RLI1 | GeneID:851665 | Saccharomyces cerevisiae
Gene Summary
[
] NCBI Entrez Gene
| Gene ID | 851665 | Official Symbol | RLI1 |
|---|---|---|---|
| Locus | YDR091C | Gene Type | protein-coding |
| Synonyms | |||
| Full Name | N/A | ||
| Description | Essential iron-sulfur protein required for ribosome biogenesis and translation initiation; facilitates binding of a multifactor complex (MFC) of translation initiation factors to the small ribosomal subunit; predicted ABC family ATPase | ||
| Chromosome | N/A | ||
| Also Known As | Rli1p | ||
| Summary | N/A | ||
Orthologs and Paralogs
[
] Homologs - NCBI's HomoloGene Group: 2205
| ID | Symbol | Protein | Species |
|---|---|---|---|
| GeneID:6059 | ABCE1 | NP_001035809.1 | Homo sapiens |
| GeneID:24015 | Abce1 | NP_056566.2 | Mus musculus |
| GeneID:39027 | CG5651 | NP_648272.1 | Drosophila melanogaster |
| GeneID:176733 | abce-1 | NP_499717.1 | Caenorhabditis elegans |
| GeneID:361390 | Abce1 | XP_001064797.1 | Rattus norvegicus |
| GeneID:406324 | abce1 | NP_998216.1 | Danio rerio |
| GeneID:422462 | ABCE1 | NP_001006440.1 | Gallus gallus |
| GeneID:461523 | ABCE1 | XP_517465.1 | Pan troglodytes |
| GeneID:475454 | ABCE1 | XP_532679.2 | Canis lupus familiaris |
| GeneID:514991 | ABCE1 | XP_592921.3 | Bos taurus |
| GeneID:813912 | MAL13P1.344 | XP_001350392.1 | Plasmodium falciparum |
| GeneID:827661 | ATRLI2 | NP_193656.2 | Arabidopsis thaliana |
| GeneID:851665 | RLI1 | NP_010376.1 | Saccharomyces cerevisiae |
| GeneID:1269374 | AgaP_AGAP002182 | XP_308004.2 | Anopheles gambiae |
| GeneID:2539753 | SPBC14F5.06 | NP_596732.1 | Schizosaccharomyces pombe |
| GeneID:2677986 | MGG_11382 | XP_362155.2 | Magnaporthe grisea |
| GeneID:2712409 | NCU03061.1 | XP_330497.1 | Neurospora crassa |
| GeneID:2891913 | KLLA0C17556g | XP_452984.1 | Kluyveromyces lactis |
| GeneID:4350692 | Os11g0546000 | NP_001068062.1 | Oryza sativa |
| GeneID:4623093 | AGOS_AGR125W | NP_986791.1 | Eremothecium gossypii |
Gene Classification
[
] Gene Ontology
| ID | Category | GO Term |
|---|---|---|
| GO:0005737 | Component | cytoplasm |
| GO:0022626 | Component | cytosolic ribosome |
| GO:0005634 | Component | nucleus |
| GO:0016887 | Function | ATPase activity |
| GO:0005524 | Function | ATP binding |
| GO:0009055 | Function | electron carrier activity |
| GO:0005506 | Function | iron ion binding |
| GO:0051536 | Function | iron-sulfur cluster binding |
| GO:0017111 | Function | nucleoside-triphosphatase activity |
| GO:0000166 | Function | nucleotide binding |
| GO:0003743 | Function | translation initiation factor activity |
| GO:0042273 | Process | ribosomal large subunit biogenesis |
| GO:0042254 | Process | ribosome biogenesis |
| GO:0000054 | Process | ribosome export from nucleus |
| GO:0006364 | Process | rRNA processing |
| GO:0006412 | Process | translation |
| GO:0006413 | Process | translational initiation |
| GO:0006810 | Process | transport |
Gene Interactions
[
] BioGRID Gene Product Interaction Database
| Symbol | Interaction Binary | Experiment | Source |
|---|---|---|---|
| AIR1 | RLI1 / AIR1 | Phenotypic Enhancement | Wilmes GM (2008) |
| BUD21 | RLI1 / BUD21 | Phenotypic Suppression | Wilmes GM (2008) |
