• Original article (Basic research) • Previous Articles     Next Articles

RNA-Seq based analysis on cSNP and gene expression level

LI Shao-bo, FU Guo-hui   

  1. Department of Pathology, Basic Medical College, Shanghai Jiao Tong University, Shanghai 200025, China
  • Online:2014-02-28 Published:2014-03-25
  • Supported by:

    National Natural Science Foundation of China, 81171939


Objective To establish the analytical method for cSNP and gene expression difference based on transcriptome RNA-Seq data, and to screen SNP loci that may alter protein functions and gene expression difference among different cell phenotypes. Methods RNA-Seq was performed for normal cultured gastric cancer cell lines MKN28 and SGC7901. The sequencing data was then compared with the reference genome and the statistic analysis was conducted for the number of reads, sequenced genes, upregulated genes of MKN28 and SGC7901, and SNP and variable splicing patterns. Online software, database and computer programming were combined to screen and predict functions of SNP in transcriptome sequencing data of two gastric cancer cell lines, and to perform analysis and comparison for the GO clustering results of differentially expressed genes. Results The SNP of 709 genes belonging to 8 different gene terms were screened and predicted and 6 cSNPs that could cause protein functional alterations were identified. The expression of serine/threonine kinase in two cell lines were obtained by analyzing gene expression differences. Some of the analytical results were confirmed by the Western blotting and PCR. Conclusion An analytical method for cSNP data of transcriptome sequencing is established. This method can efficiently screen and analyze massive SNP data. A set of protein kinase genes with high expression in MKN28 and low expression in SGC7901 are obtained by clustering analysis and comparision. These results are basis for further experiments.

Key words: cSNP, transcriptome, RNA-Seq, gene expression difference, gastric cancer