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Updated: Mar 23, 2026

Quantitative Analysis of Aspergillus nidulans Growth Rate using Live Microscopy and Open-Source Software
Published on: July 24, 2021
Development and validation of a custom microarray for global transcriptome profiling of the fungus Aspergillus
Claudine Deloménie1, Guido Grentzmann2, Nathalie Oestreicher3,4
1UMS IPSIT, Plateforme Trans-Prot, Faculté de Pharmacie, Univ. Paris-Sud, Université Paris-Saclay, 5 rue Jean-Baptiste Clément, 92296, Châtenay-Malabry, France. claudine.delomenie@u-psud.fr.
None:
Transcriptome profiling is a powerful tool for identifying gene networks from whole genome expression analysis in many living species. Here is described the first extensively characterized platform using Agilent microarray technology for transcriptome analysis in the filamentous fungus Aspergillus (Emericella) nidulans. We developed and validated a reliable gene expression microarray in 8 × 15 K format, with predictive and experimental data establishing its specificity and sensitivity. Either one or two 60-mer oligonucleotide probes were selected for each of 10,550 nuclear as well as 20 mitochondrial coding sequences. More than 99 % of probes were predicted to hybridize with 100 % identity to their aimed specific A. nidulans target only. Probe sensitivity was supported by a highly narrow distribution of melting temperatures together with thermodynamic features, which strongly favored probe-target perfect match hybridization, in comparison with predicted secondary structures. Array quality was evaluated through transcriptome comparison of two A. nidulans strains, differing by the presence or not of Escherichia coli LacZ transgene. High signal-to-noise ratios were measured, and signal reproducibility was established at intra-probe and inter-probe levels. Reproducibility of microarray performances was assessed by high correlation between two-color dye signals and between technical replicates. Results were confirmed by RT-qPCR analysis on five genes. Though it covers 100 % of the A. nidulans targeted coding sequences, this low density array allows limited experimental costs and simplified data analysis process, making it suitable for studying gene expression in this model organism through large numbers of experimental conditions, in basic, biomedical or industrial microbiology research fields.