| CYR1 | RLI1 / CYR1 | Affinity Capture-MS | Krogan NJ (2006) |
| DBP2 | RLI1 / DBP2 | Affinity Capture-MS | Gavin AC (2006) |
| DEG1 | DEG1 / RLI1 | Phenotypic Suppression | Wilmes GM (2008) |
| EAF7 | EAF7 / RLI1 | Phenotypic Enhancement | Wilmes GM (2008) |
| FUN12 | FUN12 / RLI1 | Affinity Capture-MS | Collins SR (2007) |
| GBP2 | GBP2 / RLI1 | Phenotypic Enhancement | Wilmes GM (2008) |
| HCR1 | RLI1 / HCR1 | Affinity Capture-MS | Collins SR (2007) |
| HCR1 | RLI1 / HCR1 | Affinity Capture-MS | Krogan NJ (2004) |
| HCR1 | RLI1 / HCR1 | Affinity Capture-MS | Krogan NJ (2006) |
| HCR1 | RLI1 / HCR1 | Phenotypic Suppression | Wilmes GM (2008) |
| HCR1 | RLI1 / HCR1 | Two-hybrid | Ito T (2001) |
| HCR1 | RLI1 / HCR1 | Two-hybrid | Kispal G (2005) |
| HRB1 | HRB1 / RLI1 | Phenotypic Suppression | Wilmes GM (2008) |
| IFM1 | RLI1 / IFM1 | Phenotypic Suppression | Wilmes GM (2008) |
| IKI3 | IKI3 / RLI1 | Phenotypic Suppression | Wilmes GM (2008) |
| IMD3 | RLI1 / IMD3 | Affinity Capture-MS | Gavin AC (2006) |
| IST3 | IST3 / RLI1 | Phenotypic Suppression | Wilmes GM (2008) |
| KSP1 | KSP1 / RLI1 | Biochemical Activity | Ptacek J (2005) |
| LRP1 | RLI1 / LRP1 | Phenotypic Enhancement | Wilmes GM (2008) |
| LRS4 | LRS4 / RLI1 | Phenotypic Suppression | Wilmes GM (2008) |
| MOG1 | MOG1 / RLI1 | Phenotypic Suppression | Wilmes GM (2008) |
| MSD1 | RLI1 / MSD1 | Phenotypic Suppression | Wilmes GM (2008) |
| MSK1 | RLI1 / MSK1 | Phenotypic Suppression | Wilmes GM (2008) |
| N/A | RLI1 / N/A | Affinity Capture-MS | Krogan NJ (2004) |
| N/A | RLI1 / N/A | Affinity Capture-MS | Krogan NJ (2006) |
| N/A | N/A / RLI1 | Phenotypic Enhancement | Wilmes GM (2008) |
| N/A | N/A / RLI1 | Phenotypic Suppression | Wilmes GM (2008) |
| N/A | RLI1 / N/A | Phenotypic Suppression | Wilmes GM (2008) |
| NAM7 | RLI1 / NAM7 | Phenotypic Suppression | Wilmes GM (2008) |
| NIP1 | RLI1 / NIP1 | Affinity Capture-MS | Collins SR (2007) |
| NIP1 | NIP1 / RLI1 | Affinity Capture-MS | Gavin AC (2006) |
| NIP1 | RLI1 / NIP1 | Affinity Capture-MS | Krogan NJ (2004) |
| NMD2 | RLI1 / NMD2 | Phenotypic Suppression | Wilmes GM (2008) |
| NOP12 | RLI1 / NOP12 | Phenotypic Enhancement | Wilmes GM (2008) |
| NOP16 | RLI1 / NOP16 | Phenotypic Enhancement | Wilmes GM (2008) |
| NOP6 | NOP6 / RLI1 | Affinity Capture-MS | Ho Y (2002) |
| NOP6 | RLI1 / NOP6 | Phenotypic Suppression | Wilmes GM (2008) |
| NPL3 | NPL3 / RLI1 | Phenotypic Suppression | Wilmes GM (2008) |
| NUP170 | NUP170 / RLI1 | Phenotypic Suppression | Wilmes GM (2008) |
| NVJ1 | NVJ1 / RLI1 | Two-hybrid | Miller JP (2005) |
| PHO23 | PHO23 / RLI1 | Phenotypic Suppression | Wilmes GM (2008) |
| REX2 | REX2 / RLI1 | Phenotypic Enhancement | Wilmes GM (2008) |
| REX4 | REX4 / RLI1 | Phenotypic Enhancement | Wilmes GM (2008) |
| RIT1 | RIT1 / RLI1 | Phenotypic Suppression | Wilmes GM (2008) |
| RLI1 | RLI1 / RLI1 | Affinity Capture-MS | Krogan NJ (2004) |
| RPA34 | RPA34 / RLI1 | Phenotypic Suppression | Wilmes GM (2008) |
| RPG1 | RPG1 / RLI1 | Affinity Capture-MS | Collins SR (2007) |
| RPG1 | RPG1 / RLI1 | Affinity Capture-MS | Gavin AC (2002) |
| RPG1 | RPG1 / RLI1 | Affinity Capture-MS | Gavin AC (2006) |
