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David Botstein

Publications and source records attributed to David Botstein.

At least 37 records · Page 2Linked to original sources
PubMed2005

Fungal BLAST and Model Organism BLASTP Best Hits: new comparison resources at the Saccharomyces Genome Database (SGD).

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) is a scientific database of gene, protein and genomic information for the yeast Saccharomyces cerevisiae. SGD has recently developed two new resources that facilitate nucleotide and protein sequence comparisons between S.cerevisiae and other organisms. The Fungal BLAST tool provides directed searches against all fungal nucleotide and protein sequences available from GenBank, divided into categories according to organism, status of completeness and annotation, and source. The Model Organism BLASTP Best Hits resource displays, for each S.cerevisiae protein, the single most similar protein from several model organisms and presents links to the database pages of those proteins, facilitating access to curated information about potential orthologs of yeast proteins.

Databases, Genetic↗
PubMed2005

Changing perspectives in yeast research nearly a decade after the genome sequence.

Research with budding yeast (Saccharomyces cerevisiae) has been transformed by the publication, nearly a decade ago, of the entire genome DNA sequence. The introduction of this first eukaryotic genomic sequence changed the yeast research environment significantly, not just because of dramatic progress in technical means but also because the sequence made accessible a new class of scientific questions. A central goal of yeast research remains the determination of the biological role of every sequence feature in the yeast genome. The most remarkable change has been the shift in perspective from focus on individual genes and functionalities to a more global view of how the cellular networks and systems interact and function together to produce the highly evolved organism we see today.

DNA, Fungal↗
PubMed2004

GeneXplorer: an interactive web application for microarray data visualization and analysis.

BACKGROUND: When publishing large-scale microarray datasets, it is of great value to create supplemental websites where either the full data, or selected subsets corresponding to figures within the paper, can be browsed. We set out to create a CGI application containing many of the features of some of the existing standalone software for the visualization of clustered microarray data. RESULTS: We present GeneXplorer, a web application for interactive microarray data visualization and analysis in a web environment. GeneXplorer allows users to browse a microarray dataset in an intuitive fashion. It provides simple access to microarray data over the Internet and uses only HTML and JavaScript to display graphic and annotation information. It provides radar and zoom views of the data, allows display of the nearest neighbors to a gene expression vector based on their Pearson correlations and provides the ability to search gene annotation fields. CONCLUSIONS: The software is released under the permissive MIT Open Source license, and the complete documentation and the entire source code are freely available for download from CPAN http://search.cpan.org/dist/Microarray-GeneXplorer/.

Computer Graphics↗
PubMed2004

Disruption of yeast forkhead-associated cell cycle transcription by oxidative stress.

The effects of oxidative stress on yeast cell cycle depend on the stress-exerting agent. We studied the effects of two oxidative stress agents, hydrogen peroxide (HP) and the superoxide-generating agent menadione (MD). We found that two small coexpressed groups of genes regulated by the Mcm1-Fkh2-Ndd1 transcription regulatory complex are sufficient to account for the difference in the effects of HP and MD on the progress of the cell cycle, namely, G1 arrest with MD and an S phase delay followed by a G2/M arrest with HP. Support for this hypothesis is provided by fkh1fkh2 double mutants, which are affected by MD as we find HP affects wild-type cells. The apparent involvement of a forkhead protein in HP-induced cell cycle arrest, similar to that reported for Caenorhabditis elegans and human, describes a potentially novel stress response pathway in yeast.

Cell Cycle↗
PubMed2004

A method for detecting and correcting feature misidentification on expression microarrays.

BACKGROUND: Much of the microarray data published at Stanford is based on mouse and human arrays produced under controlled and monitored conditions at the Brown and Botstein laboratories and at the Stanford Functional Genomics Facility (SFGF). Nevertheless, as large datasets based on the Stanford Human array began to accumulate, a small but significant number of discrepancies were detected that required a serious attempt to track down the original source of error. Due to a controlled process environment, sufficient data was available to accurately track the entire process leading to up to the final expression data. In this paper, we describe our statistical methods to detect the inconsistencies in microarray data that arise from process errors, and discuss our technique to locate and fix these errors. RESULTS: To date, the Brown and Botstein laboratories and the Stanford Functional Genomics Facility have together produced 40,000 large-scale (10-50,000 feature) cDNA microarrays. By applying the heuristic described here, we have been able to check most of these arrays for misidentified features, and have been able to confidently apply fixes to the data where needed. Out of the 265 million features checked in our database, problems were detected and corrected on 1.3 million of them. CONCLUSION: Process errors in any genome scale high throughput production regime can lead to subsequent errors in data analysis. We show the value of tracking multi-step high throughput operations by using this knowledge to detect and correct misidentified data on gene expression microarrays.

