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.

Cluster analysis and display of genome-wide expression patterns

A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.

A genome-wide search for susceptibility genes in human systemic lupus erythematosus sib-pair families

Systemic lupus erythematosus (SLE) is an autoimmune multisystem inflammatory disease characterized by the production of pathogenic autoantibodies. Previous genetic studies have suggested associations with HLA Class II alleles, complement gene deficiencies, and Fc receptor polymorphisms; however, it is likely that other genes contribute to SLE susceptibility and pathogenesis. Here, we report the results of a genome-wide microsatellite marker screen in 105 SLE sib-pair families. By using multipoint nonparametric methods, the strongest evidence for linkage was found near the HLA locus (6p11-p21) [D6S257, logarithm of odds (lod) = 3.90, P = 0.000011] and at three additional regions: 16q13 (D16S415, lod = 3.64, P = 0.000022), 14q21–23 (D14S276, lod = 2.81, P = 0.00016), and 20p12 (D20S186, lod = 2.62, P = 0.00025). Another nine regions (1p36, 1p13, 1q42, 2p15, 2q21–33, 3cent-q11, 4q28, 11p15, and 15q26) were identified with lod scores ≥1.00. These data support the hypothesis that multiple genes, including one in the HLA region, influence susceptibility to human SLE.

Singular value decomposition for genome-wide expression data processing and modeling

We describe the use of singular value decomposition in transforming genome-wide expression data from genes × arrays space to reduced diagonalized “eigengenes” × “eigenarrays” space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.

New susceptibility locus for rheumatoid arthritis suggested by a genome-wide linkage study

Rheumatoid arthritis (RA), the most common autoimmune disease, is associated in families with other autoimmune diseases, including insulin-dependent diabetes mellitus (IDDM). Its genetic component has been suggested by familial aggregation (λs = 5), twin studies, and segregation analysis. HLA, which is the only susceptibility locus known, has been estimated to account for one-third of this component. The aim of this paper was to identify new RA loci. A genome scan was performed with 114 European Caucasian RA sib pairs from 97 nuclear families. Linkage was significant only for HLA (P < 2.5⋅10−5) and nominal for 19 markers in 14 other regions (P < 0.05). Four of the loci implicated in IDDM potentially overlap with these regions: the putative IDDM6, IDDM9, IDDM13, and DXS998 loci. The first two of these candidate regions, defined in the RA genome scan by the markers D18S68-D18S61-D18S469 (18q22–23) and D3S1267 (3q13), respectively, were studied in 194 additional RA sib pairs from 164 nuclear families. Support for linkage to chromosome 3 only was extended significantly (P = 0.002). The analysis of all 261 families provided a linkage evidence of P = 0.001 and suggested an interaction between this putative RA locus and HLA. This locus could account for 16% of the genetic component of RA. Candidate genes include those coding for CD80 and CD86, molecules involved in antigen-specific T cell recognition. In conclusion, this first genome scan in RA Caucasian families revealed 14 candidate regions, one of which was supported further by the study of a second set of families.

A genome-wide search for chromosomal loci linked to mental health wellness in relatives at high risk for bipolar affective disorder among the Old Order Amish

Bipolar affective disorder (BPAD; manic-depressive illness) is characterized by episodes of mania and/or hypomania interspersed with periods of depression. Compelling evidence supports a significant genetic component in the susceptibility to develop BPAD. To date, however, linkage studies have attempted only to identify chromosomal loci that cause or increase the risk of developing BPAD. To determine whether there could be protective alleles that prevent or reduce the risk of developing BPAD, similar to what is observed in other genetic disorders, we used mental health wellness (absence of any psychiatric disorder) as the phenotype in our genome-wide linkage scan of several large multigeneration Old Order Amish pedigrees exhibiting an extremely high incidence of BPAD. We have found strong evidence for a locus on chromosome 4p at D4S2949 (maximum genehunter-plus nonparametric linkage score = 4.05, P = 5.22 × 10−4; sibpal Pempirical value <3 × 10−5) and suggestive evidence for a locus on chromosome 4q at D4S397 (maximum genehunter-plus nonparametric linkage score = 3.29, P = 2.57 × 10−3; sibpal Pempirical value <1 × 10−3) that are linked to mental health wellness. These findings are consistent with the hypothesis that certain alleles could prevent or modify the clinical manifestations of BPAD and perhaps other related affective disorders.

Genome-wide Responses to Mitochondrial DysfunctionV⃞

Mitochondrial dysfunction can lead to diverse cellular and organismal responses. We used DNA microarrays to characterize the transcriptional responses to different mitochondrial perturbations in Saccharomyces cerevisiae. We examined respiratory-deficient petite cells and respiratory-competent wild-type cells treated with the inhibitors of oxidative phosphorylation antimycin, carbonyl cyanide m-chlorophenylhydrazone, or oligomycin. We show that respiratory deficiency, but not inhibition of mitochondrial ATP synthesis per se, induces a suite of genes associated with both peroxisomal activities and metabolite-restoration (anaplerotic) pathways that would mitigate the loss of a complete tricarboxylic acid cycle. The array data suggested, and direct microscopic observation of cells expressing a derivative of green fluorescent protein with a peroxisomal matrix-targeting signal confirmed, that respiratory deficiency dramatically induces peroxisome biogenesis. Transcript profiling of cells harboring null alleles of RTG1, RTG2, or RTG3, genes known to control signaling from mitochondria to the nucleus, suggests that there are multiple pathways of cross-talk between these organelles in yeast.

