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At least 37 records · Page 2Linked to original sources
PubMed2006

Systematic mapping of genetic interactions in Caenorhabditis elegans identifies common modifiers of diverse signaling pathways.

Most heritable traits, including disease susceptibility, are affected by interactions between multiple genes. However, we understand little about how genes interact because very few possible genetic interactions have been explored experimentally. We have used RNA interference in Caenorhabditis elegans to systematically test approximately 65,000 pairs of genes for their ability to interact genetically. We identify approximately 350 genetic interactions between genes functioning in signaling pathways that are mutated in human diseases, including components of the EGF/Ras, Notch and Wnt pathways. Most notably, we identify a class of highly connected 'hub' genes: inactivation of these genes can enhance the phenotypic consequences of mutation of many different genes. These hub genes all encode chromatin regulators, and their activity as genetic hubs seems to be conserved across animals. We propose that these genes function as general buffers of genetic variation and that these hub genes may act as modifier genes in multiple, mechanistically unrelated genetic diseases in humans.

Animals↗
PubMed2006

Genome-wide prediction of genetic interactions in a metazoan.

Genetic interactions provide information about genes and processes with overlapping functions in biological systems. For Saccharomyces cerevisiae, computational integration of multiple types of functional genomic data is used to generate genome-wide predictions of genetic interactions. However, this methodology cannot be applied to the vastly more complex genome of metazoans, and only recently has the first metazoan genome-wide prediction of genetic interactions been reported. The prediction for Caenorhabditis elegans was generated by computationally integrating functional genomic data from S. cerevisiae, C. elegans and Drosophila melanogaster. This achievement is an important step toward system-level understanding of biological systems and human diseases.

Animals↗
PubMed2007

dSLAM analysis of genome-wide genetic interactions in Saccharomyces cerevisiae.

Analysis of genetic interactions has been extensively exploited to study gene functions and to dissect pathway structures. One such genetic interaction is synthetic lethality, in which the combination of two non-lethal mutations leads to loss of organism viability. We have developed a dSLAM (heterozygote diploid-based synthetic lethality analysis with microarrays) technology that effectively studies synthetic lethality interactions on a genome-wide scale in the budding yeast Saccharomyces cerevisiae. Typically, a query mutation is introduced en masse into a population of approximately 6000 haploid-convertible heterozygote diploid Yeast Knockout (YKO) mutants via integrative transformation. Haploid pools of single and double mutants are freshly generated from the resultant heterozygote diploid double mutant pool after meiosis and haploid selection and studied for potential growth defects of each double mutant combination by microarray analysis of the "molecular barcodes" representing each YKO. This technology has been effectively adapted to study other types of genome-wide genetic interactions including gene-compound synthetic lethality, secondary mutation suppression, dosage-dependent synthetic lethality and suppression.

Base Sequence↗
PubMed2004

A preprocessing method for inferring genetic interaction from gene expression data using Boolean algorithm.

Unknown genetic regulation mechanisms are expected to be discovered by information technology using large amount of biological data especially for gene expression data. In this study, we propose a novel inferring method for genetic interactions that combines our original preprocessing method and the Boolean algorithm. First, the performance of our method was evaluated using artificial data. The results showed that our method was able to infer genetic interactions with high specificity (specificity=0.629). Then, using our method, the genetic interaction was inferred from the experimental time course data collected using microarray on 69 genes of cell cycle for Saccharomyces cerevisiae. Our method estimated about 80% of all genetic interactions in Kyoto Encyclopedia Genes and Genomes (KEGG) for these genes. Furthermore, our method was able to infer several other genetic interactions that are not included in KEGG but whose existence is supported by other biological reports.

Journal Article↗
PubMed2005

Navigating the chaperone network: an integrative map of physical and genetic interactions mediated by the hsp90 chaperone.

