Timothy R. Hughes

Global landscape of protein complexes in the yeast Saccharomyces cerevisiae

Identification of protein–protein interactions often provides insight into protein function, and many cellular processes are performed by stable protein complexes. We used tandem affinity purification to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae. Each preparation was analysed by both matrix-assisted laser desorption/ionization–time of flight mass spectrometry and liquid chromatography tandem mass spectrometry to increase coverage and accuracy. Machine learning was used to integrate the mass spectrometry scores and assign probabilities to the protein–protein interactions. Among 4,087 different proteins identified with high confidence by mass spectrometry from 2,357 successful purifications, our core data set (median precision of 0.69) comprises 7,123 protein–protein interactions involving 2,708 proteins. A Markov clustering algorithm organized these interactions into 547 protein complexes averaging 4.9 subunits per complex, about half of them absent from the MIPS database, as well as 429 additional interactions between pairs of complexes. The data (all of which are available online) will help future studies on individual proteins as well as functional genomics and systems biology.

The DNA-encoded nucleosome organization of a eukaryotic genome

Nucleosome organization is critical for gene regulation. In living cells this organization is determined by multiple factors, including the action of chromatin remodellers, competition with site-specific DNA-binding proteins, and the DNA sequence preferences of the nucleosomes themselves. However, it has been difficult to estimate the relative importance of each of these mechanisms in vivo, because in vivo nucleosome maps reflect the combined action of all influencing factors. Here we determine the importance of nucleosome DNA sequence preferences experimentally by measuring the genome-wide occupancy of nucleosomes assembled on purified yeast genomic DNA. The resulting map, in which nucleosome occupancy is governed only by the intrinsic sequence preferences of nucleosomes, is similar to in vivo nucleosome maps generated in three different growth conditions. In vitro, nucleosome depletion is evident at many transcription factor binding sites and around gene start and end sites, indicating that nucleosome depletion at these sites in vivo is partly encoded in the genome. We confirm these results with a micrococcal nuclease-independent experiment that measures the relative affinity of nucleosomes for ∼40,000 double-stranded 150-base-pair oligonucleotides. Using our in vitro data, we devise a computational model of nucleosome sequence preferences that is significantly correlated with in vivo nucleosome occupancy in Caenorhabditis elegans. Our results indicate that the intrinsic DNA sequence preferences of nucleosomes have a central role in determining the organization of nucleosomes in vivo.

A high-resolution atlas of nucleosome occupancy in yeast

We present the first complete high-resolution map of nucleosome occupancy across the whole Saccharomyces cerevisiae genome, identifying over 70,000 positioned nucleosomes occupying 81% of the genome. On a genome-wide scale, the persistent nucleosome-depleted region identified previously in a subset of genes demarcates the transcription start site. Both nucleosome occupancy signatures and overall occupancy correlate with transcript abundance and transcription rate. In addition, functionally related genes can be clustered on the basis of the nucleosome occupancy patterns observed at their promoters. A quantitative model of nucleosome occupancy indicates that DNA structural features may account for much of the global nucleosome occupancy.

Cotranscriptional Set2 Methylation of Histone H3 Lysine 36 Recruits a Repressive Rpd3 Complex

The yeast histone deacetylase Rpd3 can be recruited to promoters to repress transcription initiation. Biochemical, genetic, and gene-expression analyses show that Rpd3 exists in two distinct complexes. The smaller complex, Rpd3C(S), shares Sin3 and Ume1 with Rpd3C(L) but contains the unique subunits Rco1 and Eaf3. Rpd3C(S) mutants exhibit phenotypes remarkably similar to those of Set2, a histone methyltransferase associated with elongating RNA polymerase II. Chromatin immunoprecipitation and biochemical experiments indicate that the chromodomain of Eaf3 recruits Rpd3C(S) to nucleosomes methylated by Set2 on histone H3 lysine 36, leading to deacetylation of transcribed regions. This pathway apparently acts to negatively regulate transcription because deleting the genes for Set2 or Rpd3C(S) bypasses the requirement for the positive elongation factor Bur1/Bur2.

Global analysis of mRNA localization reveals a prominent role in organizing cellular architecture and function.

Although subcellular mRNA trafficking has been demonstrated as a mechanism to control protein distribution, it is generally believed that most protein localization occurs subsequent to translation. To address this point, we developed and employed a high-resolution fluorescent in situ hybridization procedure to comprehensively evaluate mRNA localization dynamics during early Drosophila embryogenesis. Surprisingly, of the 3370 genes analyzed, 71% of those expressed encode subcellularly localized mRNAs. Dozens of new and striking localization patterns were observed, implying an equivalent variety of localization mechanisms. Tight correlations between mRNA distribution and subsequent protein localization and function, indicate major roles for mRNA localization in nucleating localized cellular machineries. A searchable web resource documenting mRNA expression and localization dynamics has been established and will serve as an invaluable tool for dissecting localization mechanisms and for predicting gene functions and interactions.

