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Abstract Background 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. Results 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. Conclusions 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.

Background: Wheat (Triticum aestivum) is one of the most important cereal crops, providing food for humans and feed for other animals. However, its productivity is challenged by various biotic and abiotic stresses such as fungal diseases, insects, drought, salinity, and cold. Transcription factors (TFs) regulate gene expression in different tissues and at various developmental stages in plants and animals, and they can be identified and classified into families according to their structural and specialized DNA-binding domains (DBDs). Transcription factors are important regulatory components of the genome, and are the main targets for engineering stress tolerance. Results: In total, 2407 putative TFs were identified from wheat expressed sequence tags, and then classified into 63 families by using Hmm searches against hidden Markov model (HMM) profiles. In this study, 2407 TFs represented approximately 2.22% of all genes in the wheat genome, a smaller proportion than those reported for other cereals in PlantTFDB V3.0 (3.33%-5.86%) and PlnTFDB (4.30%-6.46%). We assembled information from the various databases for individual TFs, including annotations and details of their developmental stage- and tissue-specific expression patterns. Based on this information, we identified 1257 developmental stage-specific TFs and 1104 tissue-specific TFs, accounting for 52.22% and 45.87% of the 2407 wheat TFs, respectively. We identified 338, 269, 262, 175, 49, and 18 tissue-specific TFs in the flower, seed, root, leaf, stem, and crown, respectively. There were 100, 6, 342, 141, 390, and 278 TFs specifically expressed at the dormant seed, germinating seed, reproductive, ripening, seedling, and vegetative stages, respectively. We constructed a comprehensive database of wheat TFs, designated as WheatTFDB (http://xms.sicau.edu.cn/wheatTFDB/). Conclusions: Approximately 2.22% (2407 genes) of all genes in the wheat genome were identified as TFs, and were clustered into 63 TF families. We identified 1257 developmental stage-specific TFs and 1104 tissue-specific TFs, based on information about their developmental- and tissue-specific expression patterns obtained from publicly available gene expression databases. The 2407 wheat TFs and their annotations are summarized in our database, WheatTFDB. These data will be useful identifying target TFs involved in the stress response at a particular stage of development. [ABSTRACT FROM AUTHOR]