Project description:In the family Fagaceae, fertilization is delayed by several weeks to more than one year after pollination, leading to one- or two-year fruiting species depending on whether fruiting occurs in the same or the next year of flowering. Although delayed fertilization was recorded over a century ago, underlying mechanisms remain to be explored. To uncover the key genes associated with delayed fertilization, we obtain and analyze the comparative molecular phenology data over two years in one-year (Quercus glauca) and two-year fruiting species (Lithocarpus edulis).
Project description:Purpose: The goal of this study is to provided a comprehensive genomic information for functional genomic studies in Q. mongolica. Methods:The Quercus mongolica leaves were generated by deep sequencing, using Illumina Hiseq 4000. The high-quality reads were obtained by removing the reads that contained adaptor contamination, low quality bases and undetermined bases.The transcriptome were de novo assembly. Results:A total of 52934562 raw reads were obtained from Illumina sequencing platform. After filtering out the low quality reads, we obtained 52076914 clean reads, which assembled into 39130 transcripts with a mean length of 742 bp and GC content of 42.12%, and 24196 unigenes with a mean length of 732 bp and GC content of 42.34%, based on Trinity assembly platform. Conclusions:RNA-Seq was applied to polyadenylate-enriched mRNAs from leaves of Q. mongolica to obtain the transcriptome. De novo assembly was then applied followed by gene annotation and functional classification. The SSRs and SNPs were also obtained using assembled transcripts as reference sequences. The results of this study lay the foundation for further research on genetic diversity of Quercus.
Project description:Sensitive and specific detection of the boxwood blight pathogen Calonectria pseudonaviculata with a metagenomic sequencing approach
Project description:Purpose: The goal of this study is to screen the candidate genes involved in drought avoidance of Q. liaotungensis Methods:The Q. liaotungensis leaves were generated by deep sequencing, using Illumina Hiseq 4000. The high-quality reads were obtained by removing the reads that contained adaptor contamination, low quality bases and undetermined bases.The transcriptome were de novo assembly. Results:A total of 54153182 raw reads were obtained from Illumina sequencing platform, and 53021436 clean reads were generated after filtering out the low quality reads. The clean reads were assembled into 41207 transcripts with median length 704 and GC content 42.17%, and 25593 unigenes with median length 687 and GC content 42.31%, based on Trinity assembly platform Conclusions:RNA-Seq was applied to polyadenylate-enriched mRNAs from leaves of Q. liaotungensis to obtain the transcriptome. De novo assembly was then applied followed by gene annotation and functional classification. The SSRs and SNPs were also obtained using assembled transcripts as reference sequences. The results of this study lay the foundation for further research on genetic diversity of Quercus.
Project description:Fusarium Head Blight (FHB) is a disease of wheat and other cereal crops, where Fusarium graminearum and related species infects the wheat inflorescence during and post-anthesis. The fungus produces trichothecene toxins that accumulate in the grain of infected head, and are required for disease spread. Microarrays were used to observe differential gene expression in the uninoculated spikelets of FHB-challenged wheat spikes in three wheat genotypes. A summary of our findings will be published in Plant Pathology.
Project description:Tomato crops suffer attacks of various pathogens that cause large production losses. Late blight caused by Phytophthora infestans is a devastating disease in tomatoes because of its difficultly to control. Here, we applied metabolomics based on liquid chromatography–mass spectrometry (LC-MS) and metabolic profiling by matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) in combination with multivariate data analysis in the early detection of late blight on asymptomatic tomato plants and to discriminate infection times of 4, 12, 24, 36, 48, 60, 72 and 96 h after inoculation (hpi). MALDI-MS and LC-MS profiles of metabolites combined with multivariate data analysis are able to detect early-late blight-infected tomato plants, and metabolomics based on LC-MS discriminates infection times in asymptomatic plants. We found the metabolite tomatidine as an important biomarker of infection, saponins as early infection metabolite markers and isocoumarin as early and late asymptomatic infection marker along the post infection time. MALDI-MS and LC-MS analysis can therefore be used as a rapid and effective method for the early detection of late blight-infected tomato plants, offering a suitable tool to guide the correct management and application of sanitary defense approaches. LC-MS analysis also appears to be a suitable tool for identifying major metabolites of asymptomatic late blight-infected tomato plants.