Animals↗
PubMed2004

GO::TermFinder--open source software for accessing Gene Ontology information and finding significantly enriched Gene Ontology terms associated with a list of genes.

SUMMARY: GO::TermFinder comprises a set of object-oriented Perl modules for accessing Gene Ontology (GO) information and evaluating and visualizing the collective annotation of a list of genes to GO terms. It can be used to draw conclusions from microarray and other biological data, calculating the statistical significance of each annotation. GO::TermFinder can be used on any system on which Perl can be run, either as a command line application, in single or batch mode, or as a web-based CGI script. AVAILABILITY: The full source code and documentation for GO::TermFinder are freely available from http://search.cpan.org/dist/GO-TermFinder/.

Abstracting and Indexing↗
PubMed2004

Nutritional homeostasis in batch and steady-state culture of yeast.

We studied the physiological response to limitation by diverse nutrients in batch and steady-state (chemostat) cultures of S. cerevisiae. We found that the global pattern of transcription in steady-state cultures in limiting phosphate or sulfate is essentially identical to that of batch cultures growing in the same medium just before the limiting nutrient is completely exhausted. The massive stress response and complete arrest of the cell cycle that occurs when nutrients are fully exhausted in batch cultures is not observed in the chemostat, indicating that the cells in the chemostat are "poor, not starving." Similar comparisons using leucine or uracil auxotrophs limited on leucine or uracil again showed patterns of gene expression in steady-state closely resembling those of corresponding batch cultures just before they exhaust the nutrient. Although there is also a strong stress response in the auxotrophic batch cultures, cell cycle arrest, if it occurs at all, is much less uniform. Many of the differences among the patterns of gene expression between the four nutrient limitations are interpretable in light of known involvement of the genes in stress responses or in the regulation or execution of particular metabolic pathways appropriate to the limiting nutrient. We conclude that cells adjust their growth rate to nutrient availability and maintain homeostasis in the same way in batch and steady state conditions; cells in steady-state cultures are in a physiological condition normally encountered in batch cultures.

Amino Acids↗
PubMed2004

Prediction of survival in diffuse large-B-cell lymphoma based on the expression of six genes.

BACKGROUND: Several gene-expression signatures can be used to predict the prognosis in diffuse large-B-cell lymphoma, but the lack of practical tests for a genome-scale analysis has restricted the use of this method. METHODS: We studied 36 genes whose expression had been reported to predict survival in diffuse large-B-cell lymphoma. We measured the expression of each of these genes in independent samples of lymphoma from 66 patients by quantitative real-time polymerase-chain-reaction analyses and related the results to overall survival. RESULTS: In a univariate analysis, genes were ranked on the basis of their ability to predict survival. The genes that were the strongest predictors were LMO2, BCL6, FN1, CCND2, SCYA3, and BCL2. We developed a multivariate model that was based on the expression of these six genes, and we validated the model in two independent microarray data sets. The model was independent of the International Prognostic Index and added to its predictive power. CONCLUSIONS: Measurement of the expression of six genes is sufficient to predict overall survival in diffuse large-B-cell lymphoma.

Adolescent↗
PubMed2004

Different gene expression patterns in invasive lobular and ductal carcinomas of the breast.

Invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) are the two major histological types of breast cancer worldwide. Whereas IDC incidence has remained stable, ILC is the most rapidly increasing breast cancer phenotype in the United States and Western Europe. It is not clear whether IDC and ILC represent molecularly distinct entities and what genes might be involved in the development of these two phenotypes. We conducted comprehensive gene expression profiling studies to address these questions. Total RNA from 21 ILCs, 38 IDCs, two lymph node metastases, and three normal tissues were amplified and hybridized to approximately 42,000 clone cDNA microarrays. Data were analyzed using hierarchical clustering algorithms and statistical analyses that identify differentially expressed genes (significance analysis of microarrays) and minimal subsets of genes (prediction analysis for microarrays) that succinctly distinguish ILCs and IDCs. Eleven of 21 (52%) of the ILCs ("typical" ILCs) clustered together and displayed different gene expression profiles from IDCs, whereas the other ILCs ("ductal-like" ILCs) were distributed between different IDC subtypes. Many of the differentially expressed genes between ILCs and IDCs code for proteins involved in cell adhesion/motility, lipid/fatty acid transport and metabolism, immune/defense response, and electron transport. Many genes that distinguish typical and ductal-like ILCs are involved in regulation of cell growth and immune response. Our data strongly suggest that over half the ILCs differ from IDCs not only in histological and clinical features but also in global transcription programs. The remaining ILCs closely resemble IDCs in their transcription patterns. Further studies are needed to explore the differences between ILC molecular subtypes and to determine whether they require different therapeutic strategies.

