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LOTUS and Tudor domain containing proteins have critical roles in the germline. Proteins that contain these domains, such as Tejas/Tapas in Drosophila, help localize the Vasa helicase to the germ granules and facilitate piRNA-mediated transposon silencing. The homologous proteins in mammals, TDRD5 and TDRD7, are required during spermiogenesis. Until now, proteins containing both LOTUS and Tudor domains in Caenorhabditis elegans have remained elusive. Here we describe LOTR-1 (D1081.7), which derives its name from its LOTUS and Tudor domains. Interestingly, LOTR-1 docks next to P granules to colocalize with the broadly conserved Z-granule helicase, ZNFX-1. The Tudor domain of LOTR-1 is required for its Z-granule retention. Like znfx-1 mutants, lotr-1 mutants lose small RNAs from the 3’ ends of WAGO and mutator targets, reminiscent of the loss of piRNAs from the 3’ ends of piRNA precursor transcripts in mouse Tdrd5 mutants. Our work shows that LOTR-1 acts with ZNFX-1 to bring small RNA amplifying mechanisms towards the 3’ ends of its RNA templates.

LOTUS and Tudor domain containing proteins have critical roles in the germline. Proteins that contain these domains, such as Tejas/Tapas in Drosophila, help localize Vasa to the germ granules and facilitate piRNA-mediated transposon silencing. The homologous proteins in mammals, TDRD5 and TDRD7, are required during spermiogenesis. Until now, proteins containing both LOTUS and Tudor domains in Caenorhabditis elegans have remained elusive. Here we describe LOTR-1 (D1081.7), which derives its name from its LOTUS and Tudor domains. Interestingly, LOTR-1 docks next to P granules to colocalize with the broadly conserved Z-granule helicase, ZNFX-1. LOTR-1’s Z-granule association requires its Tudor domain, but both LOTUS and Tudor deletions affect brood size when coupled with a knockdown of the Vasa homolog glh-1. In addition to interacting with the germ-granule components WAGO-1, PRG-1 and DEPS-1, we identified a Tudor-dependent association with ZNFX-1. Like znfx-1 mutants, lotr-1 mutants lose small RNAs from the 3’ ends of WAGO and Mutator targets, reminiscent of the loss of piRNAs from the 3’ ends of piRNA precursor transcripts in mouse Tdrd5 mutants. Our work suggests that LOTR-1 acts in a conserved mechanism that brings small RNA generating mechanisms towards the 3’ ends of small RNA templates or precursors.

As a simple model organism, C. elegans plays an important role in gaining insight into the relationship between bodily thrashing forces and biological effects, such as disease and aging, or physical stimuli, like touch and light. Due to their similar length scale, microfluidic chips have been extensively explored for use in various biological studies involving C. elegans. However, a formidable challenge still exists due to the complexity of integrating external stimuli (chemical, mechanical or optical) with free-moving worms and subsequent imaging on the chip. In this report, we use a microfluidic device to partially immobilize a worm, which allows for measurements of the relative changes in the thrashing force under different assay conditions. Using a device adapted to the natural escape-like coiling response of a worm to immobilization, we have quantified the relative changes in the thrashing force during different developmental stages (L1, L3, L4, and young adult) and in response to various glucose concentrations and drug treatment. Our findings showed a loss of thrashing force following the introduction of glucose into a wild type worm culture that could be reversed upon treatment with the type 2 diabetes drug metformin. A morphological study of the actin filament structures in the body wall muscles provided supporting evidence for the force measurement data. Finally, we demonstrated the multiplexing capabilities of our device through recording the thrashing activities of eight worms simultaneously. The multiplexing capabilities and facile imaging available using our device open the door for high-throughput neuromuscular studies using C. elegans.

Background The 3′ untranslated regions (UTRs) of mRNAs play a major role in post-transcriptional regulation of gene expression. Selection of transcript cleavage and polyadenylation sites is a dynamic process that produces multiple transcript isoforms for the same gene within and across different cell types. Using LITE-Seq, a new quantitative method to capture transcript 3′ ends expressed in vivo, we have characterized sex- and cell type-specific transcriptome-wide changes in gene expression and 3′UTR diversity in Caenorhabditis elegans germline cells undergoing proliferation and differentiation. Results We show that nearly half of germline transcripts are alternatively polyadenylated, that differential regulation of endogenous 3′UTR variants is common, and that alternative isoforms direct distinct spatiotemporal protein expression patterns in vivo. Dynamic expression profiling also reveals temporal regulation of X-linked gene expression, selective stabilization of transcripts, and strong evidence for a novel developmental program that promotes nucleolar dissolution in oocytes. We show that the RNA-binding protein NCL-1/Brat is a posttranscriptional regulator of numerous ribosome-related transcripts that acts through specific U-rich binding motifs to down-regulate mRNAs encoding ribosomal protein subunits, rRNA processing factors, and tRNA synthetases. Conclusions These results highlight the pervasive nature and functional potential of patterned gene and isoform expression during early animal development.

Microfluidic devices offer new technical possibilities for a precise manipulation of Caenorhabditis elegans due to the comparable length scale. C. elegans is a small, free-living nematode worm that is a popular model system for genetic, genomic, and high-throughput experimental studies of animal development and neurobiology. In this paper, we demonstrate a microfluidic system in polydimethylsiloxane (PDMS) for dispensing of a single C. elegans worm into a 96-well plate. It consists of two PDMS layers, a flow and a control layer. Using five microfluidic pneumatic valves in the control layer, a single worm is trapped upon optical detection with a pair of optical fibers integrated perpendicular to the constriction channel and then dispensed into a microplate well with a dispensing tip attached to a robotic handling system. Due to its simple design and facile fabrication, we expect that our microfluidic chip can be expanded to a multiplexed dispensation system of C. elegans worms for high-throughput drug screening.

