Cildb: a knowledgebase for centrosomes and cilia

Abstract

Ciliopathies, pleiotropic diseases provoked by defects in the structure or function of cilia or flagella, reflect the multiple roles of cilia during development, in stem cells, in somatic organs and germ cells. High throughput studies have revealed several hundred proteins that are involved in the composition, function or biogenesis of cilia. The corresponding genes are potential candidates for orphan ciliopathies. To study ciliary genes, model organisms are used in which particular questions on motility, sensory or developmental functions can be approached by genetics. In the course of high throughput studies of cilia in Paramecium tetraurelia, we were confronted with the problem of comparing our results with those obtained in other model organisms. We therefore developed a novel knowledgebase, Cildb, that integrates ciliary data from heterogeneous sources. Cildb links orthology relationships among 18 species to high throughput ciliary studies, and to OMIM data on human hereditary diseases. The web interface of Cildb comprises three tools, BioMart for complex queries, BLAST for sequence homology searches and GBrowse for browsing the human genome in relation to OMIM information for human diseases. Cildb can be used for interspecies comparisons, building candidate ciliary proteomes in any species, or identifying candidate ciliopathy genes.Database URL:http://cildb.cgm.cnrs-gif.fr.

Figure 1.

Orthology calculations and links to ciliary studies underlying Cildb. The 18 species analyzed are represented as circle arcs proportional to the size of the proteome, in red when ciliary studies exist (delineated as ticks outside the circle), in orange when centriole/cilia exist, but without high throughput studies, and in blue when no cilia or centriole exists (At: Arabidopsis thaliana; Ce: Caenorhabditis elegans; Ci: Ciona intestinalis; Cr: Chlamydomonas reinhardtii; Dd: Dictyostelium discoideum; Dm: Drosophila melanogaster; Dr: Danio rerio; Ec: Escherichia coli; Gl: Giardia lamblia; Hs: Homo sapiens; Mm: Mus musculus; Pf: Plasmodium falciparum; Pt: Paramecium tetraurelia; Rn: Rattus norvegicus; Sc: Saccharomyces cerevisiae; Sp: Schizosaccharomyces pombe; Tb: Trypanosoma brucei; Tt: Tetrahymena thermophila). The colors of the ticks for the studies are explained in the inset to distinguish proteomic, transcriptomic and comparative genomic studies. Andersen (35); Arnaiz [this article for proteomics, or Arnaiz et al. (in preparation) for transcriptome analysis]; Avidor-Reiss (36); Blacque (37); Broadhead (38); Chen (39); Efimenko (40); Keller (41); Kilburn (42); Laurençon (43); Li (16); Liu (44); Mayer (45); Ostrowski (19); Pazour (26); Smith (18); Stolc (46). For each species, the whole proteome was compared by BLASTp to itself and to all the other ones, in order to apply our three orthology filters (Inparanoid, Inparanoid + filtered best hits, BLASTp cutoff), as described in experimental procedures. The high throughput ciliary studies were then remapped to the proteins, so that links between orthology and ciliary properties are created. The genome versions and the origin of the ciliary study data in Cildb are reported in Supplementary Table S1. The human genome is also linked to the OMIM database in which genetic disorders appear.

Figure 2.

Schema of the structure and possibilities of use of Cildb. The orthology calculations and links to ciliary studies and to OMIM are at the center of Cildb. To access the data, three possibilities of queries are offered: BioMart query using key words or properties of proteins (orthology, ciliary studies, etc.); BLAST of a sequence; browsing human chromosomes with GBrowse. The BioMart (22) tool of Cildb allows the user to build a complex query using a system of filters and to display the information, pre-calculated in the database (PostgreSQL mart database). The result is a list of proteins matching the different criteria. Each protein in the list is linked to a ‘Protein page’, which describes all the information related to this protein. Data in the table can be exported as xls or tsv files, but also the corresponding sequences as fasta files. The BLAST tool uses a search by sequence alignment with an NCBI BLAST interface (23), regular BLAST, PSI-BLAST and PHI-BLAST can be performed. The user can select proteins in the BLAST output and analyze them with BioMart or go to their protein pages. The GBrowse tool (MySQL Bio::DB::SeqFeature::Store database) allows navigation through the human chromosomes to see the genes and proteins with their links to orthologs, ciliary studies and OMIM entries. The user can also analyze the proteins with BioMart or go to the protein page. The protein page itself contains a summary of all the information contained in Cildb for the protein, with internal links to the orthologs, to a BioMart interface, to Cildb BLAST links and to GBrowse for human proteins, and external links to the genuine databases for the accession ID, to OMIM entries, to BLAST at NCBI and to multiple alignment servers.

