Synthetic lethal analysis of Caenorhabditis elegans posterior embryonic patterning genes identifies conserved genetic interactions

Mslar: Microbial synthetic lethal and rescue database

Synthetic lethality (SL) occurs when mutations in two genes together lead to cell or organism death, while a single mutation in either gene does not have a significant impact. This concept can also be extended to three or more genes for SL. Computational and experimental methods have been developed to predict and verify SL gene pairs, especially for yeast and Escherichia coli. However, there is currently a lack of a specialized platform to collect microbial SL gene pairs. Therefore, we designed a synthetic interaction database for microbial genetics that collects 13,313 SL and 2,994 Synthetic Rescue (SR) gene pairs that are reported in the literature, as well as 86,981 putative SL pairs got through homologous transfer method in 281 bacterial genomes. Our database website provides multiple functions such as search, browse, visualization, and Blast. Based on the SL interaction data in the S. cerevisiae, we review the issue of duplications' essentiality and observed that the duplicated genes and singletons have a similar ratio of being essential when we consider both individual and SL. The Microbial Synthetic Lethal and Rescue Database (Mslar) is expected to be a useful reference resource for researchers interested in the SL and SR genes of microorganisms. Mslar is open freely to everyone and available on the web at http://guolab.whu.edu.cn/Mslar/.

A Multiplex Gene Expression Assay for Direct Measurement of RNA Transcripts in Crude Lysates of the Nematode Caenorhabditis elegans Used as a Bioanalytical Tool

Gene expression profiling in Caenorhabditis elegans has been demonstrated to be a potential bioanalytical tool to detect the toxic potency of environmental contaminants. The RNA transcripts of genes responding to toxic exposure can be used as biomarkers for detecting these toxins. For routine application in environmental quality monitoring, an easy-to-use multiplex assay is required to reliably quantify expression levels of these biomarkers. In the present study, a bead-based assay was developed to fingerprint gene expression in C. elegans by quantitating messenger RNAs (mRNAs) of multiple target genes directly from crude nematode lysates, circumventing RNA extraction and purification steps. The assay uses signal amplification rather than target amplification for direct measurement of toxin-induced RNA transcripts. Using a 50-gene panel, the expression changes of four candidate reference genes and 46 target mRNAs for various contaminants and wastewaters were successfully measured, and the expression profiles indicated the type of toxin present. Moreover, the multiplex assay response was in line with previous results obtained with more time-consuming reverse-transcription quantitative polymerase chain reaction and microarray analyses. In addition, the transcriptomic profiles of nematodes exposed to wastewater samples and extracts prepared from tissues of swimming crabs were evaluated. The profiles indicated the presence of organic pollutants. The present study illustrates the successful development of a multiplex fluorescent bead-based approach using nematode C. elegans crude lysates for gene expression profiling of target RNAs. This method can be used to routinely fingerprint the presence of toxic contaminants in environmental samples and to identify the most biologically active fraction of the contaminant mixture in a toxicity identification and evaluation approach. Environ Toxicol Chem 2023;42:130-142. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

The anterior Hox gene ceh-13 and elt-1/GATA activate the posterior Hox genes nob-1 and php-3 to specify posterior lineages in the C. elegans embryo

Hox transcription factors play a conserved role in specifying positional identity during animal development, with posterior Hox genes typically repressing the expression of more anterior Hox genes. Here, we dissect the regulation of the posterior Hox genes nob-1 and php-3 in the nematode C. elegans. We show that nob-1 and php-3 are co-expressed in gastrulation-stage embryos in cells that previously expressed the anterior Hox gene ceh-13. This expression is controlled by several partially redundant transcriptional enhancers. These enhancers act in a ceh-13-dependant manner, providing a striking example of an anterior Hox gene positively regulating a posterior Hox gene. Several other regulators also act positively through nob-1/php-3 enhancers, including elt-1/GATA, ceh-20/ceh-40/Pbx, unc-62/Meis, pop-1/TCF, ceh-36/Otx, and unc-30/Pitx. We identified defects in both cell position and cell division patterns in ceh-13 and nob-1;php-3 mutants, suggesting that these factors regulate lineage identity in addition to positional identity. Together, our results highlight the complexity and flexibility of Hox gene regulation and function and the ability of developmental transcription factors to regulate different targets in different stages of development.

Genetic interaction analysis in microbial pathogens: unravelling networks of pathogenesis, antimicrobial susceptibility and host interactions

Genetic interaction (GI) analysis is a powerful genetic strategy that analyzes the fitness and phenotypes of single- and double-gene mutant cells in order to dissect the epistatic interactions between genes, categorize genes into biological pathways, and characterize genes of unknown function. GI analysis has been extensively employed in model organisms for foundational, systems-level assessment of the epistatic interactions between genes. More recently, GI analysis has been applied to microbial pathogens and has been instrumental for the study of clinically important infectious organisms. Here, we review recent advances in systems-level GI analysis of diverse microbial pathogens, including bacterial and fungal species. We focus on important applications of GI analysis across pathogens, including GI analysis as a means to decipher complex genetic networks regulating microbial virulence, antimicrobial drug resistance and host-pathogen dynamics, and GI analysis as an approach to uncover novel targets for combination antimicrobial therapeutics. Together, this review bridges our understanding of GI analysis and complex genetic networks, with applications to diverse microbial pathogens, to further our understanding of virulence, the use of antimicrobial therapeutics and host-pathogen interactions. .

The C. elegans embryonic transcriptome with tissue, time, and alternative splicing resolution

We have used RNA-seq in Caenorhabditis elegans to produce transcription profiles for seven specific embryonic cell populations from gastrulation to the onset of terminal differentiation. The expression data for these seven cell populations, covering major cell lineages and tissues in the worm, reveal the complex and dynamic changes in gene expression, both spatially and temporally. Also, within genes, start sites and exon usage can be highly differential, producing transcripts that are specific to developmental periods or cell lineages. We have also found evidence of novel exons and introns, as well as differential usage of SL1 and SL2 splice leaders. By combining this data set with the modERN ChIP-seq resource, we are able to support and predict gene regulatory relationships. The detailed information on differences and similarities between gene expression in cell lineages and tissues should be of great value to the community and provides a framework for the investigation of expression in individual cells.