Genome-wide expression analysis reveals dysregulation of myelination-related genes in chronic schizophrenia

Neuropathological and brain imaging studies suggest that schizophrenia may result from neurodevelopmental defects. Cytoarchitectural studies indicate cellular abnormalities suggestive of a disruption in neuronal connectivity in schizophrenia, particularly in the dorsolateral prefrontal cortex. Yet, the molecular mechanisms underlying these findings remain unclear. To identify molecular substrates associated with schizophrenia, DNA microarray analysis was used to assay gene expression levels in postmortem dorsolateral prefrontal cortex of schizophrenic and control patients. Genes determined to have altered expression levels in schizophrenics relative to controls are involved in a number of biological processes, including synaptic plasticity, neuronal development, neurotransmission, and signal transduction. Most notable was the differential expression of myelination-related genes suggesting a disruption in oligodendrocyte function in schizophrenia.

Genome-wide gene expression profiles of the developing mouse hippocampus

We have analyzed the developmental molecular programs of the mouse hippocampus, a cortical structure critical for learning and memory, by means of large-scale DNA microarray techniques. Of 11,000 genes and expressed sequence tags examined, 1,926 showed dynamic changes during hippocampal development from embryonic day 16 to postnatal day 30. Gene-cluster analysis was used to group these genes into 16 distinct clusters with striking patterns that appear to correlate with major developmental hallmarks and cellular events. These include genes involved in neuronal proliferation, differentiation, and synapse formation. A complete list of the transcriptional changes has been compiled into a comprehensive gene profile database (http://BrainGenomics.Princeton.edu), which should prove valuable in advancing our understanding of the molecular and genetic programs underlying both the development and the functions of the mammalian brain.

The activation of human gene MAGE-1 in tumor cells is correlated with genome-wide demethylation.

Human gene MAGE-1 encodes tumor-specific antigens that are recognized on melanoma cells by autologous cytolytic T lymphocytes. This gene is expressed in a significant proportion of tumors of various histological types, but not in normal tissues except male germ-line cells. We reported previously that reporter genes driven by the MAGE-1 promoter are active not only in the tumor cell lines that express MAGE-1 but also in those that do not. This suggests that the critical factor causing the activation of MAGE-1 in certain tumors is not the presence of the appropriate transcription factors. The two major MAGE-1 promoter elements have an Ets binding site, which contains a CpG dinucleotide. We report here that these CpG are demethylated in the tumor cell lines that express MAGE-1, and are methylated in those that do not express the gene. Methylation of these CpG inhibits the binding of transcription factors, as seen by mobility shift assay. Treatment with the demethylating agent 5-aza-2'-deoxycytidine activated gene MAGE-1 not only in tumor cell lines but also in primary fibroblasts. Finally, the overall level of CpG methylation was evaluated in 20 different tumor cell lines. It was inversely correlated with the expression of MAGE-1. We conclude that the activation of MAGE-1 in cancer cells is due to the demethylation of the promoter. This appears to be a consequence of a genome-wide demethylation process that occurs in many cancers and is correlated with tumor progression.

Genome scan for teratogen-induced clefting susceptibility loci in the mouse: Evidence of both allelic and locus heterogeneity distinguishing cleft lip and cleft palate

Nonsyndromic clefting of the lip and palate in humans has a highly complex etiology, with both multiple genetic loci and exposure to teratogens influencing susceptibility. Previous studies using mouse models have examined only very small portions of the genome. Here we report the findings of a genome-wide search for susceptibility genes for teratogen-induced clefting in the AXB and BXA set of recombinant inbred mouse strains. We compare results obtained using phenytoin (which induces cleft lip) and 6-aminonicotinamide (which induces cleft palate). We use a new statistical approach based on logistic regression suitable for these categorical data to identify several chromosomal regions as possible locations of clefting susceptibility loci, and we review candidate genes located within each region. Because cleft lip and cleft palate do not frequently co-aggregate in human families and because these structures arise semi-independently during development, these disorders are usually considered to be distinct in etiology. Our data, however, implicate several of the same chromosomal regions for both forms of clefting when teratogen-induced. Furthermore, different parental strain alleles are usually associated with clefting of the lip versus that of the palate (i.e., allelic heterogeneity). Because several other chromosomal regions are associated with only one form of clefting, locus heterogeneity also appears to be involved. Our findings in this mouse model suggest several priority areas for evaluation in human epidemiological studies.

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/.

Remodeling of Yeast Genome Expression in Response to Environmental Changes

We used genome-wide expression analysis to explore how gene expression in Saccharomyces cerevisiae is remodeled in response to various changes in extracellular environment, including changes in temperature, oxidation, nutrients, pH, and osmolarity. The results demonstrate that more than half of the genome is involved in various responses to environmental change and identify the global set of genes induced and repressed by each condition. These data implicate a substantial number of previously uncharacterized genes in these responses and reveal a signature common to environmental responses that involves ∼10% of yeast genes. The results of expression analysis with MSN2/MSN4 mutants support the model that the Msn2/Msn4 activators induce the common response to environmental change. These results provide a global description of the transcriptional response to environmental change and extend our understanding of the role of activators in effecting this response.