Please note that we have stopped the regular imports of Gene Expression Omnibus (GEO) data into ArrayExpress. This may not be the latest version of this experiment.
E-GEOD-39993 - RNA sampling from a chemically diverse set of solid agar cultures of Aspergillus nidulans
Released on 4 April 2013, last updated on 22 April 2013
In this study, we design and apply a DNA expression array for Aspergillus nidulans in combination with legacy data to form a comprehensive gene expression compendium. We apply a guilt-by-association-based analysis to predict the extent of the biosynthetic clusters for the 58 synthases active in our set of experimental conditions. A comparison with legacy data shows the method to be accurate in 13 out of 16 known clusters and nearly accurate for the remaining three. Furthermore, we apply a data clustering approach, which identifies cross-chemistry between physically separate gene clusters (super clusters), and validate this both with legacy data and experimentally by prediction and verification of a new supercluster consisting of the synthase AN1242 and the transferase AN11080. This normally requires extensive sets of combinatorial gene deletions. We have employed A. nidulansfor our method development and validation due to the wealth of available biochemical data, but the method can be applied to any fungus with a sequenced and assembled genome, thus supporting further secondary metabolite pathway elucidation in the fungal kingdom. RNA was sampled from stabbed cultures on three different solid agar-based media (CYAs, YES, CYA) after 4, 8 or 10 days, resulting in a total of 8 samples.
transcription profiling by array
Mikael R Andersen <email@example.com>, Kristian F Nielsen, Lene H Blicher, Mia Zachariasen, Uffe H Mortensen
Accurate prediction of secondary metabolite gene clusters in filamentous fungi. Andersen MR, Nielsen JB, Klitgaard A, Petersen LM, Zachariasen M, Hansen TJ, Blicher LH, Gotfredsen CH, Larsen TO, Nielsen KF, Mortensen UH. , PMID:23248299