Physical, genetic, and chemical-genetic interactions centered on the conserved chaperone Hsp90 were mapped at high resolution in yeast using systematic proteomic and genomic methods. Physical interactions were identified using genome-wide two hybrid screens combined with large-scale affinity purification of Hsp90-containing protein complexes. Genetic interactions were uncovered using synthetic genetic array technology and by a microarray-based chemical-genetic screen of a set of about 4700 viable yeast gene deletion mutants for hypersensitivity to the Hsp90 inhibitor geldanamycin. An extended network, consisting of 198 putative physical interactions and 451 putative genetic and chemical-genetic interactions, was found to connect Hsp90 to cofactors and substrates involved in a wide range of cellular functions. Two novel Hsp90 cofactors, Tah1 (YCR060W) and Pih1 (YHR034C), were also identified. These cofactors interact physically and functionally with the conserved AAA(+)-type DNA helicases Rvb1/Rvb2, which are key components of several chromatin remodeling factors, thereby linking Hsp90 to epigenetic gene regulation.

Adenosine Triphosphatases↗
PubMed2005

Derivation of genetic interaction networks from quantitative phenotype data.

We have generalized the derivation of genetic-interaction networks from quantitative phenotype data. Familiar and unfamiliar modes of genetic interaction were identified and defined. A network was derived from agar-invasion phenotypes of mutant yeast. Mutations showed specific modes of genetic interaction with specific biological processes. Mutations formed cliques of significant mutual information in their large-scale patterns of genetic interaction. These local and global interaction patterns reflect the effects of gene perturbations on biological processes and pathways.

Genes, Fungal↗
PubMed2004

Genetic interactions between Brca1 and Gadd45a in centrosome duplication, genetic stability, and neural tube closure.

GADD45a is a transcription target of the breast tumor suppressor gene BRCA. It was recently shown that mouse embryonic fibroblast cells carrying a targeted deletion of exon 11 of Brca1 (Brca1(Delta11/Delta11)) or a Gadd45A-null mutation (Gadd45a(-/-)) suffer centrosome amplification. To study genetic interactions between these genes during centrosome duplication, we generated Brca1(Delta11/Delta)(11)Gadd45a(-/-) mice by crossing each mutant. We found that all Brca1(Delta11/Delta11)Gadd45a(-/-) embryos at embryonic days 9.5-10.5 were exencephalic and exhibited a high incidence of apoptosis accompanied by altered levels of BAX, BCL-2, and p53. The trigger for these events is likely the genetic instability arising from centrosome amplification that is associated, at least in part, with decreased expression of the NIMA-related kinase NEK2. We demonstrate that small interfering RNA-mediated suppression of Brca1 decreased Nek2 more dramatically in Gadd45a(-/-) cells than in wild-type cells and, conversely, that overexpression of Brca1 and/or Gadd45a up-regulated transcription of Nek2. Furthermore, we show that overexpression of Nek2 in Brca1-specific small interfering RNA-treated wild-type and Gadd45a(-/-) cells repressed abnormal centrosome amplification. These observations suggest that NEK2 plays a role in mediating the actions of BRCA1 and GADD45a in regulating centrosome duplication and in maintaining genetic stability.

Animals↗
PubMed1996

Polygenic mutation in Drosophila melanogaster: genetic interactions between selection lines and candidate quantitative trait loci.

We have investigated genetic interactions between spontaneous mutations affecting abdominal and sternopleural bristle number that have accumulated in 12 long-term selection lines derived from an inbred strain, and mutations at 14 candidate bristle number quantitative trait loci. The quantitative test for complementation was to cross the selection lines to an inbred wild-type strain (the control cross) and to a derivative of the control strain into which the mutant allele at the candidate locus to be tested was substituted (the tester strain). Genetic interactions between spontaneous mutations affecting bristle number and the candidate locus mutations were common, and in several cases the interaction effects were different in males and females. Analyses of variance of the (tester- control) differences among and within groups of replicate lines selected in the same direction for the same trait showed significant group effects for several candidate loci. Genetically, the interactions could be caused by allelism of, and/ or epistasis between, spontaneous mutations in the selection lines and the candidate locus mutations. It is possible that much of the response to selection was from new mutations at candidate bristle number quantitative trait loci, and that for some of these loci, mutation rates were high.

