BACKGROUND: Phenotypic studies in Triticeae have shown that low temperature-induced protective mechanisms are developmentally regulated and involve dynamic acclimation processes. Understanding these mechanisms is important for breeding cold-resistant wheat cultivars. In this study, we combined three computational techniques for the analysis of gene expression data from spring and winter wheat cultivars subjected to low temperature treatments. Our main objective was to construct a comprehensive network of cold response transcriptional events in wheat, and to identify novel cold tolerance candidate genes in wheat. RESULTS: We assigned novel cold stress-related roles to 35 wheat genes, uncovered novel transcription (TF)-gene interactions, and identified 127 genes representing known and novel candidate targets associated with cold tolerance in wheat. Our results also show that delays in terms of activation or repression of the same genes across wheat cultivars play key roles in phenotypic differences among winter and spring wheat cultivars, and adaptation to low temperature stress, cold shock and cold acclimation. CONCLUSIONS: Using three computational approaches, we identified novel putative cold-response genes and TF-gene interactions. These results provide new insights into the complex mechanisms regulating the expression of cold-responsive genes in wheat.

Fusarium head blight (FHB) limits wheat yield and compromises grain quality. We investigated differentially expressed genes after FHB challenge. FHB-susceptible and -resistant common wheat (Triticum aestivum) cultivars were challenged with the toxigenic fungus Fusarium graminearum and gene expression was analyzed using 61K Affymetrix wheat microarrays. We digitized trait specificity in the susceptible and resistant lines with and without the infection in order to facilitate subsequent data mining. We discovered various patterns of differential gene expression between susceptible and resistant lines in response to the infection. We performed association network analysis among genes in clusters significantly correlated with one or more quantitative trait loci known to contribute to Fusarium resistance. We found 11 interconnected hub genes responsive to FHB infection and significantly correlated with wheat resistance to FHB, among which two are predicted to encode a polygalacturonase-inhibiting protein (PGIP1).

Abstract Motivation: The computational identification of transcription factor binding sites is a major challenge in bioinformatics and an important complement to experimental approaches. Results: We describe a novel, exact discriminative seeding DNA motif discovery algorithm designed for fast and reliable prediction of cis-regulatory elements in eukaryotic promoters. The algorithm is tested on biological benchmark data and shown to perform equally or better than other motif discovery tools. The algorithm is applied to the analysis of plant tissue-specific promoter sequences and successfully identifies key regulatory elements. Availability: The Seeder Perl distribution includes four modules. It is available for download on the Comprehensive Perl Archive Network (CPAN) at http://www.cpan.org. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.