Biomedical subjects

Steven J Altschuler

Publications and source records attributed to Steven J Altschuler.

6 recordsLinked to original sources

PubMed2006

Systems-level analyses identify extensive coupling among gene expression machines.

Here, we develop computational methods to assess and consolidate large, diverse protein interaction data sets, with the objective of identifying proteins involved in the coupling of multicomponent complexes within the yeast gene expression pathway. From among approximately 43 000 total interactions and 2100 proteins, our methods identify known structural complexes, such as the spliceosome and SAGA, and functional modules, such as the DEAD-box helicases, within the interaction network of proteins involved in gene expression. Our process identifies and ranks instances of three distinct, biologically motivated motifs, or patterns of coupling among distinct machineries involved in different subprocesses of gene expression. Our results confirm known coupling among transcription, RNA processing, and export, and predict further coupling with translation and nonsense-mediated decay. We systematically corroborate our analysis with two independent, comprehensive experimental data sets. The methods presented here may be generalized to other biological processes and organisms to generate principled, systems-level network models that provide experimentally testable hypotheses for coupling among biological machines.

Cluster Analysis↗

PubMed2005

Genome-scale identification of nucleosome positions in S. cerevisiae.

The positioning of nucleosomes along chromatin has been implicated in the regulation of gene expression in eukaryotic cells, because packaging DNA into nucleosomes affects sequence accessibility. We developed a tiled microarray approach to identify at high resolution the translational positions of 2278 nucleosomes over 482 kilobases of Saccharomyces cerevisiae DNA, including almost all of chromosome III and 223 additional regulatory regions. The majority of the nucleosomes identified were well-positioned. We found a stereotyped chromatin organization at Pol II promoters consisting of a nucleosome-free region approximately 200 base pairs upstream of the start codon flanked on both sides by positioned nucleosomes. The nucleosome-free sequences were evolutionarily conserved and were enriched in poly-deoxyadenosine or poly-deoxythymidine sequences. Most occupied transcription factor binding motifs were devoid of nucleosomes, strongly suggesting that nucleosome positioning is a global determinant of transcription factor access.

Binding Sites↗

PubMed2005

Genomic characterization reveals a simple histone H4 acetylation code.

The histone code hypothesis holds that covalent posttranslational modifications of histone tails are interpreted by the cell to yield a rich combinatorial transcriptional output. This hypothesis has been the subject of active debate in the literature. Here, we investigated the combinatorial complexity of the acetylation code at the four lysine residues of the histone H4 tail in budding yeast. We constructed yeast strains carrying all 15 possible combinations of mutations among lysines 5, 8, 12, and 16 to arginine in the histone H4 tail, mimicking positively charged, unacetylated lysine states, and characterized the resulting genome-wide changes in gene expression by using DNA microarrays. Only the lysine 16 mutation had specific transcriptional consequences independent of the mutational state of the other lysines (affecting approximately 100 genes). In contrast, for lysines 5, 8, and 12, expression changes were due to nonspecific, cumulative effects seen as increased transcription correlating with an increase in the total number of mutations (affecting approximately 1,200 genes). Thus, acetylation of histone H4 is interpreted by two mechanisms: a specific mechanism for lysine 16 and a nonspecific, cumulative mechanism for lysines 5, 8, and 12.

Acetylation↗

PubMed2004

Multidimensional drug profiling by automated microscopy.

We present a method for high-throughput cytological profiling by microscopy. Our system provides quantitative multidimensional measures of individual cell states over wide ranges of perturbations. We profile dose-dependent phenotypic effects of drugs in human cell culture with a titration-invariant similarity score (TISS). This method successfully categorized blinded drugs and suggested targets for drugs of uncertain mechanism. Multivariate single-cell analysis is a starting point for identifying relationships among drug effects at a systems level and a step toward phenotypic profiling at the single-cell level. Our methods will be useful for discovering the mechanism and predicting the toxicity of new drugs.

Automation↗

PubMed2003

A panoramic view of yeast noncoding RNA processing.

Predictive analysis using publicly available yeast functional genomics and proteomics data suggests that many more proteins may be involved in biogenesis of ribonucleoproteins than are currently known. Using a microarray that monitors abundance and processing of noncoding RNAs, we analyzed 468 yeast strains carrying mutations in protein-coding genes, most of which have not previously been associated with RNA or RNP synthesis. Many strains mutated in uncharacterized genes displayed aberrant noncoding RNA profiles. Ten factors involved in noncoding RNA biogenesis were verified by further experimentation, including a protein required for 20S pre-rRNA processing (Tsr2p), a protein associated with the nuclear exosome (Lrp1p), and a factor required for box C/D snoRNA accumulation (Bcd1p). These data present a global view of yeast noncoding RNA processing and confirm that many currently uncharacterized yeast proteins are involved in biogenesis of noncoding RNA.

Cells, Cultured↗

PubMed2002

Large-scale prediction of Saccharomyces cerevisiae gene function using overlapping transcriptional clusters.

Genome sequencing has led to the discovery of tens of thousands of potential new genes. Six years after the sequencing of the well-studied yeast Saccharomyces cerevisiae and the discovery that its genome encodes approximately 6,000 predicted proteins, more than 2,000 have not yet been characterized experimentally, and determining their functions seems far from a trivial task. One crucial constraint is the generation of useful hypotheses about protein function. Using a new approach to interpret microarray data, we assign likely cellular functions with confidence values to these new yeast proteins. We perform extensive genome-wide validations of our predictions and offer visualization methods for exploration of the large numbers of functional predictions. We identify potential new members of many existing functional categories including 285 candidate proteins involved in transcription, processing and transport of non-coding RNA molecules. We present experimental validation confirming the involvement of several of these proteins in ribosomal RNA processing. Our methodology can be applied to a variety of genomics data types and organisms.

Algorithms↗