Although strong evidence supports the importance of their cooperative interactions, microRNA (miRNA)-binding sites are still largely investigated as functionally independent regulatory units. Here, a survey of alternative 3΄UTR isoforms implicates a non-canonical seedless site in cooperative miRNA-mediated silencing. While required for target mRNA deadenylation and silencing, this site is not sufficient on its own to physically recruit miRISC. Instead, it relies on facilitating interactions with a nearby canonical seed-pairing site to recruit the Argonaute complexes. We further show that cooperation between miRNA target sites is necessary for silencing in vivo in the C. elegans embryo, and for the recruitment of the Ccr4-Not effector complex. Using a structural model of cooperating miRISCs, we identified allosteric determinants of cooperative miRNA-mediated silencing that are required for both embryonic and larval miRNA functions. Our results delineate multiple cooperative mechanisms in miRNA-mediated silencing and further support the consideration of target site cooperation as a fundamental characteristic of miRNA function.

Piwi-interacting RNAs (piRNAs) control transposable elements widely across metazoans but have rapidly evolving biogenesis pathways. In Caenorhabditis elegans, almost all piRNA loci are found within two 3Mb clusters on Chromosome IV. Each piRNA locus possesses an upstream motif that recruits RNA polymerase II to produce a ∼28 nt precursor transcript. Here, we use comparative epigenomics across nematodes to gain insight into piRNA biogenesis. We show that the piRNA upstream motif is derived from core promoter elements controlling snRNA biogenesis. We describe two alternative modes of piRNA organisation in nematodes: in C. elegans and closely related nematodes, piRNAs are clustered within repressive H3K27me3 chromatin, whilst in other species, typified by Pristionchus pacificus, piRNAs are distributed genome-wide within introns of actively transcribed genes. In both groups, piRNA production depends on downstream sequence signals associated with RNA polymerase II pausing, which synergise with the chromatin environment to control piRNA precursor transcription.

Summary Piwi-interacting RNAs (piRNAs) are important for genome regulation across metazoans, but their biogenesis evolves rapidly. In Caenorhabditis elegans, piRNA loci are clustered within two 3-Mb regions on chromosome IV. Each piRNA locus possesses an upstream motif that recruits RNA polymerase II to produce an ∼28 nt primary transcript. We used comparative epigenomics across nematodes to gain insight into the origin, evolution, and mechanism of nematode piRNA biogenesis. We show that the piRNA upstream motif is derived from core promoter elements controlling snRNA transcription. We describe two alternative modes of piRNA organization in nematodes: in C. elegans and closely related nematodes, piRNAs are clustered within repressive H3K27me3 chromatin, while in other species, typified by Pristionchus pacificus, piRNAs are found within introns of active genes. Additionally, we discover that piRNA production depends on sequence signals associated with RNA polymerase II pausing. We show that pausing signals synergize with chromatin to control piRNA transcription., Graphical Abstract, Highlights • Nematode piRNA transcription evolved from small nuclear RNA biogenesis • Clustered piRNAs are produced from regulated (H3K27me3) chromatin domains • Dispersed piRNAs are produced from active (H3K36me3) chromatin domains • RNA polymerase II pausing determines the short (∼28 nt) length of piRNA precursors, piRNAs are an important genome regulatory mechanism conserved across metazoans. In the nematode C. elegans, piRNA biogenesis evolved several differences from other metazoans. Beltran et al. study the origin of these differences through an evolutionary approach, discovering that chromatin environment and RNA polymerase II pausing synergize in piRNA biogenesis.

Piwi-interacting RNAs (piRNAs) control transposable elements widely across metazoans but have rapidly evolving biogenesis pathways. In Caenorhabditis elegans, almost all piRNA loci are found within two 3Mb clusters on Chromosome IV. Each piRNA locus possesses an upstream motif that recruits RNA polymerase II to produce a ~28 nt precursor transcript. Here, we use comparative epigenomics across nematodes to gain insight into piRNA biogenesis. We show that the piRNA upstream motif is derived from core promoter elements controlling snRNA biogenesis. We describe two alternative modes of piRNA organisation in nematodes: in C. elegans and closely related nematodes, piRNAs are clustered within repressive H3K27me3 chromatin, whilst in other species, typified by Pristionchus pacificus, piRNAs are distributed genome-wide within introns of actively transcribed genes. In both groups, piRNA production depends on downstream sequence signals associated with RNA polymerase II pausing, which synergise with the chromatin environment to control piRNA precursor transcription.

