Prediction of cell type-specific gene modules: identification and initial characterization of a core set of smooth muscle-specific genes.
Journal article, 2003
Genes that are expressed in the same subset of cells potentially constitute a module regulated by shared cis-regulatory elements and a distinct set of transcription factors. Identifying such units is an important entry point to the molecular study of cell differentiation. We developed a general method to classify cell type-specific genes from expressed sequence tag (EST) data, and we optimized it for identification of smooth muscle cell (SMC)-specific genes. Expression profiles were derived from the quantitative distribution of EST data in mouse, and genes were classified based on their profile similarity to known reference genes, in this case smooth muscle myosin heavy chain. A large majority (>90%) of known SMC-specific genes were identified, together with novel candidates. Extensive experimental validation confirmed SMC-specific expression of candidates, for example, lipoma preferred partner (LPP) and a novel SMC-specific putative monoamine oxidase, SMAO. Our method performed considerably better than other computational methods in an objective cross validation comparison. The total number of SMC-specific genes is estimated to be approximately 50.
embryology
cytology
statistics & numerical data
genetics
Lens
Gene Expression Regulation
Smooth
Organ Specificity
chemistry
Smooth
Expressed Sequence Tags
Retina
Databases
genetics
Genetic
Mice
Crystalline
Genetic Markers
Muscle
In Situ Hybridization
cytology
Animals
Computational Biology
embryology
Genome
chemistry
Vascular
Gene Expression Profiling
Myosin Heavy Chains
embryology
cytology
Research Design
cytology
chemistry
Predictive Value of Tests
Muscle
Author
Sven Nelander
University of Gothenburg
Petter Mostad
Chalmers, Department of Mathematical Statistics
University of Gothenburg
Per Lindahl
University of Gothenburg
Genome Research
1088-9051 (ISSN) 1549-5469 (eISSN)
Vol. 13 8 1838-54Subject Categories
MEDICAL AND HEALTH SCIENCES
DOI
10.1101/gr.1197303
PubMed
12869577