Regulation of fiber-specific actin expression by the Drosophila SRF ortholog Blistered

Serum response factor (SRF) has an established role in controlling actin homeostasis in mammalian cells, yet its role in non-vertebrate muscle development has remained enigmatic. Here, we demonstrate that the single Drosophila SRF ortholog, termed Blistered (Bs), is expressed in all adult muscles, but Bs is required for muscle organization only in the adult indirect flight muscles. Bs is a direct activator of the flight muscle actin gene Act88F, via a conserved promoter-proximal binding site. However, Bs only activates Act88F expression in the context of the flight muscle regulatory program provided by the Pbx and Meis orthologs Extradenticle and Homothorax, and appears to function in a similar manner to mammalian SRF in muscle maturation. These studies place Bs in a regulatory framework where it functions to sustain the flight muscle phenotype in Drosophila Our studies uncover an evolutionarily ancient role for SRF in regulating muscle actin expression, and provide a model for how SRF might function to sustain muscle fate downstream of pioneer factors.

Use of genetic and chemical synthetic lethality as probes of complexity in bacterial cell systems

Different conditions and genomic contexts are known to have an impact on gene essentiality and interactions. Synthetic lethal interactions occur when a combination of perturbations, either genetic or chemical, result in a more profound fitness defect than expected based on the effect of each perturbation alone. Synthetic lethality in bacterial systems has long been studied; however, during the past decade, the emerging fields of genomics and chemical genomics have led to an increase in the scale and throughput of these studies. Here, we review the concepts of genomics and chemical genomics in the context of synthetic lethality and their revolutionary roles in uncovering novel biology such as the characterization of genes of unknown function and in antibacterial drug discovery. We provide an overview of the methodologies, examples and challenges of both genetic and chemical synthetic lethal screening platforms. Finally, we discuss how to apply genetic and chemical synthetic lethal approaches to rationalize the synergies of drugs, screen for new and improved antibacterial therapies and predict drug mechanism of action.

Regulation of C. elegans L4 cuticle collagen genes by the heterochronic protein LIN-29

The cuticle, the outer covering of the nematode C. elegans, is synthesized five times during the worm's life by the underlying hypodermis. Cuticle collagens, the major cuticle component, are encoded by a large family of col genes and, interestingly, many of these genes express predominantly at a single developmental stage. This temporal preference motivated us to investigate the mechanisms underlying col gene expression and here we focus on a subset of col genes expressed in the L4 stage. We identified minimal promoter regions of <300 bp for col-38, col-49, and col-63. In these regions, we predicted cis-regulatory sequences and evaluated their function in vivo via mutagenesis of a col-38p::yfp reporter. We used RNAi to study the requirement for candidate transcription regulators ELT-1 and ELT-3, LIN-29, and the LIN-29 co-factor MAB-10, and found LIN-29 to be necessary for the expression of four L4-specific genes (col-38, col-49, col-63, and col-138). Temporal misexpression of LIN-29 was also sufficient to activate these genes at a different developmental stage. The LIN-29 DNA-binding domain bound the col-38, col-49, and col-63 minimal promoters in vitro. For col-38 we showed that the LIN-29 sites necessary for reporter expression in vivo are also bound in vitro: this is the first identification of specific binding sites for LIN-29 necessary for in vivo target gene expression.

Synthetic Genetic Interaction (CRISPR-SGI) Profiling in Caenorhabditis elegans

Genetic interaction screens are a powerful methodology to establish novel roles for genes and elucidate functional connections between genes. Such studies have been performed to great effect in single-cell organisms such as yeast and E. coli (Schuldiner et al., 2005; Butland et al., 2008; Costanzo et al., 2010), but similar large-scale interaction studies using targeted reverse-genetic deletions in multi-cellular organisms have not been feasible. We developed a CRISPR/Cas9-based method for deleting genes in C. elegans and replacing them with a heterologous fluorescent reporter (Norris et al., 2015). Recently we took advantage of that system to perform a large-scale, reverse genetic screen using null alleles in animals for the first time, focusing on RNA binding protein genes (Norris et al., 2017). This type of approach should be similarly applicable to many other gene classes in C. elegans. Here we detail the protocols involved in generating a library of double mutants and performing medium-throughput competitive fitness assays to test for genetic interactions resulting in fitness changes.

Augmented reality for personalized nanomedicines

As our understanding of onset and progress of diseases at the genetic and molecular level rapidly progresses, the potential of advanced technologies, such as 3D-printing, Socially-Assistive Robots (SARs) or augmented reality (AR), that are applied to personalized nanomedicines (PNMs) to alleviate pathological conditions, has become more prominent. Among advanced technologies, AR in particular has the greatest potential to address those challenges and facilitate the translation of PNMs into formidable clinical application of personalized therapy. As AR is about to adapt additional new methods, such as speech, voice recognition, eye tracing and motion tracking, to enable interaction with host response or biological systems in 3-D space, a combination of multiple approaches to accommodate varying environmental conditions, such as public noise and atmosphere brightness, will be explored to improve its therapeutic outcomes in clinical applications. For instance, AR glasses still being developed by Facebook or Microsoft will serve as new platform that can provide people with the health information they are interested in or various measures through which they can interact with medical services. This review has addressed the current progress and impact of AR on PNMs and its application to the biomedical field. Special emphasis is placed on the application of AR based PNMs to the treatment strategies against senior care, drug addiction and medication adherence.

CRISPR-mediated genetic interaction profiling identifies RNA binding proteins controlling metazoan fitness

Genetic interaction screens have aided our understanding of complex genetic traits, diseases, and biological pathways. However, approaches for synthetic genetic analysis with null-alleles in metazoans have not been feasible. Here, we present a CRISPR/Cas9-based Synthetic Genetic Interaction (CRISPR-SGI) approach enabling systematic double-mutant generation. Applying this technique in Caenorhabditis elegans, we comprehensively screened interactions within a set of 14 conserved RNA binding protein genes, generating all possible single and double mutants. Many double mutants displayed fitness defects, revealing synthetic interactions. For one interaction between the MBNL1/2 ortholog mbl-1 and the ELAVL ortholog exc-7, double mutants displayed a severely shortened lifespan. Both genes are required for regulating hundreds of transcripts and isoforms, and both may play a critical role in lifespan extension through insulin signaling. Thus, CRISPR-SGI reveals a rich genetic interaction landscape between RNA binding proteins in maintaining organismal health, and will serve as a paradigm applicable to other biological questions.