We present DevStaR, an automated computer vision and machine learning system that provides rapid, accurate, and quantitative measurements of C. elegans embryonic viability in high-throughput (HTP) applications. A leading genetic model organism for the study of animal development and behavior, C. elegans is particularly amenable to HTP functional genomic analysis due to its small size and ease of cultivation, but the lack of efficient and quantitative methods to score phenotypes has become a major bottleneck. DevStaR addresses this challenge using a novel hierarchical object recognition machine that rapidly segments, classifies, and counts animals at each developmental stage in images of mixed-stage populations of C. elegans. Here, we describe the algorithmic design of the DevStaR system and demonstrate its performance in scoring image data acquired in HTP screens. Fil: White, Amelia G.. Rutgers University. Department of Computational Biology and Molecular Biophysics; Estados Unidos de América; New York University. Department of Biology. Center for Genomics and Systems Biology; Estados Unidos de América; Fil: Lees, Brandon. New York University. Department of Biology. Center for Genomics and Systems Biology; Estados Unidos de América; Fil: Kao, Huey-Ling. New York University. Department of Biology. Center for Genomics and Systems Biology; Estados Unidos de América; Fil: Cipriani, P. Giselle. New York University. Department of Biology. Center for Genomics and Systems Biology; Estados Unidos de América; Fil: Munarriz, Eliana Rosa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Parque Centenario. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales; Argentina; New York University. Department of Biology. Center for Genomics and Systems Biology; Estados Unidos de América; Fil: Paaby, Annalyse B.. New York University. Department of Biology. Center for Genomics and Systems Biology; Estados Unidos de América; Fil: Erickson, Katherine. New York University. Department of Biology. Center for Genomics and Systems Biology; Estados Unidos de América; Fil: Guzman, Sherly. New York University. Department of Biology. Center for Genomics and Systems Biology; Estados Unidos de América; Fil: Rattanakorn, Kirk. New York University. Department of Biology. Center for Genomics and Systems Biology; Estados Unidos de América; Fil: Sontag, Eduardo. Rutgers University. Department of Mathematics; Estados Unidos de América; Fil: Geiger, Davi. New York University. Courant Institute of Mathematical Sciences. Department of Computer Science; Estados Unidos de América; Fil: Gunsalus, Kristin C.. New York University. Department of Biology. Center for Genomics and Systems Biology; Estados Unidos de América; Fil: Piano, Fabio. New York University. Department of Biology. Center for Genomics and Systems Biology; Estados Unidos de América

Current computational analysis of microRNA interactions is based largely on primary and secondary structure analysis. Computationally efficient tertiary structure-based methods are needed to enable more realistic modeling of the molecular interactions underlying miRNA-mediated translational repression. We incorporate algorithms for predicting duplex RNA structures, ionic strength effects, duplex entropy and free energy, and docking of duplex–Argonaute protein complexes into a pipeline to model and predict miRNA–target duplex binding energies. To ensure modeling accuracy and computational efficiency, we use an all-atom description of RNA and a continuum description of ionic interactions using the Poisson–Boltzmann equation. Our method predicts the conformations of two constructs of Caenorhabditis elegans let-7 miRNA–target duplexes to an accuracy of ∼3.8 Å root mean square distance of their NMR structures. We also show that the computed duplex formation enthalpies, entropies, and free energies for eight miRNA–target duplexes agree with titration calorimetry data. Analysis of duplex–Argonaute docking shows that structural distortions arising from single-base-pair mismatches in the seed region influence the activity of the complex by destabilizing both duplex hybridization and its association with Argonaute. Collectively, these results demonstrate that tertiary structure-based modeling of miRNA interactions can reveal structural mechanisms not accessible with current secondary structure-based methods.

International audience; Studying protein interactions in whole organisms is fundamental to understanding development. Here, we combine in vivo expressed GFP-tagged proteins with quantitative proteomics to identify protein-protein interactions of selected key proteins involved in early C. elegans embryogenesis. Co-affinity purification of interaction partners for eight bait proteins resulted in a pilot in vivo interaction map of proteins with a focus on early development. Our network reflects known biology and is highly enriched in functionally relevant interactions. To demonstrate the utility of the map, we looked for new regulators of P granule dynamics and found that GEI-12, a novel binding partner of the DYRK family kinase MBK-2, is a key regulator of P granule formation and germline maintenance. Our data corroborate a recently proposed model in which the phosphorylation state of GEI-12 controls P granule dynamics. In addition, we find that GEI-12 also induces granule formation in mammalian cells, suggesting a common regulatory mechanism in worms and humans. Our results show that in vivo interaction proteomics provides unique insights into animal development.

Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of functionally related gene products, is an important challenge in analyzing biological networks. However, existing tools to identify modules are insufficient when applied to dense networks of experimentally derived interaction data. To address this problem, we have developed an agglomerative clustering method that is able to identify highly modular sets of gene products within highly interconnected molecular interaction networks.MINE outperforms MCODE, CFinder, NEMO, SPICi, and MCL in identifying non-exclusive, high modularity clusters when applied to the C. elegans protein-protein interaction network. The algorithm generally achieves superior geometric accuracy and modularity for annotated functional categories. In comparison with the most closely related algorithm, MCODE, the top clusters identified by MINE are consistently of higher density and MINE is less likely to designate overlapping modules as a single unit. MINE offers a high level of granularity with a small number of adjustable parameters, enabling users to fine-tune cluster results for input networks with differing topological properties.MINE was created in response to the challenge of discovering high quality modules of gene products within highly interconnected biological networks. The algorithm allows a high degree of flexibility and user-customisation of results with few adjustable parameters. MINE outperforms several popular clustering algorithms in identifying modules with high modularity and obtains good overall recall and precision of functional annotations in protein-protein interaction networks from both S. cerevisiae and C. elegans.

From Genome to Regulatory Networks For biologists, having a genome in hand is only the beginning—much more investigation is still needed to characterize how the genome is used to help to produce a functional organism (see the Perspective by Blaxter ). In this vein, Gerstein et al. (p. 1775 ) summarize for the Caenorhabditis elegans genome, and The modENCODE Consortium (p. 1787 ) summarize for the Drosophila melanogaster genome, full transcriptome analyses over developmental stages, genome-wide identification of transcription factor binding sites, and high-resolution maps of chromatin organization. Both studies identified regions of the nematode and fly genomes that show highly occupied targets (or HOT) regions where DNA was bound by more than 15 of the transcription factors analyzed and the expression of related genes were characterized. Overall, the studies provide insights into the organization, structure, and function of the two genomes and provide basic information needed to guide and correlate both focused and genome-wide studies.