Breast Neoplasms↗
PubMed2004

Universal Reference RNA as a standard for microarray experiments.

BACKGROUND: Obtaining reliable and reproducible two-color microarray gene expression data is critically important for understanding the biological significance of perturbations made on a cellular system. Microarray design, RNA preparation and labeling, hybridization conditions and data acquisition and analysis are variables difficult to simultaneously control. A useful tool for monitoring and controlling intra- and inter-experimental variation is Universal Reference RNA (URR), developed with the goal of providing hybridization signal at each microarray probe location (spot). Measuring signal at each spot as the ratio of experimental RNA to reference RNA targets, rather than relying on absolute signal intensity, decreases variability by normalizing signal output in any two-color hybridization experiment. RESULTS: Human, mouse and rat URR (UHRR, UMRR and URRR, respectively) were prepared from pools of RNA derived from individual cell lines representing different tissues. A variety of microarrays were used to determine percentage of spots hybridizing with URR and producing signal above a user defined threshold (microarray coverage). Microarray coverage was consistently greater than 80% for all arrays tested. We confirmed that individual cell lines contribute their own unique set of genes to URR, arguing for a pool of RNA from several cell lines as a better configuration for URR as opposed to a single cell line source for URR. Microarray coverage comparing two separately prepared batches each of UHRR, UMRR and URRR were highly correlated (Pearson's correlation coefficients of 0.97). CONCLUSION: Results of this study demonstrate that large quantities of pooled RNA from individual cell lines are reproducibly prepared and possess diverse gene representation. This type of reference provides a standard for reducing variation in microarray experiments and allows more reliable comparison of gene expression data within and between experiments and laboratories.

Animals↗
PubMed2004

Diverse and specific gene expression responses to stresses in cultured human cells.

We used cDNA microarrays in a systematic study of the gene expression responses of HeLa cells and primary human lung fibroblasts to heat shock, endoplasmic reticulum stress, oxidative stress, and crowding. Hierarchical clustering of the data revealed groups of genes with coherent biological themes, including genes that responded to specific stresses and others that responded to multiple types of stress. Fewer genes increased in expression after multiple stresses than in free-living yeasts, which have a large general stress response program. Most of the genes induced by multiple diverse stresses are involved in cell-cell communication and other processes specific to higher organisms. We found substantial differences between the stress responses of HeLa cells and primary fibroblasts. For example, many genes were induced by oxidative stress and dithiothreitol in fibroblasts but not HeLa cells; conversely, a group of transcription factors, including c-fos and c-jun, were induced by heat shock in HeLa cells but not in fibroblasts. The dataset is freely available for search and download at http://microarray-pubs.stanford.edu/human_stress/Home.shtml.

Adenocarcinoma↗
PubMed2004

Introductory science and mathematics education for 21st-Century biologists.

Galileo wrote that "the book of nature is written in the language of mathematics"; his quantitative approach to understanding the natural world arguably marks the beginning of modern science. Nearly 400 years later, the fragmented teaching of science in our universities still leaves biology outside the quantitative and mathematical culture that has come to define the physical sciences and engineering. This strikes us as particularly inopportune at a time when opportunities for quantitative thinking about biological systems are exploding. We propose that a way out of this dilemma is a unified introductory science curriculum that fully incorporates mathematics and quantitative thinking.

Biological Science Disciplines↗
PubMed2004

Gene expression signature of fibroblast serum response predicts human cancer progression: similarities between tumors and wounds.

Cancer invasion and metastasis have been likened to wound healing gone awry. Despite parallels in cellular behavior between cancer progression and wound healing, the molecular relationships between these two processes and their prognostic implications are unclear. In this study, based on gene expression profiles of fibroblasts from ten anatomic sites, we identify a stereotyped gene expression program in response to serum exposure that appears to reflect the multifaceted role of fibroblasts in wound healing. The genes comprising this fibroblast common serum response are coordinately regulated in many human tumors, allowing us to identify tumors with gene expression signatures suggestive of active wounds. Genes induced in the fibroblast serum-response program are expressed in tumors by the tumor cells themselves, by tumor-associated fibroblasts, or both. The molecular features that define this wound-like phenotype are evident at an early clinical stage, persist during treatment, and predict increased risk of metastasis and death in breast, lung, and gastric carcinomas. Thus, the transcriptional signature of the response of fibroblasts to serum provides a possible link between cancer progression and wound healing, as well as a powerful predictor of the clinical course in several common carcinomas.

Disease Progression↗
PubMed2004

Gene expression profiling identifies clinically relevant subtypes of prostate cancer.

