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Motif identification has been one of the most widely studied problems in bioinformatics. Many methods have been developed to discover binding motifs from a large set of genes. But when the given genes are only a partial set of target genes, the statistical significance usually contains a bias towards the input. If we can identify the TF binding motif from a partial set of target genes, we can save the labor costs and resources for doing many experiments. In this paper, we propose a method MISA (Motif Identification through Segments Assembly) to identify binding motifs from a subset of target genes. By ranking and assembling the segments, MISA discovers a set of binding motifs with the best length to fit our proposed objective function. We also predict the additional target genes as an application of regulatory network inference. We compare our approach with two widely used methods MEME and AlignACE by analyzing both the quality of the binding motif and network inference. Using two model organisms S. cerevisiae and E. coli, we show that with 20 percent of the target genes (minimum sample size of 20), we can achieve a motif similarity of 82 percent with the known motifs. Our results also show that 73 percent of target genes on average can be correctly predicted without introducing many false target genes. [ABSTRACT FROM AUTHOR]

Head blight caused by Fusarium graminearum threatens world-wide wheat production, resulting in both yield loss and mycotoxin contamination., We reconstructed the global F. graminearum gene regulatory network (GRN) from a large collection of transcriptomic data using Bayesian network inference, a machine-learning algorithm. This GRN reveals connectivity between key regulators and their target genes. Focusing on key regulators, this network contains eight distinct but interwoven modules. Enriched for unique functions, such as cell cycle, DNA replication, transcription, translation and stress responses, each module exhibits distinct expression profiles., Evolutionarily, the F. graminearum genome can be divided into core regions shared with closely related species and variable regions harboring genes that are unique to F. graminearum and perform species-specific functions. Interestingly, the inferred top regulators regulate genes that are significantly enriched from the same genomic regions ( P < 0.05), revealing a compartmentalized network structure that may reflect network rewiring related to specific adaptation of this plant pathogen., This first-ever reconstructed filamentous fungal GRN primes our understanding of pathogenicity at the systems biology level and provides enticing prospects for novel disease control strategies involving the targeting of master regulators in pathogens. The program can be used to construct GRNs of other plant pathogens. [ABSTRACT FROM AUTHOR]

The cyclic adenosine monophosphate-protein kinase A (c AMP- PKA) pathway is a central signalling cascade that transmits extracellular stimuli and governs cell responses through the second messenger cAMP. The importance of cAMP signalling in fungal biology has been well documented and the key conserved components, adenylate cyclase ( AC) and the catalytic subunit of PKA ( CPKA), have been functionally characterized. However, other genes involved in this signalling pathway and their regulation are not well understood in filamentous fungi. Here, we performed a comparative transcriptomics analysis of AC and CPKA mutants in two closely related fungi: Fusarium graminearum ( Fg) and F. verticillioides ( Fv). Combining available Fg transcriptomics and phenomics data, we reconstructed the Fg cAMP signalling pathway. We developed a computational program that combines sequence conservation and patterns of orthologous gene expression to facilitate global transcriptomics comparisons between different organisms. We observed highly correlated expression patterns for most orthologues (80%) between Fg and Fv. We also identified a subset of 482 (6%) diverged orthologues, whose expression under all conditions was at least 50% higher in one genome than in the other. This enabled us to dissect the conserved and unique portions of the cAMP- PKA pathway. Although the conserved portions controlled essential functions, such as metabolism, the cell cycle, chromatin remodelling and the oxidative stress response, the diverged portions had species-specific roles, such as the production and detoxification of secondary metabolites unique to each species. The evolution of the cAMP- PKA signalling pathway seems to have contributed directly to fungal divergence and niche adaptation. [ABSTRACT FROM AUTHOR]