Sequence-level analysis of the diploidization process in the triplicated FLOWERING LOCUS C region of Brassica rapa

Strong evidence exists for polyploidy having occurred during the evolution of the tribe Brassiceae. We show evidence for the dynamic and ongoing diploidization process by comparative analysis of the sequences of four paralogous Brassica rapa BAC clones and the homologous 124-kb segment of Arabidopsis thaliana chromosome 5. We estimated the times since divergence of the paralogous and homologous lineages. The three paralogous subgenomes of B. rapa triplicated 13 to 17 million years ago (MYA), very soon after the Arabidopsis and Brassica divergence occurred at 17 to 18 MYA. In addition, a pair of BACs represents a more recent segmental duplication, which occurred approximately 0.8 MYA, and provides an exception to the general expectation of three paralogous segments within the B. rapa genome. The Brassica genome segments show extensive interspersed gene loss relative to the inferred structure of the ancestral genome, whereas the Arabidopsis genome segment appears little changed. Representatives of all 32 genes in the Arabidopsis genome segment are represented in Brassica, but the hexaploid complement of 96 has been reduced to 54 in the three subgenomes, with compression of the genomic region lengths they occupy to between 52 and 110 kb. The gene content of the recently duplicated B. rapa genome segments is identical, but intergenic sequences differ.     

The effect of histidine residue modification on tyrosinase activity and conformation: inhibition kinetics and computational prediction

We found that the histidine chemical modification of tyrosinase conspicuously inactivated enzyme activity. The substrate reactions with diethylpyridinecarbamate showed slow-binding inhibition kinetics (K(I) = 0.24 +/- 0.03 mM). Bromoacetate, as another histidine modifier, was also applied in order to study inhibition kinetics. The bromoacetate directly induced the exposures of hydrophobic surfaces following by complete inactivation via ligand binding. For further insights, we predicted the 3D structure of tyrosinase and simulated the docking between tyrosinase and diethylpyridinecarbamate. The docking simulation was shown to the significant binding energy scores (-3.77 kcal/mol by AutoDock4 and -25.26 kcal/mol by Dock6). The computational prediction was informative to elucidate the role of free histidine residues at the active site, which are related to substrate accessibility during tyrosinase catalysis.     

Protein network prediction and topological analysis in <Emphasis Type=Italic>Leishmania major</Emphasis> as a tool for drug target selection

Background  

Leishmaniasis is a virulent parasitic infection that causes a worldwide disease burden. Most treatments have toxic side-effects and efficacy has decreased due to the emergence of resistant strains. The outlook is worsened by the absence of promising drug targets for this disease. We have taken a computational approach to the detection of new drug targets, which may become an effective strategy for the discovery of new drugs for this tropical disease.     

Mutational hotspots in the mitochondrial genome of lung cancer

We determined the somatic mutations in the mitochondrial genomes of 70 lung cancer patients by pair-wise comparative analyses of the normal- and tumor-genome sequences acquired using Affymetrix Mitochondrial Resequencing Array 2.0. The overall mutation rates in lung cancers were Approximately 100 fold higher than those in normal cells, with significant statistical correlation with smoking (p = 0.00088). Total of 532 somatic mutations were evenly distributed in 499 positions with very low overall frequency (1.07/bp), but the non-synonymous mutations causing amino acid substitution occurred more frequently (1.83/bp), particularly at two positions, 8701 and 10398 (10.5/bp) that code for ATPase6 and NADH dehydrogenase 3, respectively. Despite the randomness or even distribution of the mutations, these two mutations occurred together in 86% of the cases. The linkage between the two most frequent mutations suggests that they were selected together, possibly due to their cooperative role during cancer development. Indeed, the mutation at 10398 was shown by Canter, Pezzotti, and their colleagues in 2009, as a risk factor for breast cancer. In this study, we identified two potential biomarkers that might be functionally linked together during the development of cancer.