The primary objective of the Human Genome Project was to produce high-quality sequences not just for the human genome but also for those of the chief model organisms: Escherichia coli, yeast (Saccharomyces cerevisiae), worm (Caenorhabditis elegans), fly (Drosophila melanogaster) and mouse (Mus musculus). Free access to the resultant data has prompted much biological research, including development of a map of common human genetic variants (the International HapMap Project)1, expression profiling of healthy and diseased cells2 and in-depth studies of many individual genes. These genome sequences have enabled researchers to carry out genetic and functional genomic studies not previously possible, revealing new biological insights with broad relevance across the animal kingdom 3, 4.

To provide accurate biological hypotheses and elucidate global properties of cellular networks, systematic identification of protein-protein interactions must meet high quality standards.We present an expanded C. elegans protein-protein interaction network, or 'interactome' map, derived from testing a matrix of approximately 10,000 x approximately 10,000 proteins using a highly specific, high-throughput yeast two-hybrid system. Through a new empirical quality control framework, we show that the resulting data set (Worm Interactome 2007, or WI-2007) was similar in quality to low-throughput data curated from the literature. We filtered previous interaction data sets and integrated them with WI-2007 to generate a high-confidence consolidated map (Worm Interactome version 8, or WI8). This work allowed us to estimate the size of the worm interactome at approximately 116,000 interactions. Comparison with other types of functional genomic data shows the complementarity of distinct experimental approaches in predicting different functional relationships between genes or proteins, Journal Article, Research Support, N.I.H. Extramural, Research Support, Non-U.S. Gov't, Research Support, U.S. Gov't, Non-P.H.S., info:eu-repo/semantics/published

The complex cellular events that occur in response to fertilization are essential for mediating the oocyte-to-embryo transition. Here, we describe a comprehensive small-molecule screen focused on identifying compounds that affect early embryonic events in Caenorhabditis elegans. We identify a single novel compound that disrupts early embryogenesis with remarkable stage and species specificity. The compound, named C22, primarily impairs eggshell integrity, leading to osmotic sensitivity and embryonic lethality. The C22-induced phenotype is dependent upon the upregulation of the LET-607/CREBH transcription factor and its candidate target genes, which primarily encode factors involved in diverse aspects of protein trafficking. Together, our data suggest that in the presence of C22, one or more key components of the eggshell are inappropriately processed, leading to permeable, inviable embryos. The remarkable specificity and reversibility of this compound will facilitate further investigation into the role and regulation of protein trafficking in the early embryo, as well as serve as a tool for manipulating the life cycle for other studies such as those involving aging.

Embryogenesis is an essential and stereotypic process that nevertheless evolves among species. Its essentiality may favor the accumulation of cryptic genetic variation (CGV) that has no effect in the wild-type but that enhances or suppresses the effects of rare disruptions to gene function. Here, we adapted a classical modifier screen to interrogate the alleles segregating in natural populations of Caenorhabditis elegans: we induced gene knockdowns and used quantitative genetic methodology to examine how segregating variants modify the penetrance of embryonic lethality. Each perturbation revealed CGV, indicating that wild-type genomes harbor myriad genetic modifiers that may have little effect individually but which in aggregate can dramatically influence penetrance. Phenotypes were mediated by many modifiers, indicating high polygenicity, but the alleles tend to act very specifically, indicating low pleiotropy. Our findings demonstrate the extent of conditional functionality in complex trait architecture. DOI: http://dx.doi.org/10.7554/eLife.09178.001, eLife digest Individuals of the same species have similar, but generally not identical, DNA sequences. This ‘genetic variation’ is due to random changes in the DNA—known as mutations—that occur among individuals. These mutations may be passed on to these individuals' offspring, who in turn pass them on to their descendants. Some of these mutations may have a positive or negative effect on the ability of the organisms to survive and reproduce, but others may have no effect at all. The process by which an embryo forms (which is called embryogenesis) follows a precisely controlled series of events. Within the same species, there is genetic variation in the DNA that programs embryogenesis, but it is not clear what effect this variation has on how the embryo develops. Here, Paaby et al. adapted a genetics technique called a ‘modifier screen’ to study how genetic variation affects the development of a roundworm known as Caenorhabditis elegans. The experiments show that populations of worms harbor a lot of genetic variation that affects how they tolerate the loss of an important gene. One by one, Paaby et al. interrupted the activity of specific genes that embryos need in order to develop. How this affected the embryo, and whether or not it was able to survive, was due in large part to the naturally-occurring genetic variation in other genes in these worms. Paaby et al.'s findings serve as a reminder that the effect of a mutation depends on other DNA sequences in the organism. In humans, for example, a gene that causes a genetic disease may produce severe symptoms in one patient but mild symptoms in another. Future experiments will reveal the details of how genetic variation affects embryogenesis, which may also provide new insights into how complex processes in animals evolve over time. DOI: http://dx.doi.org/10.7554/eLife.09178.002

Insulin and insulin-like growth factor have an essential role in growth, development and the maintenance of metabolic homeostasis, including glucose uptake from the bloodstream. Researchers have identified mutations in insulin receptors that cause severe insulin resistance, and a temperature-sensitive daf-2 (a gene encoding an insulin receptor-like protein) mutant in Caenorhabditis elegans has served as an insulin resistance model. Here we report a forward chemical genetic approach with a tagged library that we used to identify a small molecule, GAPDH segregator (GAPDS), that suppresses the dauer formation induced by the daf-2 mutant. Like insulin, GAPDS increased both glucose uptake and the concentration of phosphatidylinositol-3,4,5-trisphosphate (PtdIns(3,4,5)P(3)) in mammalian preadipocytes. Using affinity matrices and RNA interference, we identified glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as a GAPDS target. We discovered that GAPDH stimulates phosphatase activity against not only PtdIns(3,4,5)P(3) but also PtdIns(4,5)P(2). These results suggest that GAPDH is both an active regulator in the phosphoinositide-mediated signaling pathway and a potential new target for insulin resistance treatment.

