A GUI Application "CA Plot Viewer" for Large-Scale Gene Expression Analysis with Next-Generation Sequencing Technology

High-throughput RNA sequencing technologies with next generation sequencers (NGS) facilitate identification of novel genes and their biological functions. The large-scale gene expression data from NGS leads to more detailed classifications of genes according to the similarities in expression profiles. We have developed a statistical method and GUI software based on correspondence analysis to quickly classify genes and construct gene expression networks in a personal computer.

We employed rice and Arabidopsis Illumina sequences (NCBI SRA) to show the theoretical advantage of this method in classification of genes according to expression profiles. To obtain digital gene expression profiles, the number of reads mapped onto each cDNA was used as the expression level. Our method allows us to efficiently detect genes related to phenotypes or biological conditions of interest. The comparisons of gene expression networks between rice and Arabidopsis can be also easily performed. A calculation for the large-scale data presented here takes within 1 minute with a Windows PC [4GB memory, Core(TM)2 Duo]. We have also developed GUI software “CA Plot Viewer” to quickly analyze large-scale expression data and easily detect genes with similar expression profiles by the 3D graphical viewer. “CA Plot Viewer” is available from our web-site (http://bioinf.mind.meiji.ac.jp/lab/). We have also developed a pipeline for detection of genome-wide SNPs by using the RAD-Seq method. With the large-scale SNP data, the high-throughput method for large-scale expression profiles facilitates the understanding of biological functions of genes.

This work is partially supported by Resarch Funding for Computational Software Supporting Program in Meiji University