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.

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.

Dynamics of Gene Expression Revealed by Comparison of Serial Analysis of Gene Expression Transcript Profiles from Yeast Grown on Two Different Carbon SourcesD⃞

We describe a genome-wide characterization of mRNA transcript levels in yeast grown on the fatty acid oleate, determined using Serial Analysis of Gene Expression (SAGE). Comparison of this SAGE library with that reported for glucose grown cells revealed the dramatic adaptive response of yeast to a change in carbon source. A major fraction (>20%) of the 15,000 mRNA molecules in a yeast cell comprised differentially expressed transcripts, which were derived from only 2% of the total number of ∼6300 yeast genes. Most of the mRNAs that were differentially expressed code for enzymes or for other proteins participating in metabolism (e.g., metabolite transporters). In oleate-grown cells, this was exemplified by the huge increase of mRNAs encoding the peroxisomal β-oxidation enzymes required for degradation of fatty acids. The data provide evidence for the existence of redox shuttles across organellar membranes that involve peroxisomal, cytoplasmic, and mitochondrial enzymes. We also analyzed the mRNA profile of a mutant strain with deletions of the PIP2 and OAF1 genes, encoding transcription factors required for induction of genes encoding peroxisomal proteins. Induction of genes under the immediate control of these factors was abolished; other genes were up-regulated, indicating an adaptive response to the changed metabolism imposed by the genetic impairment. We describe a statistical method for analysis of data obtained by SAGE.

Global analysis of gene expression in pulmonary fibrosis reveals distinct programs regulating lung inflammation and fibrosis

The molecular mechanisms of pulmonary fibrosis are poorly understood. We have used oligonucleotide arrays to analyze the gene expression programs that underlie pulmonary fibrosis in response to bleomycin, a drug that causes lung inflammation and fibrosis, in two strains of susceptible mice (129 and C57BL/6). We then compared the gene expression patterns in these mice with 129 mice carrying a null mutation in the epithelial-restricted integrin β6 subunit (β6−/−), which develop inflammation but are protected from pulmonary fibrosis. Cluster analysis identified two distinct groups of genes involved in the inflammatory and fibrotic responses. Analysis of gene expression at multiple time points after bleomycin administration revealed sequential induction of subsets of genes that characterize each response. The availability of this comprehensive data set should accelerate the development of more effective strategies for intervention at the various stages in the development of fibrotic diseases of the lungs and other organs.

Generation of longer cDNA fragments from serial analysis of gene expression tags for gene identification

We have developed a technique called the generation of longer cDNA fragments from serial analysis of gene expression (SAGE) tags for gene identification (GLGI), to convert SAGE tags of 10 bases into their corresponding 3′ cDNA fragments covering hundred bases. A primer containing the 10-base SAGE tag is used as the sense primer, and a single base anchored oligo(dT) primer is used as an antisense primer in PCR, together with Pfu DNA polymerase. By using this approach, a cDNA fragment extending from the SAGE tag toward the 3′ end of the corresponding sequence can be generated. Application of the GLGI technique can solve two critical issues in applying the SAGE technique: one is that a longer fragment corresponding to a SAGE tag, which has no match in databases, can be generated for further studies; the other is that the specific fragment corresponding to a SAGE tag can be identified from multiple sequences that match the same SAGE tag. The development of the GLGI method provides several potential applications. First, it provides a strategy for even wider application of the SAGE technique for quantitative analysis of global gene expression. Second, a combined application of SAGE/GLGI can be used to complete the catalogue of the expressed genes in human and in other eukaryotic species. Third, it can be used to identify the 3′ cDNA sequence from any exon within a gene. It can also be used to confirm the reality of exons predicted by bioinformatic tools in genomic sequences. Fourth, a combined application of SAGE/GLGI can be applied to define the 3′ boundary of expressed genes in the genomic sequences in human and in other eukaryotic genomes.

Toward functional genomics in bacteria: Analysis of gene expression in Escherichia coli from a bacterial artificial chromosome library of Bacillus cereus

As the study of microbes moves into the era of functional genomics, there is an increasing need for molecular tools for analysis of a wide diversity of microorganisms. Currently, biological study of many prokaryotes of agricultural, medical, and fundamental scientific interest is limited by the lack of adequate genetic tools. We report the application of the bacterial artificial chromosome (BAC) vector to prokaryotic biology as a powerful approach to address this need. We constructed a BAC library in Escherichia coli from genomic DNA of the Gram-positive bacterium Bacillus cereus. This library provides 5.75-fold coverage of the B. cereus genome, with an average insert size of 98 kb. To determine the extent of heterologous expression of B. cereus genes in the library, we screened it for expression of several B. cereus activities in the E. coli host. Clones expressing 6 of 10 activities tested were identified in the library, namely, ampicillin resistance, zwittermicin A resistance, esculin hydrolysis, hemolysis, orange pigment production, and lecithinase activity. We analyzed selected BAC clones genetically to identify rapidly specific B. cereus loci. These results suggest that BAC libraries will provide a powerful approach for studying gene expression from diverse prokaryotes.

