Background: Genes interact with each other as basic building blocks of life, forming a complicated network. The relationship between groups of genes with different functions can be represented as gene networks. With the deposition of huge microarray data sets in public domains, study on gene networking is now possible. In recent years, there has been an increasing interest in the reconstruction of gene networks from gene expression data. Recent work includes linear models, Boolean network models, and Bayesian networks. Among them, Bayesian networks seem to be the most effective in constructing gene networks. A major problem with the Bayesian network approach is the excessive computational time. This problem is due to the interactive feature of the method that requires large search space. Since fitting a model by using the copulas does not require iterations, elicitation of the priors, and complicated calculations of posterior distributions, the need for reference to extensive search spaces can be eliminated leading to manageable computational affords. Bayesian network approach produces a discretely expression of conditional probabilities. Discreteness of the characteristics is not required in the copula approach which involves use of uniform representation of the continuous random variables. Our method is able to overcome the limitation of Bayesian network method for gene-gene interaction, i.e. information loss due to binary transformation. Results: We analyzed the gene interactions for two gene data sets (one group is eight histone genes and the other group is 19 genes which include DNA polymerases, DNA helicase, type B cyclin genes, DNA primases, radiation sensitive genes, repaire related genes, replication protein A encoding gene, DNA replication initiation factor, securin gene, nucleosome assembly factor, and a subunit of the cohesin complex) by adopting a measure of directional dependence based on a copula function. We have compared our results with those from other methods in the literature. Although microarray results show a transcriptional co-regulation pattern and do not imply that the gene products are physically interactive, this tight genetic connection may suggest that each gene product has either direct or indirect connections between the other gene products. Indeed, recent comprehensive analysis of a protein interaction map revealed that those histone genes are physically connected with each other, supporting the results obtained by our method. Conclusion: The results illustrate that our method can be an alternative to Bayesian networks in modeling gene interactions. One advantage of our approach is that dependence between genes is not assumed to be linear. Another advantage is that our approach can detect directional dependence. We expect that our study may help to design artificial drug candidates, which can block or activate biologically meaningful pathways. Moreover, our copula approach can be extended to investigate the effects of local environments on protein-protein interactions. The copula mutual information approach will help to propose the new variant of ARACNE (Algorithm for the Reconstruction of Accurate Cellular Networks): an algorithm for the reconstruction of gene regulatory networks.

The b-Zip transcription factor AtfA plays a key role in regulating stress responses in the filamentous fungus Aspergillus nidulans. To identify the core regulons of AtfA, we examined genome-wide expression changes caused by various stresses in the presence/absence of AtfA using A. nidulans microarrays. We also intended to address the intriguing question regarding the existence of core environmental stress response in this important model eukaryote. Examination of the genome wide expression changes caused by five different oxidative stress conditions in wild type and the atfA null mutant has identified a significant number of stereotypically regulated genes (Core Oxidative Stress Response genes). The deletion of atfA increased the oxidative stress sensitivity of A. nidulans and affected mRNA accumulation of several genes under both unstressed and stressed conditions. The numbers of genes under the AtfA control appear to be specific to a stress-type. We also found that both oxidative and salt stresses induced expression of some secondary metabolite gene clusters and the deletion of atfA enhanced the stress responsiveness of additional clusters. Moreover, certain clusters were down-regulated by the stresses tested. Our data suggest that the observed co-regulations were most likely consequences of the overlapping physiological effects of the stressors and not of the existence of a general environmental stress response. The function of AtfA in governing various stress responses is much smaller than anticipated and/or other regulators may play a redundant or overlapping role with AtfA. Both stress inducible and stress repressive regulations of secondary metabolism seem to be frequent features in A. nidulans.

In filamentous fungal Aspergillus species, growth, development, and secondary metabolism are genetically programmed biological processes, which require precise coordination of diverse signaling elements, transcription factors (TFs), upstream and downstream regulators, and biosynthetic genes. For the last few decades, regulatory roles of these controllers in asexual/sexual development and primary/secondary metabolism of Aspergillus species have been extensively studied. Among a wide spectrum of regulators, a handful of global regulators govern upstream regulation of development and metabolism by directly and/or indirectly affecting the expression of various genes including TFs. In this review, with the model fungus Aspergillus nidulans as the central figure, we summarize the most well-studied main upstream regulators and their regulatory roles. Specifically, we present key functions of heterotrimeric G proteins and G protein-coupled receptors in signal transduction), the velvet family proteins governing development and metabolism, LaeA as a global regulator of secondary metabolism, and NsdD, a key GATA-type TF, affecting development and secondary metabolism and provide a snapshot of overall upstream regulatory processes underlying growth, development, and metabolism in Aspergillus fungi.

Han KH. Mycobiology. 2009 Sep;37(3):171-182. http://dx.doi.org/10.4489/MYCO.2009.37.3.171

The velvet regulator VosA plays a pivotal role in asexual sporulation in the model filamentous fungus Aspergillus nidulans. In the present study, we characterize the roles of VosA in sexual spores (ascospores) in A. nidulans. During ascospore maturation, the deletion of vosA causes a rapid decrease in spore viability. The absence of vosA also results in a lack of trehalose biogenesis and decreased tolerance of ascospores to thermal and oxidative stresses. RNA-seq-based genome-wide expression analysis demonstrated that the loss of vosA leads to elevated expression of sterigmatocystin (ST) biosynthetic genes and a slight increase in ST production in ascospores. Moreover, the deletion of vosA causes upregulation of additional gene clusters associated with the biosynthesis of other secondary metabolites, including asperthecin, microperfuranone, and monodictyphenone. On the other hand, the lack of vosA results in the downregulation of various genes involved in primary metabolism. In addition, vosA deletion alters mRNA levels of genes associated with the cell wall integrity and trehalose biosynthesis. Overall, these results demonstrate that the velvet regulator VosA plays a key role in the maturation and the cellular and metabolic integrity of sexual spores in A. nidulans.

Aspergillus pseudoglaucus is a xerophilic filamentous fungus which can produce various secondary metabolites. Here, we reported the complete mitochondrial genome sequence of A. pseudoglaucus isolated from Meju, a soybean brick in Korea. Its mitochondrial genome was successfully assembled from raw reads sequenced using MiSeq by Velvet and SOAPGapCloser. Total length of the mitochondrial genome is 53,882 bp, which is third longest among known Aspergillus mitochondrial genomes and encoded 58 genes (30 protein-coding genes including hypothetical ORFs, two rRNAs, and 26 tRNAs). Nucleotide sequence of coding regions takes over 66.6% and overall GC content is 27.8%. Phylogenetic trees present that A. pseudoglaucus is located outside of section Nidulantes. Additional researches will be required for clarifying phylogenetic position of section Aspergillus.