Hypoxia-induced gene expression profiling in the euryoxic fish Gillichthys mirabilis

Hypoxia is important in both biomedical and environmental contexts and necessitates rapid adaptive changes in metabolic organization. Mammals, as air breathers, have a limited capacity to withstand sustained exposure to hypoxia. By contrast, some aquatic animals, such as certain fishes, are routinely exposed and resistant to severe environmental hypoxia. Understanding the changes in gene expression in fishes exposed to hypoxic stress could reveal novel mechanisms of tolerance that may shed new light on hypoxia and ischemia in higher vertebrates. Using cDNA microarrays, we have studied gene expression in a hypoxia-tolerant burrow-dwelling goby fish, Gillichthys mirabilis. We show that a coherent picture of a complex transcriptional response can be generated for a nonmodel organism for which sequence data were unavailable. We demonstrate that: (i) although certain shifts in gene expression mirror changes in mammals, novel genes are differentially expressed in fish; and (ii) tissue-specific patterns of expression reflect the different metabolic roles of tissues during hypoxia.

Comprehensive copy number and gene expression profiling of the 17q23 amplicon in human breast cancer

The biological significance of DNA amplification in cancer is thought to be due to the selection of increased expression of a single or few important genes. However, systematic surveys of the copy number and expression of all genes within an amplified region of the genome have not been performed. Here we have used a combination of molecular, genomic, and microarray technologies to identify target genes for 17q23, a common region of amplification in breast cancers with poor prognosis. Construction of a 4-Mb genomic contig made it possible to define two common regions of amplification in breast cancer cell lines. Analysis of 184 primary breast tumors by fluorescence in situ hybridization on tissue microarrays validated these results with the highest amplification frequency (12.5%) observed for the distal region. Based on GeneMap'99 information, 17 known genes and 26 expressed sequence tags were localized to the contig. Analysis of genomic sequence identified 77 additional transcripts. A comprehensive analysis of expression levels of these transcripts in six breast cancer cell lines was carried out by using complementary DNA microarrays. The expression patterns varied from one cell line to another, and several overexpressed genes were identified. Of these, RPS6KB1, MUL, APPBP2, and TRAP240 as well as one uncharacterized expressed sequence tag were located in the two common amplified regions. In summary, comprehensive analysis of the 17q23 amplicon revealed a limited number of highly expressed genes that may contribute to the more aggressive clinical course observed in breast cancer patients with 17q23-amplified tumors.

Regional and strain-specific gene expression mapping in the adult mouse brain

To determine the genetic causes and molecular mechanisms responsible for neurobehavioral differences in mice, we used highly parallel gene expression profiling to detect genes that are differentially expressed between the 129SvEv and C57BL/6 mouse strains at baseline and in response to seizure. In addition, we identified genes that are differentially expressed in specific brain regions. We found that approximately 1% of expressed genes are differentially expressed between strains in at least one region of the brain and that the gene expression response to seizure is significantly different between the two inbred strains. The results lead to the identification of differences in gene expression that may account for distinct phenotypes in inbred strains and the unique functions of specific brain regions.

Yeast microarrays for genome wide parallel genetic and gene expression analysis

We have developed high-density DNA microarrays of yeast ORFs. These microarrays can monitor hybridization to ORFs for applications such as quantitative differential gene expression analysis and screening for sequence polymorphisms. Automated scripts retrieved sequence information from public databases to locate predicted ORFs and select appropriate primers for amplification. The primers were used to amplify yeast ORFs in 96-well plates, and the resulting products were arrayed using an automated micro arraying device. Arrays containing up to 2,479 yeast ORFs were printed on a single slide. The hybridization of fluorescently labeled samples to the array were detected and quantitated with a laser confocal scanning microscope. Applications of the microarrays are shown for genetic and gene expression analysis at the whole genome level.

