Knowledge-based analysis of microarray gene expression data by using support vector machines

We introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering and self-organizing maps. SVMs have many mathematical features that make them attractive for gene expression analysis, including their flexibility in choosing a similarity function, sparseness of solution when dealing with large data sets, the ability to handle large feature spaces, and the ability to identify outliers. We test several SVMs that use different similarity metrics, as well as some other supervised learning methods, and find that the SVMs best identify sets of genes with a common function using expression data. Finally, we use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.

Identification and characterization of a second melanin-concentrating hormone receptor, MCH-2R

Melanin-concentrating hormone (MCH) is a 19-aa cyclic neuropeptide originally isolated from chum salmon pituitaries. Besides its effects on the aggregation of melanophores in fish several lines of evidence suggest that in mammals MCH functions as a regulator of energy homeostasis. Recently, several groups reported the identification of an orphan G protein-coupled receptor as a receptor for MCH (MCH-1R). We hereby report the identification of a second human MCH receptor termed MCH-2R, which shares about 38% amino acid identity with MCH-1R. MCH-2R displayed high-affinity MCH binding, resulting in inositol phosphate turnover and release of intracellular calcium in mammalian cells. In contrast to MCH-1R, MCH-2R signaling is not sensitive to pertussis toxin and MCH-2R cannot reduce forskolin-stimulated cAMP production, suggesting an exclusive Gαq coupling of the MCH-2R in cell-based systems. Northern blot and in situ hybridization analysis of human and monkey tissue shows that expression of MCH-2R mRNA is restricted to several regions of the brain, including the arcuate nucleus and the ventral medial hypothalamus, areas implicated in regulation of body weight. In addition, the human MCH-2R gene was mapped to the long arm of chromosome 6 at band 6q16.2–16.3, a region reported to be associated with cytogenetic abnormalities of obese patients. The characterization of a second mammalian G protein-coupled receptor for MCH potentially indicates that the control of energy homeostasis in mammals by the MCH neuropeptide system may be more complex than initially anticipated.

Conformation, energy, and folding ability of selected amino acid sequences.

Evolutionary selection of sequences is studied with a knowledge-based Hamiltonian to find the design principle for folding to a model protein structure. With sequences selected by naive energy minimization, the model structure tends to be unstable and the folding ability is low. Sequences with high folding ability have only the low-lying energy minimum but also an energy landscape which is similar to that found for the native sequence over a wide region of the conformation space. Though there is a large fluctuation in foldable sequences, the hydrophobicity pattern and the glycine locations are preserved among them. Implications of the design principle for the molecular mechanism of folding are discussed.

Real-time detection of DNA hybridization and melting on oligonucleotide arrays by using optical wave guides.

The challenge of the Human Genome Project is to increase the rate of DNA sequence acquisition by two orders of magnitude to complete sequencing of the human genome by the year 2000. The present work describes a rapid detection method using a two-dimensional optical wave guide that allows measurement of real-time binding or melting of a light-scattering label on a DNA array. A particulate label on the target DNA acts as a light-scattering source when illuminated by the evanescent wave of the wave guide and only the label bound to the surface generates a signal. Imaging/visual examination of the scattered light permits interrogation of the entire array simultaneously. Hybridization specificity is equivalent to that obtained with a conventional system using autoradiography. Wave guide melting curves are consistent with those obtained in the liquid phase and single-base discrimination is facile. Dilution experiments showed an apparent lower limit of detection at 0.4 nM oligonucleotide. This performance is comparable to the best currently known fluorescence-based systems. In addition, wave guide detection allows manipulation of hybridization stringency during detection and thereby reduces DNA chip complexity. It is anticipated that this methodology will provide a powerful tool for diagnostic applications that require rapid cost-effective detection of variations from known sequences.