Alternaria blotch disease of apple (Malus × domestica Borkh.), caused by the apple pathotype of Alternaria alternata, is one of the most serious fungal diseases to affect apples. To develop an understanding of how apples respond to A. alternata apple pathotype (AAAP) infection, we examined the host transcript accumulation over the period between 0 and 72 h post AAAP inoculation. Large-scale gene expression analysis was conducted of the compatible interaction between “Starking Delicious” apple cultivar and AAAP using RNA-Seq and digital gene expression (DGE) profiling methods. Our results show that a total of 9080 differentially expressed genes (DEGs) were detected (>two-fold and FDR < 0.001) by RNA-Seq. During the early phase of infection, 12 h post inoculation (HPI), AAAP exhibited limited fungal development and little change in the transcript accumulation status (950 DEGs). During the intermediate phase of infection, the period between 18 and 36 HPI, increased fungal development, active infection, and increased transcript accumulation were detected (4111 and 3838 DEGs detected at each time point, respectively). The majority of DEGs were detected by 72 HPI, suggesting that this is an important time point in the response of apples' AAAP infection. Subsequent gene ontology (GO) and pathway enrichment analyses showed that DEGs are predominately involved in biological processes and metabolic pathways; results showed that almost gene associated with photosynthesis, oxidation-reduction were down-regulated, while transcription factors (i.e., WRKY, MYB, NAC, and Hsf) and DEGs involved in cell wall modification, defense signaling, the synthesis of defense-related metabolites, including pathogenesis-related (PRs) genes and phenylpropanoid/cyanoamino acid /flavonoid biosynthesis, were activated during this process. Our study also suggested that the cell wall defensive vulnerability and the down-regulation of most PRs and HSP70s in “Starking Delicious” following AAAP infection might interpret its susceptible to AAAP.

Background 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. Results 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. Conclusion These results provide useful information for the development of functional markers and exploration of candidate genes in vegetable soybean high-yield breeding programs. Electronic supplementary material The online version of this article (10.1186/s12863-019-0737-9) contains supplementary material, which is available to authorized users.

Soybean is one of the most important economic and oil crops across the world. Phytophthora root rot (PRR), caused by Phytophthora sojae (P. sojae), is a major disease in most soybean-growing regions worldwide. Here, we investigated metabolic changes in hypocotyls of two soybean lines, Nannong 10-1 (resistant line, R) and 06-070583 (susceptible line, S), at two time points (12 and 36 hpi) after P. sojae infection and metabolic differences between the R line and the S line. In total, 90 differentially accumulated metabolites (DAMs) were identified after P. sojae infection; the levels of 50 metabolites differed between the R line and the S line. There are 28 DAMs that not only differentially accumulated between the R line and the S line but also differentially accumulated after P. sojae infection. Based on the changes of these DAMs in response to P. sojae infection in different lines and at different timepoints, and the differences in the contents of these DAMs between the R line and the S line, we speculated that DAMs, including sugars (monosaccharides and oligosaccharides), organic acids (oxalic acid, cumic acid), amino acid derivatives, and other secondary metabolites (mannitol, octanal, hypoxanthine, and daidzein etc.) may participate in the metabolic-level defense response of soybean to P. sojae. In this study, an integrated pathway-level analysis of transcriptomics (obtained by RNA-Seq) and metabolomics data illustrated the poor connections and interdependencies between the metabolic and transcriptional responses of soybean to P. sojae infection. This work emphasizes the value of metabolomic studies of plant–pathogen interactions and paves the way for future research of critical metabolic determinants of the soybean-P. sojae interaction.

No abstract

No abstract