Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Daniel D. Shoemaker is active.

Publication


Featured researches published by Daniel D. Shoemaker.


Nature | 2002

Functional profiling of the Saccharomyces cerevisiae genome

Guri Giaever; Angela M. Chu; Li Ni; Carla Connelly; Linda Riles; Steeve Veronneau; Sally Dow; Ankuta Lucau-Danila; Keith R. Anderson; Bruno André; Adam P. Arkin; Anna Astromoff; Mohamed El Bakkoury; Rhonda Bangham; Rocío Benito; Sophie Brachat; Stefano Campanaro; Matt Curtiss; Karen Davis; Adam M. Deutschbauer; Karl Dieter Entian; Patrick Flaherty; Francoise Foury; David J. Garfinkel; Mark Gerstein; Deanna Gotte; Ulrich Güldener; Johannes H. Hegemann; Svenja Hempel; Zelek S. Herman

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.


Nature Biotechnology | 2001

Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer

Timothy Hughes; Mao Mao; Allan R. Jones; Julja Burchard; Matthew J. Marton; Karen W. Shannon; Steven M. Lefkowitz; Michael Ziman; Janell M. Schelter; Michael R. Meyer; Sumire V. Kobayashi; Colleen P. Davis; Hongyue Dai; Yudong D. He; Guy Cavet; Wynn L. Walker; Anne E. West; Ernest M. Coffey; Daniel D. Shoemaker; Roland Stoughton; Alan P. Blanchard; Stephen H. Friend; Peter S. Linsley

We describe a flexible system for gene expression profiling using arrays of tens of thousands of oligonucleotides synthesized in situ by an ink-jet printing method employing standard phosphoramidite chemistry. We have characterized the dependence of hybridization specificity and sensitivity on parameters including oligonucleotide length, hybridization stringency, sequence identity, sample abundance, and sample preparation method. We find that 60-mer oligonucleotides reliably detect transcript ratios at one copy per cell in complex biological samples, and that ink-jet arrays are compatible with several different sample amplification and labeling techniques. Furthermore, results using only a single carefully selected oligonucleotide per gene correlate closely with those obtained using complementary DNA (cDNA) arrays. Most of the genes for which measurements differ are members of gene families that can only be distinguished by oligonucleotides. Because different oligonucleotide sequences can be specified for each array, we anticipate that ink-jet oligonucleotide array technology will be useful in a wide variety of DNA microarray applications.


Nature Genetics | 1996

Quantitative phenotypic analysis of yeast deletion mutants using a highly parallel molecular bar–coding strategy

Daniel D. Shoemaker; Deval Lashkari; Don Morris; Mike Mittmann; Ronald W. Davis

A quantitative and highly parallel method for analysing deletion mutants has been developed to aid in determining the biological function of thousands of newly identified open reading frames (ORFs) in Saccharomyces cerevisiae. This approach uses a PCR targeting strategy to generate large numbers of deletion strains. Each deletion strain is labelled with a unique 20–base tag sequence that can be detected by hybridization to a high–density oligonucleotide array. The tags serve as unique identifiers (molecular bar codes) that allow analysis of large numbers of deletion strains simultaneously through selective growth conditions. Hybridization experiments show that the arrays are specific, sensitive and quantitative. A pilot study with 11 known yeastgenes suggests that the method can be extended to include all of the ORFs in the yeast genome, allowing whole genome analysis with a single selective growth condition and a single hybridization.


Nature Genetics | 1999

Genomic profiling of drug sensitivities via induced haploinsufficiency

Guri Giaever; Daniel D. Shoemaker; Ted Jones; Hong Liang; Elizabeth Winzeler; Anna Astromoff; Ronald W. Davis

Lowering the dosage of a single gene from two copies to one copy in diploid yeast results in a heterozygote that is sensitized to any drug that acts on the product of this gene. This haploinsufficient phenotype thereby identifies the gene product of the heterozygous locus as the likely drug target. We exploited this finding in a genomic approach to drug-target identification. Genome sequence information was used to generate molecularly tagged heterozygous yeast strains that were pooled, grown competitively in drug and analysed for drug sensitivity using high-density oligonucleotide arrays. Individual heterozygous strain analysis verified six known drug targets. Parallel analysis identified the known target and two hypersensitive loci in a mixed culture of 233 strains in the presence of the drug tunicamycin. Our discovery that both drug target and hypersensitive loci exhibit drug-induced haploinsufficiency may have important consequences in pharmacogenomics and variable drug toxicity observed in human populations.


Nature | 2001

Experimental annotation of the human genome using microarray technology.

Daniel D. Shoemaker; Eric E. Schadt; Christopher D. Armour; Yudong He; Philip W. Garrett-engele; P. D. McDonagh; Patrick M. Loerch; Amy Leonardson; Pek Yee Lum; Guy Cavet; Lani F. Wu; Steven J. Altschuler; Seve Edwards; J. King; John S. Tsang; G. Schimmack; J. M. Schelter; J. Koch; M. Ziman; Matthew J. Marton; B. Li; P. Cundiff; T. Ward; John Castle; M. Krolewski; Michael R. Meyer; Mao Mao; Julja Burchard; M. J. Kidd; Hongyue Dai

The most important product of the sequencing of a genome is a complete, accurate catalogue of genes and their products, primarily messenger RNA transcripts and their cognate proteins. Such a catalogue cannot be constructed by computational annotation alone; it requires experimental validation on a genome scale. Using ‘exon’ and ‘tiling’ arrays fabricated by ink-jet oligonucleotide synthesis, we devised an experimental approach to validate and refine computational gene predictions and define full-length transcripts on the basis of co-regulated expression of their exons. These methods can provide more accurate gene numbers and allow the detection of mRNA splice variants and identification of the tissue- and disease-specific conditions under which genes are expressed. We apply our technique to chromosome 22q under 69 experimental condition pairs, and to the entire human genome under two experimental conditions. We discuss implications for more comprehensive, consistent and reliable genome annotation, more efficient, full-length complementary DNA cloning strategies and application to complex diseases.