Analysis of Variance↗
PubMed2006

Heart defects in X-linked heterotaxy: evidence for a genetic interaction of Zic3 with the nodal signaling pathway.

The complex cardiac defects that occur in heterotaxy result from abnormal left-right patterning. Mutations in the zinc finger transcription factor ZIC3 cause X-linked heterotaxy, HTX1. We previously have generated a targeted deletion of the murine Zic3 locus and demonstrated that these knockout mice correctly model HTX1. Fifty percent of Zic3 null embryos have cardiac looping anomalies at embryonic day 10.5 to 14.5, with ventral looping and sinistral looping as the predominant phenotypes. The penetrance of these phenotypes is increased in mice that are also haploinsufficient for Nodal. Zic3(+/-); Nodal (+/-) compound heterozygous mice are born in significantly reduced numbers (P=0.0001), indicating a genetic interaction between the loci. Furthermore, an upstream Nodal enhancer is responsive to Zic3 in both Xenopus and mouse. These studies provide evidence that Zic3 interacts genetically with Nodal in left-right patterning and subsequent cardiac development and delineate a critical Zic3-responsive enhancer required for mediating Nodal expression at the node.

Animals↗
PubMed2005

Genetic interaction among three genomic regions creates distinct contributions to early- and late-onset type 1 diabetes mellitus.

There are two peaks in the distribution of the age of onset of type 1 diabetes mellitus (T1DM)--the first in early childhood and the second at the time of puberty. Although T1DM results from the interaction of genetic and non-genetic factors, it has not been established which factors contribute to the bimodal distribution. The genetic component of T1DM is in large part related to genes from the human leukocyte antigen (HLA) complex (IDDM1); however, loci from the variable nucleotide tandem repeat (VNTR) region of the insulin (INS) gene (IDDM2) and more recently, the cytotoxic T-lymphocyte-associated protein-4 region (CTLA4, IDDM12) have also been implicated. Therefore, we examined the potential interaction between these loci through the influence of the age of onset of T1DM in diabetic and control Caucasian individuals. We discovered that younger individuals with HLA-DRB1*0301/DRB1*04 and INS I/I genotypes exhibited increased susceptibility to T1DM, whereas the interaction of INS I/I and CTLA4 G/G genotypes was more common in older children with T1DM. Combining the age of onset of T1DM with specific genotypes may operate to produce a single disease through different underlying causes.

Adolescent↗
PubMed2005

The synthetic genetic interaction spectrum of essential genes.

The nature of synthetic genetic interactions involving essential genes (those required for viability) has not been previously examined in a broad and unbiased manner. We crossed yeast strains carrying promoter-replacement alleles for more than half of all essential yeast genes to a panel of 30 different mutants with defects in diverse cellular processes. The resulting genetic network is biased toward interactions between functionally related genes, enabling identification of a previously uncharacterized essential gene (PGA1) required for specific functions of the endoplasmic reticulum. But there are also many interactions between genes with dissimilar functions, suggesting that individual essential genes are required for buffering many cellular processes. The most notable feature of the essential synthetic genetic network is that it has an interaction density five times that of nonessential synthetic genetic networks, indicating that most yeast genetic interactions involve at least one essential gene.

Gene Expression Regulation, Fungal↗
PubMed2006

Genetic interaction between Rb and N-ras: differentiation control and metastasis.

The retinoblastoma tumor suppressor gene, Rb, and the ras proto-oncogenes regulate various cellular processes, including differentiation and proliferation. Rb and ras genetically interact to positively influence differentiation in the mouse. This genetic interaction between Rb and ras also affects tumor development, either positively or negatively depending on cell type. Loss of one or two N-ras alleles allows medullary thyroid (C cell) adenomas occurring in Rb heterozygous mice to progress to metastatic carcinomas, an event associated with C cells displaying a less-differentiated phenotype. Here, we discuss the genetic interaction between Rb and ras and the development of a mouse model of medullary thyroid carcinoma.

