BACKGROUND: Lung cancer is the most common cause of cancer-related death worldwide. Recently, deep transcriptional sequencing has been used as an effective genomic assay to get an insight into this disease.
AIM: This study is carried out to identify specific regulatory elements (SREs) in lung cancer.
MATERIALS AND METHODS: The RNA-sequencing data on lung cancer sample and normal sample were downloaded from NCBI. TopHat and Cufflinks were used to analyze differential alternative splicing in lung cancer by using RNA-sequenceing data. Further, we searched specific SREs in lung cancer through finding over-represented hexamers around high expression exons.
RESULTS: According to the Jensen-Shannon divergence between two samples and the p-value of t-test, we found 53 genes with differential alternative splicing in lung cancer. In the analysis of SREs, we found 763 specific SREs between lung cancer sample and normal sample.
CONCLUSIONS: These results may give an insight into how alternative splicing causes differential expression in lung cancer.Free PDF Download
To cite this article
R.-l. Chen, W. Guo, Y. Shi, H. Wu, J. Wang, G. Sun
Computational identification of specific splicing regulatory elements from RNA-seq in lung cancer
Eur Rev Med Pharmacol Sci
Vol. 17 - N. 13