Bayesian inference of population expansions in domestic bovines

< p > The past population dynamics of four domestic and one wild species of bovine were estimated using Bayesian skyline plots, a coalescent Markov chain Monte Carlo method that does not require an assumed parametric model of demographic history. Four dom

Bayesian mixed models and divergence time estimation of Chinese cavefishes (Cyprinidae : Sinocyclocheilus)

The genus Sinocyclocheilus is distributed in Yun-Gui Plateau and its surrounding region only, within more than 10 cave species showing different degrees of degeneration of eyes and pigmentation with wonderful adaptations. To present, published morphological and molecular phylogenetic hypotheses of Sinocyclocheilus from prior works are very different and the relationships within the genus are still far from clear. We obtained the sequences of cytochrome b (cyt b) and NADH dehydrogenase subunit 4 (ND4) of 34 species within Sinocyclocheilus, which represent the most dense taxon sampling to date. We performed Bayesian mixed models analyses with this data set. Under this phylogenetic framework, we estimated the divergence times of recovered clades using different methods under relaxed molecular clock. Our phyloegentic results supported the monophyly of Sinocyclocheilus and showed that this genus could be subdivided into 6 major clades. In addition, an earlier finding demonstrating the polyphyletic of cave species and the most basal position of S. jii was corroborated. Relaxed divergence-time estimation suggested that Sinocyclocheilus originated at the late Miocene, about 11 million years ago (Ma), which is older than what have been assumed.

Biogeography and molecular phylogeny of the genus Schizothorax (Teleostei : Cyprinidae) in China inferred from cytochrome b sequences

Aim: To test a vicariant speciation hypothesis derived from geological evidence of large-scale changes in drainage patterns in the late Miocene that affected the drainages in the south-eastern Tibetan Plateau. Location: The Tibetan Plateau and adjacent areas. Methods: The cytochrome b DNA sequences of 30 species of the genus Schizothorax from nine different river systems were analysed. These DNA sequences were analysed using parsimony, maximum likelihood and Bayesian methods. The approximately unbiased and Shimodaira-Hasegawa tests were applied to evaluate the statistical significance of the shortest trees relative to alternative hypotheses. Dates of divergences between lineages were estimated using the nonparametric rate smoothing method, and confidence intervals of dates were obtained by parametric bootstrapping. Results: The phylogenetic relationships recovered from molecular data were inconsistent with traditional taxonomy, but apparently reflected geographical associations with rivers. Within the genus Schizothorax, we observed a divergence between the lineages from the Irrawaddy-Lhuit and Tsangpo-Parlung rivers, and tentatively dated this vicariant event back to the late Miocene (7.3-6.8 Ma). We also observed approximately simultaneous geographical splits within drainages of the south-eastern Tibetan Plateau, the Irrawaddy, the Yangtze and the Mekong-Salween rivers in the late Miocene (7.1-6.2 Ma). Main conclusions: Our molecular evidence tentatively highlights the importance of palaeoriver connections and the uplift of the Tibetan Plateau in understanding the evolution of the genus Schizothorax. Molecular estimates of divergence times allowed us to date these vicariant scenarios back to the late Miocene, which agrees with geological suggestions for the separation of these drainages caused by tectonic uplift in south-eastern Tibet. Our results indicated the substantial role of vicariant-based speciation in shaping the current distribution pattern of the genus Schizothorax.

Bayesian inference of plastosphere viscosities near the Kunlun Fault, northern Tibet

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An in silico approach for screening flavonoids as P-glycoprotein inhibitors based on a Bayesian-regularized neural network

P-glycoprotein (P-gp), an ATP-binding cassette (ABC) transporter, functions as a biological barrier by extruding cytotoxic agents out of cells, resulting in an obstacle in chemotherapeutic treatment of cancer. In order to aid in the development of potential P-gp inhibitors, we constructed a quantitative structure-activity relationship (QSAR) model of flavonoids as P-gp inhibitors based on Bayesian-regularized neural network (BRNN). A dataset of 57 flavonoids collected from a literature binding to the C-terminal nucleotide-binding domain of mouse P-gp was compiled. The predictive ability of the model was assessed using a test set that was independent of the training set, which showed a standard error of prediction of 0.146 +/- 0.006 (data scaled from 0 to 1). Meanwhile, two other mathematical tools, back-propagation neural network (BPNN) and partial least squares (PLS) were also attempted to build QSAR models. The BRNN provided slightly better results for the test set compared to BPNN, but the difference was not significant according to F-statistic at p = 0.05. The PLS failed to build a reliable model in the present study. Our study indicates that the BRNN-based in silico model has good potential in facilitating the prediction of P-gp flavonoid inhibitors and might be applied in further drug design.