Discovery of gene regulatory networks via in silico analysis and their application in abiotic stress responses

다국어 초록 (Multilingual Abstract)

In order to uncover gene regulatory networks clustering of co-expressing genes was performed using a rice micorarray dataset of 155 gene expression omnibus sample (GSM) plates in NCBI, generating a total of 1660 clusters. One cluster with 85 co-expressing genes was measured with the correlation coefficient between pairs, resulting in an average r value of 0.66 with a range of -0.08 to 0.98. This result might support the notion that genes included in each cluster play common functional role(s). We also retrieved 23 Affymetrix GeneChip spots IDs corresponding to each of candidate genes related to abiotic stresses obtained from the P1antQTL-GE database and subsequently detected 23 clusters including co-expressing genes with each of the genes. Expression profiles of co-expressing genes revealed some degree of tissue-specific expression patterns, probably reflecting the existence of, at least partial, parallel versions of stress-related networks with evolutionary process, such as subfuntionalization. The finding that several cis-elements related to abiotic stresses was detected by differences in frequency between co-expressing genes and randomly selected genes. Clustering, expression profiles, and putative cis-acting regulatory elements of co-expressing genes related to abiotic stresses may provide clues to shed further light on the gene regulatory network of stress-responsive pathway.