Assessing gene expression variation in normal human tissues using GeneTag™, a novel, global, sensitive profiling method

• Published in: Journal of biotechnology Vol. 101; no. 3; pp. 199 - 217
• Main Authors: Wong, Lily Y, Hafeman, Andrea, Boyd, Victoria L, Bodeau, John, Lazaruk, Katherine D, Liew, Sueh-Ning, Casey, Peter, Belonogoff, Victor, Bit, Somaya, Sumner, Craig, Bredo, Alisa, Ho, Norman, Chu, Erwin, Olson, Sheri, Rabkin, Steven, Maltchenko, Sergei, Spier, Gene, Gilbert, Dennis, Baumhueter, Susanne
• Format: Journal Article
• Language: English
• Published: Lausanne Elsevier B.V 20-03-2003; Amsterdam Elsevier; New York, NY
• Subjects: AFLP; Biological and medical sciences; Biotechnology; Brain; Brain Chemistry; Differential; DNA Fingerprinting - methods; DNA, Complementary - analysis; Expression; Female; Fundamental and applied biological sciences. Psychology; Gene Expression - genetics; Gene Expression Profiling - methods; Humans; Liver - chemistry; Liver - embryology; Lung - chemistry; Male; Organ Specificity; Placenta - chemistry; Polymorphism, Restriction Fragment Length; Pregnancy; Profiling; Random Amplified Polymorphic DNA Technique - methods; Reproducibility of Results; RNA, Messenger - analysis; Sensitivity and Specificity; Sequence Alignment - methods; Transcription, Genetic - genetics; Transcript; CV, coefficient of variation; Profiling; AFLP, amplified fragment length polymorphism; Differential; FAM, 6-carboxyfluorescein; ROX, X-rhodamine; EST, expressed sequence tag; HPLC, high performance liquid chromatography; SAGE, serial analysis of gene expression; SNP, single nucleotide polymorphism; Expression; AFLP; bp, base pair; EDTA, ethylenediaminetetraacetate; PCR, polymerase chain reaction; SD, standard deviation; TOGA, total gene expression analysis; READS, restriction enzyme analysis of differentially expressed sequences; Human; Tissue; Variations; Method; Gene expression
• ISSN: 0168-1656; 1873-4863
• DOI: 10.1016/S0168-1656(02)00301-2

GeneTag™ is a novel expression profiling method that allows the visualization, quantification and identification of expressed genes—whether known or novel—in any species, tissue or cell type, independent of knowledge of the underlying sequence. Here we describe the application of this method to determine variation of gene expression in individual human liver samples and the identification of tissue-specific genes by comparing expression patterns across several human organs. Expression data are stored in a database for future reference and data analysis relies on proprietary software, which allows complex comparisons to be performed. Differentially expressed genes are quickly identified through a link to a sequence database. The results from our study underscore the importance of knowledge of individual variation of gene expression for the design and interpretation of transcript profiling experiments in the context of any biological question.