Prostate cancer, a leading cause of cancer death, displays a broad range of clinical behavior from relatively indolent to aggressive metastatic disease. To explore potential molecular variation underlying this clinical heterogeneity, we profiled gene expression in 62 primary prostate tumors, as well as 41 normal prostate specimens and nine lymph node metastases, using cDNA microarrays containing approximately 26,000 genes. Unsupervised hierarchical clustering readily distinguished tumors from normal samples, and further identified three subclasses of prostate tumors based on distinct patterns of gene expression. High-grade and advanced stage tumors, as well as tumors associated with recurrence, were disproportionately represented among two of the three subtypes, one of which also included most lymph node metastases. To further characterize the clinical relevance of tumor subtypes, we evaluated as surrogate markers two genes differentially expressed among tumor subgroups by using immunohistochemistry on tissue microarrays representing an independent set of 225 prostate tumors. Positive staining for MUC1, a gene highly expressed in the subgroups with "aggressive" clinicopathological features, was associated with an elevated risk of recurrence (P = 0.003), whereas strong staining for AZGP1, a gene highly expressed in the other subgroup, was associated with a decreased risk of recurrence (P = 0.0008). In multivariate analysis, MUC1 and AZGP1 staining were strong predictors of tumor recurrence independent of tumor grade, stage, and preoperative prostate-specific antigen levels. Our results suggest that prostate tumors can be usefully classified according to their gene expression patterns, and these tumor subtypes may provide a basis for improved prognostication and treatment stratification.

Biomarkers, Tumor↗
PubMed2004

Saccharomyces Genome Database (SGD) provides tools to identify and analyze sequences from Saccharomyces cerevisiae and related sequences from other organisms.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/), a scientific database of the molecular biology and genetics of the yeast Saccharomyces cerevisiae, has recently developed several new resources that allow the comparison and integration of information on a genome-wide scale, enabling the user not only to find detailed information about individual genes, but also to make connections across groups of genes with common features and across different species. The Fungal Alignment Viewer displays alignments of sequences from multiple fungal genomes, while the Sequence Similarity Query tool displays PSI-BLAST alignments of each S.cerevisiae protein with similar proteins from any species whose sequences are contained in the non-redundant (nr) protein data set at NCBI. The Yeast Biochemical Pathways tool integrates groups of genes by their common roles in metabolism and displays the metabolic pathways in a graphical form. Finally, the Find Chromosomal Features search interface provides a versatile tool for querying multiple types of information in SGD.

Amino Acid Sequence↗
PubMed2004

Saccharomyces genome database: underlying principles and organisation.

A scientific database can be a powerful tool for biologists in an era where large-scale genomic analysis, combined with smaller-scale scientific results, provides new insights into the roles of genes and their products in the cell. However, the collection and assimilation of data is, in itself, not enough to make a database useful. The data must be incorporated into the database and presented to the user in an intuitive and biologically significant manner. Most importantly, this presentation must be driven by the user's point of view; that is, from a biological perspective. The success of a scientific database can therefore be measured by the response of its users - statistically, by usage numbers and, in a less quantifiable way, by its relationship with the community it serves and its ability to serve as a model for similar projects. Since its inception ten years ago, the Saccharomyces Genome Database (SGD) has seen a dramatic increase in its usage, has developed and maintained a positive working relationship with the yeast research community, and has served as a template for at least one other database. The success of SGD, as measured by these criteria, is due in large part to philosophies that have guided its mission and organisation since it was established in 1993. This paper aims to detail these philosophies and how they shape the organisation and presentation of the database.

Databases, Nucleic Acid↗
PubMed2003

Transcriptional remodeling in response to iron deprivation in Saccharomyces cerevisiae.

The budding yeast Saccharomyces cerevisiae responds to depletion of iron in the environment by activating Aft1p, the major iron-dependent transcription factor, and by transcribing systems involved in the uptake of iron. Here, we have studied the transcriptional response to iron deprivation and have identified new Aft1p target genes. We find that other metabolic pathways are regulated by iron: biotin uptake and biosynthesis, nitrogen assimilation, and purine biosynthesis. Two enzymes active in these pathways, biotin synthase and glutamate synthase, require an iron-sulfur cluster for activity. Iron deprivation activates transcription of the biotin importer and simultaneously represses transcription of the entire biotin biosynthetic pathway. Multiple genes involved in nitrogen assimilation and amino acid metabolism are induced by iron deprivation, whereas glutamate synthase, a key enzyme in nitrogen assimilation, is repressed. A CGG palindrome within the promoter of glutamate synthase confers iron-regulated expression, suggesting control by a transcription factor of the binuclear zinc cluster family. We provide evidence that yeast subjected to iron deprivation undergo a transcriptional remodeling, resulting in a shift from iron-dependent to parallel, but iron-independent, metabolic pathways.

Base Sequence↗