A team of heterochromatin factors collaborates with small RNA pathways to combat repetitive elements and germline stress

Repetitive sequences derived from transposons make up a large fraction of eukaryotic genomes and must be silenced to protect genome integrity. Repetitive elements are often found in heterochromatin; however, the roles and interactions of heterochromatin proteins in repeat regulation are poorly understood. Here we show that a diverse set of C. elegans heterochromatin proteins act together with the piRNA and nuclear RNAi pathways to silence repetitive elements and prevent genotoxic stress in the germ line. Mutants in genes encoding HPL-2/HP1, LIN-13, LIN-61, LET-418/Mi-2, and H3K9me2 histone methyltransferase MET-2/SETDB1 also show functionally redundant sterility, increased germline apoptosis, DNA repair defects, and interactions with small RNA pathways. Remarkably, fertility of heterochromatin mutants could be partially restored by inhibiting cep-1/p53, endogenous meiotic double strand breaks, or the expression of MIRAGE1 DNA transposons. Functional redundancy among factors and pathways underlies the importance of safeguarding the genome through multiple means.

Genes and networks regulating root anatomy and architecture

The root is an excellent model for studying developmental processes that underlie plant anatomy and architecture. Its modular structure, the lack of cell movement and relative accessibility to microscopic visualization facilitate research in a number of areas of plant biology. In this review, we describe several examples that demonstrate how cell type-specific developmental mechanisms determine cell fate and the formation of defined tissues with unique characteristics. In the last 10 yr, advances in genome-wide technologies have led to the sequencing of thousands of plant genomes, transcriptomes and proteomes. In parallel with the development of these high-throughput technologies, biologists have had to establish computational, statistical and bioinformatic tools that can deal with the wealth of data generated by them. These resources provide a foundation for posing more complex questions about molecular interactions, and have led to the discovery of new mechanisms that control phenotypic differences. Here we review several recent studies that shed new light on developmental processes, which are involved in establishing root anatomy and architecture. We highlight the power of combining large-scale experiments with classical techniques to uncover new pathways in root development.

Developmental robustness in the Caenorhabditis elegans embryo

Developmental robustness is the ability of an embryo to develop normally despite many sources of variation, from differences in the environment to stochastic cell-to-cell differences in gene expression. The nematode Caenorhabditis elegans exhibits an additional level of robustness: Unlike most other animals, the embryonic pattern of cell divisions is nearly identical from animal to animal. The endoderm (gut) lineage is an ideal model for studying such robustness as the juvenile gut has a simple anatomy, consisting of 20 cells that are derived from a single cell, E, and the gene regulatory network that controls E specification shares features with developmental regulatory networks in many other systems, including genetic redundancy, parallel pathways, and feed-forward loops. Early studies were initially concerned with identifying the genes in the network, whereas recent work has focused on understanding how the endoderm produces a robust developmental output in the face of many sources of variation. Genetic control exists at three levels of endoderm development: Progenitor specification, cell divisions within the developing gut, and maintenance of gut differentiation. Recent findings show that specification genes regulate all three of these aspects of gut development, and that mutant embryos can experience a "partial" specification state in which some, but not all, E descendants adopt a gut fate. Ongoing studies using newer quantitative and genome-wide methods promise further insights into how developmental gene-regulatory networks buffer variation.

A Synthetic Lethal Screen Identifies a Role for Lin-44/Wnt in C. elegans Embryogenesis

BACKGROUND

The C. elegans proteins PTP-3/LAR-RPTP and SDN-1/Syndecan are conserved cell adhesion molecules. Loss-of-function (LOF) mutations in either ptp-3 or sdn-1 result in low penetrance embryonic developmental defects. Work from other systems has shown that syndecans can function as ligands for LAR receptors in vivo. We used double mutant analysis to test whether ptp-3 and sdn-1 function in a linear genetic pathway during C. elegans embryogenesis.

RESULTS

We found animals with LOF in both sdn-1 and ptp-3 exhibited a highly penetrant synthetic lethality (SynLet), with only a small percentage of animals surviving to adulthood. Analysis of the survivors demonstrated that these animals had a synergistic increase in the penetrance of embryonic developmental defects. Together, these data strongly suggested PTP-3 and SDN-1 function in parallel during embryogenesis. We subsequently used RNAi to knockdown ~3,600 genes predicted to encode secreted and/or transmembrane molecules to identify genes that interacted with ptp-3 or sdn-1. We found that the Wnt ligand, lin-44, was SynLet with sdn-1, but not ptp-3. We used 4-dimensional time-lapse analysis to characterize the interaction between lin-44 and sdn-1. We found evidence that loss of lin-44 caused defects in the polarization and migration of endodermal precursors during gastrulation, a previously undescribed role for lin-44 that is strongly enhanced by the loss of sdn-1.

CONCLUSIONS

PTP-3 and SDN-1 function in compensatory pathways during C. elegans embryonic and larval development, as simultaneous loss of both genes has dire consequences for organismal survival. The Wnt ligand lin-44 contributes to the early stages of gastrulation in parallel to sdn-1, but in a genetic pathway with ptp-3. Overall, the SynLet phenotype provides a robust platform to identify ptp-3 and sdn-1 interacting genes, as well as other genes that function in development, yet might be missed in traditional forward genetic screens.

Predicting functional and regulatory divergence of a drug resistance transporter gene in the human malaria parasite

Background

The paradigm of resistance evolution to chemotherapeutic agents is that a key coding mutation in a specific gene drives resistance to a particular drug. In the case of resistance to the anti-malarial drug chloroquine (CQ), a specific mutation in the transporter pfcrt is associated with resistance. Here, we apply a series of analytical steps to gene expression data from our lab and leverage 3 independent datasets to identify pfcrt-interacting genes. Resulting networks provide insights into pfcrt’s biological functions and regulation, as well as the divergent phenotypic effects of its allelic variants in different genetic backgrounds.

