Lamprosema indicate is a major leaf feeding insect pest to soybean, which has caused serious yield losses in central and southern China. To explore the defense mechanisms of soybean resistance to Lamprosema indicate, a highly resistant line (Gantai-2-2) and a highly susceptible line (Wan 82–178) were exposed to Lamprosema indicate larval feedings for 0 h and 48 h, and the differential proteomic analyses of these two lines were carried out. The results showed that 31 differentially expressed proteins (DEPs) were identified in the Gantai-2-2 when comparing 48 h feeding with 0 h feeding, and 53 DEPs were identified in the Wan 82–178. 28 DEPs were identified when comparing Gantai-2-2 with Wan 82–178 at 0 h feeding. The bioinformatic analysis results showed that most of the DEPs were associated with ribosome, linoleic acid metabolism, flavonoid biosynthesis, phenylpropanoid biosynthesis, peroxisome, stilbenoid, diarylheptanoid and gingerol biosynthesis, glutathione metabolism, pant hormone signal transduction, and flavone and flavonol biosynthesis, as well as other resistance related metabolic pathways. The MRM analysis showed that the iTRAQ results were reliable. According to the analysis of the DEPs results, the soybean defended or resisted the Lamprosema indicate damage by the induction of a synthesis of anti-digestive proteins which inhibit the growth and development of insects, reactive oxygen species scavenging, signaling pathways, secondary metabolites synthesis, and so on.

Soybean is one of most important oilseed crop worldwide, however, its production is often limited by many insect pests. Bean pyralid is one of the major soybean leaf-feeding insects in China. To explore the defense mechanisms of soybean resistance to bean pyralid, the comparative transcriptome sequencing was completed between the leaves infested with bean pyralid larvae and no worm of soybean (Gantai-2-2 and Wan82–178) on the Illumina HiSeq™ 2000 platform. In total, we identified 1744 differentially expressed genes (DEGs) in the leaves of Gantai-2-2 (1064) and Wan82–178 (680) fed by bean pyralid for 48 h, compared to 0 h. Interestingly, 315 DEGs were shared by Gantai-2-2 and Wan82–178, while 749 and 365 DEGs specifically identified in Gantai-2-2 and Wan82–178, respectively. When comparing Gantai-2-2 with Wan82–178, 605 DEGs were identified at 0 h feeding, and 468 DEGs were identified at 48 h feeding. Gene Ontology (GO) annotation analysis revealed that the DEGs were mainly involved in the metabolic process, single-organism process, cellular process, responses to stimulus, catalytic activities and binding. Pathway analysis showed that most of the DEGs were associated with the plant-pathogen interaction, phenylpropanoid biosynthesis, phenylalanine metabolism, flavonoid biosynthesis, peroxisome, plant hormone signal transduction, terpenoid backbone biosynthesis, and so on. Finally, we used qRT-PCR to validate the expression patterns of several genes and the results showed an excellent agreement with deep sequencing. According to the comparative transcriptome analysis results and related literature reports, we concluded that the response to bean pyralid feeding might be related to the disturbed functions and metabolism pathways of some key DEGs, such as DEGs involved in the ROS removal system, plant hormone metabolism, intracellular signal transduction pathways, secondary metabolism, transcription factors, biotic and abiotic stresses. We speculated that these genes may have played an important role in synthesizing substances to resist insect attacks in soybean. Our results provide a valuable resource of soybean defense genes that will benefit other studies in this field.

Soybean is one of the most important oil crops in the world. Bean pyralid is a major leaf-feeding insect of soybean. In order to screen out the functional genes and regulatory pathways related to the resistance for bean pyralid larvae, the small RNA and transcriptome sequencing were performed based on the highly resistant material (Gantai-2-2) and highly susceptible material (Wan 82-178) of soybean. The results showed that, when comparing 48 h feeding with 0 h feeding, 55 differentially expressed miRNAs were identified in Gantai-2-2 and 58 differentially expressed miRNAs were identified in Wan82-178. When comparing Gantai-2-2 with Wan82-178, 77 differentially expressed miRNAs were identified at 0 h feeding, and 70 differentially expressed miRNAs were identified at 48 h feeding. The pathway analysis of the predicted target genes revealed that the plant hormone signal transduction, RNA transport, protein processing in the endoplasmic reticulum, zeatin biosynthesis, ubiquinone and other terpenoid-quinone biosynthesis, and isoquinoline alkaloid biosynthesis may play important roles in soybean’s defense against the stress caused by bean pyralid larvae. According to conjoint analysis of the miRNA/mRNA, a total of 20 differentially expressed miRNAs were negatively correlated with 26 differentially expressed target genes. The qRT-PCR analysis verified that the small RNA sequencing results were credible. According to the analyses of the differentially expressed miRNAs, we speculated that miRNAs are more likely to play key roles in the resistance to insects. Gma-miR156q, Gma-miR166u, Gma-miR166b, Gma-miR166j-3p, Gma-miR319d, Gma-miR394a-3p, Gma-miR396e, and so on—as well as their negatively regulated differentially expressed target genes—may be involved in the regulation of soybean resistance to bean pyralid larvae. These results laid a foundation for further in-depth research regarding the action mechanisms of insect resistance.

