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Centre of Marine Sciences, Universidade do Algarve, Campus de Gambelas, 8000-810 Faro, Portugal
1 British Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET, UK
2 UPRES Biodiversité, Faculté des Sciences St Charles, 3 Place Victor Hugo, case 17, 13331 Marseilles cedex 3, France
(Requests for offprints should be addressed to M S Clark; email: mscl{at}bas.ac.uk.)
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Abstract |
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Introduction |
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Genomic analyses of GPCRs have largely concentrated on categorisation into clades and families (Attwood & Findlay 1994, Kolakowski 1994, Horn et al. 1998, Fredriksson et al. 2003). This overall classification has changed little over the years and the most commonly used is the A–F (1–5) system (Attwood & Findlay 1994, Kolakowski 1994, Horn et al. 1998): A, rhodopsin-like; B, secretin-like; C, metabotrophic glutamate/pheromone; D, fungal pheromone; E, cAMP (Dictyostelium); F, frizzled/smoothened family). However, there are problems with global-type analyses: not all classes of GPCR receptors exist in all organisms and some families are currently represented by a very limited number of species. So although a number of in silico phylogenetic studies have been conducted (Josefsson 1999, Graul & Sadee 2001, Fredriksson et al. 2003), it is virtually impossible to make global predictions about the evolutionary origins of the GPCRs. Some analyses have concluded that there is potentially a single common ancestor for all GPCRs (Graul & Sadee 2001, Fredriksson et al. 2003), while others do not disregard multiple origins and indicate that it is not possible to strictly exclude either convergent evolution or combinatorial evolution (Fryxell 1995, Bockaert & Pin 1999, Josefsson 1999) as contributing factors.
Looking at some of the different classifications, the members of one group remain fairly constant: the secretin family (also known as family B, family 2). The family name arose because secretin was the first ligand to be isolated from this group by Bayliss and Starling (1902). These receptors are activated by large peptides such as hormones and neuropeptides and are characterised by the existence of a large N-terminal domain, with at least six highly conserved cysteines that are proposed to be involved in ligand binding. The ligands are well characterised and have been isolated from a whole range of organisms such as tunicates, insects and vertebrates (reviewed in Campbell and Scanes (1992) and Sherwood et al.(2000)). In mammals this family comprises receptors for the peptides: secretin, vasoactive intestinal peptide (VIP), pituitary adenylate cyclase-activating polypeptide (PACAP), corticotrophin releasing factor (CRF), growth hormone releasing hormone (GHRH), parathyroid hormone (PTH), PTH-related peptide (PTHrP), glucagon, glucagon-like peptide (GLP), calcitonin and calcitonin gene-related peptide (CGRP). While the ligands have been isolated and comprehensively studied, the majority of the receptors are poorly characterised with sequences mainly available from the higher vertebrates.
To date our research has focussed on the isolation and characterisation of ligands and receptors from this family in the teleost fish Takifugu rubripes (Power et al. 2000, 2002, Clark et al. 2002, Cardoso et al. 2003a,b, 2004). Most of these were identified either via heterologous hybridisation or degenerate PCR techniques. However, the availability of the Takifugu genome sequence (Aparicio et al. 2002) has enabled comprehensive data-mining for teleost orthologues of this receptor family and characterisation of additional family members. Here we present the results of that data-mining and also the searches for orthologues in other species where genome information is publicly available.
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Methods |
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To supplement the secretin family of GPCRs from the publicly annotated Swissprot and Trembl datasets each of the Takifugu receptor genes were used to search for similar genes in the zebrafish, medaka, Tetraodon, Caenorhabditis elegans, Drosophila melanogaster, Ciona (Ciona intestinalis) and Saccharomyces cerevisae databases (Table 1
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). Data on some of the TM domains was incomplete due to either gaps in the genomic sequence or regions unidentifiable using BLAST sequence similarity searching. Therefore data analysis was restricted to TM regions common to all identified genes (TMs 2, 4, 5 and 6) in Takifugu. Because of the conservative motif in the TM domain, it was difficult to postulate that no exon shuffling had occurred in this gene family (i.e. that TM domain 1 for species 1 was the orthologue of TM domain 1 for species 2) (Fig. 1) (Taylor & Agarwal 1993, Patthy 1999). Considering this potential alignment artefact, we developed the following approach: in a preliminary analysis all the TM domains for each sequence were extracted and separated, and a multiple alignment was constructed using Clustal W (Thompson et al. 1994) with the default parameters (382 TM domains from 98 species). Phylogenetic trees were constructed based on neighbor-joining (NJ) (Saitou & Nei 1987), with Poisson correction distance and pairwise deletion comparison (midpoint rooting). The monophyly of each TM domain was distinguished by high distance values and supported by high bootstrap proportion (BP>69%) (Felsenstein 1985). The internal branch test was used when the number of taxa was higher than the number of sites (Sitnikova 1995).