Results

To identify pfcrt-interacting genes, we analyze pfcrt co-expression networks in 2 phenotypic states - CQ-resistant (CQR) and CQ-sensitive (CQS) recombinant progeny clones - using a computational approach that prioritizes gene interactions into functional and regulatory relationships. For both phenotypic states, pfcrt co-expressed gene sets are associated with hemoglobin metabolism, consistent with CQ’s expected mode of action. To predict the drivers of co-expression divergence, we integrate topological relationships in the co-expression networks with available high confidence protein-protein interaction data. This analysis identifies 3 transcriptional regulators from the ApiAP2 family and histone acetylation as potential mediators of these divergences. We validate the predicted divergences in DNA mismatch repair and histone acetylation by measuring the effects of small molecule inhibitors in recombinant progeny clones combined with quantitative trait locus (QTL) mapping.

Conclusions

This work demonstrates the utility of differential co-expression viewed in a network framework to uncover functional and regulatory divergence in phenotypically distinct parasites. pfcrt-associated co-expression in the CQ resistant progeny highlights CQR-specific gene relationships and possible targeted intervention strategies. The approaches outlined here can be readily generalized to other parasite populations and drug resistances.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1261-6) contains supplementary material, which is available to authorized users.

Proposal for a new therapy for drug-resistant malaria using Plasmodium synthetic lethality inference

Many antimalarial drugs kill malaria parasites, but antimalarial drug resistance (ADR) and toxicity to normal cells limit their usefulness. To solve this problem, we suggest a new therapy for drug-resistant malaria. The approach consists of data integration and inference through homology analysis of yeast-human-Plasmodium. If one gene of a Plasmodium synthetic lethal (SL) gene pair has a mutation that causes ADR, a drug targeting the other gene of the SL pair might be used as an effective treatment for drug-resistant strains of malaria. A simple computational tool to analyze the inferred SL genes of Plasmodium species (malaria parasites Plasmodium falciparum and Plasmodium vivax for human malarial therapy, and rodent parasite Plasmodium berghei for in vivo studies of human malarias) was established to identify SL genes that can be used as drug targets. Information on SL gene pairs with ADR genes and their first neighbors was inferred from yeast SL genes to search for pertinent antimalarial drug targets. We not only suggest drug target gene candidates for further experimental validation, but also provide information on new usage for already-described drugs. The proposed specific antimalarial drug candidates can be inferred by searching drugs that cause a fitness defect in yeast SL genes.

Duplication and retention biases of essential and non-essential genes revealed by systematic knockdown analyses

When a duplicate gene has no apparent loss-of-function phenotype, it is commonly considered that the phenotype has been masked as a result of functional redundancy with the remaining paralog. This is supported by indirect evidence showing that multi-copy genes show loss-of-function phenotypes less often than single-copy genes and by direct tests of phenotype masking using select gene sets. Here we take a systematic genome-wide RNA interference approach to assess phenotype masking in paralog pairs in the Caenorhabditis elegans genome. Remarkably, in contrast to expectations, we find that phenotype masking makes only a minor contribution to the low knockdown phenotype rate for duplicate genes. Instead, we find that non-essential genes are highly over-represented among duplicates, leading to a low observed loss-of-function phenotype rate. We further find that duplicate pairs derived from essential and non-essential genes have contrasting evolutionary dynamics: whereas non-essential genes are both more often successfully duplicated (fixed) and lost, essential genes are less often duplicated but upon successful duplication are maintained over longer periods. We expect the fundamental evolutionary duplication dynamics presented here to be broadly applicable.

Duplicate genes occur in all organisms. It has been found that mutations in duplicate genes cause defects much less often than when single copy genes are mutated. It is widely believed that this is due to functional redundancy—that is, the two genes can carry out similar functions so that the non-mutated duplicate gene can cover for or “mask” the phenotype of the mutation in the first duplicate. To determine whether this hypothesis is true, it is necessary to test systematically whether defects indeed occur in the organism when both duplicate genes are inhibited. We have for the first time carried out such an analysis in a multicellular organism, the nematode Caenorhabditis elegans. In contrast to expectations, we observed that when both copies of duplicate genes are inhibited deleterious effects are very rare. We show that this is because duplicate genes are much more often non-essential compared to genes where there is only a single copy. Non-essential genes are also lost from the genome much more often than essential genes. However, when essential genes are duplicated, they remain present in the genome over longer periods. Our results give a framework to explain the evolutionary dynamics of duplications in the genome.

Network inference of pal-1 lineage-specific regulation in the C. elegans embryo by structural equation modeling

The elucidation of spatial and temporal control during developmental stages is one of the central tasks for systems biology, and a variety of intracellular factors are known as regulators for specific gene expression. The activity information of those various factors is not directly reflected in their gene expression profiles. Hence, a method based on Structural Equation Modeling (SEM) is described. SEM can include the latent variables within the constructed model and infer the relationships among latent and observed variables, as a network model. An improved SEM approach for the construction of an optimal model is applied to infer the regulatory network for the determination of C lineage fate in C. elegans development. The inferred network model shows that the 13 analysed transcription factor genes were regulated by several other factors in addition to pal-1 expression. The other regulatory factors are those involved in protein accumulation and localization as important regulatory factors for normal development. Those regulatory factors were regulated sequentially in the network model. The regulation of the known pal-1 regulated genes was dependent on this sequential control of the regulatory factors. The interpretation of the network model shows insights to the complex regulation occurring during the C lineage determination by pal-1.

A regulatory network modeled from wild-type gene expression data guides functional predictions in Caenorhabditis elegans development

BACKGROUND

Complex gene regulatory networks underlie many cellular and developmental processes. While a variety of experimental approaches can be used to discover how genes interact, few biological systems have been systematically evaluated to the extent required for an experimental definition of the underlying network. Therefore, the development of computational methods that can use limited experimental data to define and model a gene regulatory network would provide a useful tool to evaluate many important but incompletely understood biological processes. Such methods can assist in extracting all relevant information from data that are available, identify unexpected regulatory relationships and prioritize future experiments.