| RPL10 | RLI1 / RPL10 | Affinity Capture-MS | Kispal G (2005) |
| RPL12A | RLI1 / RPL12A | Affinity Capture-MS | Gavin AC (2006) |
| RPL13A | RLI1 / RPL13A | Affinity Capture-MS | Kispal G (2005) |
| RPL13B | RLI1 / RPL13B | Affinity Capture-MS | Kispal G (2005) |
| RPL16A | RLI1 / RPL16A | Affinity Capture-MS | Kispal G (2005) |
| RPL1A | RLI1 / RPL1A | Affinity Capture-MS | Gavin AC (2006) |
| RPL2B | RLI1 / RPL2B | Affinity Capture-MS | Kispal G (2005) |
| RPL3 | RLI1 / RPL3 | Affinity Capture-MS | Kispal G (2005) |
| RPL4A | RLI1 / RPL4A | Affinity Capture-MS | Kispal G (2005) |
| RPL4B | RLI1 / RPL4B | Affinity Capture-MS | Kispal G (2005) |
| RPL7A | RLI1 / RPL7A | Affinity Capture-MS | Gavin AC (2006) |
| RPL7A | RLI1 / RPL7A | Affinity Capture-MS | Kispal G (2005) |
| RPL7B | RLI1 / RPL7B | Affinity Capture-MS | Kispal G (2005) |
| RPL8B | RLI1 / RPL8B | Affinity Capture-MS | Gavin AC (2006) |
| RPL8B | RLI1 / RPL8B | Affinity Capture-MS | Kispal G (2005) |
| RPP0 | RLI1 / RPP0 | Affinity Capture-MS | Krogan NJ (2004) |
| RPP1B | RLI1 / RPP1B | Affinity Capture-MS | Krogan NJ (2006) |
| RPS16B | RLI1 / RPS16B | Affinity Capture-MS | Kispal G (2005) |
| RPS17A | RLI1 / RPS17A | Affinity Capture-MS | Gavin AC (2006) |
| RPS17A | RLI1 / RPS17A | Affinity Capture-MS | Kispal G (2005) |
| RPS1A | RLI1 / RPS1A | Affinity Capture-MS | Kispal G (2005) |
| RPS1B | RLI1 / RPS1B | Affinity Capture-MS | Gavin AC (2006) |
| RPS1B | RLI1 / RPS1B | Affinity Capture-MS | Kispal G (2005) |
| RPS22B | RLI1 / RPS22B | Affinity Capture-MS | Gavin AC (2006) |
| RPS4A | RLI1 / RPS4A | Affinity Capture-MS | Kispal G (2005) |
| RPS4B | RLI1 / RPS4B | Affinity Capture-MS | Kispal G (2005) |
| RPS7A | RLI1 / RPS7A | Affinity Capture-MS | Collins SR (2007) |
| RPS7A | RLI1 / RPS7A | Affinity Capture-MS | Gavin AC (2006) |
| RPS8A | RLI1 / RPS8A | Affinity Capture-MS | Kispal G (2005) |
| RPS8B | RLI1 / RPS8B | Affinity Capture-MS | Kispal G (2005) |
| SLS1 | RLI1 / SLS1 | Phenotypic Suppression | Wilmes GM (2008) |
| SLX9 | SLX9 / RLI1 | Phenotypic Suppression | Wilmes GM (2008) |
| SOH1 | SOH1 / RLI1 | Phenotypic Suppression | Wilmes GM (2008) |
| SPT2 | SPT2 / RLI1 | Affinity Capture-MS | Ho Y (2002) |
| SPT5 | SPT5 / RLI1 | Affinity Capture-MS | Lindstrom DL (2003) |
| STM1 | RLI1 / STM1 | Affinity Capture-MS | Krogan NJ (2006) |
| SUP35 | SUP35 / RLI1 | Phenotypic Enhancement | Wilmes GM (2008) |
| SXM1 | SXM1 / RLI1 | Phenotypic Suppression | Wilmes GM (2008) |
| TEF4 | TEF4 / RLI1 | Phenotypic Enhancement | Wilmes GM (2008) |
| TGS1 | TGS1 / RLI1 | Phenotypic Suppression | Wilmes GM (2008) |
| TIF1 | RLI1 / TIF1 | Phenotypic Suppression | Wilmes GM (2008) |
| TIF34 | RLI1 / TIF34 | Affinity Capture-MS | Collins SR (2007) |
| TIF35 | TIF35 / RLI1 | Affinity Capture-MS | Gavin AC (2006) |
| TIF5 | RLI1 / TIF5 | Affinity Capture-MS | Collins SR (2007) |
| TIF5 | TIF5 / RLI1 | Affinity Capture-MS | Gavin AC (2002) |
| TIF5 | TIF5 / RLI1 | Affinity Capture-MS | Gavin AC (2006) |
| TRM1 | TRM1 / RLI1 | Phenotypic Enhancement | Wilmes GM (2008) |
| UPF3 | RLI1 / UPF3 | Phenotypic Suppression | Wilmes GM (2008) |
| VPS71 | VPS71 / RLI1 | Phenotypic Enhancement | Wilmes GM (2008) |
