Project description:We present a comprehensive transcriptome of ciliate T. thermophila using the Illumina RNA-seq platform. The data was generated from the six mRNA samples of growth, starvation and conjugation of Tetrahymena. Despite an AT rich genome, there are about 124.6 million reads mapped to T. thermophila genome. Using these mapped reads, we have significantly improved the previous genome annotation and investigated the gene expression. Besides, our result also provided a comprehensive understanding of the alternative splicing in T. thermophila, and suggested the existence of the regulated unproductive splicing and translation (RUST) in the single-celled eukaryote. RNA-seq for six samples of Tetrahymena growth, starvation and conjugation.

2012-03-15 | E-GEOD-27971 | biostudies-arrayexpress

Lutibacter oricola strain:DSM 24956 | isolate:DSM 24956

Project description:Lutibacter oricola DSM 24956 genome sequencing

| PRJNA331369 | ENA

RNA-seq analysis of Tetrahymena thermophila

2012-03-15 | GSE27971 | GEO

Tetrahymena thermophila strain:CU427/CU428

Project description:Tetrahymena thermophila strain:CU427/CU428 Genome sequencing

| PRJNA338999 | ENA

Reconstruction and analysis genome-scale metabolic model of thermophilic fungus Myceliophthora thermophila

Project description:Myceliophthora thermophila is a thermophilic fungus with great biotechnological characteristics for industrial applications, which can degrade and utilize all major polysaccharides in plant biomass. Nowadays, it has been developing into a platform for production of enzyme, commodity chemicals and biofuels. Therefore, an accurate genome-scale metabolic model would be an accelerator for this fungus becoming a universal chassis for biomanufacturing. Here we present a genome-scale metabolic model for M. thermophila constructed using an auto-generating pipeline with consequent thorough manual curation. Temperature plays a basic and critical role for the microbe growth. we are particularly interested in the genome wide response at metabolic layer of M. thermophilia as it is a thermophlic fungus. To study the effects of temperature on metabolic characteristics of M. thermophila growth, the fungus was cultivated under different temperature. The metabolic rearrangement predicted using context-specific GEMs integrating transcriptome data.The developed model provides new insights into thermophilic fungi metabolism and highlights model-driven strain design to improve biotechnological applications of this thermophilic lignocellulosic fungus.

2022-09-14 | GSE184074 | GEO

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