RESULTS

To facilitate the analysis of gene regulatory networks, we have developed a computational modeling pipeline method that complements traditional evaluation of experimental data. For a proof-of-concept example, we have focused on the gene regulatory network in the nematode C. elegans that mediates the developmental choice between mesodermal (muscle) and ectodermal (skin) cell fates in the embryonic C lineage. We have used gene expression data to build two models: a knowledge-driven model based on gene expression changes following gene perturbation experiments, and a data-driven mathematical model derived from time-course gene expression data recovered from wild-type animals. We show that both models can identify a rich set of network gene interactions. Importantly, the mathematical model built only from wild-type data can predict interactions demonstrated by the perturbation experiments better than chance, and better than an existing knowledge-driven model built from the same data set. The mathematical model also provides new biological insight, including a dissection of zygotic from maternal functions of a key transcriptional regulator, PAL-1, and identification of non-redundant activities of the T-box genes tbx-8 and tbx-9.

CONCLUSIONS

This work provides a strong example for a mathematical modeling approach that solely uses wild-type data to predict an underlying gene regulatory network. The modeling approach complements traditional methods of data analysis, suggesting non-intuitive network relationships and guiding future experiments.

Transcription factor redundancy and tissue-specific regulation: evidence from functional and physical network connectivity

Two major transcriptional regulators of Caenorhabditis elegans bodywall muscle (BWM) differentiation, hlh-1 and unc-120, are expressed in muscle where they are known to bind and regulate several well-studied muscle-specific genes. Simultaneously mutating both factors profoundly inhibits formation of contractile BWM. These observations were consistent with a simple network model in which the muscle regulatory factors drive tissue-specific transcription by binding selectively near muscle-specific targets to activate them. We tested this model by measuring the number, identity, and tissue-specificity of functional regulatory targets for each factor. Some joint regulatory targets (218) are BWM-specific and enriched for nearby HLH-1 binding. However, contrary to the simple model, the majority of genes regulated by one or both muscle factors are also expressed significantly in non-BWM tissues. We also mapped global factor occupancy by HLH-1, and created a genetic interaction map that identifies hlh-1 collaborating transcription factors. HLH-1 binding did not predict proximate regulatory action overall, despite enrichment for binding among BWM-specific positive regulatory targets of hlh-1. We conclude that these tissue-specific factors contribute much more broadly to the transcriptional output of muscle tissue than previously thought, offering a partial explanation for widespread HLH-1 occupancy. We also identify a novel regulatory connection between the BWM-specific hlh-1 network and the hlh-8/twist nonstriated muscle network. Finally, our results suggest a molecular basis for synthetic lethality in which hlh-1 and unc-120 mutant phenotypes are mutually buffered by joint additive regulation of essential target genes, with additional buffering suggested via newly identified hlh-1 interacting factors.

Cell-type-specific nuclei purification from whole animals for genome-wide expression and chromatin profiling

An understanding of developmental processes requires knowledge of transcriptional and epigenetic landscapes at the level of tissues and ultimately individual cells. However, obtaining tissue- or cell-type-specific expression and chromatin profiles for animals has been challenging. Here we describe a method for purifying nuclei from specific cell types of animal models that allows simultaneous determination of both expression and chromatin profiles. The method is based on in vivo biotin-labeling of the nuclear envelope and subsequent affinity purification of nuclei. We describe the use of the method to isolate nuclei from muscle of adult Caenorhabditis elegans and from mesoderm of Drosophila melanogaster embryos. As a case study, we determined expression and nucleosome occupancy profiles for affinity-purified nuclei from C. elegans muscle. We identified hundreds of genes that are specifically expressed in muscle tissues and found that these genes are depleted of nucleosomes at promoters and gene bodies in muscle relative to other tissues. This method should be universally applicable to all model systems that allow transgenesis and will make it possible to determine epigenetic and expression profiles of different tissues and cell types.

Predicting mutation outcome from early stochastic variation in genetic interaction partners

Many mutations, including those that cause disease, only have a detrimental effect in a subset of individuals. The reasons for this are usually unknown, but may include additional genetic variation and environmental risk factors. However, phenotypic discordance remains even in the absence of genetic variation, for example between monozygotic twins, and incomplete penetrance of mutations is frequent in isogenic model organisms in homogeneous environments. Here we propose a model for incomplete penetrance based on genetic interaction networks. Using Caenorhabditis elegans as a model system, we identify two compensation mechanisms that vary among individuals and influence mutation outcome. First, feedback induction of an ancestral gene duplicate differs across individuals, with high expression masking the effects of a mutation. This supports the hypothesis that redundancy is maintained in genomes to buffer stochastic developmental failure. Second, during normal embryonic development we find that there is substantial variation in the induction of molecular chaperones such as Hsp90 (DAF-21). Chaperones act as promiscuous buffers of genetic variation, and embryos with stronger induction of Hsp90 are less likely to be affected by an inherited mutation. Simultaneously quantifying the variation in these two independent responses allows the phenotypic outcome of a mutation to be more accurately predicted in individuals. Our model and methodology provide a framework for dissecting the causes of incomplete penetrance. Further, the results establish that inter-individual variation in both specific and more general buffering systems combine to determine the outcome inherited mutations in each individual.

Networks in Caenorhabditis elegans

The network paradigm has become a pervasive theme in biology over the last decade, as increasingly large functional genomic datasets are being collected to interrogate regulatory influences, physical interactions, and genetic dependencies between genes, transcripts, and proteins. These 'molecular interaction' networks can be analyzed collectively and individually to define their global architecture and local patterns of connectivity. These structural features ultimately underlie functional properties such as robustness, modularity, component circuitry (e.g. feedback loops), dynamics, and responses to perturbations. This review focuses on recent progress in elucidating molecular interaction networks using different kinds of functional assays in the classical genetic model for animal development, the roundworm Caenorhabditis elegans, with representative examples to illustrate current directions in different areas of network biology.

