In order to assist the design of short interfering ribonucleic acids （siRNA）, 573 non-redundant siRNAs were collected from published literatures and the relationship between siRNAs sequences and RNA interference （RNAi） effect is analyzed by a support vector machine （SVM） based algorithm relied on a basebase correlation （BBC） feature. The results show that the proposed algorithm has the highest area under curve （AUC） value （0. 73） of the receive operating characteristic （ROC） curve and the greatest r value （0. 43） of the Pearson＇s correlation coefficient. This indicates that the proposed algorithm is better than the published algorithms on the collected datasets and that more attention should be paid to the base-base correlation information in future siRNA design.
The complex regulatory network between microRNAs and gene expression remains an unclear domain of active research.We proposed to address in part this complex regulation with a novel approach for the genome-wide identification of biomodules derived from paired microRNA and mRNA profiles,which could reveal correlations associated with a complex network of dys-regulation in human cancer.Two published expression datasets for 68 samples with 11 distinct types of epithelial cancers and 21 samples of normal tissues were used,containing microRNA expression and gene expression profiles,respectively.As results,the microRNA expression used jointly with mRNA expression can provide better classifiers of epithelial cancers against normal epithelial tissue than either dataset alone(P=1×10-10,F-test).We identified a combination of 6 microRNA-mRNA biomodules that optimally classified epithelial cancers from normal epithelial tissue(total accuracy = 93.3%;95% confidence intervals:86%-97%),using penalized logistic regression(PLR) algorithm and three-fold cross-validation.Three of these biomodules are individually sufficient to cluster epithelial cancers from normal tissue using mutual information distance.The biomodules contain 10 distinct microRNAs and 98 distinct genes,including well known tumor markers such as miR-15a,miR-30e,IRAK1,TGFBR2,DUSP16,CDC25B and PDCD2.In addition,there is a significant enrichment(Fisher's exact test P=3×10-10) between putative microRNA-target gene pairs reported in 5 microRNA target databases and the inversely correlated microRNA-mRNA pairs in the biomodules.Further,microRNAs and genes in the biomodules were found in abstracts mentioning epithelial cancers(Fisher's Exact test,unadjusted P<0.05).Taken together,these results strongly suggest that the discovered microRNA-mRNA biomodules correspond to regulatory mechanisms common to human epithelial cancer samples.In conclusion,we developed and evaluated a novel comprehensive method to systematically identify,on a genome scale,microRNA-mRNA expression b
YANG XiNanLEE YoungheeFAN HongSUN XiaoLUSSIER Yves A
Nucleosome positioning in promoters is important for gene transcription regulation. In this paper, with a nucleosome prediction model, curvature profile, the characteristics of nucleosome positioning in promoters are analyzed for miRNA genes and protein-coding genes. In the vicinity of transcription start site (TSS), there is a nucleosome-free region (NFR) followed by a positioned nucleosome at ～200 bp downstream of TSS. A similar characteristic is observed in independent intronic promoters and intergenic promoters, namely, both types of promoters have a longer NFR in 0—-400 bp upstream of TSS. Moreover, transcription factor binding sites (TFBSs) locate in the NFR with a high concentration. However, nucleosome pattern in dependent intronic promoters are like that in protein-coding promoters, with two nucleosomes positioned at -200—-400 bp and -400—-600 bp upstream of TSS. The results indicate nucleosome positioning is probably different in independent miRNA promoters and protein-coding promoters; and positioning seems to be an important factor not only in regulation of protein-coding gene, but also in that of miRNA gene.
LIU HongDe ZHANG DeJin XIE JianMing YUAN ZhiDong MA Xin LU ZhiYuan GONG LeJun SUN Xiao
