Wnt/Wingless signaling controls many fundamental processes during animal development. Wnt transduction is mediated by the association of beta-catenin with nuclear TCF DNA binding factors. Here we report the identification of two segment polarity genes in Drosophila, legless (lgs), and pygopus (pygo), and we show that their products are required for Wnt signal transduction at the level of nuclear beta-catenin. Lgs encodes the homolog of human BCL9, and we provide genetic and molecular evidence that these proteins exert their function by physically linking Pygo to beta-catenin. Our results suggest that the recruitment of Pygo permits beta-catenin to transcriptionally activate Wnt target genes and raise the possibility that a deregulation of these events may play a causal role in the development of B cell malignancies.

Members of the Wnt/Wingless (Wg) family of signalling proteins organize many aspects of animal development by regulating the expression of particular target genes in responding cells. Recent biochemical studies indicate that the vertebrate HMG-domain proteins Lef-1 and XTcf-3 can physically interact with beta-catenin, a homologue of Drosophila Armadillo (Arm), the most downstream component known in the Wnt signal transduction pathway. However, these studies do not address whether the endogenous Lef/Tcf family members are required in vivo to transduce Wnt signals. Using genetic methods in Drosophila, we define a new segment polarity gene, pangolin (pan), and show that its product is required in vivo for Wg signal transduction in embryos and in developing adult tissues. In addition, we show that pan encodes a Lef/Tcf homologue and provide evidence that its protein product binds to the beta-catenin homologue Armadillo in vivo. Finally, we demonstrate that Pan functions downstream of Arm to transduce the Wg signal. Thus, our results indicate that Pan is an essential component of the Wg transduction pathway and suggest that it acts directly to regulate gene transcription in response to Wg signalling.

Understanding how proteins and their complex interaction networks convert the genomic information into a dynamic living organism is a fundamental challenge in biological sciences. As an important step towards understanding the systems biology of a complex eukaryote, we cataloged 63% of the predicted Drosophila melanogaster proteome by detecting 9,124 proteins from 498,000 redundant and 72,281 distinct peptide identifications. This unprecedented high proteome coverage for a complex eukaryote was achieved by combining sample diversity, multidimensional biochemical fractionation and analysis-driven experimentation feedback loops, whereby data collection is guided by statistical analysis of prior data. We show that high-quality proteomics data provide crucial information to amend genome annotation and to confirm many predicted gene models. We also present experimentally identified proteotypic peptides matching approximately 50% of D. melanogaster gene models. This library of proteotypic peptides should enable fast, targeted and quantitative proteomic studies to elucidate the systems biology of this model organism.

The nematode Caenorhabditis elegans is a popular model system in genetics, not least because a majority of human disease genes are conserved in C. elegans. To generate a comprehensive inventory of its expressed proteome, we performed extensive shotgun proteomics and identified more than half of all predicted C. elegans proteins. This allowed us to confirm and extend genome annotations, characterize the role of operons in C. elegans, and semiquantitatively infer abundance levels for thousands of proteins. Furthermore, for the first time to our knowledge, we were able to compare two animal proteomes (C. elegans and Drosophila melanogaster). We found that the abundances of orthologous proteins in metazoans correlate remarkably well, better than protein abundance versus transcript abundance within each organism or transcript abundances across organisms; this suggests that changes in transcript abundance may have been partially offset during evolution by opposing changes in protein abundance.

Pollen, the male gametophyte of flowering plants, represents an ideal biological system to study developmental processes, such as cell polarity, tip growth, and morphogenesis. Upon hydration, the metabolically quiescent pollen rapidly switches to an active state, exhibiting extremely fast growth. This rapid switch requires relevant proteins to be stored in the mature pollen, where they have to retain functionality in a desiccated environment. Using a shotgun proteomics approach, we unambiguously identified ∼3500 proteins in Arabidopsis pollen, including 537 proteins that were not identified in genetic or transcriptomic studies. To generate this comprehensive reference data set, which extends the previously reported pollen proteome by a factor of 13, we developed a novel deterministic peptide classification scheme for protein inference. This generally applicable approach considers the gene model–protein sequence–protein accession relationships. It allowed us to classify and eliminate ambiguities inherently associated with any shotgun proteomics data set, to report a conservative list of protein identifications, and to seamlessly integrate data from previous transcriptomics studies. Manual validation of proteins unambiguously identified by a single, information-rich peptide enabled us to significantly reduce the false discovery rate, while keeping valuable identifications of shorter and lower abundant proteins. Bioinformatic analyses revealed a higher stability of pollen proteins compared to those of other tissues and implied a protein family of previously unknown function in vesicle trafficking. Interestingly, the pollen proteome is most similar to that of seeds, indicating physiological similarities between these developmentally distinct tissues.