A key challenge of functional genomics today is to generate well-annotated data sets that can be interpreted across different platforms and technologies. Large-scale functional genomics data often fail to connect to standard experimental approaches of gene characterization in individual laboratories. Furthermore, a lack of universal annotation standards for phenotypic data sets makes it difficult to compare different screening approaches. Here we address this problem in a screen designed to identify all genes required for the first two rounds of cell division in the Caenorhabditis elegans embryo. We used RNA-mediated interference to target 98% of all genes predicted in the C. elegans genome in combination with differential interference contrast time-lapse microscopy. Through systematic annotation of the resulting movies, we developed a phenotypic profiling system, which shows high correlation with cellular processes and biochemical pathways, thus enabling us to predict new functions for previously uncharacterized genes.

A continuing challenge in contemporary biology is to extract meaningful functional data from the genome sequence. High-throughput functional genomics projects are currently ongoing in several model systems to characterize gene function on multiple levels, including gene expression patterns (Spellman et al. 1998; Reinke et al. 2000, 2004; Jiang et al. 2001; Arbeitman et al. 2002; Baugh et al. 2003), protein-protein interactions (Uetz et al. 2000; Walhout et al. 2000; Ito et al. 2001; Giot et al. 2003; Li et al. 2004), and protein structures (Chance et al. 2002; Goh et al. 2003). Phenotypic data complement these studies and are necessary to make the connection between predicted biochemical function and biological role in living cells. The development of RNA interference (RNAi) (Guo and Kemphues 1995; Fire et al. 1998) has made possible large-scale in vivo gene analyses in a functional genomic context in Caenorhabditis elegans (Gonczy et al. 2000; Piano et al. 2000, 2002; Hanazawa et al. 2001; Maeda et al. 2001; Kamath et al. 2003; Simmer et al. 2003; Rual et al. 2004) and in cell culture systems from Drosophila melanogaster and mammals (Somma et al. 2002; Kiger et al. 2003; Berns et al. 2004; Boutros et al. 2004; Paddison et al. 2004). RNAi studies enable loss-of-function analyses to be performed on genes that had not been uncovered previously by mutagenesis, thus potentially allowing phenotypic characterization of every gene in the genome. Data from different types of functional genomics projects can be combined to make inferences about gene function and protein networks on a large scale (Marcotte et al. 1999; Ge et al. 2001; Boulton et al. 2002; von Mering et al. 2002; Walhout et al. 2002). C. elegans embryogenesis is a powerful in vivo model to study gene function in the context of animal development. Its germline is highly sensitive to RNAi, facilitating the detection of genes with essential functions in the embryo. The set of genes known to be required during embryogenesis is enriched for components of pathways that drive cell proliferation and other fundamental processes, and these genes tend to be highly conserved across species (Gonczy et al. 2000; Piano et al. 2000, 2002; Kamath et al. 2003). Thus defining a comprehensive set of genes needed for C. elegans embryogenesis is an important step toward gaining general insights into mechanisms underlying animal development. Having in hand a complete list of genes required for fertility and embryogenesis is important both to systems biologists who study large networks and to classical biologists who study in detail the genes that control a single process. Despite the unprecedented scale of in vivo functional data obtained using RNAi, there are technical challenges to RNAi-based phenotypic analysis. In C. elegans, variables that can affect RNAi include the double-stranded (ds)RNA template source, the delivery method, and scoring criteria (for review, see Piano and Gunsalus 2002). Different studies have varied in their use of dsRNAs derived from genome amplicons that include intronic sequences (Gonczy et al. 2000; Piano et al. 2002; Kamath et al. 2003; Simmer et al. 2003) or from cDNA clones composed exclusively of exonic sequences (Piano et al. 2000; Hanazawa et al. 2001; Maeda et al. 2001; Rual et al. 2004). Delivery of dsRNA has been accomplished by injection (Guo and Kemphues 1995; Fire et al. 1998), by feeding animals on bacterial strains expressing dsRNA (Timmons and Fire 1998), and by soaking them in a solution containing dsRNA (Tabara et al. 1998). Despite these various approaches and the inherent complexities of phenotypic analyses, independent large-scale RNAi studies have shown a relatively high reproducibility rate (Piano and Gunsalus 2002; Simmer et al. 2003). However, just as a genome must be sequenced at several-fold depth to achieve sufficient coverage and accuracy, comparisons between different RNAi studies also suggest that multiple passes of genome-wide RNAi will be necessary to obtain a comprehensive view of the in vivo functions of each gene in C. elegans. Previous RNAi studies in C. elegans have shown that the set of genes expressed at higher levels in the ovary, relative to the soma or male germline, is enriched for genes required for embryogenesis (Piano et al. 2002). Using a partial C. elegans microarray, Reinke et al. (2000) identified 766 genes enriched in the ovary, and RNAi analysis revealed that at least 43% of these genes are required for embryogenesis (Piano et al. 2002). Recently, using a C. elegans genome-wide microarray containing about 90% of predicted genes, a total of 3015 ovary-enriched genes were identified (Reinke et al. 2004). However, only ∼28% of genes tested from this set have been found to be required for embryogenesis in any published RNAi study to date, suggesting that hundreds more remain to be identified (Reinke et al. 2004). To identify new genes required for embryogenesis, we analyzed 1011 ovary-enriched genes represented in the ORFeome. Over 85% of these had been assayed by RNAi in prior studies and not shown embryonic lethality. This group of genes may thus be enriched for genes whose embryonic requirement, if any, is more difficult to detect by RNAi. We used a combination of repeated RNAi by soaking and injection, and here report the identification of 192 genes involved in egg production or embryogenesis, 155 of which have no previously reported requirement in these stages. A majority of the genes in the ovary-enriched set have now been studied by RNAi by at least three independent studies, making it the most deeply studied set of genes available in C. elegans. Using the combined data from all previous studies of this set, we now include the dimension of penetrance in our analyses of phenotypic trends among the ovary-enriched genes. We observe that trends with regard to sequence similarity, expression level, and chromosomal location are predominantly due to genes with highly penetrant embryonic lethality or sterility. We also observe a relationship between the pattern of conservation across phyla and the penetrance level of embryonic lethality elicited by RNAi.