Animals↗
PubMed2003

Genetic interaction of BBS1 mutations with alleles at other BBS loci can result in non-Mendelian Bardet-Biedl syndrome.

Bardet-Biedl syndrome is a genetically and clinically heterogeneous disorder caused by mutations in at least seven loci (BBS1-7), five of which are cloned (BBS1, BBS2, BBS4, BBS6, and BBS7). Genetic and mutational analyses have indicated that, in some families, a combination of three mutant alleles at two loci (triallelic inheritance) is necessary for pathogenesis. To date, four of the five known BBS loci have been implicated in this mode of oligogenic disease transmission. We present a comprehensive analysis of the spectrum, distribution, and involvement in non-Mendelian trait transmission of mutant alleles in BBS1, the most common BBS locus. Analyses of 259 independent families segregating a BBS phenotype indicate that BBS1 participates in complex inheritance and that, in different families, mutations in BBS1 can interact genetically with mutations at each of the other known BBS genes, as well as at unknown loci, to cause the phenotype. Consistent with this model, we identified homozygous M390R alleles, the most frequent BBS1 mutation, in asymptomatic individuals in two families. Moreover, our statistical analyses indicate that the prevalence of the M390R allele in the general population is consistent with an oligogenic rather than a recessive model of disease transmission. The distribution of BBS oligogenic alleles also indicates that all BBS loci might interact genetically with each other, but some genes, especially BBS2 and BBS6, are more likely to participate in triallelic inheritance, suggesting a variable ability of the BBS proteins to interact genetically with each other.

Alleles↗
PubMed2005

Genetic Interaction Motif Finding by expectation maximization--a novel statistical model for inferring gene modules from synthetic lethality.

BACKGROUND: Synthetic lethality experiments identify pairs of genes with complementary function. More direct functional associations (for example greater probability of membership in a single protein complex) may be inferred between genes that share synthetic lethal interaction partners than genes that are directly synthetic lethal. Probabilistic algorithms that identify gene modules based on motif discovery are highly appropriate for the analysis of synthetic lethal genetic interaction data and have great potential in integrative analysis of heterogeneous datasets. RESULTS: We have developed Genetic Interaction Motif Finding (GIMF), an algorithm for unsupervised motif discovery from synthetic lethal interaction data. Interaction motifs are characterized by position weight matrices and optimized through expectation maximization. Given a seed gene, GIMF performs a nonlinear transform on the input genetic interaction data and automatically assigns genes to the motif or non-motif category. We demonstrate the capacity to extract known and novel pathways for Saccharomyces cerevisiae (budding yeast). Annotations suggested for several uncharacterized genes are supported by recent experimental evidence. GIMF is efficient in computation, requires no training and automatically down-weights promiscuous genes with high degrees. CONCLUSION: GIMF effectively identifies pathways from synthetic lethality data with several unique features. It is mostly suitable for building gene modules around seed genes. Optimal choice of one single model parameter allows construction of gene networks with different levels of confidence. The impact of hub genes the generic probabilistic framework of GIMF may be used to group other types of biological entities such as proteins based on stochastic motifs. Analysis of the strongest motifs discovered by the algorithm indicates that synthetic lethal interactions are depleted between genes within a motif, suggesting that synthetic lethality occurs between-pathway rather than within-pathway.

Algorithms↗
PubMed2001

Genetic interactions between the 5' and 3' splice site consensus sequences and U6 snRNA during the second catalytic step of pre-mRNA splicing.

