the wild type (WT) plant, GmNAC8 overexpression and GmNAC8 knockout lines exhibited significantly higher and lower drought tolerance, respectively. Furthermore, the SOD activity and proline content were significantly higher in the GmNAC8 overexpression lines and significantly lower in the GmNAC8 knockout lines than in the WT plants under drought stress. In addition, GmNAC8 protein was found to physically interact with the drought-induced protein GmDi19-3 in the nucleus. Moreover, the GmDi19-3 expression pattern showed the same trend as the GmNAC8 gene did under drought and hormone (ABA, ETH and SA) treatments, and GmDi19-3 overexpression lines (GmDi19-3-OE9, GmDi19-3-OE10 and GmDi19-3-OE31) showed enhanced drought tolerance compared to that of the WT plants. Hence, the above results indicated that GmNAC8 acts as a positive regulator of drought tolerance in soybean and inferred that GmNAC8 probably functions by interacting with another positive regulatory protein, GmDi19-3.

Identification of QTN and Candidate Gene for Seed-flooding Tolerance in Soybean [Glycine max (L.) Merr.] using Genome-Wide Association Study (GWAS).

Seed-flooding stress is one of the major abiotic constraints severely affecting soybean yield and quality. Understanding the molecular mechanism and genetic basis underlying seed-flooding tolerance will be of greatly importance in soybean breeding. However, very limited information is available about the genetic basis of seed-flooding tolerance in soybean. The present study performed Genome-Wide Association Study (GWAS) to identify the quantitative trait nucleotides (QTNs) associated with three seed-flooding tolerance related traits, viz., germination rate (GR), normal seedling rate (NSR) and electric conductivity (EC), using a panel of 347 soybean lines and the genotypic data of 60,109 SNPs with MAF > 0.05. A total of 25 and 21 QTNs associated with all three traits were identified via mixed linear model (MLM) and multi-locus random-SNP-effect mixed linear model (mrMLM) in three different environments (JP14, HY15, and Combined). Among these QTNs, three major QTNs, viz., QTN13, qNSR-10 and qEC-7-2, were identified through both methods MLM and mrMLM. Interestingly, QTN13 located on Chr.13 has been consistently identified to be associated with all three studied traits in both methods and multiple environments. Within the 1.0 Mb physical interval surrounding the QTN13, nine candidate genes were screened for their involvement in seed-flooding tolerance based on gene annotation information and available literature. Based on the qRT-PCR and sequence analysis, only one gene designated as GmSFT (Glyma.13g248000) displayed significantly higher expression level in all tolerant genotypes compared to sensitive ones under flooding treatment, as well as revealed nonsynonymous mutation in tolerant genotypes, leading to amino acid change in the protein. Additionally, subcellular localization showed that GmSFT was localized in the nucleus and cell membrane. Hence, GmSFT was considered as the most likely candidate gene for seed-flooding tolerance in soybean. In conclusion, the findings of the present study not only increase our knowledge of the genetic control of seed-flooding tolerance in soybean, but will also be of great utility in marker-assisted selection and gene cloning to elucidate the mechanisms of seed-flooding tolerance.