Multiple reaction monitoring (MRM)-based targeted metabolomics can simultaneously analyze up to hundreds of metabolites with high-throughput, good reproducibility, and wide dynamic range. However, when hundreds or thousands of MRM transitions are measured with tens to hundreds of biological samples, the complexity of MRM dataset acquired is no longer amenable to manual evaluation, and presents a challenge for targeted metabolomics. Here, we developed an R package, namely MRMAnalyzer, to process large set of MRM-based targeted metabolomics data automatically without any manual intervention. To demonstrate our MRMAnalyzer program, we first developed a targeted metabolomic method that simultaneously analyzes 182 metabolites in one 15-min LC run, and demonstrated the data processing procedures using MRMAnalyzer. The data processing steps include ''pseudo'' accurate m/z transformation, peak detection and alignment, metabolite identification, quality control check and statistical analysis. Finally, a targeted metabolomic assay was designed and integrated with MRMAnalyzer to profile the metabolic changes in Escherichia coli subjected to the protein expression. The generated MRM dataset consisting of more than 8000 MRM transitions were readily processed using MRMAnalyzer within 20 min without any manual intervention. Fourty seven out of 140 detected metabolites, enriched in six metabolic pathways, were found significantly affected in E. coli metabolome. In summary, a targeted metabolomic platform is developed for high-throughput metabolite profiling and automated data processing, and the MRMAnalyzer program is a high efficient informatics tool for large scale targeted metabolomics.

Powdery mildew (PM), which is caused by the pathogen Erysiphe necator (Schw.) Burr., is the single most damaging disease of cultivated grapes (Vitis vinifera) worldwide. However, little is known about the transcriptional response of grapes to infection with PM. RNA-seq analysis was used for deep sequencing of the leaf transcriptome to study PM resistance in Chinese wild grapes (V. pseudoreticulata Baihe 35-1) to better understand the interaction between host and pathogen. Greater than 100 million (M) 90-nt cDNA reads were sequenced from a cDNA library derived from PM-infected leaves. Among the sequences obtained, 6541 genes were differentially expressed (DEG) and were annotated with Gene Ontology terms and by pathway enrichment. The significant categories that were identified included the following: defense, salicylic acid (SA) and jasmonic acid (JA) responses; systemic acquired resistance (SAR); hypersensitive response; plant–pathogen interaction; flavonoid biosynthesis; and plant hormone signal transduction. Various putative secretory proteins were identified, indicating potential defense responses to PM infection. In all, 318 putative R-genes and 183 putative secreted proteins were identified, including the defense-related R-genes BAK1, MRH1 and MLO3 and the defense-related secreted proteins GLP and PR5. The expression patterns of 16 genes were further illuminated by RT-qPCR. The present study identified several candidate genes and pathways that may contribute to PM resistance in grapes and illustrated that RNA-seq is a powerful tool for studying gene expression. The RT-qPCR results reveal that effective resistance responses of grapes to PM include enhancement of JA and SAR responses and accumulation of phytoalexins.

Grapevine powdery mildew is one of the most damaging fungal diseases. Therefore, a precise understanding of the grapevine disease resistance system becomes a subject of significant importance. Plant microRNAs(miRNAs) have been implicated to play regulatory roles in plant biotic stress responses. In this study, high-throughput sequencing and miRDeep-P were employed to identify miRNAs in Chinese wild Vitis pseudoreticulata leaves following inoculation with Erysiphe necator. Altogether, 126 previously identified microRNAs and 124 novel candidates of miRNA genes were detected. Among them, 43 conserved miRNAs belong to 20 families and 23 non-conserved but previously-known miRNAs belong to 15 families. Following E. necator inoculation, 119 miRNAs were down-regulated and 131 were up-regulated. Furthermore, the expression changes occurring in 32 miRNAs were significant. The expression patterns of some miRNAs were validated by semi-quantitative RT-PCR and qRT-PCR. A total of 485 target genes were predicted and categorized by Gene Ontology (GO). In addition, 14 vvi-miRNAs were screened with 36 targets which may be involved in powdery mildew resistance in grape. Highly accumulated vvi-NewmiR2118 was detected from accession “Baihe-35-1,” whose targets were mostly NBS-LRR resistance genes. It was down-regulated rapidly and strongly in “Baihe-35-1” leaves after inoculated with E. necator, indicating its involvement in grape powdery mildew resistance. Finally, the study verified interaction between vvi-NewmiR2118 and RPP13 by histochemical staining and GUS fluorescence quantitative assay.

Apple (Malus domestica Borkh.) is a commercially important fruit worldwide. Detailed information on genomic DNA polymorphisms, which are important for understanding phenotypic traits, is lacking for the apple. We re-sequenced two elite apple varieties, ‘Nagafu No. 2’ and ‘Qinguan,’ which have different characteristics. We identified many genomic variations, including 2,771,129 single nucleotide polymorphisms (SNPs), 82,663 structural variations (SVs), and 1,572,803 insertion/deletions (INDELs) in ‘Nagafu No. 2’ and 2,262,888 SNPs, 63,764 SVs, and 1,294,060 INDELs in ‘Qinguan.’ The ‘SNP,’ ‘INDEL,’ and ‘SV’ distributions were non-random, with variation-rich or -poor regions throughout the genomes. In ‘Nagafu No. 2’ and ‘Qinguan’ there were 171,520 and 147,090 non-synonymous SNPs spanning 23,111 and 21,400 genes, respectively; 3,963 and 3,196 SVs in 3,431 and 2,815 genes, respectively; and 1,834 and 1,451 INDELs in 1,681 and 1,345 genes, respectively. Genetic linkage maps of 190 flowering genes associated with multiple flowering pathways in ‘Nagafu No. 2,’ ‘Qinguan,’ and ‘Golden Delicious,’ identified complex regulatory mechanisms involved in floral induction, flower bud formation, and flowering characteristics, which might reflect the genetic variation of the flowering genes. Expression profiling of key flowering genes in buds and leaves suggested that the photoperiod and autonomous flowering pathways are major contributors to the different floral-associated traits between ‘Nagafu No. 2’ and ‘Qinguan.’ The genome variation data provided a foundation for the further exploration of apple diversity and gene–phenotype relationships, and for future research on molecular breeding to improve apple and related species.