The YAG/ consensus sequence at the 3' end of introns (the slash indicates the location of the 3' splice site) is essential for catalysis of the second step of pre-mRNA splicing. Little is known about the interactions formed by these three nucleotides in the spliceosome. Although previous observations have suggested that the G of the YAG/ interacts with the first nucleotide of the /GUA consensus sequence at the 5' end of the intron, additional interactions have not been identified. Here we report several striking genetic interactions between A+3 of the 5' /GUA with Y-3 of the 3' YAG/ and G50 of the highly conserved ACAGAG motif in U6 snRNA. Two mutations in U6 G50 of the ACAGAG can weakly suppress two mutations in A+3 of the 5' /GUA. This suppression is significantly enhanced upon the inclusion of a specific mutation Y-3 in the 3' YAG/. RNA analysis confirmed that the severe splicing defect observed in A+3 and Y-3 double mutants can be rescued to near wild-type levels by the mutations in U6 G50. The contributions of each mutation to the genetic interaction and the strong position specificity of suppression, combined with previous findings, support a model in which the 5' /GUA and the GAG of U6 function in binding the 3' YAG/ during the second catalytic step.

Base Sequence↗
PubMed2006

Genome-wide prediction of C. elegans genetic interactions.

To obtain a global view of functional interactions among genes in a metazoan genome, we computationally integrated interactome data, gene expression data, phenotype data, and functional annotation data from three model organisms-Saccharomyces cerevisiae, Caenorhabditis elegans, and Drosophila melanogaster-and predicted genome-wide genetic interactions in C. elegans. The resulting genetic interaction network (consisting of 18,183 interactions) provides a framework for system-level understanding of gene functions. We experimentally tested the predicted interactions for two human disease-related genes and identified 14 new modifiers.

Algorithms↗
PubMed1962

Increased resistance to chloramphenicol in Rickettsia prowazekii with a note on failure to demonstrate genetic interaction among.

Weiss, Emilio (Naval Medical Research Institute, Bethesda, Md.) and Harry R. Dressler. Increased resistance to chloramphenicol in Rickettsia prowazekii with a note on failure to demonstrate genetic interaction among strains. J. Bacteriol. 83:409-414. 1962.-A further effort to produce genetically labeled Rickettsia prowazekii was made by serially passing the Madrid E strain in eggs in the presence of increasing concentrations of chloramphenicol. After 40 serial and 1 limit-dilution passages, a substrain, called C(r), was isolated, which appeared to be the result of a two-step change, each involving a twofold increase in resistance to the antibiotic. Chloramphenicol resistance was retained after 10 drugless egg passages. Cross-resistance to thiocymetin, but not to unrelated drugs, was shown. Several attempts were made to demonstrate genetic interaction, in eggs or entodermal cell cultures, among strains resistant to chloramphenicol, erythromycin, and p-aminobenzoic acid. They have not been successful.

4-Aminobenzoic Acid↗
PubMed1999

Analysis of background-dependent genetic interactions without inbred strains.

Experimental analysis of background dependent effects of genetic interactions can be designed using strains generated by introgression of small genetic regions containing identical genotypes at loci in question into different inbred strains. We use a novel multilocus paradigm, denoted conditional intergenic functional association (CIFA), to simulate this procedure, with the trade-off of power for convenience that is affordable when sufficiently strong effects are present. We analyze nine enzyme loci at three chromosomes in groups of D. melanogaster with different developmental rates that showed similar allelic frequencies at individual loci. Results obtained suggest the presence of adaptive interaction between particular alleles at two loci when genetic variation at seven background loci is eliminated. Biochemical considerations show that, in the resulting developmental context, strong interaction between these genes may emerge from shifted control of the pentose phosphate pathway, with cascading effects on the glycolysis, TCA cycle, and biosynthetic pathways: one gene may assume control of the irreversible rate-limiting step in the pentose phosphate pathway, whereas the other gene may assume control of the NADP+ level that regulates the same rate-limiting step as an electron acceptor. The newly developing functional genomics research and the absence of inbreeding make CIFA directly applicable to complex human traits in large samples.

Animals↗