ABSTRACT
Many mutations cause genetic disorders. However, two people inheriting the same mutation often have different severity of symptoms, and this is partly genetic. The effects of genetic background on mutant phenotypes are poorly understood, but predicting them is critical for personalized medicine. To study this phenomenon comprehensively and systematically, we used RNAi to compare loss-of-function phenotypes for â¼1,400 genes in two isolates of C. elegans and find that â¼20% of genes differ in the severity of phenotypes in these two genetic backgrounds. Crucially, this effect of genetic background on the severity of both RNAi and mutant phenotypes can be predicted from variation in the expression levels of the affected gene. This is also true in mammalian cells, suggesting it is a general property of genetic networks. We suggest that differences in the manifestation of mutant phenotypes between individuals are largely the result of natural variation in gene expression.
Subject(s)
Caenorhabditis elegans/genetics , Mutation , Animals , Caenorhabditis elegans/classification , Gene Knockdown Techniques , Genetic Variation , Phenotype , RNA InterferenceABSTRACT
Cellular processes often depend on stable physical associations between proteins. Despite recent progress, knowledge of the composition of human protein complexes remains limited. To close this gap, we applied an integrative global proteomic profiling approach, based on chromatographic separation of cultured human cell extracts into more than one thousand biochemical fractions that were subsequently analyzed by quantitative tandem mass spectrometry, to systematically identify a network of 13,993 high-confidence physical interactions among 3,006 stably associated soluble human proteins. Most of the 622 putative protein complexes we report are linked to core biological processes and encompass both candidate disease genes and unannotated proteins to inform on mechanism. Strikingly, whereas larger multiprotein assemblies tend to be more extensively annotated and evolutionarily conserved, human protein complexes with five or fewer subunits are far more likely to be functionally unannotated or restricted to vertebrates, suggesting more recent functional innovations.
Subject(s)
Multiprotein Complexes/analysis , Protein Interaction Maps , Proteins/chemistry , Proteomics/methods , Humans , Tandem Mass SpectrometryABSTRACT
Cytosine methylation of DNA CpG dinucleotides in gene promoters is an epigenetic modification that regulates gene transcription. While many methods exist to interrogate methylation states, few current methods offer large-scale, targeted, single CpG resolution. We report an approach combining bisulfite treatment followed by microdroplet PCR with next-generation sequencing to assay the methylation state of 50 genes in the regions 1 kb upstream of and downstream from their transcription start sites. This method yielded 96% coverage of the targeted CpGs and demonstrated high correlation between CpG island (CGI) DNA methylation and transcriptional regulation. The method was scaled to interrogate the methylation status of 77,674 CpGs in the promoter regions of 2100 genes in primary CD4 T cells. The 2100 gene library yielded 97% coverage of all targeted CpGs and 99% of the target amplicons.
Subject(s)
High-Throughput Nucleotide Sequencing/methods , Microchemistry/methods , Polymerase Chain Reaction/methods , Sequence Analysis, DNA/methods , Base Sequence , CpG Islands , DNA/chemistry , DNA/genetics , DNA Methylation , DNA Primers/chemistry , Epigenesis, Genetic , Humans , Jurkat Cells , Promoter Regions, Genetic , Sulfites/chemistryABSTRACT
The human protein interaction network will offer global insights into the molecular organization of cells and provide a framework for modeling human disease, but the network's large scale demands new approaches. We report a set of 7000 physical associations among human proteins inferred from indirect evidence: the comparison of human mRNA co-expression patterns with those of orthologous genes in five other eukaryotes, which we demonstrate identifies proteins in the same physical complexes. To evaluate the accuracy of the predicted physical associations, we apply quantitative mass spectrometry shotgun proteomics to measure elution profiles of 3013 human proteins during native biochemical fractionation, demonstrating systematically that putative interaction partners tend to co-sediment. We further validate uncharacterized proteins implicated by the associations in ribosome biogenesis, including WBSCR20C, associated with Williams-Beuren syndrome. This meta-analysis therefore exploits non-protein-based data, but successfully predicts associations, including 5589 novel human physical protein associations, with measured accuracies of 54+/-10%, comparable to direct large-scale interaction assays. The new associations' derivation from conserved in vivo phenomena argues strongly for their biological relevance.
Subject(s)
Gene Expression Profiling/methods , Protein Interaction Mapping , RNA, Messenger/metabolism , Animals , Chromosome Mapping , Cluster Analysis , Gene Expression , HeLa Cells , Humans , Mass Spectrometry/methods , Models, Biological , Models, Statistical , Proteins/chemistry , Proteomics/methods , Reproducibility of ResultsABSTRACT
BACKGROUND: Identifying all protein complexes in an organism is a major goal of systems biology. In the past 18 months, the results of two genome-scale tandem affinity purification-mass spectrometry (TAP-MS) assays in yeast have been published, along with corresponding complex maps. For most complexes, the published data sets were surprisingly uncorrelated. It is therefore useful to consider the raw data from each study and generate an accurate complex map from a high-confidence data set that integrates the results of these and earlier assays. RESULTS: Using an unsupervised probabilistic scoring scheme, we assigned a confidence score to each interaction in the matrix-model interpretation of the large-scale yeast mass-spectrometry data sets. The scoring metric proved more accurate than the filtering schemes used in the original data sets. We then took a high-confidence subset of these interactions and derived a set of complexes using MCL. The complexes show high correlation with existing annotations. Hierarchical organization of some protein complexes is evident from inter-complex interactions. CONCLUSION: We demonstrate that our scoring method can generate an integrated high-confidence subset of observed matrix-model interactions, which we subsequently used to derive an accurate map of yeast complexes. Our results indicate that essentiality is a product of the protein complex rather than the individual protein, and that we have achieved near saturation of the yeast high-abundance, rich-media-expressed "complex-ome."