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In-depth phylogenetic analysis concentrated on the PACAP family members (PAC1R, VPAC1R and VPAC2R). Branch lengths differed considerably between different receptor groups, so, as a test, the nucleotide sequences of the designated TM domains were compared with the protein sequences in all members of the VPAC2 and PAC1 receptors. Comparison of branch length differences produced using DNA and protein sequences from the PAC1 and VPAC2 receptors was analysed using both the neighbor-joining (Phylip neighbor programme) and a neighbor-joining consensus tree (Phylip seqboot, neighbor and consense programmes) with 500 bootstrap replicates and also the neighbour-joining method (Saitou & Nei 1987) via the PHYLO_WIN interface v1.2 (Galtier et al. 1996) Phylowin with 500 bootstrap replicates. The tree was produced using the postscript output from the Phylowin programme. ClustalW was used to calculate percentage identities for the consensus sequences.
For the more rigorous cDNA nucleotide sequences were downloaded from the databases, coding sequence extracted using extractseq (EMBOSS) and aligned using clustalW. To minimise long branch length artefacts, the most 5' and 3' ends of each sequence were removed, as these are the most evolutionary diverged regions. The sequences were converted to Phylip interleaved format using the EMBOSS (Rice et al. 2000) seqret programme for analysis using the Phylip package (Felsenstein 1985). Transition/transversion ratios were calculated using TREE-PUZZLE v.5. A DNA distance matrix was calculated using the Phylip (v3.6 (alpha 2)) dnadist programme v3.6a.2.1. Default parameters were used except D (D=distance) was set to the Kimura-2-parameter method and the transition/transversion ratio set to 1.23. Phylogenetic trees were constructed from the nucleotide data using maximum likelihood (Phylip dnaml programme with global rearrangements), neighbor-joining (Phylip neighbor programme) and a neighbor-joining consensus tree (Phylip seqboot, neighbor and consense programmes) with 500 bootstrap replicates. Trees were drawn with Treetool (Olsen et al. 1992), saved in NEWICK format and produced as .gif output using the Phylodendron tree-print programme: http://www.es.embnet.org/Doc/phylodendron/treeprint-form.html.
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Results |
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). Orthologues of the vertebrate secretin receptors were identified with the exception of secretin, GIP and GLP2. Duplicated genes were identified for seven of the family members, namely the receptors for PACAP/VIP, calcitonin, CGRP, GHRH and PTHrP/PTH (Fig. 2).
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), of which four clones (Cin 0372, 0752, 0005A and 0005B) clustered most strongly with the VIP/GHRH/PTR receptors. Although both the Tetraodon and zebrafish genome databases comprise almost 6x genome coverage each, identification of secretin family GPCR members was limited. Sixteen members were identified in Tetraodon (in ten of which the full complement of TMs 2, 4, 5 and 6 were deduced) and only five were identified in zebrafish (Table 2). Of the zebrafish sequences, it was only possible in three to deduce TMs 2, 4, 5 and 6 and one (ZC163F10) was orthologous to the PTR1 gene already in the protein databases. The medaka genome data so far comprise only 0.9x coverage and all of the contigs were too small to produce meaningful data for this project.
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). It clearly shows good support for there being three main groups within the secretin family of GPCR (CALR/CGRP, CRF1/CRF2 and VPAC/PAC1/secretin/GHRH/PTH/GLP/GIP). Bootstrap values (not shown) provided strong support for each of the distinct clusters, but relatively poor support linking the different groupings. Principal component analysis showed that the CALR/CGRP and CRF1/CRF2 arms were clearly distinct from the rest of the tree (Fig. 3), as were all the C. elegans and Drosophila receptors. Where the Ciona receptors grouped outside the main families (e.g. Cin0070, Cin0093, etc.), these too showed as separate blocks on the principal component analysis.