Figure 3.

Screenshot of a typical query page of Cildb, here using the Homo sapiens whole proteome as a dataset and displaying the categories of filters that can be used for the query.

Figure 4.

Comparison of ciliary proteomic studies from different unicellular models. Using Cildb, we compared the proteomic studies of purified cilia/flagella of Chalmydomonas, Paramecium, Tetrahymena and Trypanosoma. The protocol was the same for each study: (i) Build a BioMart ‘new query’ in Cildb using the ‘Inparanoid and filtered best hits’ as homology method. (ii) Choose the species in which the ciliary study examined was conducted (e.g. Chlamydomonas). (iii) Filter proteins identified in the relevant proteomic study (e.g. Pazour’s proteomics) with medium stringency confidence (two or more different peptides). (iv) Select the ‘number of ciliary studies in all species with medium confidence’ as an attribute. (v) Count and display the results as xls tables. In the first column of each graph, the total height represents the number of proteins identified in the study, the dark blue proteins are those found as ciliary in at least another study, pale blue proteins are those found as ciliary only in this study, and grey proteins are those annotated as ribosomal proteins or histones, representing likely contaminants of the ciliary preparation. (vi) Filter proteins using the same criteria as in (iii) as well as the existence of ‘orthologs’ in each species used in this comparison (the other protists plus human). This represents as many queries as species examined and gives the height of the green bars for each species (the grey part corresponding to ribosomal proteins and histones). (vii) Filter as in (vi) and look in the results for proteins identified by ciliary proteomics in the target species [e.g. this study for Paramecium or Broadhead et al. (38) for Trypanosoma], represented as dark green, whether they have been found as ciliary in other species (medium green) or not (pale green).

Figure 5.

Finding novel ciliopathy candidate genes with Cildb. Starting successively with the proteomes of three species, Paramecium tetraurelia, Homo sapiens and Chlamydomonas reinhardtii, we applied the same BioMart filters, ‘at least 3 ciliary evidences with medium confidence’ and ‘has a human ortholog linked to a disorder reported in OMIM’. As a result, we extracted the OMIM entries linked to a human disorder, as revealed by the filter applied to each species. Of the 2358 disorders present in the GeneMap section of OMIM, 216 passed the filter and 20 of the 42 known ciliopathies with links with a disorder entry in OMIM (Table 1) were found. The 2142 other disorders include the 22 remaining known ciliopathies. This is not surprising since many ciliopathy genes are not revealed by high throughput studies. Nevertheless ciliopathy genes are highly enriched by our filter (1/10 versus 1/100). Detailed examination of the other disorders provided by the filter allowed us to propose 11 of them as candidate ciliopathies (see Table 1). Inset: the filter used results in linking OMIM entries to ciliary studies, however by passing through their association with a human gene. Three configurations can provide these links. (i) the human protein is directly concerned by a high throughput study in man. (ii) the human protein displays a ciliary evidence through orthology with a ciliary protein in another species. (iii) a non-human protein (sp2) can have a ciliary evidence through orthology with another species (sp3) and a link to OMIM through orthology with a human protein. In some cases, although linked to Sp2, the human and Sp3 proteins have no direct links, so that the human protein itself is not flagged as ciliary, whereas the associated OMIM entry is.