Subject(s)
Genes, Fungal , Protein Interaction Mapping/methods , Saccharomyces cerevisiae Proteins/chemistry , Saccharomyces cerevisiae Proteins/metabolism , Saccharomyces cerevisiae/metabolism , Algorithms , Bayes Theorem , Cluster Analysis , Databases, Protein , Gene Expression Regulation, Fungal , Mass Spectrometry , Multiprotein Complexes , Proteome , ProteomicsABSTRACT
We have described a protocol for performing high-throughput immunofluorescence microscopy on microarrays of yeast cells. This approach employs immunostaining of spheroplasted yeast cells printed as high-density cell microarrays, followed by imaging using automated microscopy. A yeast spheroplast microarray can contain more than 5,000 printed spots, each containing cells from a given yeast strain, and is thus suitable for genome-wide screens focusing on single cell phenotypes, such as systematic localization or co-localization studies or genetic assays for genes affecting probed targets. We demonstrate the use of yeast spheroplast microarrays to probe microtubule and spindle defects across a collection of yeast strains harboring tetracycline-down-regulatable alleles of essential genes.
Subject(s)
High-Throughput Screening Assays/methods , Spheroplasts/genetics , Tissue Array Analysis/methods , Yeasts/genetics , Down-Regulation , Genes, Fungal , Microscopy, Fluorescence , Microtubules/metabolism , Spindle Apparatus/metabolism , Spindle Apparatus/pathology , Tetracycline/pharmacologyABSTRACT
In this study, we tested the NuGEN Ovation RNA-Seq System for library preparation followed by next-generation sequencing on an Illumina GAIIx. The cDNA product of the NuGEN kit may have significant amounts of ssDNA with hairpin structures that are generated during the amplification process. These structures interfere with efficient downstream end repair, A-tailing, and adapter ligation, all standard steps in post-amplification sequencing library construction. We were able to increase the efficiency of sequencing library yields 4- to 6-fold or greater by treatment of NuGEN-amplified cDNA product with the single-strand endonuclease S1. These results suggest that this treatment effectively cleaves hairpin structures generated during amplification that are resistant to the standard enzyme cocktails used for the end-repair step.
Subject(s)
RNA/genetics , Sequence Analysis, RNA/methods , CD4-Positive T-Lymphocytes/metabolism , DNA, Complementary/genetics , Gene Library , Humans , Polymerase Chain Reaction/methods , Sequence Analysis, RNA/economicsABSTRACT
Polarizing cells extensively restructure cellular components in a spatially and temporally coupled manner along the major axis of cellular extension. Budding yeast are a useful model of polarized growth, helping to define many molecular components of this conserved process. Besides budding, yeast cells also differentiate upon treatment with pheromone from the opposite mating type, forming a mating projection (the 'shmoo') by directional restructuring of the cytoskeleton, localized vesicular transport and overall reorganization of the cytosol. To characterize the proteomic localization changes accompanying polarized growth, we developed and implemented a novel cell microarray-based imaging assay for measuring the spatial redistribution of a large fraction of the yeast proteome, and applied this assay to identify proteins localized along the mating projection following pheromone treatment. We further trained a machine learning algorithm to refine the cell imaging screen, identifying additional shmoo-localized proteins. In all, we identified 74 proteins that specifically localize to the mating projection, including previously uncharacterized proteins (Ycr043c, Ydr348c, Yer071c, Ymr295c, and Yor304c-a) and known polarization complexes such as the exocyst. Functional analysis of these proteins, coupled with quantitative analysis of individual organelle movements during shmoo formation, suggests a model in which the basic machinery for cell polarization is generally conserved between processes forming the bud and the shmoo, with a distinct subset of proteins used only for shmoo formation. The net effect is a defined ordering of major organelles along the polarization axis, with specific proteins implicated at the proximal growth tip.
Subject(s)
Green Fluorescent Proteins/metabolism , Pheromones/metabolism , Proteomics/methods , Saccharomyces cerevisiae/physiology , Saccharomycetales/metabolism , Cell Polarity/genetics , Cytoskeleton/metabolism , Cytosol/metabolism , Fungal Proteins/chemistry , Microscopy, Fluorescence/methods , Models, Biological , Protein Array Analysis/methods , Protein Precursors/metabolism , Saccharomyces cerevisiae/metabolism , Saccharomyces cerevisiae Proteins/metabolismABSTRACT
We estimate the full yeast protein-protein interaction network to contain 37,800-75,500 interactions and the human network 154,000-369,000, but owing to a high false-positive rate, current maps are roughly only 50% and 10% complete, respectively. Paradoxically, releasing raw, unfiltered assay data might help separate true from false interactions.
Subject(s)
Protein Interaction Mapping , Saccharomyces cerevisiae Proteins/metabolism , Saccharomyces cerevisiae/metabolism , Databases, Protein , Humans , Protein BindingABSTRACT
We have developed spotted cell microarrays for measuring cellular phenotypes on a large scale. Collections of cells are printed, stained for subcellular features, then imaged via automated, high-throughput microscopy, allowing systematic phenotypic characterization. We used this technology to identify genes involved in the response of yeast to mating pheromone. Besides morphology assays, cell microarrays should be valuable for high-throughput in situ hybridization and immunoassays, enabling new classes of genetic assays based on cell imaging.