Biomedical subjects

Daniel D Shoemaker

Publications and source records attributed to Daniel D Shoemaker.

4 recordsLinked to original sources

PubMed2003

Parallel analysis of tagged deletion mutants efficiently identifies genes involved in endoplasmic reticulum biogenesis.

Increased levels of HMG-CoA reductase induce cell type- and isozyme-specific proliferation of the endoplasmic reticulum. In yeast, the ER proliferations induced by Hmg1p consist of nuclear-associated stacks of smooth ER membranes known as karmellae. To identify genes required for karmellae assembly, we compared the composition of populations of homozygous diploid S. cerevisiae deletion mutants following 20 generations of growth with and without karmellae. Using an initial population of 1,557 deletion mutants, 120 potential mutants were identified as a result of three independent experiments. Each experiment produced a largely non-overlapping set of potential mutants, suggesting that differences in specific growth conditions could be used to maximize the comprehensiveness of similar parallel analysis screens. Only two genes, UBC7 and YAL011W, were identified in all three experiments. Subsequent analysis of individual mutant strains confirmed that each experiment was identifying valid mutations, based on the mutant's sensitivity to elevated HMG-CoA reductase and inability to assemble normal karmellae. The largest class of HMG-CoA reductase-sensitive mutations was a subset of genes that are involved in chromatin structure and transcriptional regulation, suggesting that karmellae assembly requires changes in transcription or that the presence of karmellae may interfere with normal transcriptional regulation.

DNA, Fungal↗

PubMed2003

Microarray standard data set and figures of merit for comparing data processing methods and experiment designs.

MOTIVATION: There is a very large and growing level of effort toward improving the platforms, experiment designs, and data analysis methods for microarray expression profiling. Along with a growing richness in the approaches there is a growing confusion among most scientists as to how to make objective comparisons and choices between them for different applications. There is a need for a standard framework for the microarray community to compare and improve analytical and statistical methods. RESULTS: We report on a microarray data set comprising 204 in-situ synthesized oligonucleotide arrays, each hybridized with two-color cDNA samples derived from 20 different human tissues and cell lines. Design of the approximately 24 000 60mer oligonucleotides that report approximately 2500 known genes on the arrays, and design of the hybridization experiments, were carried out in a way that supports the performance assessment of alternative data processing approaches and of alternative experiment and array designs. We also propose standard figures of merit for success in detecting individual differential expression changes or expression levels, and for detecting similarities and differences in expression patterns across genes and experiments. We expect this data set and the proposed figures of merit will provide a standard framework for much of the microarray community to compare and improve many analytical and statistical methods relevant to microarray data analysis, including image processing, normalization, error modeling, combining of multiple reporters per gene, use of replicate experiments, and sample referencing schemes in measurements based on expression change. AVAILABILITY/SUPPLEMENTARY INFORMATION: Expression data and supplementary information are available at http://www.rii.com/publications/2003/HE_SDS.htm

Base Sequence↗

PubMed2002

Functional profiling of the Saccharomyces cerevisiae genome.

Determining the effect of gene deletion is a fundamental approach to understanding gene function. Conventional genetic screens exhibit biases, and genes contributing to a phenotype are often missed. We systematically constructed a nearly complete collection of gene-deletion mutants (96% of annotated open reading frames, or ORFs) of the yeast Saccharomyces cerevisiae. DNA sequences dubbed 'molecular bar codes' uniquely identify each strain, enabling their growth to be analysed in parallel and the fitness contribution of each gene to be quantitatively assessed by hybridization to high-density oligonucleotide arrays. We show that previously known and new genes are necessary for optimal growth under six well-studied conditions: high salt, sorbitol, galactose, pH 8, minimal medium and nystatin treatment. Less than 7% of genes that exhibit a significant increase in messenger RNA expression are also required for optimal growth in four of the tested conditions. Our results validate the yeast gene-deletion collection as a valuable resource for functional genomics.

Cell Size↗

PubMed2002

Recent developments in DNA microarrays.

DNA microarrays are used to quantify tens of thousands of DNA or RNA sequences in a single assay. Upon their introduction approximately six years ago, DNA microarrays were viewed as a disruptive technology that would fundamentally alter the scientific landscape. Supporting this view, the number of applications of DNA microarray technology has since expanded exponentially. Here, we review recent advances in microarray technology and selected new applications of the technology.

Animals↗