Pliny A Smith et al. (2004) West Coast Worm Meeting "Genome-wide analysis of pharynx development"

Susan E Mango, Pliny A Smith, Chris Armstrong, Dirk McMurray, Mike Overfield, Marc Vidal, Tala Fakhouri

[West Coast Worm Meeting, 2004]

We have undertaken a functional genomics approach to identify genes required for organogenesis of the pharynx. 376 candidate pharyngeal genes were examined by RNAi or high through-put yeast two hybrid screening to develop a pharyngeal gene network. For RNAi, we developed a sensitized screening method using viable smg-1 ; pha-4 double mutants. With this approach, we identified 88 genes (23%) with an RNAi phenotype, of which 60 (68%) had an obvious pharynx phenotype. The pharyngeal phenotypes fell into three categories: those that affected cell fate decisions, those with altered morphogenesis and those with apparent normal development but poor function. To establish the pharynx interactome, we tested 236 pharyngeal proteins (baits) by yeast two hybrid against the worm genome (prey) and discovered 354 interacting proteins. Two lines of evidence suggest the interactome was successful. First, we validated some interactions using the co-affinity purification method. Second, we observed hubs of interacting proteins that localized to the same subcellular compartment or functioned in the same process. For example, there are hubs of nuclear proteins, including one associated with the developmental transcription factor PHA-4, and hubs of structural proteins, such as those involved in muscle function. Intriguingly, the pharyngeal gene network preferentially uses genes conserved among multicellular organisms or worms. This enrichment is at the expense of ancient genes that have orthologues in Saccharomyces cerevisiae as well as animals. Only 11% of genes from the pharyngeal gene network are ancient in origin, compared to 23% of genes from the worm interactome network. This reduction suggests that evolution of a metazoan structure, an organ, relies on inventing genes that are metazoan-specific. We have begun to investigate individual components of the pharyngeal gene network in greater detail. For example, inactivation of the T box transcription factor tbx-2 leads to a loss of anterior pharyngeal muscles, suggesting tbx-2 is required to pattern the pharynx primordium. A small cohort of genes can suppress pha-4 loss-of-function mutations, suggesting they are negative regulators of PHA-4 activity or expression. Our current goal is to probe the pharyngeal gene network further and understand the regulatory logic that underlies growth and development of the pharynx.

Zhiping Weng et al. (2005) International Worm Meeting "A C. elegans transcription regulatory network of the digestive tract."

Lynn Doucette-Stam, Zhiping Weng, Natalia Martinez, Wanyuan Ao, Ahmed Elewa, Christian Grove, Dirk McMurray, Bart Deplancke, Reynaldo Sequerra

[International Worm Meeting, 2005]

The control of gene expression is highly combinatorial: most transcription factors (TFs) regulate the expression of multiple genes, and most genes are themselves regulated by multiple TFs. Interactions between TFs and their target genes can be visualized in transcription regulatory networks. Such networks allow insights into higher order regulation of gene expression, for example by the identification and characterization of network <sym08>hubs<sym09> and network motifs. Here, we present a transcription regulatory network of the C. elegans digestive tract. To identify TF-target gene interactions in a high-throughput manner, we developed a Gateway-compatible yeast one-hybrid (Y1H) system. This Y1H system can be used to identify TFs that can bind to a gene promoter. Our Y1H system is compatible with ORFeome (for TF-encoding ORFs) and Promoterome (for target gene promoters) resources, and allows the identification of TF-target gene interactions from a <sym08>gene centered<sym09> perspective. Thus, this system provides information that is distinct from, but complementary to data obtained from <sym08>TF centered<sym09> chromatin-immunoprecipitation-based methods. We used our Y1H system to identify TF-promoter interactions for 180 genes involved in development of the worm digestive tract. We identified >300 TF-DNA interactions and visualized these into a transcription regulatory network. The resulting network is highly connected and contains several TF and promoter <sym08>hubs<sym09> (e.g. TFs that bind to many genes and vice versa). We characterized several TF hubs in more detail. For instance, we inspected the collection of DNA fragments they can interact with to predict consensus TF binding sites. We also identified several other network motifs, including feed forward loops, regulator chains and single- and multi-input motifs. We have begun to experimentally test several hypotheses derived from this network. Taken together, the Y1H system provides a powerful tool for the high-throughput mapping of transcription regulatory networks in metazoan systems.

H Van Luenen et al. (1999) International C. elegans Meeting "World-wide worm SNPs: Dissecting the molecular evolution of the species using a high density SNP map"

R Plasterk, R Koch, H Van Luenen

[International C. elegans Meeting, 1999]

We would like to reconstruct the history of the C. elegans species at the genome level, therefore we sampled the genomes of four natural isolates (strain CB4857 isolated in Claremont, California, RC301 from Freiburg, Germany, TR403 from Madison, Wisconsin and AB1 from Adelaide, Australia) for single nucleotide polymorphisms (SNPs). Random genomic DNA fragments from the 4 strains were shotgun cloned and sequenced. There was no selection for transcribed or non-transcribed regions of the genome. In total we sequenced 1572 clones resulting in over 1 Mb of sequence information. The sequences are compared to the canonical Bristol N2 sequence to ask the question whether the clone maps to a unique sequence, and -if so- whether it contains polymorphisms. Once a SNP is identified we check other strains for the presence of the same polymorphism by PCR amplification and sequence analysis. In an initial experiment we found approximately one SNP per 3000 bp sequenced. The SNPs are randomly spread over the genome. Based on these observations we expect to find approximately 500 SNPs, one in every 200 kb. In the initial experiment we found, as expected, that several SNPs initially detected in one strain were also present in some but not all other strains. For example: a T in the Australian AB1, is a G at the same position in Bristol N2 in cosmid K10D2 at position 27946, and we found it to be like AB1 in the Californian CB4857 strain and the German RC301 strain, while the TR403 strain from Wisconsin resembles the Bristol N2 strain. Thus different patches of the genome have different ancestors. With our high density SNP map we will generate a genome map for each isolate which will show how each genome is patched together from a limited set of parental strains. The SNP's will be added to ACeDB, and can also be used as markers on the genetic map. They can be recognised by PCR followed by sequencing, but we also found that the SNPs we looked at could be visualised by SSCP analysis. We thank Jane Rogers and Amanda McMurray for their assistance in sequencing the clones.