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:Here, we performed deep transcriptome sequencing for the aerial-tissues and the roots of S. japonica, generating over 2 billion raw reads with an average length of 101 nt by using an Illumina paired-end sequencing by HiSeq2000 platform. Using a combined approach of three popular assemblers, de novo transcriptome assembly for S. japonica was obtained, yielding in 81,729 unigenes with an average length as 884bps and N50-value as 1,452bps, with 46,963 unigenes being annotated based on the sequence similarity against NCBI-nr protein database. Transcriptome profiling of the aerial-tissues and the roots of Swertia japonica
Project description:Here, we performed deep transcriptome sequencing for the aerial-tissues and the roots of S. japonica, generating over 2 billion raw reads with an average length of 101 nt by using an Illumina paired-end sequencing by HiSeq2000 platform. Using a combined approach of three popular assemblers, de novo transcriptome assembly for S. japonica was obtained, yielding in 81,729 unigenes with an average length as 884bps and N50-value as 1,452bps, with 46,963 unigenes being annotated based on the sequence similarity against NCBI-nr protein database.
2016-07-01 | GSE80057 | GEO
Project description:Transcriptome of tissues in the pen shell Atrina pectinata
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.