A compendium of RNA-binding motifs for decoding gene regulation

RNA-binding proteins are key regulators of gene expression, yet only a small fraction have been functionally characterized. Here we report a systematic analysis of the RNA motifs recognized by RNA-binding proteins, encompassing 205 distinct genes from 24 diverse eukaryotes. The sequence specificities of RNA-binding proteins display deep evolutionary conservation, and the recognition preferences for a large fraction of metazoan RNA-binding proteins can thus be inferred from their RNA-binding domain sequence. The motifs that we identify in vitro correlate well with in vivo RNA-binding data. Moreover, we can associate them with distinct functional roles in diverse types of post-transcriptional regulation, enabling new insights into the functions of RNA-binding proteins both in normal physiology and in human disease. These data provide an unprecedented overview of RNA-binding proteins and their targets, and constitute an invaluable resource for determining post-transcriptional regulatory mechanisms in eukaryotes.

Integration of chemical-genetic and genetic interaction data links bioactive compounds to cellular target pathways

Bioactive compounds can be valuable research tools and drug leads, but it is often difficult to identify their mechanism of action or cellular target. Here we investigate the potential for integration of chemical-genetic and genetic interaction data to reveal information about the pathways and targets of inhibitory compounds. Taking advantage of the existing complete set of yeast haploid deletion mutants, we generated drug-hypersensitivity (chemical-genetic) profiles for 12 compounds. In addition to a set of compound-specific interactions, the chemical-genetic profiles identified a large group of genes required for multidrug resistance. In particular, yeast mutants lacking a functional vacuolar H+-ATPase show multidrug sensitivity, a phenomenon that may be conserved in mammalian cells. By filtering chemical-genetic profiles for the multidrug-resistant genes and then clustering the compound-specific profiles with a compendium of large-scale genetic interaction profiles, we were able to identify target pathways or proteins. This method thus provides a powerful means for inferring mechanism of action.

DNA-binding specificities of human transcription factors.

Although the proteins that read the gene regulatory code, transcription factors (TFs), have been largely identified, it is not well known which sequences TFs can recognize. We have analyzed the sequence-specific binding of human TFs using high-throughput SELEX and ChIP sequencing. A total of 830 binding profiles were obtained, describing 239 distinctly different binding specificities. The models represent the majority of human TFs, approximately doubling the coverage compared to existing systematic studies. Our results reveal additional specificity determinants for a large number of factors for which a partial specificity was known, including a commonly observed A- or T-rich stretch that flanks the core motifs. Global analysis of the data revealed that homodimer orientation and spacing preferences, and base-stacking interactions, have a larger role in TF-DNA binding than previously appreciated. We further describe a binding model incorporating these features that is required to understand binding of TFs to DNA.

Exploration of Essential Gene Functions via Titratable Promoter Alleles

Nearly 20% of yeast genes are required for viability, hindering genetic analysis with knockouts. We created promoter-shutoff strains for over two-thirds of all essential yeast genes and subjected them to morphological analysis, size profiling, drug sensitivity screening, and microarray expression profiling. We then used this compendium of data to ask which phenotypic features characterized different functional classes and used these to infer potential functions for uncharacterized genes. We identified genes involved in ribosome biogenesis (HAS1, URB1, and URB2), protein secretion (SEC39), mitochondrial import (MIM1), and tRNA charging (GSN1). In addition, apparent negative feedback transcriptional regulation of both ribosome biogenesis and the proteasome was observed. We furthermore show that these strains are compatible with automated genetic analysis. This study underscores the importance of analyzing mutant phenotypes and provides a resource to complement the yeast knockout collection.

A Snf2 Family ATPase Complex Required for Recruitment of the Histone H2A Variant Htz1

Deletions of three yeast genes, SET2, CDC73, and DST1, involved in transcriptional elongation and/or chromatin metabolism were used in conjunction with genetic array technology to screen approximately 4700 yeast deletions and identify double deletion mutants that produce synthetic growth defects. Of the five deletions interacting genetically with all three starting mutations, one encoded the histone H2A variant Htz1 and three encoded components of a novel 13 protein complex, SWR-C, containing the Snf2 family ATPase, Swr1. The SWR-C also copurified with Htz1 and Bdf1, a TFIID-interacting protein that recognizes acetylated histone tails. Deletions of the genes encoding Htz1 and seven nonessential SWR-C components caused a similar spectrum of synthetic growth defects when combined with deletions of 384 genes involved in transcription, suggesting that Htz1 and SWR-C belong to the same pathway. We show that recruitment of Htz1 to chromatin requires the SWR-C. Moreover, like Htz1 and Bdf1, the SWR-C promotes gene expression near silent heterochromatin.