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). This potentially indicates that these sequences are undergoing different rates of evolution. The use of DNA sequences, as opposed to protein sequences discriminated the positions of the chicken (Gga) and Xenopus (Xla) PAC1 receptors better. Using DNA sequences, the receptors of these two organisms clustered together which is more logical from an evolutionary point of view than the scattered distribution produced using the protein sequences. In the latter the chicken PAC1 receptor clustered with the fish PAC1A receptors while the Xenopus PAC1 receptor clustered with the Takifugu PAC1B.
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Discussion |
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This whole receptor family was originally named after the first ligand identified: secretin (Bayliss & Starling 1902). Therefore, it is slightly ironic that so far this is the only receptor still to be identified in Takifugu (and indeed the other databases used). This is in spite of extensive database searching, library screening and degenerate PCR experiments. To further investigate this, screening of the Fugu Genome Consortium database for the ligand was also carried out, with negative results. In fact, the secretin receptor has so far only been characterised in mammals. In contrast, the gene for the ligand, secretin, has been identified in both mammals and birds (Sherwood et al. 2000). In the former group secretin is a potent stimulant of pancreatic secretion. In the latter group, avian and mammalian VIPs are more potent stimulants of the avian pancreas than secretin (Dockray 1975, 1979). Further work aimed at establishing when the secretin receptor first arose in tetrapods will be required. Two principal models exist for the evolution of secretin (Bell 1986, Ohkubo et al. 1992). One suggests that secretin and VIP shared a common ancestor and secretin arose recently (310 million years ago) by gene duplication, the other suggests that it evolved much earlier from an ancestral glucagon ligand (Campbell & Scanes 1992). Assuming a certain level of co-evolution of ligand and receptor, we propose that the absence of a secretin receptor in Takifugu favours the former model with the divergence of bony fish from the tetrapods (approximately 405 million years ago) occurring prior to the duplication that gave rise to secretin. It is interesting that in all of the phylogenetic trees generated in the present study each receptor family shows a very clear fish/bird/amphibian–mammalian split. So although most of the receptors evolved prior to the appearance of the fishes 450 million years ago, they may have evolved along distinct lines in the different phyla with the secretin receptor evolving later in response to a specific demand of the physiological adaptations necessary for the colonisation of the terrestrial environment. As these receptors do not appear to be present in the fungal lineage, but are present in the nematode lineage, it is possible to determine that they arose between 1600 and 1200 million years ago (Wang et al. 1999).
It is now well documented that fish contain a large number of duplicated genes (Wittbrodt et al. 1998). It is therefore no great surprise that a number of duplicated secretin family receptors are also present in the Takifugu genome. Orthologues were identified in Tetraodon for the duplicated PTR1, VPAC1A, VPAC1B, GHRH1A, PAC1A and VPAC2B Takifugu receptors. Several of the Tetraodon sequences and two zebrafish sequences also appeared to have Takifugu orthologues in the CALR/CGRP and GIP/GLR groupings. However, topology within these families was less well defined and therefore accurate determination of duplicates is difficult.