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.

Saccharomyces Genome Database provides tools to survey gene expression and functional analysis data

Upon the completion of the Saccharomyces cerevisiae genomic sequence in 1996 [Goffeau,A. et al. (1997) Nature, 387, 5], several creative and ambitious projects have been initiated to explore the functions of gene products or gene expression on a genome-wide scale. To help researchers take advantage of these projects, the Saccharomyces Genome Database (SGD) has created two new tools, Function Junction and Expression Connection. Together, the tools form a central resource for querying multiple large-scale analysis projects for data about individual genes. Function Junction provides information from diverse projects that shed light on the role a gene product plays in the cell, while Expression Connection delivers information produced by the ever-increasing number of microarray projects. WWW access to SGD is available at genome-www.stanford.edu/Saccharomyces/.

High-sensitivity array analysis of gene expression for the early detection of disseminated breast tumor cells in peripheral blood

Early detection is an effective means of reducing cancer mortality. Here, we describe a highly sensitive high-throughput screen that can identify panels of markers for the early detection of solid tumor cells disseminated in peripheral blood. The method is a two-step combination of differential display and high-sensitivity cDNA arrays. In a primary screen, differential display identified 170 candidate marker genes differentially expressed between breast tumor cells and normal breast epithelial cells. In a secondary screen, high-sensitivity arrays assessed expression levels of these genes in 48 blood samples, 22 from healthy volunteers and 26 from breast cancer patients. Cluster analysis identified a group of 12 genes that were elevated in the blood of cancer patients. Permutation analysis of individual genes defined five core genes (P ≤ 0.05, permax test). As a group, the 12 genes generally distinguished accurately between healthy volunteers and patients with breast cancer. Mean expression levels of the 12 genes were elevated in 77% (10 of 13) untreated invasive cancer patients, whereas cluster analysis correctly classified volunteers and patients (P = 0.0022, Fisher's exact test). Quantitative real-time PCR confirmed array results and indicated that the sensitivity of the assay (1:2 × 108 transcripts) was sufficient to detect disseminated solid tumor cells in blood. Expression-based blood assays developed with the screening approach described here have the potential to detect and classify solid tumor cells originating from virtually any primary site in the body.

An orchestrated gene expression component of neuronal programmed cell death revealed by cDNA array analysis

Programmed cell death (PCD) during neuronal development and disease has been shown to require de novo RNA synthesis. However, the time course and regulation of target genes is poorly understood. By using a brain-biased array of over 7,500 cDNAs, we profiled this gene expression component of PCD in cerebellar granule neurons challenged separately by potassium withdrawal, combined potassium and serum withdrawal, and kainic acid administration. We found that hundreds of genes were significantly regulated in discreet waves including known genes whose protein products are involved in PCD. A restricted set of genes was regulated by all models, providing evidence that signals inducing PCD can regulate large assemblages of genes (of which a restricted subset may be shared in multiple pathways).

Analysis of gene expression during myc oncogene-induced lymphomagenesis in the bursa of Fabricius

The transcriptional effects of deregulated myc gene overexpression are implicated in tumorigenesis in a spectrum of experimental and naturally occurring neoplasms. In follicles of the chicken bursa of Fabricius, myc induction of B-cell neoplasia requires a target cell population present during early bursal development and progresses through preneoplastic transformed follicles to metastatic lymphomas. We developed a chicken immune system cDNA microarray to analyze broad changes in gene expression that occur during normal embryonic B-cell development and during myc-induced neoplastic transformation in the bursa. The number of mRNAs showing at least 3-fold change was greater during myc-induced lymphomagenesis than during normal development, and hierarchical cluster analysis of expression patterns revealed that levels of several hundred mRNAs varied in concert with levels of myc overexpression. A set of 41 mRNAs were most consistently elevated in myc-overexpressing preneoplastic and neoplastic cells, most involved in processes thought to be subject to regulation by Myc. The mRNAs for another cluster of genes were overexpressed in neoplasia independent of myc expression level, including a small subset with the expression signature of embryonic bursal lymphocytes. Overexpression of myc, and some of the genes overexpressed with myc, may be important for generation of preneoplastic transformed follicles. However, expression profiles of late metastatic tumors showed a large variation in concert with myc expression levels, and some showed minimal myc overexpression. Therefore, high-level myc overexpression may be more important in the early induction of these lymphomas than in maintenance of late-stage metastases.

