Widespread Expansion of Protein Interaction Capabilities by Alternative Splicing.

While alternative splicing is known to diversify the functional characteristics of some genes, the extent to which protein isoforms globally contribute to functional complexity on a proteomic scale remains unknown. To address this systematically, we cloned full-length open reading frames of alternatively spliced transcripts for a large number of human genes and used protein-protein interaction profiling to functionally compare hundreds of protein isoform pairs. The majority of isoform pairs share less than 50% of their interactions. In the global context of interactome network maps, alternative isoforms tend to behave like distinct proteins rather than minor variants of each other. Interaction partners specific to alternative isoforms tend to be expressed in a highly tissue-specific manner and belong to distinct functional modules. Our strategy, applicable to other functional characteristics, reveals a widespread expansion of protein interaction capabilities through alternative splicing and suggests that many alternative "isoforms" are functionally divergent (i.e., "functional alloforms").

A proteome-scale map of the human interactome network.

Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ?14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ?30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a "broader" human interactome network than currently appreciated. The map also uncovers significant interconnectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high-quality interactome models will help "connect the dots" of the genomic revolution.

Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins.

Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or 'passenger', cancer mutations from causal, or 'driver', mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer.

An inter-species protein-protein interaction network across vast evolutionary distance.

In cellular systems, biophysical interactions between macromolecules underlie a complex web of functional interactions. How biophysical and functional networks are coordinated, whether all biophysical interactions correspond to functional interactions, and how such biophysical-versus-functional network coordination is shaped by evolutionary forces are all largely unanswered questions. Here, we investigate these questions using an "inter-interactome" approach. We systematically probed the yeast and human proteomes for interactions between proteins from these two species and functionally characterized the resulting inter-interactome network. After a billion years of evolutionary divergence, the yeast and human proteomes are still capable of forming a biophysical network with properties that resemble those of intra-species networks. Although substantially reduced relative to intra-species networks, the levels of functional overlap in the yeast-human inter-interactome network uncover significant remnants of co-functionality widely preserved in the two proteomes beyond human-yeast homologs. Our data support evolutionary selection against biophysical interactions between proteins with little or no co-functionality. Such non-functional interactions, however, represent a reservoir from which nascent functional interactions may arise.

NOTCH2 and FLT3 gene mis-splicings are common events in patients with acute myeloid leukemia (AML): new potential targets in AML.

Our previous studies revealed an increase in alternative splicing of multiple RNAs in cells from patients with acute myeloid leukemia (AML) compared with CD34(+) bone marrow cells from normal donors. Aberrantly spliced genes included a number of oncogenes, tumor suppressor genes, and genes involved in regulation of apoptosis, cell cycle, and cell differentiation. Among the most commonly mis-spliced genes (>70% of AML patients) were 2, NOTCH2 and FLT3, that encode myeloid cell surface proteins. The splice variants of NOTCH2 and FLT3 resulted from complete or partial exon skipping and utilization of cryptic splice sites. Longitudinal analyses suggested that NOTCH2 and FLT3 aberrant splicing correlated with disease status. Correlation analyses between splice variants of these genes and clinical features of patients showed an association between NOTCH2-Va splice variant and overall survival of patients. Our results suggest that NOTCH2 and FLT3 mis-splicing is a common characteristic of AML and has the potential to generate transcripts encoding proteins with altered function. Thus, splice variants of these genes might provide disease markers and targets for novel therapeutics.

Network-based analysis of genome wide association data provides novel candidate genes for lipid and lipoprotein traits.

Genome wide association studies (GWAS) identify susceptibility loci for complex traits, but do not identify particular genes of interest. Integration of functional and network information may help in overcoming this limitation and identifying new susceptibility loci. Using GWAS and comorbidity data, we present a network-based approach to predict candidate genes for lipid and lipoprotein traits. We apply a prediction pipeline incorporating interactome, co-expression, and comorbidity data to Global Lipids Genetics Consortium (GLGC) GWAS for four traits of interest, identifying phenotypically coherent modules. These modules provide insights regarding gene involvement in complex phenotypes with multiple susceptibility alleles and low effect sizes. To experimentally test our predictions, we selected four candidate genes and genotyped representative SNPs in the Malmö Diet and Cancer Cardiovascular Cohort. We found significant associations with LDL-C and total-cholesterol levels for a synonymous SNP (rs234706) in the cystathionine beta-synthase (CBS) gene (p = 1 × 10(-5) and adjusted-p = 0.013, respectively). Further, liver samples taken from 206 patients revealed that patients with the minor allele of rs234706 had significant dysregulation of CBS (p = 0.04). Despite the known biological role of CBS in lipid metabolism, SNPs within the locus have not yet been identified in GWAS of lipoprotein traits. Thus, the GWAS-based Comorbidity Module (GCM) approach identifies candidate genes missed by GWAS studies, serving as a broadly applicable tool for the investigation of other complex disease phenotypes.

A genome-wide aberrant RNA splicing in patients with acute myeloid leukemia identifies novel potential disease markers and therapeutic targets.

PURPOSE: Despite new treatments, acute myeloid leukemia (AML) remains an incurable disease. More effective drug design requires an expanded view of the molecular complexity that underlies AML. Alternative splicing of RNA is used by normal cells to generate protein diversity. Growing evidence indicates that aberrant splicing of genes plays a key role in cancer. We investigated genome-wide splicing abnormalities in AML and based on these abnormalities, we aimed to identify novel potential biomarkers and therapeutic targets. EXPERIMENTAL DESIGN: We used genome-wide alternative splicing screening to investigate alternative splicing abnormalities in two independent AML patient cohorts [Dana-Farber Cancer Institute (DFCI) (Boston, MA) and University Hospital de Nantes (UHN) (Nantes, France)] and normal donors. Selected splicing events were confirmed through cloning and sequencing analysis, and than validated in 193 patients with AML. RESULTS: Our results show that approximately 29% of expressed genes genome-wide were differentially and recurrently spliced in patients with AML compared with normal donors bone marrow CD34(+) cells. Results were reproducible in two independent AML cohorts. In both cohorts, annotation analyses indicated similar proportions of differentially spliced genes encoding several oncogenes, tumor suppressor proteins, splicing factors, and heterogeneous-nuclear-ribonucleoproteins, proteins involved in apoptosis, cell proliferation, and spliceosome assembly. Our findings are consistent with reports for other malignances and indicate that AML-specific aberrations in splicing mechanisms are a hallmark of AML pathogenesis. CONCLUSIONS: Overall, our results suggest that aberrant splicing is a common characteristic for AML. Our findings also suggest that splice variant transcripts that are the result of splicing aberrations create novel disease markers and provide potential targets for small molecules or antibody therapeutics for this disease.

Independently evolved virulence effectors converge onto hubs in a plant immune system network.

Plants generate effective responses to infection by recognizing both conserved and variable pathogen-encoded molecules. Pathogens deploy virulence effector proteins into host cells, where they interact physically with host proteins to modulate defense. We generated an interaction network of plant-pathogen effectors from two pathogens spanning the eukaryote-eubacteria divergence, three classes of Arabidopsis immune system proteins, and ~8000 other Arabidopsis proteins. We noted convergence of effectors onto highly interconnected host proteins and indirect, rather than direct, connections between effectors and plant immune receptors. We demonstrated plant immune system functions for 15 of 17 tested host proteins that interact with effectors from both pathogens. Thus, pathogens from different kingdoms deploy independently evolved virulence proteins that interact with a limited set of highly connected cellular hubs to facilitate their diverse life-cycle strategies.