Identification of diverse nerve growth factor-regulated genes by serial analysis of gene expression (SAGE) profiling

Neurotrophic factors such as nerve growth factor (NGF) promote a wide variety of responses in neurons, including differentiation, survival, plasticity, and repair. Such actions often require changes in gene expression. To identify the regulated genes and thereby to more fully understand the NGF mechanism, we carried out serial analysis of gene expression (SAGE) profiling of transcripts derived from rat PC12 cells before and after NGF-promoted neuronal differentiation. Multiple criteria supported the reliability of the profile. Approximately 157,000 SAGE tags were analyzed, representing at least 21,000 unique transcripts. Of these, nearly 800 were regulated by 6-fold or more in response to NGF. Approximately 150 of the regulated transcripts have been matched to named genes, the majority of which were not previously known to be NGF-responsive. Functional categorization of the regulated genes provides insight into the complex, integrated mechanism by which NGF promotes its multiple actions. It is anticipated that as genomic sequence information accrues the data derived here will continue to provide information about neurotrophic factor mechanisms.

BodyMap incorporated PCR-based expression profiling data and a gene ranking system

BodyMap is a human and mouse gene expression database that is based on site-directed 3′-expressed sequence tags generated at Osaka University. To date, it contains more than 300 000 tag sequences from 64 human and 39 mouse tissues. For the recent release, the precise anatomical expression patterns for more than half of the human gene entries were generated by introduced amplified fragment length polymorphism (iAFLP), which is a PCR-based high-throughput expression profiling method. The iAFLP data incorporated into BodyMap describe the relative contents of more than 12 000 transcripts across 30 tissue RNAs. In addition, a newly developed gene ranking system helps users obtain lists of genes that have desired expression patterns according to their significance. BodyMap supports complete transfer of unique data sets and provides analysis that is accessible through the WWW at http://bodymap.ims.u-tokyo.ac.jp.

Delineating developmental and metabolic pathways in vivo by expression profiling using the RIKEN set of 18,816 full-length enriched mouse cDNA arrays

We have systematically characterized gene expression patterns in 49 adult and embryonic mouse tissues by using cDNA microarrays with 18,816 mouse cDNAs. Cluster analysis defined sets of genes that were expressed ubiquitously or in similar groups of tissues such as digestive organs and muscle. Clustering of expression profiles was observed in embryonic brain, postnatal cerebellum, and adult olfactory bulb, reflecting similarities in neurogenesis and remodeling. Finally, clustering genes coding for known enzymes into 78 metabolic pathways revealed a surprising coordination of expression within each pathway among different tissues. On the other hand, a more detailed examination of glycolysis revealed tissue-specific differences in profiles of key regulatory enzymes. Thus, by surveying global gene expression by using microarrays with a large number of elements, we provide insights into the commonality and diversity of pathways responsible for the development and maintenance of the mammalian body plan.

Importance of replication in microarray gene expression studies: Statistical methods and evidence from repetitive cDNA hybridizations

We present statistical methods for analyzing replicated cDNA microarray expression data and report the results of a controlled experiment. The study was conducted to investigate inherent variability in gene expression data and the extent to which replication in an experiment produces more consistent and reliable findings. We introduce a statistical model to describe the probability that mRNA is contained in the target sample tissue, converted to probe, and ultimately detected on the slide. We also introduce a method to analyze the combined data from all replicates. Of the 288 genes considered in this controlled experiment, 32 would be expected to produce strong hybridization signals because of the known presence of repetitive sequences within them. Results based on individual replicates, however, show that there are 55, 36, and 58 highly expressed genes in replicates 1, 2, and 3, respectively. On the other hand, an analysis by using the combined data from all 3 replicates reveals that only 2 of the 288 genes are incorrectly classified as expressed. Our experiment shows that any single microarray output is subject to substantial variability. By pooling data from replicates, we can provide a more reliable analysis of gene expression data. Therefore, we conclude that designing experiments with replications will greatly reduce misclassification rates. We recommend that at least three replicates be used in designing experiments by using cDNA microarrays, particularly when gene expression data from single specimens are being analyzed.