title: Dissecting the global variation of gene expression for the functional interpretation of transcriptome data.
abstract: To perform their biological functions, individual genes exhibit varying ranges of expression levels. Thus, considering the intrinsic variability of gene expression can improve geneset-based functional analyses which are typically used to interpret transcriptome data. Through the extensive quantitative analysis of the expressional variability of individual genes using large collections of transcriptome and proteome data, we found the existence of the intrinsic variability of gene expression at the transcriptional level. Interestingly, genes under post-translational regulation were not sensitively regulated at the transcriptional level. Because genes have intrinsically different levels of regulation at the transcription and translation stages, the functional geneset-based interpretation of transcriptome data should only include genes that are significantly varied at the transcriptional level. Thus, by removing genes with low transcriptional variation from the DNA microarray data, we showed that geneset enrichment analysis could provide improved resolution in prioritizing target functional pathways in several different experimental datasets.
authors.affiliation: Department of Biological Sciences, Sookmyung Women's University, Seoul 140-742, Republic of Korea. Electronic address: wwkd0324@sookmyung.ac.kr.
authors.forename: Nayoung
authors.initials: N
authors.lastname: Kim
authors.affiliation: Center for Advanced Bioinformatics & Systems Medicine, Sookmyung Women's University, Seoul 140-742, Republic of Korea. Electronic address: eajeong@sookmyung.ac.kr.
authors.forename: Euna
authors.initials: E
authors.lastname: Jeong
authors.affiliation: Department of Biological Sciences, Sookmyung Women's University, Seoul 140-742, Republic of Korea. Electronic address: applele89@sookmyung.ac.kr.
authors.forename: Xiaoqi
authors.initials: X
authors.lastname: Wang
authors.affiliation: Department of Biological Sciences, Sookmyung Women's University, Seoul 140-742, Republic of Korea; Center for Advanced Bioinformatics & Systems Medicine, Sookmyung Women's University, Seoul 140-742, Republic of Korea. Electronic address: yoonsj@sookmyung.ac.kr.
authors.forename: Sukjoon
authors.initials: S
authors.lastname: Yoon
mesh_terms: D000465:Algorithms; D045744:Cell Line, Tumor; D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic; D015894:Genome, Human; D006801:Humans; D020543:Proteome / Q000235:genetics / Q000378:metabolism*; D059467:Transcriptome
chemical_list: D020543:Proteome
keywords: DNA microarray; Geneset enrichment analysis; Pathway analysis; Proteome; Transcriptome