Bean pyralid is one of the major leaf-feeding insects that affect soybean crops. DNA methylation can control the networks of gene expressions, and it plays an important role in responses to biotic stress. However, at present the genome-wide DNA methylation profile of the soybean resistance to bean pyralid has not been reported so far. Using whole-genome bisulfite sequencing (WGBS) and RNA-sequencing (RNA-seq), we analyzed the highly resistant material (Gantai-2-2, HRK) and highly susceptible material (Wan82–178, HSK), under bean pyralid larvae feeding 0 h and 48 h, to clarify the molecular mechanism of the soybean resistance and explore its insect-resistant genes. We identified 2194, 6872, 39,704 and 40,018 differentially methylated regions (DMRs), as well as 497, 1594, 9596 and 9554 differentially methylated genes (DMGs) in the HRK0/HRK48, HSK0/HSK48, HSK0/HRK0 and HSK48/HRK48 comparisons, respectively. Through the analysis of global methylation and transcription, 265 differentially expressed genes (DEGs) were negatively correlated with DMGs, there were 34, 49, 141 and 116 negatively correlated genes in the HRK0/HRK48, HSK0/HSK48, HSK0/HRK0 and HSK48/HRK48, respectively. The MapMan cluster analysis showed that 114 negatively correlated genes were clustered in 24 pathways, such as protein biosynthesis and modification; primary metabolism; secondary metabolism; cell cycle, cell structure and component; RNA biosynthesis and processing, and so on. Moreover, CRK40; CRK62; STK; MAPK9; L-type lectin-domain containing receptor kinase VIII.2; CesA; CSI1; fimbrin-1; KIN-14B; KIN-14 N; KIN-4A; cytochrome P450 81E8; BEE1; ERF; bHLH25; bHLH79; GATA26, were likely regulatory genes involved in the soybean responses to bean pyralid larvae. Finally, 5 DMRs were further validated that the genome-wide DNA data were reliable through PS-PCR and 5 DEGs were confirmed the relationship between DNA methylation and gene expression by qRT-PCR. The results showed an excellent agreement with deep sequencing. Genome-wide DNA methylation profile of soybean response to bean pyralid was obtained for the first time. Several specific DMGs which participated in protein kinase, cell and organelle, flavonoid biosynthesis and transcription factor were further identified to be likely associated with soybean response to bean pyralid. Our data will provide better understanding of DNA methylation alteration and their potential role in soybean insect resistance.

Crops often face light intensity fluctuations in natural settings. Intercropping is widely used to improve crop yield and resource utilization worldwide, but crops suffer from high-frequency and high-intensity light fluctuations due to mutual crop influence. Soybean is an important legume crop and is often intercropped with other crops, but little is known about soybean’s response to light fluctuation environments. Herein, three fluctuation frequencies (1, 10, and 20 min/cycle) were used to analyze soybean photosynthesis responses by measuring leaf growth, chlorophyll content, gas exchange, and electron transfer. Our data revealed that faster fluctuation frequencies led to the stronger suppression of soybean morphology and photosynthesis, with significant reductions of 31.31% and 21.58%, respectively. Damage to photosystems II (PSII) and I (PSI) also intensified, with significant decreases of 18.52% and 18.38% in their effective quantum yields Y(II) and Y(I). Additionally, increased fluctuation frequency exacerbated the consumption of the plastoquinone pool and linear electron flow but enhanced the cyclic electron flow across the thylakoid membrane and, thus, increased heat dissipation in PSII. Our findings indicate that an increased fluctuation frequency inflicted more severe damage on the soybean photosynthesis system. However, PSI-enhanced CEF improved NPQ and coordinated photoprotection to some extent.

Shade tolerance is a key trait for cultivars in inter/relay-cropped soybeans in maize fields. Our previous genome-wide association study (GWAS) results on southern China soybean germplasm revealed that the shade tolerance was conferred by a complex of genes with multiple alleles. To complete our understanding of the shade tolerance gene system, GWAS with gene–allele sequences as markers (designated GASM-RTM-GWAS) was conducted in a recombinant inbred line (RIL) population between two extreme parents using the shade tolerance index (STI) and relative pith cell length (RCL) as indicators. Altogether, 211 genes, comprising 99 and 119 genes (seven shared) for STI and RCL, respectively, were identified and then annotated into a similar set of five biological categories. Furthermore, transcriptome analysis detected 7837 differentially expressed genes (DEGs), indicating plentiful DEGs involved in the expression of regulatory/causal GWAS genes. Protein–protein interaction (PPI) analysis and gene functional analysis for both GWAS genes and DEGs showed a group of interrelated causal genes and a group of interrelated DEGs; the former were included in the latter and their functions were interconnected as a gene network. For further understanding of the response of soybean to shade stress in a sequential connection, six chronological gene modules were grouped as signal activation and transport, signal-transduction, signal amplification, gene expression, regulated metabolites, and material transport. From the modules, 12 key genes were selected as entry points for further analysis. Our study provides an overview of the shade tolerance gene network as a new insight into a complex-trait genetic system, rather than the usual way of starting from a hand-picked single gene.