Genetic evidence for pax-3 function in myogenesis in the nematode Pristionchus pacificus

PAX3 is a member of the PAX3/7 subfamily of the paired box proteins. In vertebrates, Pax3 is essential for skeletal myogenesis by activating a cascade of transcriptional events that are necessary and sufficient for skeletal myogenesis. Four related basic helix-loop-helix transcription factors, MyoD, Myf5, Mrf4, and Myogenin, are targets of PAX3 and serve as myogenic regulatory factors. Although the role of Pax3 in myogenesis is well studied in vertebrates, little is known about invertebrate PAX-3 proteins and myogenesis. Here, we took advantage of viable alleles of pax-3 in the nematode satellite model organism Pristionchus pacificus to investigate the function of PAX-3 in myogenesis. Two strong reduction-of-function alleles of Ppa-pax-3 show severe muscle-derived abnormalities and phalloidin staining indicates a disruption of body wall muscle patterning. Furthermore, we identified a myogenic regulatory factor-related gene Ppa-hlh-1/MyoD and a serum response factor-related gene Ppa-unc-120. Expression of both genes in Ppa-pax-3 mutant animals is down regulated suggesting that Ppa-pax-3 acts upstream in the regulatory network. Together, our results provide the first genetic evidence for a conserved function of PAX-3 in myogenesis between vertebrates and nematodes.

Human synthetic lethal inference as potential anti-cancer target gene detection

Background

Two genes are called synthetic lethal (SL) if mutation of either alone is not lethal, but mutation of both leads to death or a significant decrease in organism's fitness. The detection of SL gene pairs constitutes a promising alternative for anti-cancer therapy. As cancer cells exhibit a large number of mutations, the identification of these mutated genes' SL partners may provide specific anti-cancer drug candidates, with minor perturbations to the healthy cells. Since existent SL data is mainly restricted to yeast screenings, the road towards human SL candidates is limited to inference methods.

Results

In the present work, we use phylogenetic analysis and database manipulation (BioGRID for interactions, Ensembl and NCBI for homology, Gene Ontology for GO attributes) in order to reconstruct the phylogenetically-inferred SL gene network for human. In addition, available data on cancer mutated genes (COSMIC and Cancer Gene Census databases) as well as on existent approved drugs (DrugBank database) supports our selection of cancer-therapy candidates.

Conclusions

Our work provides a complementary alternative to the current methods for drug discovering and gene target identification in anti-cancer research. Novel SL screening analysis and the use of highly curated databases would contribute to improve the results of this methodology.

Using RNA interference to identify specific modifiers of a temperature-sensitive, embryonic-lethal mutation in the Caenorhabditis elegans ubiquitin-like Nedd8 protein modification pathway E1-activating gene rfl-1

The essential Caenorhabditis elegans gene rfl-1 encodes one subunit of a heterodimeric E1-activating enzyme in the Nedd8 ubiquitin-like protein conjugation pathway. This pathway modifies the Cullin scaffolds of E3 ubiquitin ligases with a single Nedd8 moiety to promote ligase function. To identify genes that influence neddylation, we used a synthetic screen to identify genes that, when depleted with RNAi, enhance or suppress the embryonic lethality caused by or198ts, a temperature-sensitive (ts) mutation in rfl-1. We identified reproducible suppressor and enhancer genes and employed a systematic specificity analysis for each modifier using four unrelated ts embryonic lethal mutants. Results of this analysis highlight the importance of specificity controls in identifying genetic interactions relevant to a particular biological process because 8/14 enhancers and 7/21 suppressors modified lethality in other mutants. Depletion of the strongest specific suppressors rescued the early embryonic cell division defects in rfl-1(or198ts) mutants. RNAi knockdown of some specific suppressors partially restored Cullin neddylation in rfl-1(or198ts) mutants, consistent with their gene products normally opposing neddylation, and GFP fusions to several suppressors were detected in the cytoplasm or the nucleus, similar in pattern to Nedd8 conjugation pathway components in early embryonic cells. In contrast, depletion of the two strongest specific enhancers did not affect the early embryonic cell division defects observed in rfl-1(or198ts) mutants, suggesting that they may act at later times in other essential processes. Many of the specific modifiers are conserved in other organisms, and most are nonessential. Thus, when controlled properly for specificity, modifier screens using conditionally lethal C. elegans mutants can identify roles for nonessential but conserved genes in essential processes.

Caudal-like PAL-1 directly activates the bodywall muscle module regulator hlh-1 in C. elegans to initiate the embryonic muscle gene regulatory network

Previous work in C. elegans has shown that posterior embryonic bodywall muscle lineages are regulated through a genetically defined transcriptional cascade that includes PAL-1/Caudal-mediated activation of muscle-specific transcription factors, including HLH-1/MRF and UNC-120/SRF, which together orchestrate specification and differentiation. Using chromatin immunoprecipitation (ChIP) in embryos, we now demonstrate direct binding of PAL-1 in vivo to an hlh-1 enhancer element. Through mutational analysis of the evolutionarily conserved sequences within this enhancer, we identify two cis-acting elements and their associated transacting factors (PAL-1 and HLH-1) that are crucial for the temporal-spatial expression of hlh-1 and proper myogenesis. Our data demonstrate that hlh-1 is indeed a direct target of PAL-1 in the posterior embryonic C. elegans muscle lineages, defining a novel in vivo binding site for this crucial developmental regulator. We find that the same enhancer element is also a target of HLH-1 positive auto regulation, underlying (at least in part) the sustained high levels of CeMyoD in bodywall muscle throughout development. Together, these results provide a molecular framework for the gene regulatory network activating the muscle module during embryogenesis.

Massively parallel sequencing of the polyadenylated transcriptome of C. elegans

Using massively parallel sequencing by synthesis methods, we have surveyed the polyA+ transcripts from four stages of the nematode Caenorhabditis elegans to an unprecedented depth. Using novel statistical approaches, we evaluated the coverage of annotated features of the genome and of candidate processed transcripts, including splice junctions, trans-spliced leader sequences, and polyadenylation tracts. The data provide experimental support for >85% of the annotated protein-coding transcripts in WormBase (WS170) and confirm additional details of processing. For example, the total number of confirmed splice junctions was raised from 70,911 to over 98,000. The data also suggest thousands of modifications to WormBase annotations and identify new spliced junctions and genes not part of any WormBase annotation, including at least 80 putative genes not found in any of three predicted gene sets. The quantitative nature of the data also suggests that mRNA levels may be measured by this approach with unparalleled precision. Although most sequences align with protein-coding genes, a small fraction falls in introns and intergenic regions. One notable region on the X chromosome encodes a noncoding transcript of >10 kb localized to somatic nuclei.