In the few short years since its discovery, RNA interference (RNAi) has revolutionized the functional analysis of genomes: both technical and conceptual approaches to the investigation of gene function are being transformed as a result of this new technology. Genome-scale RNAi analyses have already been performed in the model organisms Caenorhabditis elegans (in vivo) and Drosophila melanogaster (in cell lines), ushering in a new era of RNAi-based approaches to probing the inner workings of the cell. The transformation of complex phenotypic data into mineable 'digitized' formats is fostering the emergence of a new area of bioinformatics related to the phenome.

To initiate studies on how protein-protein interaction (or “interactome”) networks relate to multicellular functions, we have mapped a large fraction of the Caenorhabditis elegans interactome network. Starting with a subset of metazoan-specific proteins, more than 4000 interactions were identified from high-throughput, yeast two-hybrid (HT=Y2H) screens. Independent coaffinity purification assays experimentally validated the overall quality of this Y2H data set. Together with already described Y2H interactions and interologs predicted in silico , the current version of the Worm Interactome (WI5) map contains ∼5500 interactions. Topological and biological features of this interactome network, as well as its integration with phenome and transcriptome data sets, lead to numerous biological hypotheses.

RNA interference (RNAi) is being used in large-scale genomic studies as a rapid way to obtain in vivo functional information associated with specific genes. How best to archive and mine the complex data derived from these studies provides a series of challenges associated with both the methods used to elicit the RNAi response and the functional data gathered. RNAiDB (RNAi Database; http://www. rnai.org) has been created for the archival, distribution and analysis of phenotypic data from large-scale RNAi analyses in Caenorhabditis elegans. The database contains a compendium of publicly available data and provides information on experimental methods and phenotypic results, including raw data in the form of images and streaming time-lapse movies. Phenotypic summaries together with graphical displays of RNAi to gene mappings allow quick intuitive comparison of results from different RNAi assays and visualization of the gene product(s) potentially inhibited by each RNAi experiment based on multiple sequence analysis methods. RNAiDB can be searched using combinatorial queries and using the novel tool PhenoBlast, which ranks genes according to their overall phenotypic similarity. RNAiDB could serve as a model database for distributing and navigating in vivo functional information from large-scale systematic phenotypic analyses in different organisms.

By integrating functional genomic and proteomic mapping approaches, biological hypotheses should be formulated with increasing levels of confidence [1–5]. For example, yeast interactome and transcriptome data can be correlated in biologically meaningful ways [6–9]. Here, we combine interactome mapping data generated for a multicellular organism with data from both large-scale phenotypic analysis ("phenome mapping") and transcriptome profiling. First, we generated a two-hybrid interactome map of the Caenorhabditis elegans germline by using 600 transcripts enriched in this tissue [10]. We compared this map to a phenome map of the germline obtained by RNA interference (RNAi) [34] and to a transcriptome map obtained by clustering worm genes across 553 expression profiling experiments [11]. In this dataset, we find that essential proteins have a tendency to interact with each other, that pairs of genes encoding interacting proteins tend to exhibit similar expression profiles, and that, for ∼24% of germline interactions, both partners show overlapping embryonic lethal or high incidence of males RNAi phenotypes and similar expression profiles. We propose that these interactions are most likely to be relevant to germline biology. Similar integration of interactome, phenome, and transcriptome data should be possible for other biological processes in the nematode and for other organisms, including humans.

Characterizing the functions of the many genes discovered by the sequencing projects is now the primary focus of genome-scale studies. Although sequence or structure-based comparisons are helping to generate hypotheses on the biochemical functions of many gene products, determining the in vivo role(s) for large sets of genes remains a critical objective. RNA interference (RNAi) offers a rapid way to gain a first look at loss-of-function phenotypes associated with specific genes. So far RNAi has been used to test the function of a third of the predicted genes in the Caenorhabditis elegans (C. elegans) genome, and it can be expected that a first pass survey of the entire genome will soon be completed. From the current body of work an initial estimate of the power and challenges of using RNAi for genome-wide analyses can be made. A comparison of results obtained from independent large-scale RNAi studies reveals that despite a high degree of congruence, no single study is likely to achieve a comprehensive RNAi-based phenotypic "map" of the C. elegans genome; instead a more accurate picture will be assembled from a composite of independent results for the same genes. RNAi analysis, together with other functional genomic approaches such as expression profiling and protein interaction mapping, is transforming C. elegans into a premier model system for the development and integration of functional genomic approaches in a metazoan.

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.