Expression Analysis of a Ripening-Specific, Auxin-Repressed Endo-1,4-β-Glucanase Gene in Strawberry

A cDNA (Cel1) encoding an endo-1,4-β-glucanase (EGase) was isolated from ripe fruit of strawberry (Fragaria × ananassa). The deduced protein of 496 amino acids contains a presumptive signal sequence, a common feature of cell wall-localized EGases, and one potential N-glycosylation site. Southern- blot analysis of genomic DNA from F. × ananassa, an octoploid species, and that from the diploid species Fragaria vesca indicated that the Cel1 gene is a member of a divergent multigene family. In fruit, Cel1 mRNA was first detected at the white stage of development, and at the onset of ripening, coincident with anthocyanin accumulation, Cel1 mRNA abundance increased dramatically and remained high throughout ripening and subsequent fruit deterioration. In all other tissues examined, Cel1 expression was invariably absent. Antibodies raised to Cel1 protein detected a protein of 62 kD only in ripening fruit. Upon deachenation of young white fruit to remove the source of endogenous auxins, ripening, as visualized by anthocyanin accumulation, and Cel1 mRNA accumulation were both accelerated. Conversely, auxin treatment of white fruit repressed accumulation of both Cel1 mRNA and ripening. These results indicate that strawberry Cel1 is a ripening-specific and auxin-repressed EGase, which is regulated during ripening by a decline in auxin levels originating from the achenes.

Analysis of differential gene expression by display of 3' end restriction fragments of cDNAs.

We have developed an approach to study changes in gene expression by selective PCR amplification and display of 3' end restriction fragments of double-stranded cDNAs. This method produces highly consistent and reproducible patterns, can detect almost all mRNAs in a sample, and can resolve hidden differences such as bands that differ in their sequence but comigrate on a gel. Bands corresponding to known cDNAs move to predictable positions on the gel, making this a powerful approach to correlate gel patterns with cDNA data bases. Applying this method, we have examined differences in gene expression patterns during T-cell activation. Of a total of 700 bands that were evaluated in this study, as many as 3-4% represented mRNAs that are upregulated, while approximately 2% were down-regulated within 4 hr of activation of Jurkat T cells. These and other results suggest that this approach is suitable for the systematic, expeditious, and nearly exhaustive elucidation of subtle changes in the patterns of gene expression in cells with altered physiologic states.

Identification and expression analysis of a potential familial Alzheimer disease gene on chromosome 1 related to AD3.

The inheritance of much early-onset Alzheimer disease (AD) has been linked to a dominant-acting locus on chromosome 14. Recently, the gene likely responsible for this genetic linkage has been identified and termed AD3. Five mutations have been found in AD3 that segregate with the disease phenotype in seven AD families and are not present in unaffected individuals. Here we report the existence of a gene encoding a seven transmembrane domain protein very similar to that encoded by AD3 in structure and sequence. This gene is located on chromosome 1, is expressed in a variety of tissues, including brain, and is predicted to harbor mutations causing nonchromosome 14 familial AD. The presence of several S/TPXX DNA binding motifs in both the AD3 protein and the AD3-like protein /AD4 protein suggests a possible role in intracellular signaling and gene expression or in linking chromatin to the nuclear membrane. Ways in which mutations in either gene could lead to AD are discussed.

Comparative expressed-sequence-tag analysis of differential gene expression profiles in PC-12 cells before and after nerve growth factor treatment.

Nerve growth factor-induced differentiation of adrenal chromaffin PC-12 cells to a neuronal phenotype involves alterations in gene expression and represents a model system to study neuronal differentiation. We have used the expressed-sequence-tag approach to identify approximately 600 differentially expressed mRNAs in untreated and nerve growth factor-treated PC-12 cells that encode proteins with diverse structural and biochemical functions. Many of these mRNAs encode proteins belonging to cellular pathways not previously known to be regulated by nerve growth factor. Comparative expressed-sequence-tag analysis provides a basis for surveying global changes in gene-expression patterns in response to biological signals at an unprecedented scale, is a powerful tool for identifying potential interactions between different cellular pathways, and allows the gene-expression profiles of individual genes belonging to a particular pathway to be followed.