| YAE1 | RLI1 / YAE1 | Affinity Capture-MS | Krogan NJ (2006) |
| YCK1 | YCK1 / RLI1 | Biochemical Activity | Ptacek J (2005) |
Selected Publications
[
] Gene-related publications indexed at PubMed
- [
] Collins SR, et al. (2007) "Toward a comprehensive atlas of the physical interactome of Saccharomyces cerevisiae." Mol Cell Proteomics. 6(3):439-450. PMID:17200106 - [
] Gavin AC, et al. (2006) "Proteome survey reveals modularity of the yeast cell machinery." Nature. 440(7084):631-636. PMID:16429126 - [
] Krogan NJ, et al. (2006) "Global landscape of protein complexes in the yeast Saccharomyces cerevisiae." Nature. 440(7084):637-643. PMID:16554755 - [
] Kispal G, et al. (2005) "Biogenesis of cytosolic ribosomes requires the essential iron-sulphur protein Rli1p and mitochondria." EMBO J. 24(3):589-598. PMID:15660134 - [
] Yarunin A, et al. (2005) "Functional link between ribosome formation and biogenesis of iron-sulfur proteins." EMBO J. 24(3):580-588. PMID:15660135 - [
] Miller JP, et al. (2005) "Large-scale identification of yeast integral membrane protein interactions." Proc Natl Acad Sci U S A. 102(34):12123-12128. PMID:16093310 - [
] Ptacek J, et al. (2005) "Global analysis of protein phosphorylation in yeast." Nature. 438(7068):679-684. PMID:16319894 - [
] Krogan NJ, et al. (2004) "High-definition macromolecular composition of yeast RNA-processing complexes." Mol Cell. 13(2):225-239. PMID:14759368 - [
] Dong J, et al. (2004) "The essential ATP-binding cassette protein RLI1 functions in translation by promoting preinitiation complex assembly." J Biol Chem. 279(40):42157-42168. PMID:15277527 - [
] Lindstrom DL, et al. (2003) "Dual roles for Spt5 in pre-mRNA processing and transcription elongation revealed by identification of Spt5-associated proteins." Mol Cell Biol. 23(4):1368-1378. PMID:12556496 - [
] Huh WK, et al. (2003) "Global analysis of protein localization in budding yeast." Nature. 425(6959):686-691. PMID:14562095 - [
] Gavin AC, et al. (2002) "Functional organization of the yeast proteome by systematic analysis of protein complexes." Nature. 415(6868):141-147. PMID:11805826 - [
] Ho Y, et al. (2002) "Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry." Nature. 415(6868):180-183. PMID:11805837 - [
] Ito T, et al. (2001) "A comprehensive two-hybrid analysis to explore the yeast protein interactome." Proc Natl Acad Sci U S A. 98(8):4569-4574. PMID:11283351 - [
] Jacq C, et al. (1997) "The nucleotide sequence of Saccharomyces cerevisiae chromosome IV." Nature. 387(6632 Suppl):75-78. PMID:9169867 - [
] Goffeau A, et al. (1996) "Life with 6000 genes." Science. 274(5287):546, 563-546, 567. PMID:8849441
Defining protein complexes is critical to virtually all aspects of cell biology. Two recent affinity purification/mass spectrometry studies in Saccharomyces cerevisiae have vastly increased the available protein interaction data. The practical utility of such high throughput interaction sets, however, is substantially decreased by the presence of false positives. Here we created a novel probabilistic metric that takes advantage of the high density of these data, including both the presence and absence