A New Look at Old Data Although the full genome of Caenorhabditis elegans has been available for over 10 years, only a portion of the full-length messenger RNAs (mRNAs) and their expression through development has been analyzed. By combining multiple methods, involving a careful reannotation of existing data sets, sequencing of poly-A captured RNAs from multiple developmental stages, as well as cloning and deep sequencing of a subset of genes, Mangone et al. (p. 432 , published online 3 June) defined ∼26,000 distinct mRNA three-prime untranslated regions (3′UTRs) for ∼85% of the protein-coding genes. Most C. elegans genes have more than one 3′UTR, arising through different mechanisms including trans-splicing–coupled cleavage and polyadenylation. The work highlights the importance of the 3'UTRs in the regulation of mRNA stability and translation.

Three-prime untranslated regions (3′UTRs) are widely recognized as important post-transcriptional regulatory regions of mRNAs. RNA-binding proteins and small non-coding RNAs such as microRNAs (miRNAs) bind to functional elements within 3′UTRs to influence mRNA stability, translation and localization. These interactions play many important roles in development, metabolism and disease. However, even in the most well-annotated metazoan genomes, 3′UTRs and their functional elements are not well defined. Comprehensive and accurate genome-wide annotation of 3′UTRs and their functional elements is thus critical. We have developed an open-access database, available at http://www.UTRome.org, to provide a rich and comprehensive resource for 3′UTR biology in the well-characterized, experimentally tractable model system Caenorhabditis elegans. UTRome.org combines data from public repositories and a large-scale effort we are undertaking to characterize 3′UTRs and their functional elements in C. elegans, including 3′UTR sequences, graphical displays, predicted and validated functional elements, secondary structure predictions and detailed data from our cloning pipeline. UTRome.org will grow substantially over time to encompass individual 3′UTR isoforms for the majority of genes, new and revised functional elements, and in vivo data on 3′UTR function as they become available. The UTRome database thus represents a powerful tool to better understand the biology of 3′UTRs.

The architecture and dynamics of molecular networks can provide an understanding of complex biological processes complementary to that obtained from the in-depth study of single genes and proteins. With a completely sequenced and well-annotated genome, a fully characterized cell lineage, and powerful tools available to dissect development, Caenorhabditis elegans, among metazoans, provides an optimal system to bridge cellular and organismal biology with the global properties of macromolecular networks. This chapter considers omic technologies available for C. elegans to describe molecular networks--encompassing transcriptional and phenotypic profiling as well as physical interaction mapping--and discusses how their individual and integrated applications are paving the way for a network-level understanding of C. elegans biology.

Background: Metazoan miRNAs regulate protein-coding genes by binding the 3′ UTR of cognate mRNAs. Identifying targets for the 115 known C. elegans miRNAs is essential for understanding their function. Results: By using a new version of PicTar and sequence alignments of three nematodes, we predict that miRNAs regulate at least 10% of C. elegans genes through conserved interactions. We have developed a new experimental pipeline to assay 3′ UTR-mediated posttranscriptional gene regulation via an endogenous reporter expression system amenable to high-throughput cloning, demonstrating the utility of this system using one of the most intensely studied miRNAs, let-7. Our expression analyses uncover several new potential let-7 targets and suggest a new let-7 activity in head muscle and neurons. To explore genome-wide trends in miRNA function, we analyzed functional categories of predicted target genes, finding that one-third of C. elegans miRNAs target gene sets are enriched for specific functional annotations. We have also integrated miRNA target predictions with other functional genomic data from C. elegans. Conclusions: At least 10% of C. elegans genes are predicted miRNA targets, and a number of nematode miRNAs seem to regulate biological processes by targeting functionally related genes. We have also developed and successfully utilized an in vivo system for testing miRNA target predictions in likely endogenous expression domains. The thousands of genome-wide miRNA target predictions for nematodes, humans, and flies are available from the PicTar website and are linked to an accessible graphical network-browsing tool allowing exploration of miRNA target predictions in the context of various functional genomic data resources.

We report molecular genetic studies of three genes involved in early germ-line proliferation in Caenorhabditis elegans that lend unexpected insight into a germ-line/soma functional separation of autosomal/X-linked duplicated gene pairs. In a genetic screen for germ-line proliferation-defective mutants, we identified mutations in rpl-11.1 (L11 protein of the large ribosomal subunit), pab-1 [a poly(A)-binding protein], and glp-3/eft-3 (an elongation factor 1-α homolog). All three are members of autosome/X gene pairs. Consistent with a germ-line-restricted function of rpl-11.1 and pab-1, mutations in these genes extend life span and cause gigantism. We further examined the RNAi phenotypes of the three sets of rpl genes (rpl-11, rpl-24, and rpl-25) and found that for the two rpl genes with autosomal/X-linked pairs (rpl-11 and rpl-25), zygotic germ-line function is carried by the autosomal copy. Available RNAi results for highly conserved autosomal/X-linked gene pairs suggest that other duplicated genes may follow a similar trend. The three rpl and the pab-1/2 duplications predate the divergence between C. elegans and C. briggsae, while the eft-3/4 duplication appears to have occurred in the lineage to C. elegans after it diverged from C. briggsae. The duplicated C. briggsae orthologs of the three C. elegans autosomal/X-linked gene pairs also display functional differences between paralogs. We present hypotheses for evolutionary mechanisms that may underlie germ-line/soma subfunctionalization of duplicated genes, taking into account the role of X chromosome silencing in the germ line and analogous mammalian phenomena.

