Hereditas最新文献

Background: Enhancers are tissue specific distal regulation elements, playing vital roles in gene regulation and expression. The prediction and identification of enhancers are important but challenging issues for bioinformatics studies. Existing computational methods, mostly single classifiers, can only predict the transcriptional coactivator EP300 based enhancers and show low generalization performance.

Results: We built a hybrid classifier called eRFSVM in this study, using random forests as a base classifier, and support vector machines as a main classifier. eRFSVM integrated two components as eRFSVM-ENCODE and eRFSVM-FANTOM5 with diverse features and labels. The base classifier trained datasets from a single tissue or cell with random forests. The main classifier made the final decision by support vector machines algorithm, with the predicting results of base classifiers as inputs. For eRFSVM-ENCODE, we trained datasets from cell lines including Gm12878, Hep, H1-hesc and Huvec, using ChIP-Seq datasets as features and EP300 based enhancers as labels. We tested eRFSVM-ENCODE on K562 dataset, and resulted in a predicting precision of 83.69 %, which was much better than existing classifiers. For eRFSVM-FANTOM5, with enhancers identified by RNA in FANTOM5 project as labels, the precision, recall, F-score and accuracy were 86.17 %, 36.06 %, 50.84 % and 93.38 % using eRFSVM, increasing 23.24 % (69.92 %), 97.05 % (18.30 %), 76.90 % (28.74 %), 4.69 % (89.20 %) than the existing algorithm, respectively.

Conclusions: All these results demonstrated that eRFSVM was a better classifier in predicting both EP300 based and FAMTOM5 RNAs based enhancers.

Background: The grasshopper family Lentulidae is endemic to eastern and southern Africa, with its center of diversity situated in South Africa, the highest diversity being found in the Cape Floristic Region, which is one of the global biodiversity hotspots. The family consists of 35 genera sorted in two subfamilies. This study provides first insights into the phylogeny of Lentulidae. Two mitochondrial genes (12S and NDS) were sequenced and the phylogeny was inferred through Maximum Likelihood and Bayesian Inference.

Results: Our results indicate that the current classification into the subfamilies Lentulinae and Shelforditinae may be incorrect as Uvarovidium, Leatettix (Shelforditinae) and Devylderia (Lentulinae) clustered together in one main clade, while Betiscoides, Basutacris and Gymnidium (all Lentulinae) formed the second main clade. The genera Uvarovidium and Leatettix, which had been assigned to the Acrididae (subfamily Hemiacridinae) in the past, grouped within the Lentulidae, confirming their current assignment to this family. The East African Usambilla group is likely to represent a sister clade to the south African Lentula and Eremidium. Diversification patterns in the genus Devylderia and Betiscoides suggest a higher number of species than currently known.

Conclusions: Our phylogeny is not in line with the current systematics of Lentulidae, suggesting that a broader sampling and a study of the genitalia would be useful to clarify the taxonomy. Furthermore, some genera (particularly Betiscoides and Devylderia) are in need of taxonomic revision, as the number of species within these genera is likely to be higher than the current taxonomy suggests.