of individual associations, to provide a measure of the relative confidence of each potential protein-protein interaction. This analysis largely overcomes the noise inherent in high throughput immunoprecipitation experiments. For example, of the 12,122 binary interactions in the general repository of interaction data (BioGRID) derived from these two studies, we marked 7504 as being of substantially lower confidence. Additionally, applying our metric and a stringent cutoff we identified a set of 9074 interactions (including 4456 that were not among the 12,122 interactions) with accuracy comparable to that of conventional small scale methodologies. Finally we organized proteins into coherent multisubunit complexes using hierarchical clustering. This work thus provides a highly accurate physical interaction map of yeast in a format that is readily accessible to the biological community.
Protein complexes are key molecular entities that integrate multiple gene products to perform cellular functions. Here we report the first genome-wide screen for complexes in an organism, budding yeast, using affinity purification and mass spectrometry. Through systematic tagging of open reading frames (ORFs), the majority of complexes were purified several times, suggesting screen saturation. The richness of the data set enabled a de novo characterization of the composition and organization of the cellular machinery. The ensemble of cellular proteins partitions into 491 complexes, of which 257 are novel, that differentially combine with additional attachment proteins or protein modules to enable a diversification of potential functions. Support for this modular organization of the proteome comes from integration with available data on expression, localization, function, evolutionary conservation, protein structure and binary interactions. This study provides the largest collection of physically determined eukaryotic cellular machines so far and a platform for biological data integration and modelling.
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.
Mitochondria perform a central function in the biogenesis of cellular iron-sulphur (Fe/S) proteins. It is unknown to date why this biosynthetic pathway is indispensable for life, the more so as no essential mitochondrial Fe/S proteins are known. Here, we show that the soluble ATP-binding cassette (ABC) protein Rli1p carries N-terminal Fe/S clusters that require the mitochondrial and cytosolic Fe/S protein biogenesis machineries for assembly. Mutations in critical cysteine residues of Rli1p abolish association with Fe/S clusters and lead to loss of cell viability. Hence, the essential character of Fe/S clusters in Rli1p explains the indispensable character of mitochondria in eukaryotes. We further report that Rli1p is associated with ribosomes and with Hcr1p, a protein involved in rRNA processing and translation initiation. Depletion of Rli1p causes a nuclear export defect of the small and large ribosomal subunits and subsequently a translational arrest. Thus, ribosome biogenesis and function are intimately linked to the crucial role of mitochondria in the maturation of the essential Fe/S protein Rli1p.
