Project description:We first report the use of next-generation massively parallel sequencing technologies and de novo transcriptome assembly to gain insight into the wide range of transcriptome of Hevea brasiliensis. The output of sequenced data showed that more than 12 million sequence reads with average length of 90nt were generated. Totally 48,768 unigenes (mean size = 488 bp) were assembled through transcriptome de novo assembly, which represent more than 3-fold of all the sequences of Hevea brasiliensis deposited in the GenBank. Assembled sequences were annotated with gene descriptions, gene ontology and clusters of orthologous group terms. Total 37,373 unigenes were successfully annotated and more than 10% of unigenes were aligned to known proteins of Euphorbiaceae. The unigenes contain nearly complete collection of known rubber-synthesis-related genes. Our data provides the most comprehensive sequence resource available for study rubber tree and demonstrates the availability of Illumina sequencing and de novo transcriptome assembly in a species lacking genome information. The transcriptome of latex and leaf in Hevea brasiliensis
Project description:We describe an application of deep sequencing and de novo assembly of short RNA reads to investigate small interfering (si)RNAs mediated immunity in leaf samples from eight tree taxa naturally occurring in Wytham Woods, Oxfordshire, UK. BLAST search for homologues of contigs in the GenBank identified siRNA populations against a number of RNA viruses and a Ty1-copia retrotransposons in these tree species. Small RNA sequencing and de novo assembly
Project description:In this study, we aim to present a global transcriptome analysis of medicinal plant, Catharanthus roseus. We generated about 343 million high-quality reads from three tissues (leaf, root and flower) using Illumina platform. We performed an optimized de novo assembly of the reads and estimated transcript abundance in different tissue samples. The transcriptome dynamics was studied by differential gene expression analyses among tissue samples. We collected different tissue samples from the mature plants. Total RNA isolated from these tissue samples was subjected to Illumina sequencing. The sequence data was further filtered using NGS QC Toolkit to obtain high-quality reads. The filtered reads were used for de novo assembly optimization. The reads were further mapped to the Catharanthus transcripts via CLC Genomics Workbench and differential gene expression analysis was performed using DESeq software.
Project description:In this study, we performed de novo transcriptome assembly for L. japonica, representing transcripts from nine different tissues. A total of 22Gbps clean RNA-seq reads from nine tissues of L. japonica were used, resulting in 243,185 unigenes, with 99,938 unigenes annotated based on homology search using blastx against NCBI-nr protein database. Unsupervised principal component analysis and correlation studies using transcripts expression data from all nine tissues of L. japonica showed relationships between tissues explaining their association at different developmental stages. Homologs for all genes associated with chlorogenic acid, luteolin, and secoiridoid biosynthesis pathways were identified in the L. japonica transcriptome assembly. Expression of unigenes associated with chlorogenic acid were enriched in stem and leaf-2, unigenes from luteolin were enriched in stem and flowers, while unigenes from secoiridoid metabolic pathways were enriched in leaf-1 and shoot apex. Our results showed that different tissues of L. japonica are enriched with sets of unigenes associated with a specific pharmaceutically important metabolic pathways, and therefore, possess unique medicinal properties. Present study will serve as a resource for future attempts for functional characterization of enzyme coding genes within key metabolic processes. De novo transcriptome assembly and characterization, and transcriptome profiling for nine tissues of Lonicera japonica
Project description:In this study, we aim to present a global transcriptome analysis of medicinal plant, Catharanthus roseus. We generated about 343 million high-quality reads from three tissues (leaf, root and flower) using Illumina platform. We performed an optimized de novo assembly of the reads and estimated transcript abundance in different tissue samples. The transcriptome dynamics was studied by differential gene expression analyses among tissue samples.
Project description:In order to understand the mechanism of single-cell C4 photosynthesis, we extracted total RNA from leaf tissues at young, intermediate, and mature stages. We then conducted gene expression profiling using RNA-seq and de novo transcriptome assembly. The gene expression data was normalized using Transcript Per Million, which was additionally adjusted by the Trimmed Mean of the M values (TPMTMM).