Current Genomics - Volume 3, Issue 2, 2002

C. elegans is entering the postgenomic era, which is expected to provide an unprecedented basis for a functional description of this simple model organism at the gene level. Reviews by G. Jansen on gene inactivation in C. elegans, F. Piano and K. Gunsalus on RNAibased functional genomics in C. elegans, JF. Rual et al. on the C. elegans interactome mapping project., V. Reinke on defining development through gene expression profiling, and E.M. Schwarz et al. on C. elegans databases (Current Genomics vol. 3, 2002) present detailed information suggesting that the horizontal integration of different genome-wide biological tags may profoundly impact on the practice of evolutionnary developmental biology research and biomedical research.

Reverse genetics in Caenorhabditis elegans has had an enormous boost in the last decade. From the mere ability to inactivate genes and make transgenic animals in the late 1980s or early 1990s, this field has evolved to genome wide approaches that aim to inactivate all C. elegans genes and determine all expression patterns. Since this luxury position has not yet been attained, we still have to go through these experiments ourselves. Two different approaches exist to inactivate genes in C. elegans. One approach uses PCR to select for deletions in the gene of interest. Deletions can be generated using transposons or chemical mutagenesis. An alternative, or rather complementary, technique inactivates genes through RNA interference (RNAi). In this review I will describe these techniques and discuss their advantages and disadvantages. Finally, I will give an update on the current status of the genomic knockout projects.

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.

With the near availability of a cloned Caenorhabditis elegans ORFeome, the development of a high-throughput worm interactome mapping project has now become feasible. After reviewing the increasing interest for C. elegans as a model organism, from ”classical“ biology to the post-genomic era, this article presents the early steps accomplished for the generation of a C. elegans protein interaction map using the twohybrid system. Different approaches have been examined in order to determine the appropriate strategy to screen protein-protein interactions on a large scale. Our version of the two-hybrid system has been used to generate prototype maps for 4 different C. elegans biological modules (vulval development, proteasome, DNA repair / cell cycle and dauer). Those pilot projects helped us developing experimental procedures to avoid most false positive protein interactions while covering a satisfactory proportion of geniune interactions. In silico analysis and experimental validation of the potential protein interactions have already demonstrated biological relevance for some of the networks of interactions obtained.

For an ever-increasing number of species, the completed genomic sequence is available, providing a means to identify all the genes encoded in a genome. The functional relationships between these genes must be defined in order to generate a cohesive understanding of the molecular events that direct metazoan development. The model organism C. elegans, with its completed genomic sequence, defined cell lineage and robust genetics, provides an excellent opportunity to reconstruct the genetic relationships that underlie the development of a relatively simple animal. The change in expression of every predicted gene in the genome can be quantified under defined experimental conditions using DNA microarrays, thus providing a ”molecular signature“ of particular developmental processes. Because DNA microarray analysis does not rely upon detection of a gross morphological phenotype, genes whose function escapes identification in mutation screens can now be associated with different developmental processes. Together, C. elegans and DNA microarrays are a powerful combination with which to attack complex problems in developmental biology and work toward a more complete understanding of the underlying genetic networks governing development.

Caenorhabditis elegans (C. elegans) allows exhaustive analysis of animal biology, in detail once thought possible only for microbial organisms. This detail includes the entire cellular lineage from egg to adult, the complete adult cell complement, a full wiring diagram of the nervous system, and several hundred gene mutants that produce classical phenotypes. With the rise of genomic sequencing and functional genomics, analysis of C. elegans has grown to include reverse genetics, microarray assays of gene expression, and protein-protein interactions. Such studies should soon touch upon all ∼19,400 predicted C. elegans proteins and their detailed expression patterns. This should illuminate, but also complicate, our understanding of C. elegans cells and genetic pathways. Moreover, the newer forms of analysis are explicitly directed at acquiring data that are highly valuable with computational analysis but unintelligible without it. We describe the existing data sets and databases for C. elegans, and discuss ways in which large C. elegans data sets may be integrated.