In genetic screens for ribosomal export mutants, we identified CFD1, NBP35 and NAR1 as factors involved in ribosome biogenesis. Notably, these components were recently reported to function in extramitochondrial iron-sulfur (Fe-S) cluster biosynthesis. In particular, Nar1 was implicated to generate the Fe-S clusters within Rli1, a potential substrate protein of unknown function. We tested whether the Fe-S protein Rli1 functions in ribosome formation. We report that rli1 mutants are impaired in pre-rRNA processing and defective in the export of both ribosomal subunits. In addition, Rli1p is associated with both pre-40S particles and mature 40S subunits, and with the eIF3 translation initiation factor complex. Our data reveal an unexpected link between ribosome biogenesis and the biosynthetic pathway of cytoplasmic Fe-S proteins.
We carried out a large-scale screen to identify interactions between integral membrane proteins of Saccharomyces cerevisiae by using a modified split-ubiquitin technique. Among 705 proteins annotated as integral membrane, we identified 1,985 putative interactions involving 536 proteins. To ascribe confidence levels to the interactions, we used a support vector machine algorithm to classify interactions based on the assay results and protein data derived from the literature. Previously identified and computationally supported interactions were used to train the support vector machine, which identified 131 interactions of highest confidence, 209 of the next highest confidence, 468 of the next highest, and the remaining 1,085 of low confidence. This study provides numerous putative interactions among a class of proteins that have been difficult to analyze on a high-throughput basis by other approaches. The results identify potential previously undescribed components of established biological processes and roles for integral membrane proteins of ascribed functions.
Protein phosphorylation is estimated to affect 30% of the proteome and is a major regulatory mechanism that controls many basic cellular processes. Until recently, our biochemical understanding of protein phosphorylation on a global scale has been extremely limited; only one half of the yeast kinases have known in vivo substrates and the phosphorylating kinase is known for less than 160 phosphoproteins. Here we describe, with the use of proteome chip technology, the in vitro substrates recognized by most yeast protein kinases: we identified over 4,000 phosphorylation events involving 1,325 different proteins. These substrates represent a broad spectrum of different biochemical functions and cellular roles. Distinct sets of substrates were recognized by each protein kinase, including closely related kinases of the protein kinase A family and four cyclin-dependent kinases that vary only in their cyclin subunits. Although many substrates reside in the same cellular compartment or belong to the same functional category as their phosphorylating kinase, many others do not, indicating possible new roles for several kinases. Furthermore, integration of the phosphorylation results with protein-protein interaction and transcription factor binding data revealed novel regulatory modules. Our phosphorylation results have been assembled into a first-generation phosphorylation map for yeast. Because many yeast proteins and pathways are conserved, these results will provide insights into the mechanisms and roles of protein phosphorylation in many eukaryotes.
A remarkably large collection of evolutionarily conserved proteins has been implicated in processing of noncoding RNAs and biogenesis of ribonucleoproteins. To better define the physical and functional relationships among these proteins and their cognate RNAs, we performed 165 highly stringent affinity purifications of known or predicted RNA-related proteins from Saccharomyces cerevisiae. We systematically identified and estimated the relative abundance of stably associated polypeptides and RNA species using a combination of gel densitometry, protein mass spectrometry, and oligonucleotide microarray hybridization. Ninety-two discrete proteins or protein complexes were identified comprising 489 different polypeptides, many associated with one or more specific RNA molecules. Some of the pre-rRNA-processing complexes that were obtained are discrete sub-complexes of those previously described. Among these, we identified the IPI complex required for proper processing of the ITS2 region of the ribosomal RNA primary transcript. This study provides a high-resolution overview of the modular topology of noncoding RNA-processing machinery.