The limited data available from Takifugu and the other fish species, indicates that the secretin family duplications are specific to the teleost lineage. The mechanism by which the piscine ‘extra’ genes were generated still remains an area of contention between two hypotheses. On the one hand, it is suggested that the teleost fish underwent a third round of whole genome duplication (Amores et al. 1998, Wittbrodt et al. 1998, Postlethwait et al. 2000, Taylor et al. 2003, Christoffels et al. 2004, Naruse et al. 2004, Vandepoele et al. 2004) with subsequent gene loss; alternatively, it is suggested that they were subjected to a whole range of smaller chromosomal, segmental or gene-wide duplications at different times through their evolutionary past (Robinson-Rechavi et al. 2001a,b). However, it is probably fair to say that the datasets available at the moment are still too restricted, particularly with regard to the range of fish species for which there is genomic information available. Therefore it is not yet possible to determine accurately with any statistical significance which of the two duplication processes was involved in the evolution of the ‘extra’ genes. However, these data, with their preponderance of additional Takifugu genes do provide further support towards the hypothesis of an extra whole genome duplication having taken place in the teleost ancestor in line with the findings of Amores et al. 1998, Wittbrodt et al. 1998, Postlethwait et al. 2000, Taylor et al. 2003, Christoffels et al. 2004, Naruse et al. 2004 and Vandepoele et al. 2004. While the issue of an extra whole genome duplication event in fish remains a contentious issue, the preponderance of polyploid genomes within the fish certainly complicates genome analysis and a resolution of this issue (Lim et al. 1975, Ferris & Whitt 1977, Schmidtke et al. 1979, Allendorf & Thorgaard 1984, Larhammar & Risinger 1993, 1994). It also raises a further question, as to why these events occurred and the benefits for the organisms involved. It is generally acknowledged that gene duplication has played a significant role in the metazoan radiation (Ohno 1970). Further duplications in the fish could have fuelled their incredible speciation, as they comprise over half of all vertebrate species and, unlike mammals, their genomes (and the ploidy levels) are not constrained by a rigid sex chromosome system. The procession of duplicated genes with differential expression patterns and functional differences (reviewed in Postlethwait et al. (2004)) may also, to a certain extent, obviate the need for alternative splicing. The duplications identified here enhance the dataset of duplicated fish genes and therefore will be available for more global analyses of this evolutionary process in fish. The identification of scaffolds will also allow exploitation of the Takifugu genes by groups with specific interests in functional characterisation of this gene set.
Without a doubt, there are problems with global GPCR analyses (similar to those presented here) when trying to determine evolutionary events and timings, the main one being that not all receptors are present in all species (for example, clan D which only comprises the fungal pheromone receptors) (Donnelly 1997) and some groups contain duplicated genes. GPCRs are present in large numbers in the genome (1000–2000 members in vertebrates and approximately 1100 in C. elegans (Bargmann et al. 1998)). Because of these huge numbers, some of the analyses have only been carried out on human data (Fredriksson et al. 2003) and also do not include non-GPCR receptors (Josefsson 1999, Fredriksson et al. 2003). So it is entirely possible that by only using GPCRs in the dataset, artifactual groupings are produced, simply because there are no alternatives. In the present work, phylogenetic analysis of the secretin receptor family alone produces three distinct groupings of CALR/CGRP, CRF1/CRF2 and VPAC1R/VPAC2R/PAC1R/secretin/GHRH/PTR/GLP/GIP. This is mirrored in other broader phylogenetic analyses (Josefsson 1999, Fredriksson et al. 2003). In the former analysis, the calcitonin, PACAP and glucagon receptors, while belonging to the same clade, branch separately. The more comprehensive analysis of Fredriksson et al.(2003) produces four branches within the same clade, comprising: (i) VPAC1R/VPAC2R/PAC1R/SCTR/GHRH; (ii) CRF; (iii) CALR; and (iv) GLP1/GLP2/GIP/GLR/PTH2/PTR. Global analyses can provide statistical confirmation of the main receptor family groups (e.g. GHRH, VPAC1, VPAC2, etc.). However, it must be remembered that such analyses are very restricted as regards species content, which can influence the tree topography. The relatedness between the different families is difficult to prove with any statistical certainty and principal component analysis of secretin receptor family members alone indicates no relationship between these three groupings identified in this analysis. Therefore once the datasets are restricted and multiple species added, the differences between the receptor families magnify, indicating possible polyphyly or convergent evolution within the designated clade.
Reducing the content of the tree, as regards the different numbers of families, does not resolve this issue as confidence levels of topology are still weak between the different family members (data not shown) although, as stated above, within families they are very high. This situation does not change whether examining protein or DNA data; however it is important to use DNA sequences when higher resolution is required. This enables a more accurate measure of variation and is particularly useful when considering the evolution of closely related receptor families. This is exemplified by the amino acid/DNA comparisons of the PAC1R and VPAC2R receptors. PAC1R is highly conserved at the protein level, but actually has a similar rate of variability at the DNA level when compared with VPAC2R. Therefore our more in-depth analysis concentrated only on the PAC1R, VPAC1R and VPAC2R family which share a common set of ligands (VIP and PACAP), but with different affinities depending on the receptor (Harmar et al. 1998). These are found in the brain and gut and share a certain level of common functionality. The most closely related gene family to the PACAP receptors is GHRH and secretin; these have very different functions and localisations, with the GRF ligand being found mainly in the brain and secretin in the pancreas (Sherwood et al. 2000).
