Molecular phylogeny of Colletotrichum (Sordariomycetes: Glomerellaceae) inferred from multiple gene sequences.

The genus Colletotrichum contains many important plant pathogens mainly distributed in tropical areas. Previous studies that utilized morphology or single genes have failed to resolve the phylogenetic relationships among the species. In this study, sequences of ß-tubulin, 28S ribosomal DNA, and ITS region from nine species were analyzed separately and combined to establish a fast method to infer the phylogeny of Colletotrichum using maximum parsimony, maximum likelihood, and Bayesian inference methods. The tree topologies inferred from the combined data set received higher bootstrap and posterior probability support than those inferred from the individual data sets. Obtained phylogenies highly supported C. capsici as the earliest diverging lineage followed by C. nymphaeae. The remaining seven species clustered into two distinct clades. Clade 1 consists of two monophyletic subclades: C. circinans, C. trichellum, and C. caudatum form one subclade and three accessions of C. dematium form another subclade. In Clade 2, C. incarnatum is in the basal-most clade. Three accessions of C. musae and C. caricae form a strongly supported clade indicating their close relationship. Spore shape analysis reveals an interesting evolutionary trend in the spore shape from acute- to obtuse-ended conidia and from curved to straight conidia in the sampled group of species. A quick and reliable way to infer the phylogeny of Colletotrichum based on combined DNA sequence data is presented in this paper.

Transcriptome network-based method to identify genes associated with unruptured intracranial aneurysms.

Intracranial aneurysm is a balloon or sac-like dilatation of blood vessels inside the brain. Despite their importance, the biological mechanisms of intracranial aneurysms are not totally understood. We used public genome-wide gene expression profile data to identify potential genes that are involved in intracranial aneurysm in order to construct a regulation network. Some of the transcription factors and target genes that we identified in this network had been identified as related to intracranial aneurysm in previous studies. We found additional transcription factors and target genes that are apparently related to intracranial aneurysm with this method. The confirmation of previously identified genes and transcription factors supports the usefulness of this transcriptome network analysis for the identification of candidate genes involved in intracranial aneurysm.