RLI1 is an essential yeast protein closely related in sequence to two soluble members of the ATP-binding cassette family of proteins that interact with ribosomes and function in translation elongation (YEF3) or translational control (GCN20). We show that affinity-tagged RLI1 co-purifies with eukaryotic translation initiation factor 3 (eIF3), eIF5, and eIF2, but not with other translation initiation factors or with translation elongation or termination factors. RLI1 is associated with 40 S ribosomal subunits in vivo, but it can interact with eIF3 and -5 independently of ribosomes. Depletion of RLI1 in vivo leads to cessation of growth, a lower polysome content, and decreased average polysome size. There was also a marked reduction in 40 S-bound eIF2 and eIF1, consistent with an important role for RLI1 in assembly of 43 S preinitiation complexes in vivo. Mutations of conserved residues in RLI1 expected to function in ATP hydrolysis were lethal. A mutation in the second ATP-binding cassette domain of RLI1 had a dominant negative phenotype, decreasing the rate of translation initiation in vivo, and the mutant protein inhibited translation of a luciferase mRNA reporter in wild-type cell extracts. These findings are consistent with a direct role for the ATP-binding cassettes of RLI1 in translation initiation. RLI1-depleted cells exhibit a deficit in free 60 S ribosomal subunits, and RLI1-green fluorescent protein was found in both the nucleus and cytoplasm of living cells. Thus, RLI1 may have dual functions in translation initiation and ribosome biogenesis.
During transcription elongation, eukaryotic RNA polymerase II (Pol II) must contend with the barrier presented by nucleosomes. The conserved Spt4-Spt5 complex has been proposed to regulate elongation through nucleosomes by Pol II. To help define the mechanism of Spt5 function, we have characterized proteins that coimmunopurify with Spt5. Among these are the general elongation factors TFIIF and TFIIS as well as Spt6 and FACT, factors thought to regulate elongation through nucleosomes. Spt5 also coimmunopurified with the mRNA capping enzyme and cap methyltransferase, and spt4 and spt5 mutations displayed genetic interactions with mutations in capping enzyme genes. Additionally, we found that spt4 and spt5 mutations lead to accumulation of unspliced pre-mRNA. Spt5 also copurified with several previously unstudied proteins; we demonstrate that one of these is encoded by a new member of the SPT gene family. Finally, by immunoprecipitating these factors we found evidence that Spt5 participates in at least three Pol II complexes. These observations provide new evidence of roles for Spt4-Spt5 in pre-mRNA processing and transcription elongation.
A fundamental goal of cell biology is to define the functions of proteins in the context of compartments that organize them in the cellular environment. Here we describe the construction and analysis of a collection of yeast strains expressing full-length, chromosomally tagged green fluorescent protein fusion proteins. We classify these proteins, representing 75% of the yeast proteome, into 22 distinct subcellular localization categories, and provide localization information for 70% of previously unlocalized proteins. Analysis of this high-resolution, high-coverage localization data set in the context of transcriptional, genetic, and protein-protein interaction data helps reveal the logic of transcriptional co-regulation, and provides a comprehensive view of interactions within and between organelles in eukaryotic cells.
Most cellular processes are carried out by multiprotein complexes. The identification and analysis of their components provides insight into how the ensemble of expressed proteins (proteome) is organized into functional units. We used tandem-affinity purification (TAP) and mass spectrometry in a large-scale approach to characterize multiprotein complexes in Saccharomyces cerevisiae. We processed 1,739 genes, including 1,143 human orthologues of relevance to human biology, and purified 589 protein assemblies. Bioinformatic analysis of these assemblies defined 232 distinct multiprotein complexes and proposed new cellular roles for 344 proteins, including 231 proteins with no previous functional annotation. Comparison of yeast and human complexes showed that conservation across species extends from single proteins to their molecular environment. Our analysis provides an outline of the eukaryotic proteome as a network of protein complexes at a level of organization beyond binary interactions. This higher-order map contains fundamental biological information and offers the context for a more reasoned and informed approach to drug discovery.
