Project description:We performed transcriptome assembly and gene expression analysis using short-read sequencing technology combined with a tag-based digital gene expression (DGE) system. The results generated a total number of 13,288,892 reads (accumulated length of 1,196,000,280 nt), 169,579 contings and 23,796 unigenes. Based on similarity search with known proteins, a total of 9,398 unigenes were identified with a cut-off E-value of 10-5. Assembled sequences were annotated with gene descriptions, such as gene ontology (GO) and clusters of orthologous group terms (COG). In addition, we obtained approximately 6 million raw tags and a larger number of genes at different fermentation stages (48 h, 100 h and 144 h). The related genes of growth characteristic and lipid biosynthesis were analyzed in detail. Some genes associated with the lipid biosynthesis were selected randomly to confirm digital gene expression (DGE) results by quantitative real-time PCR (qRT-PCR). The transcriptome improves our genetic understanding of Pythium splendens RBB-5 greatly and makes a large number of available gene sequences for further study. Notably, the transcriptome and DGE profiling data of Pythium splendens RBB-5 provide the comprehensive insight into gene expression profiles at different fermentation stages and lay a foundation for further study of optimizing lipid content and growth speed at the molecular level.
Project description:Globisporangium splendens (formerly Pythium splendens) is an oomycete pathogen of many economically important vegetable crops. Here, we present the first draft genome of P. splendens, which comprises 197 scaffolds with a total length of 53.3 Mb and 17,350 predicted protein-coding genes.
Project description:Comparative gene expression analysis of two wine yeast strains at three time points (days 2, 5 and 14) during fermentation of colombar must. In our study we conducted parallel fermentations with the VIN13 and BM45 wine yeast strains in two different media, namely MS300 (syntheticmust) and Colombar must. The intersection of transcriptome datasets from both MS300 (simulated wine must;GSE11651) and Colombar fermentations should help to delineate relevant and ‘noisy’ changes in gene expression in response to experimental factors such as fermentation stage and strain identity.