The phylogenetic analyses of this family sub-set (Fig. 5) produced a primary branching between VPAC1R and PAC1R/VPAC2R and then divergence of PAC1R and VPAC2R. Although the branch lengths are very small and similar, when considered with all the other evidence (presented below) it implies that VPAC1R is the most ancestral form of this gene. This substantiates the less rigorous phylogenetic analyses and the evolutionary linkage data presented in Cardoso et al.(2004). The PACAP ligand and the receptor are the most conserved at the amino acid level and have been thought in the past to be the more ancient molecules of this grouping, certainly the PACAP ligand (along with a GRF-like peptide) was identified in tunicates (McRory & Sherwood 1997). PACAP has also been shown to be the pivotal molecule in the functional sense, being present in all organs and tissues in which this superfamily is expressed. DNA analysis indicates that the PACAP receptor (PAC1R) evolved after VPAC1R. This does not present a problem when considering the pharmacological properties of the receptors and the ligands as VPAC1R and VPAC2R both bind PACAP and VIP with equal affinity, whereas PAC1R has developed a more specialised role, binding PACAP with greater affinity than VIP (Harmar et al. 1998). It will definitely require ligand-binding assays on the receptors from lower vertebrates to help determine the evolutionary origins of this receptor sub-set and to examine the whole question of ligand-receptor evolution. This is supported by chromosomal mapping of the receptors in human and rat. Both VPAC2R and PAC1R map to human chromosome 7 and rat chromosome 4, whereas VPAC1R is located on human chromosome 3 and rat chromosome 8. Using this as a guide, a first duplication would produce the VPAC1R gene and a common ancestor for VPAC2R/PAC1R. A second duplication event acting on the ancestral VPAC2R/PAC1R gene would produce the two separate genes (Sreedharan et al. 1993, Cai et al. 1995, Brabet et al. 1996, Mackay et al. 1996, Vaudry et al. 2000). The distance between the VPAC1R and PAC1R/VPAC2R nodes is relatively small, indicating that there was rapid duplication of the original VPAC1R gene to form the PAC1R/VPAC2R ancestor. Timing of these duplication events is difficult because of the presence of the duplicated Takifugu genes and also the limited species range, which in most cases is restricted to only mammals and fish (the Tetraodon genes are only partial sequences and so could not be included in this analysis). This is exemplified by the VPAC2R topology which shows long branch lengths for the Takifugu genes. These fish genes are very different to their mammalian orthologues with the duplicated genes being as different to each other as they are to their mammalian orthologues (Cardoso et al. 2004), indicating that there has been considerable species-specific evolution of this duplicated gene set in Takifugu.
Clearly the relationships between different family 2 GPCR members are complex and sequence similarity comparisons are only the first stage in the characterisation and categorisation process. Increasing the range of vertebrate species included in the phylogenetic analysis and reducing the dataset to clade level certainly adds value and increases the definition of inter-family relationships. Sequence similarity does not necessarily equate to function and it is still to be determined whether the Takifugu genes (and the duplicated ones, in particular) have the same range and functionality as the higher vertebrate secretin family receptors. Also it is not strictly accurate to describe the receptors identified in Drosophila, Ciona and C. elegans as ‘ancestral’ molecules purely on the basis of sequence similarity. It is really only with functional determination that more exact relationships can be defined. Indeed this is one of the main problems of wholesale data-mining that sequence similarity may not represent functional equivalence, particularly when comparing such a diverse range of species. Indeed, reviewing the differences between GPCRs from all species, the question is raised whether membership of the club is purely down to possession of physical components, such as the number of TM domains, conserved cysteine residues and N-glycosylation sites. A more comprehensive species collection of GPCR data and functional information will start to answer this question.
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References |
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