The recent abundance of genome sequence data has brought an urgent need for systematic proteomics to decipher the encoded protein networks that dictate cellular function. To date, generation of large-scale protein-protein interaction maps has relied on the yeast two-hybrid system, which detects binary interactions through activation of reporter gene expression. With the advent of ultrasensitive mass spectrometric protein identification methods, it is feasible to identify directly protein complexes on a proteome-wide scale. Here we report, using the budding yeast Saccharomyces cerevisiae as a test case, an example of this approach, which we term high-throughput mass spectrometric protein complex identification (HMS-PCI). Beginning with 10% of predicted yeast proteins as baits, we detected 3,617 associated proteins covering 25% of the yeast proteome. Numerous protein complexes were identified, including many new interactions in various signalling pathways and in the DNA damage response. Comparison of the HMS-PCI data set with interactions reported in the literature revealed an average threefold higher success rate in detection of known complexes compared with large-scale two-hybrid studies. Given the high degree of connectivity observed in this study, even partial HMS-PCI coverage of complex proteomes, including that of humans, should allow comprehensive identification of cellular networks.
Protein-protein interactions play crucial roles in the execution of various biological functions. Accordingly, their comprehensive description would contribute considerably to the functional interpretation of fully sequenced genomes, which are flooded with novel genes of unpredictable functions. We previously developed a system to examine two-hybrid interactions in all possible combinations between the approximately 6,000 proteins of the budding yeast Saccharomyces cerevisiae. Here we have completed the comprehensive analysis using this system to identify 4,549 two-hybrid interactions among 3,278 proteins. Unexpectedly, these data do not largely overlap with those obtained by the other project [Uetz, P., et al. (2000) Nature (London) 403, 623-627] and hence have substantially expanded our knowledge on the protein interaction space or interactome of the yeast. Cumulative connection of these binary interactions generates a single huge network linking the vast majority of the proteins. Bioinformatics-aided selection of biologically relevant interactions highlights various intriguing subnetworks. They include, for instance, the one that had successfully foreseen the involvement of a novel protein in spindle pole body function as well as the one that may uncover a hitherto unidentified multiprotein complex potentially participating in the process of vesicular transport. Our data would thus significantly expand and improve the protein interaction map for the exploration of genome functions that eventually leads to thorough understanding of the cell as a molecular system.
The complete DNA sequence of the yeast Saccharomyces cerevisiae chromosome IV has been determined. Apart from chromosome XII, which contains the 1-2 Mb rDNA cluster, chromosome IV is the longest S. cerevisiae chromosome. It was split into three parts, which were sequenced by a consortium from the European Community, the Sanger Centre, and groups from St Louis and Stanford in the United States. The sequence of 1,531,974 base pairs contains 796 predicted or known genes, 318 (39.9%) of which have been previously identified. Of the 478 new genes, 225 (28.3%) are homologous to previously identified genes and 253 (32%) have unknown functions or correspond to spurious open reading frames (ORFs). On average there is one gene approximately every two kilobases. Superimposed on alternating regional variations in G+C composition, there is a large central domain with a lower G+C content that contains all the yeast transposon (Ty) elements and most of the tRNA genes. Chromosome IV shares with chromosomes II, V, XII, XIII and XV some long clustered duplications which partly explain its origin.
The genome of the yeast Saccharomyces cerevisiae has been completely sequenced through a worldwide collaboration. The sequence of 12,068 kilobases defines 5885 potential protein-encoding genes, approximately 140 genes specifying ribosomal RNA, 40 genes for small nuclear RNA molecules, and 275 transfer RNA genes. In addition, the complete sequence provides information about the higher order organization of yeast's 16 chromosomes and allows some insight into their evolutionary history. The genome shows a considerable amount of apparent genetic redundancy, and one of the major problems to be tackled during the next stage of the yeast genome project is to elucidate the biological functions of all of these genes.