Seedling drought stress is one of the most important constraints affecting soybean yield and quality. To unravel the molecular mechanisms under soybean drought tolerance, we conducted comprehensive comparative transcriptome analyses of drought-tolerant genotype Jindou 21 (JD) and drought-sensitive genotype Tianlong No.1 (N1) seedlings that had been exposed to drought treatment. A total of 6038 and 4112 differentially expressed genes (DEGs) were identified in drought-tolerant JD and drought-sensitive N1, respectively. Subsequent KEGG pathway analyses showed that numerous DEGs in JD are predominately involved in signal transduction pathways, including plant hormone signaling pathway, calcium signaling pathway, and MAPK signaling pathway. Interestingly, JA and BR plant hormone signal transduction pathways were found specifically participating in drought-tolerant JD. Meanwhile, the differentially expressed CPKs, CIPKs, MAPKs, and MAP3Ks of calcium and MAPK signaling pathway were only identified in JD. The number of DEGs involved in transcription factors (TFs) is larger in JD than that of in N1. Moreover, some differently expressed transcriptional factor genes were only identified in drought-tolerant JD, including FAR1, RAV, LSD1, EIL, and HB-PHD. In addition, this study suggested that JD could respond to drought stress by regulating the cell wall remodeling and stress-related protein genes such as EXPs, CALSs, CBPs, BBXs, and RD22s. JD is more drought tolerant than N1 owing to more DEGs being involved in multiple signal transduction pathways (JA, BR, calcium, MAPK signaling pathway), stress-related TFs, and proteins. The above valuable genes and pathways will deepen the understanding of the molecular mechanisms under drought stress in soybean.

Drought is a major environmental constraint that causes substantial reductions in plant growth and yield. Expression of stress-related genes is largely regulated by transcription factors (TFs), including in soybean [Glycine max (L.) Merr.]. In this study, 301 GmAP2/ERF genes that encode TFs were identified in the soybean genome. The TFs were divided into five categories according to their homology. Results of previous studies were then used to select the target gene GmAP2/ERF144 from among those up-regulated by drought and salt stress in the transcriptome. According to respective tissue expression analysis and subcellular determination, the gene was highly expressed in leaves and encoded a nuclear-localized protein. To validate the function of GmAP2/ERF144, the gene was overexpressed in soybean using Agrobacterium-mediated transformation. Compared with wild-type soybean, drought resistance of overexpression lines increased significantly. Under drought treatment, leaf relative water content was significantly higher in overexpressed lines than in the wild-type genotype, whereas malondialdehyde content and electrical conductivity were significantly lower than those in the wild type. Thus, drought resistance of transgenic soybean increased with overexpression of GmAP2/ERF144. To understand overall function of the gene, network analysis was used to predict the genes that interacted with GmAP2/ERF144. Reverse-transcription quantitative PCR showed that expression of those interacting genes in two transgenic lines was 3 to 30 times higher than that in the wild type. Therefore, GmAP2/ERF144 likely interacted with those genes; however, that conclusion needs to be verified in further specific experiments.

Background: Phytophthora sojae causes soybean root and stem rot, resulting in an annual loss of 1-2 billion US dollars in soybean production worldwide. A proteomic technique was used to determine the effects on soybean hypocotyls of infection with P. sojae. Results: In the present study, 46 differentially expressed proteins were identified in soybean hypocotyls infected with P. sojae, using two-dimensional electrophoresis and matrix-assisted laser desorption/ionization tandem time of flight (MALDI-TOF/TOF). The expression levels of 26 proteins were significantly affected at various time points in the tolerant soybean line, Yudou25, (12 up-regulated and 14 down-regulated). In contrast, in the sensitive soybean line, NG6255, only 20 proteins were significantly affected (11 up-regulated and 9 down-regulated). Among these proteins, 26% were related to energy regulation, 15% to protein destination and storage, 11% to defense against disease, 11% to metabolism, 9% to protein synthesis, 4% to secondary metabolism, and 24% were of unknown function. Conclusion: Our study provides important information on the use of proteomic methods for studying protein regulation during plant-oomycete interactions.

The 100-pod fresh weight (PFW), 100-seed fresh weight (SFW), 100-seed dry weight (SDW) and moisture content of fresh seeds (MCFS) at the R6 stage are crucial factors for vegetable soybean yield. However, the genetic basis of yield at the R6 stage remains largely ambiguous in soybean. To better understand the molecular mechanism underlying yield, we investigated four yield-related traits of 133 soybean landraces in two consecutive years and conducted a genome-wide association study (GWAS) using 82,187 single nucleotide polymorphisms (SNPs). The GWAS results revealed a total of 14, 15, 63 and 48 SNPs for PFW, SFW, SDW and MCFS, respectively. Among these markers, 35 SNPs were repeatedly identified in all evaluated environments (2015, 2016, and the average across the two years), and most co-localized with yield-related QTLs identified in previous studies. AX-90496773 and AX-90460290 were large-effect markers for PFW and MCFS, respectively. The two markers were stably identified in all environments and tagged to linkage disequilibrium (LD) blocks. Six potential candidate genes were predicted in LD blocks; five of them showed significantly different expression levels between the extreme materials with large PFW or MCFS variation at the seed development stage. Therefore, the five genes Glyma.16g018200, Glyma.16g018300, Glyma.05g243400, Glyma.05g244100 and Glyma.05g245300 were regarded as candidate genes associated with PFW and MCFS. These results provide useful information for the development of functional markers and exploration of candidate genes in vegetable soybean high-yield breeding programs.