Widespread conservation of genetic redundancy during a billion years of eukaryotic evolution

Genetic redundancy means that two genes can perform the same function. Using a comprehensive phylogenetic analysis, we show here in both Saccharomyces cerevisiae and Caenorhabditis elegans that genetic redundancy is not just a transient consequence of gene duplication, but is often an evolutionary stable state. In multiple examples, genes have retained redundant functions since the divergence of the animal, plant and fungi kingdoms over a billion years ago. The stable conservation of genetic redundancy contrasts with the more rapid evolution of genetic interactions between unrelated genes and can be explained by theoretical models including a 'piggyback' mechanism in which overlapping redundant functions are co-selected with nonredundant ones.

A Caenorhabditis elegans genetic-interaction map wiggles into view

Systematic mapping of genetic-interaction networks will provide an essential foundation for understanding complex genetic disorders, mechanisms of genetic buffering and principles of robustness and evolvability. A recent study of signaling pathways in Caenorhabditis elegans lays the next row of bricks in this foundation.

Pairing of competitive and topologically distinct regulatory modules enhances patterned gene expression

Biological networks are inherently modular, yet little is known about how modules are assembled to enable coordinated and complex functions. We used RNAi and time series, whole-genome microarray analyses to systematically perturb and characterize components of a Caenorhabditis elegans lineage-specific transcriptional regulatory network. These data are supported by selected reporter gene analyses and comprehensive yeast one-hybrid and promoter sequence analyses. Based on these results, we define and characterize two modules composed of muscle- and epidermal-specifying transcription factors that function together within a single cell lineage to robustly specify multiple cell types. The expression of these two modules, although positively regulated by a common factor, is reliably segregated among daughter cells. Our analyses indicate that these modules repress each other, and we propose that this cross-inhibition coupled with their relative time of induction function to enhance the initial asymmetry in their expression patterns, thus leading to the observed invariant gene expression patterns and cell lineage. The coupling of asynchronous and topologically distinct modules may be a general principle of module assembly that functions to potentiate genetic switches.

Modelling genotype-phenotype relationships and human disease with genetic interaction networks

Probably all heritable traits, including disease susceptibility, are affected by interactions between mutations in multiple genes. We understand little, however, about how genes interact to produce phenotypes, and there is little power to detect interactions between genes in human population studies. An alternative approach towards understanding how mutations combine to produce phenotypes is to construct systematic genetic interaction networks in model organisms. Here I describe the methods that are being used to map genetic interactions in yeast and C. elegans, and the insights that these networks provide for human disease. I also discuss the mechanistic interpretation of genetic interaction networks, how genetic interactions can be used to understand gene function, and methods that have been developed to predict genetic interactions on a genome-wide scale.

Automated data integration for developmental biological research

In an era exploding with genome-scale data, a major challenge for developmental biologists is how to extract significant clues from these publicly available data to benefit our studies of individual genes, and how to use them to improve our understanding of development at a systems level. Several studies have successfully demonstrated new approaches to classic developmental questions by computationally integrating various genome-wide data sets. Such computational approaches have shown great potential for facilitating research: instead of testing 20,000 genes, researchers might test 200 to the same effect. We discuss the nature and state of this art as it applies to developmental research.

Exploring genetic interactions and networks with yeast

The development and application of genetic tools and resources has enabled a partial genetic-interaction network for the yeast Saccharomyces cerevisiae to be compiled. Analysis of the network, which is ongoing, has already provided a clear picture of the nature and scale of the genetic interactions that robustly sustain biological systems, and how cellular buffering is achieved at the molecular level. Recent studies in yeast have begun to define general principles of genetic networks, and also pave the way for similar studies in metazoan model systems. A comparative understanding of genetic-interaction networks promises insights into some long-standing genetic problems, such as the nature of quantitative traits and the basis of complex inherited disease.

Defining the transcriptional redundancy of early bodywall muscle development in C. elegans: evidence for a unified theory of animal muscle development

Myogenic regulatory factors (MRFs) are required for mammalian skeletal myogenesis. In contrast, bodywall muscle is readily detectable in Caenorhabditis elegans embryos lacking activity of the lone MRF ortholog HLH-1, indicating that additional myogenic factors must function in the nematode. We find that two additional C. elegans proteins, UNC-120/SRF and HND-1/HAND, can convert naïve blastomeres to muscle when overproduced ectopically in the embryo. In addition, we have used genetic null mutants to demonstrate that both of these factors act in concert with HLH-1 to regulate myogenesis. Loss of all three factors results in embryos that lack detectable bodywall muscle differentiation, identifying this trio as a set that is both necessary and sufficient for bodywall myogenesis in C. elegans. In mammals, SRF and HAND play prominent roles in regulating smooth and cardiac muscle development. That C. elegans bodywall muscle development is dependent on transcription factors that are associated with all three types of mammalian muscle supports a theory that all animal muscle types are derived from a common ancestral contractile cell type.

Toward a global picture of development: lessons from genome-scale analysis in Caenorhabditis elegans embryonic development

Development is the result of complex events, including cascades of transcriptional programs and numerous molecular interactions. Traditionally, research focus has been given to the characterization of individual mutants, regulators, or interactions. With the availability of complete genome sequences and high-throughput (HT) experimental techniques, probing development on a system level has become feasible. Pioneering work initiated in invertebrate model systems such as Caenorhabditis elegans has provided first drafts of catalogs of essential components, transcriptional regulatory diagrams and molecular interaction networks underlying developmental processes. Integrating these drafts approximates a system-level picture of development and provides local models for protein/gene functions. Here we summarize the progress toward elucidating developmental processes on a system level, including the applications of genomic technologies and computational analyses. We discuss C. elegans embryonic development in case studies to illustrate how various HT approaches can be integrated and how biological insights can be gained from these approaches.

