Abstract
Coexpression analysis is a powerful approach to infer function of genes, as it is presumable that member genes in the same coexpression group have related functions. With the accumulation of microarray data of tomato, it has become feasible to perform gene coexpression analysis for this model crop. Here, we applied a coexpression network-based approach to infer functions of unknown genes of tomato.
From 73 Affymetrix Tomato Genome Array data, we first calculated gene-to-gene correlation coeffcients. According to the cutoff of correlation coefficient and specificity of network connectivity, we detected coexpression groups. In some of the groups, genes that have related functional annotation were clustered. Interestingly, tomato transcription factor genes whose functions are unknown were found in coexpression groups such as flavonoid biosynthesis genes and proteinase inhibitor genes. This suggests that the transcription factors regulate these biological processes.
