High-quality co-expression networks for accurate gene function predictions in the fungal cell factory Aspergillus niger and beyond
Co-expression networks have recently emerged as a useful approach for updating and improving gene annotation at a near-genome level. This is based on the hypothesis that function can be inferred by delineating transcriptional networks in which a gene of interest is embedded. In this study, we generated a co-expression network for the filamentous cell factory Aspergillus niger from 128 RNA-seq experiments. We confirm that over 70% of the >14,000 A. niger genes are represented in this network and show that gene functions can be accurately predicted as evidenced by analysis of various control sub-networks. Our analyses further indicate that this RNA-seq co-expression network has a higher predictive power compared to the microarray co-expression network that we published in 2019. To demonstrate the potential of the new co-expression network to unveil complex and non-intuitive predictions for gene regulation phenomena, we provide here new insights into the temporal, spatial and metabolic expression profile that connects a secreted antifungal peptide with mycelial growth, asexual development, secondary metabolism and pectin degradation in A. niger. To empower biologists to generate or apply co-expression networks in the fungal kingdom and beyond, we also demonstrate that (i) high quality networks can be generated from only 32 transcriptional experiments; (ii) such low numbers of experiments can be safely compensated for by using higher thresholds for defining co-expression pairs; and (iii) a 'safety in numbers' rule applies, whereby experimental conditions have minimal impact on network content provided a certain number of experiments are included. Overall design: This experiment aimed to determine the effect of anafp (A. niger antifungal protein) expression on the mRNA profile of A. niger. The goal was to validate predictions made by the co-expression network. Illumina HiSeq RNA sequencing was performed on Aspergillus niger mRNA, obtained from biomass cultivated in the presence or absence of anafp. To express anafp, the doxycycline (Dox)-responsive Tet-On gene switch ws utilized. RNA was extracted from biomass that had been cultivated in a 4-liter bioreactor (using liquid CM medium, without doxycycline) until the mid-exponential growth phase. The biomass was then transferred to agar plates lacking a carbon source and incubated for 35 hours, in the presence or absence of 5 µg/ml doxycycline before harvesting. The experiment was conducted in biological duplicates. For differential gene expression analysis, the mRNA profile of A. niger STS4.10 (Tet-On anafp) with 5 µg/ml doxycycline (representing the overexpression phenotype) was compared to that of STS4.10 with 0 µg/ml doxycycline (representing the knockout phenotype). Additionally, differential gene expression was assessed for A. niger VG8.27 (Tet-On-luciferase) in the presence or absence of 5 µg/ml doxycycline, which served as an overexpression control strain.