Experimental approaches to identify genetic networks

Systems biology offers the promise of a fully integrated view of cellular physiology. To realize this potential requires the analysis of diverse genome-wide datasets and the incorporation of these analyses into integrated networks. In the past decade, the budding yeast Saccharomyces cerevisiae has provided the benchmark for the design of such large-scale experiments. Many of these experimental approaches have been adopted and adapted to study other systems, including worm, fly, fish and mammalian cultured cells, using an ingenious set of molecular tools.

Role of T-box gene tbx-2 for anterior foregut muscle development in C. elegans

During organogenesis, pluripotent precursor cells acquire a defined identity such as muscle or nerve. The transition from naïve precursor towards the differentiated state is characterized by sequential waves of gene expression that are determined by regulatory transcription factors. A key question is how transcriptional circuitry dictates the succession of events that accompanies developmental competence, cell fate specification and differentiation. To address this question, we have examined how anterior muscles are established within the Caenorhabditis elegans foregut (pharynx). We find that the T-box transcription factor tbx-2 is essential to form anterior pharyngeal muscles from the ABa blastomere. In the absence of tbx-2 function, ABa-derived cells initiate development normally: they receive glp-1/Notch signaling cues, activate the T-box gene TBX-38 and express the organ selector gene PHA-4/FoxA. However, these cells subsequently arrest development, extinguish PHA-4 and fail to activate PHA-4 target genes. tbx-2 mutant cells do not undergo apoptosis and there is no evidence for adoption of an alternative fate. TBX-2 is expressed in ABa descendants and depends on activation by pha-4 and repression by components of glp-1/Notch signaling. Our analysis suggests that a positive feedback loop between tbx-2 and pha-4 is required for ABa-derived precursors to commit to pharyngeal muscle fate.

Combinatorial RNA interference in Caenorhabditis elegans reveals that redundancy between gene duplicates can be maintained for more than 80 million years of evolution

High-throughput combinatorial RNAi demonstrates that many duplicated genes in C. elegans can retain redundant functions for more than 80 million years

Background

Systematic analyses of loss-of-function phenotypes have been carried out for most genes in Saccharomyces cerevisiae, Caenorhabditis elegans, and Drosophila melanogaster. Although such studies vastly expand our knowledge of single gene function, they do not address redundancy in genetic networks. Developing tools for the systematic mapping of genetic interactions is thus a key step in exploring the relationship between genotype and phenotype.

Results

We established conditions for RNA interference (RNAi) in C. elegans to target multiple genes simultaneously in a high-throughput setting. Using this approach, we can detect the great majority of previously known synthetic genetic interactions. We used this assay to examine the redundancy of duplicated genes in the genome of C. elegans that correspond to single orthologs in S. cerevisiae or D. melanogaster and identified 16 pairs of duplicated genes that have redundant functions. Remarkably, 14 of these redundant gene pairs were duplicated before the divergence of C. elegans and C. briggsae 80-110 million years ago, suggesting that there has been selective pressure to maintain the overlap in function between some gene duplicates.

Conclusion

We established a high throughput method for examining genetic interactions using combinatorial RNAi in C. elegans. Using this technique, we demonstrated that many duplicated genes can retain redundant functions for more than 80 million years of evolution. This provides strong support for evolutionary models that predict that genetic redundancy between duplicated genes can be actively maintained by natural selection and is not just a transient side effect of recent gene duplication events.

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.

Genomics in C. elegans: so many genes, such a little worm

The Caenorhabditis elegans genome sequence is now complete, fully contiguous telomere to telomere and totaling 100,291,840 bp. The sequence has catalyzed the collection of systematic data sets and analyses, including a curated set of 19,735 protein-coding genes--with >90% directly supported by experimental evidence--and >1300 noncoding RNA genes. High-throughput efforts are under way to complete the gene sets, along with studies to characterize gene expression, function, and regulation on a genome-wide scale. The success of the worm project has had a profound effect on genome sequencing and on genomics more broadly. We now have a solid platform on which to build toward the lofty goal of a true molecular understanding of worm biology with all its implications including those for human health.

A compendium of Caenorhabditis elegans regulatory transcription factors: a resource for mapping transcription regulatory networks

BACKGROUND

Transcription regulatory networks are composed of interactions between transcription factors and their target genes. Whereas unicellular networks have been studied extensively, metazoan transcription regulatory networks remain largely unexplored. Caenorhabditis elegans provides a powerful model to study such metazoan networks because its genome is completely sequenced and many functional genomic tools are available. While C. elegans gene predictions have undergone continuous refinement, this is not true for the annotation of functional transcription factors. The comprehensive identification of transcription factors is essential for the systematic mapping of transcription regulatory networks because it enables the creation of physical transcription factor resources that can be used in assays to map interactions between transcription factors and their target genes.

RESULTS

By computational searches and extensive manual curation, we have identified a compendium of 934 transcription factor genes (referred to as wTF2.0). We find that manual curation drastically reduces the number of both false positive and false negative transcription factor predictions. We discuss how transcription factor splice variants and dimer formation may affect the total number of functional transcription factors. In contrast to mouse transcription factor genes, we find that C. elegans transcription factor genes do not undergo significantly more splicing than other genes. This difference may contribute to differences in organism complexity. We identify candidate redundant worm transcription factor genes and orthologous worm and human transcription factor pairs. Finally, we discuss how wTF2.0 can be used together with physical transcription factor clone resources to facilitate the systematic mapping of C. elegans transcription regulatory networks.

CONCLUSION

wTF2.0 provides a starting point to decipher the transcription regulatory networks that control metazoan development and function.

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.

Genomic Regulatory Networks and Animal Development

The synthesis of gene expression data and cis-regulatory analysis permits the elucidation of genomic regulatory networks. These networks provide a direct visualization of the functional interconnections among the regulatory genes and signaling components leading to cell-specific patterns of gene activity. Complex developmental processes are thereby illuminated in ways not revealed by the conventional analysis of individual genes. In this review, we describe emerging networks in several different model systems, and compare them with the gene regulatory network that controls dorsoventral patterning of the Drosophila embryo.