The early stages of embryogenesis in the nematode Caenorhabditis elegans are an ideal system in which to test the potential of ‘system-level’ approaches to understanding biological processes, as opposed to the conventional reductionist approach that focuses on individual enzymes. By integrating information on how proteins interact with each other, how genes are expressed and the effect of ‘knocking-down’ hundreds of genes, Gunsalus et al. have generated a string of models of molecular machines involved in driving early embryogenesis, and are able to propose functional links between these machines. Ten previously uncharacterized proteins were identified as significant in these pathways, showing how the systems can feed information back into single-reaction experiments. Although numerous fundamental aspects of development have been uncovered through the study of individual genes and proteins, system-level models are still missing for most developmental processes. The first two cell divisions of Caenorhabditis elegans embryogenesis constitute an ideal test bed for a system-level approach. Early embryogenesis, including processes such as cell division and establishment of cellular polarity, is readily amenable to large-scale functional analysis. A first step toward a system-level understanding is to provide ‘first-draft’ models both of the molecular assemblies involved1 and of the functional connections between them. Here we show that such models can be derived from an integrated gene/protein network generated from three different types of functional relationship2: protein interaction3, expression profiling similarity4 and phenotypic profiling similarity5, as estimated from detailed early embryonic RNA interference phenotypes systematically recorded for hundreds of early embryogenesis genes6. The topology of the integrated network suggests that C. elegans early embryogenesis is achieved through coordination of a limited set of molecular machines. We assessed the overall predictive value of such molecular machine models by dynamic localization of ten previously uncharacterized proteins within the living embryo.

Recently, a set of 766 genes that are enriched in the ovary as compared to the soma was identified by microarray analysis [1]. Here, we report a functional analysis of 98% of these genes by RNA interference (RNAi). Over half the genes tested showed at least one detectable phenotype, most commonly embryonic lethality, consistent with the expectation that ovary transcripts would be enriched for genes that are essential in basic cellular and developmental processes. We find that essential genes are more likely to be conserved and to be highly expressed in the ovary. We extend previous observations [2, 3] and find that fewer than the expected number of ovary-expressed essential genes are present on the X chromosome. We characterized early embryonic defects for 161 genes and used time-lapse microscopy to systematically describe the defects for each gene in terms of 47 RNAi-associated phenotypes. In this paper, we discuss the use of these data to group genes into "phenoclusters"; in the accompanying paper, we use these data as one component in the integration of different types of large-scale functional analyses [4]. We find that phenoclusters correlate well with sequence-based functional predictions and thus may be useful in predicting functions of uncharacterized genes.

A Drosophila melanogaster homologue of Caenorhabditis elegans par-1 acts at an early step in embryonic-axis formation

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.

Background The actin cytoskeleton plays critical roles in early development in Caenorhabditis elegans. To further understand the complex roles of actin in early embryogenesis we use RNAi and in vivo imaging of filamentous actin (F-actin) dynamics. Results Using RNAi, we found processes that are differentially sensitive to levels of actin during early embryogenesis. Mild actin depletion shows defects in cortical ruffling, pseudocleavage, and establishment of polarity, while more severe depletion shows defects in polar body extrusion, cytokinesis, chromosome segregation, and eventually, egg production. These defects indicate that actin is required for proper oocyte development, fertilization, and a wide range of important events during early embryogenesis, including proper chromosome segregation. In vivo visualization of the cortical actin cytoskeleton shows dynamics that parallel but are distinct from the previously described myosin dynamics. Two distinct types of actin organization are observed at the cortex. During asymmetric polarization to the anterior, or the establishment phase (Phase I), actin forms a meshwork of microfilaments and focal accumulations throughout the cortex, while during the anterior maintenance phase (Phase II) it undergoes a morphological transition to asymmetrically localized puncta. The proper asymmetric redistribution is dependent on the PAR proteins, while both asymmetric redistribution and morphological transitions are dependent upon PFN-1 and NMY-2. Just before cytokinesis, actin disappears from most of the cortex and is only found around the presumptive cytokinetic furrow. Finally, we describe dynamic actin-enriched comets in the early embryo. Conclusion During early C. elegans embryogenesis actin plays more roles and its organization is more dynamic than previously described. Morphological transitions of F-actin, from meshwork to puncta, as well as asymmetric redistribution, are regulated by the PAR proteins. Results from this study indicate new insights into the cellular and developmental roles of the actin cytoskeleton.

Many protein-protein interactions are mediated through independently folding modular domains. Proteome-wide efforts to model protein-protein interaction or "interactome" networks have largely ignored this modular organization of proteins. We developed an experimental strategy to efficiently identify interaction domains and generated a domain-based interactome network for proteins involved in C. elegans early-embryonic cell divisions. Minimal interacting regions were identified for over 200 proteins, providing important information on their domain organization. Furthermore, our approach increased the sensitivity of the two-hybrid system, resulting in a more complete interactome network. This interactome modeling strategy revealed insights into C. elegans centrosome function and is applicable to other biological processes in this and other organisms., Journal Article, Research Support, N.I.H. Extramural, Research Support, Non-U.S. Gov't, Research Support, U.S. Gov't, Non-P.H.S., info:eu-repo/semantics/published

Summary High-content screening for gene profiling has generally been limited to single cells. Here, we explore an alternative approach—profiling gene function by analyzing effects of gene knockdowns on the architecture of a complex tissue in a multicellular organism. We profile 554 essential C. elegans genes by imaging gonad architecture and scoring 94 phenotypic features. To generate a reference for evaluating methods for network construction, genes were manually partitioned into 102 phenotypic classes, predicting functions for uncharacterized genes across diverse cellular processes. Using this classification as a benchmark, we developed a robust computational method for constructing gene networks from high-content profiles based on a network context-dependent measure that ranks the significance of links between genes. Our analysis reveals that multi-parametric profiling in a complex tissue yields functional maps with a resolution similar to genetic interaction-based profiling in unicellular eukaryotes—pinpointing subunits of macromolecular complexes and components functioning in common cellular processes. PaperFlick