Cell | 2004

Discovering modes of action for therapeutic compounds using a genome-wide screen of yeast heterozygotes.

Pek Yee Lum; Christopher D. Armour; Sergey Stepaniants; Guy Cavet; Maria K. Wolf; J. Scott Butler; Jerald C. Hinshaw; Philippe Garnier; Glenn D. Prestwich; Amy Leonardson; Philip W. Garrett-engele; Christopher M. Rush; Martin Bard; Greg Schimmack; John W. Phillips; Christopher J. Roberts; Daniel D. Shoemaker

Modern medicine faces the challenge of developing safer and more effective therapies to treat human diseases. Many drugs currently in use were discovered without knowledge of their underlying molecular mechanisms. Understanding their biological targets and modes of action will be essential to design improved second-generation compounds. Here, we describe the use of a genome-wide pool of tagged heterozygotes to assess the cellular effects of 78 compounds in Saccharomyces cerevisiae. Specifically, lanosterol synthase in the sterol biosynthetic pathway was identified as a target of the antianginal drug molsidomine, which may explain its cholesterol-lowering effects. Further, the rRNA processing exosome was identified as a potential target of the cell growth inhibitor 5-fluorouracil. This genome-wide screen validated previously characterized targets or helped identify potentially new modes of action for over half of the compounds tested, providing proof of this principle for analyzing the modes of action of clinically relevant compounds.


Genome Biology | 2004

A comprehensive transcript index of the human genome generated using microarrays and computational approaches

Eric E. Schadt; Stephen Edwards; Debraj GuhaThakurta; Dan Holder; Lisa Ying; Vladimir Svetnik; Amy Leonardson; Kyle W Hart; Archie Russell; Guoya Li; Guy Cavet; John Castle; Paul McDonagh; Zhengyan Kan; Ronghua Chen; Andrew Kasarskis; Mihai Margarint; Ramon M Caceres; Jason M. Johnson; Christopher D. Armour; Philip W. Garrett-engele; Nicholas F. Tsinoremas; Daniel D. Shoemaker

BackgroundComputational and microarray-based experimental approaches were used to generate a comprehensive transcript index for the human genome. Oligonucleotide probes designed from approximately 50,000 known and predicted transcript sequences from the human genome were used to survey transcription from a diverse set of 60 tissues and cell lines using ink-jet microarrays. Further, expression activity over at least six conditions was more generally assessed using genomic tiling arrays consisting of probes tiled through a repeat-masked version of the genomic sequence making up chromosomes 20 and 22.ResultsThe combination of microarray data with extensive genome annotations resulted in a set of 28,456 experimentally supported transcripts. This set of high-confidence transcripts represents the first experimentally driven annotation of the human genome. In addition, the results from genomic tiling suggest that a large amount of transcription exists outside of annotated regions of the genome and serves as an example of how this activity could be measured on a genome-wide scale.ConclusionsThese data represent one of the most comprehensive assessments of transcriptional activity in the human genome and provide an atlas of human gene expression over a unique set of gene predictions. Before the annotation of the human genome is considered complete, however, the previously unannotated transcriptional activity throughout the genome must be fully characterized.


Bioinformatics | 2003

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

Yudong D. He; Hongyue Dai; Eric E. Schadt; Guy Cavet; Stephen Edwards; Sergey Stepaniants; Sven Duenwald; Robert Kleinhanz; Allan R. Jones; Daniel D. Shoemaker; Roland Stoughton

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


Genome Biology | 2003

Optimization of oligonucleotide arrays and RNA amplification protocols for analysis of transcript structure and alternative splicing.

John Castle; Phil Garrett-Engele; Christopher D. Armour; Sven Duenwald; Patrick M. Loerch; Michael R. Meyer; Eric E. Schadt; Roland Stoughton; Mark L Parrish; Daniel D. Shoemaker; Jason M. Johnson

Microarrays offer a high-resolution means for monitoring pre-mRNA splicing on a genomic scale. We have developed a novel, unbiased amplification protocol that permits labeling of entire transcripts. Also, hybridization conditions, probe characteristics, and analysis algorithms were optimized for detection of exons, exon-intron edges, and exon junctions. These optimized protocols can be used to detect small variations and isoform mixtures, map the tissue specificity of known human alternative isoforms, and provide a robust, scalable platform for high-throughput discovery of alternative splicing.


Current Opinion in Microbiology | 2002

Recent developments in DNA microarrays.

Daniel D. Shoemaker; Peter S. Linsley

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.

Collaboration


Dive into the Daniel D. Shoemaker's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar

Eric E. Schadt

Icahn School of Medicine at Mount Sinai

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge