- Research article
- Open Access
Genome wide survey of G protein-coupled receptors in Tetraodon nigroviridis
© Metpally and Sowdhamini; licensee BioMed Central Ltd. 2005
- Received: 25 February 2005
- Accepted: 15 July 2005
- Published: 15 July 2005
The G-protein-coupled receptors (GPCRs) constitute one of the largest and most ancient superfamilies of membrane proteins. They play a central role in physiological processes affecting almost all aspects of the life cycle of an organism. Availability of the complete sets of putative members of a family from diverse species provides the basis for cross genome comparative studies.
We have defined the repertoire of GPCR superfamily of Tetraodon complement with the availability of complete sequence of the freshwater puffer fish Tetraodon nigroviridis. Almost all 466 Tetraodon GPCRs (Tnig-GPCRs) identified had a clear human homologue. 189 putative human and Tetraodon GPCR orthologous pairs could be identified. Tetraodon GPCRs are classified into five GRAFS families, by phylogenetic analysis, concurrent with human GPCR classification.
Direct comparison of GPCRs in Tetraodon and human genomes displays a high level of orthology and supports large-scale gene duplications in Tetraodon. Examples of lineage specific gene expansions were also observed in opsin and odorant receptors. The human and Tetraodon GPCR sequences are analogous in terms of GPCR subfamilies but display disproportionate numbers of receptors at the subfamily level. The teleost genome with its expanded set of GPCRs provides additional and interesting comparators to study both evolution and function of these receptors.
- Additional Data File
- Taste Receptor
- Odorant Receptor
- Medaka Fish
- Boot Strap
The G-protein-coupled receptors (GPCRs) constitute one of the largest and most ancient superfamilies of membrane proteins, accounting for 1–2% of the vertebrate genome. GPCRs are characterized by the presence of highly conserved molecular architecture encoding seven transmembrane (TM) hydrophobic regions linked by three extracellular loops that alternate with three intracellular loops . The extracellular N-terminus is usually glycosylated and the cytoplasmic C-terminus is generally phosphorylated. The extracellular side of these receptors contains residues that are specifically recognized by ligands and is therefore involved in ligand-specific binding. The endogenous ligands for GPCRs have exceptionally high chemical diversity. They include biogenic amines, glycoproteins, ions, lipids, nucleotides, peptides and proteases. Moreover, the sensation of exogenous stimuli such as light, odor and taste is also mediated via this superfamily of receptors. Ligand-induced activation of all GPCRs leads to a conformational change of the receptor and triggers a family of heterotrimeric GTP binding proteins (G proteins) and modulates several cellular signaling pathways.
GPCRs have been aggressively pursued as drug targets due to their central role in physiological processes affecting almost all aspects of the life cycle of an organism . Almost half of the GPCRs are likely to encode sensory receptors and the rest of receptors could be considered as potential drug targets . It is estimated that about 50% of all current drug targets are GPCRs and are the most successful of any target class in terms of therapeutic benefit [4, 5]. A major goal of GPCR research is to expand the knowledge of GPCR structure/function in order to validate additional GPCR family members as tractable drug targets. Much effort, therefore, has been made to identify novel GPCRs and their ligands with potential therapeutic value [6–8].
The completion of several other vertebrate and invertebrate genome sequencing projects paves the way for "functional genomics". The quest for assigning function to putative gene products exploits the sequence and structural similarities to known genes and further could be elucidated using molecular biology techniques [9, 10]. Such studies have important implications in biology and in understanding the evolution of distinct organisms. Sequencing of the model organisms can be an important source of information on the function of human target class members. For example, evolutionary comparison of GPCR sequences between species can help to identify conserved motifs and may recognize key functional residues [11–13]. The majority of GPCR functional data have been derived from studies in genetic models such as mice, rat, worm and Drosophila; additional species provide new comparators for GPCR studies. Teleost fish, Tetraodon nigroviridis is one of the smallest known vertebrate genomes. It has all the specialized functions of higher vertebrates and can be a good vertebrate model system to study [14, 15]. The first available nearly complete sequence of T. nigroviridis genome now allows for the identification and analysis of its full set of GPCRs. Here, we describe the genome wide survey of Tnig-GPCR repertoire and a detailed analysis of opsin, fish-odorant receptors (FOR) and taste receptors (T1R).
G protein-coupled receptors of Tetraodon nigroviridis (Tn). The numbers predicted in each family and sub-family are shown in comparison to humans (Hs)
1+3 = 4
2+2 = 4
1+2 = 3
1+2+1 = 4
1+4+1+4 = 10
1+2+1+1 = 5
Rhodopsin family in Tetraodon has up to one and half times the number of receptors compared with human (excluding olfactory receptors), whereas about two fold as many GPCR sequences as in fugu and about three fourth of the zebrafish GPCRs . Tetraodon also has similar numbers of frizzled receptors as expected in mammals and fish genomes. Some of the gene families in Tetraodon like opsins and fish odorant receptors have shown species-specific expansions similar to trace amine receptors in zebrafish . However, taste receptors type 2 (TAS2) and mas related (MRG) receptors seem to be absent in Tetraodon like other known fish genomes .
23 candidate odorant receptors (OR) were identified in fish odorant receptor (FOR) subfamily of rhodopsins in Tetraodon. These OR genes are found in clusters of 3–4 members in the Tetraodon genome, located on different chromosomes. They display higher sequence identity within a cluster suggesting tandem duplication events might be responsible for OR gene family expansion in Tetraodon as observed in the genomes of every vertebrate organism investigated earlier, including zebrafish, mice and humans . Phylogenetic analysis of Tetraodon ORs with fish odorant receptor subfamily members (mainly zebrafish, channel catfish, Japanese pufferfish, medaka fish, goldfish etc) grouped them into six clusters of orthologues with very high boot strap support (Figure 5). In teleost lineage, different members of FOR subfamily have shown species specific gene expansion. For example, there is a large group of FORs with 18 zebrafish members, 6 catfish members, 4 medaka fish and one each of Tetraodon and channel catfish. Another group consists of 12 Tetraodon members, 2 medaka fish members and one each of goldfish and Japanese pufferfish (Figure 5). High differences in numbers of OR genes in specific fish reflect creature-specific lifestyle and these receptors are responsible for binding ligands important to a particular species [18–20, 25].
We have identified and analyzed repertoire of Tetraodon GPCRs and found high level of orthology with human counterparts. The human and Tetraodon GPCR sequences are analogous in terms of GPCR subfamilies, but display disproportionate number of receptors at the subfamily level. The teleost genome, with its expanded set of GPCRs, provides an additional and interesting model to study both evolution and function of these receptors. The availability of repertoire of Tetraodon GPCRs will facilitate further studies through "functional genomics" and "reverse pharmacological" strategies to match their cognate ligands and to elucidate biological functions. Systematic mutation of Tetraodon GPCRs will help to determine their neural, developmental and behavioral roles. They might also yield novel insights into the physiological functions and mutational pathologies of their human homologues in particular and other vertebrate homologues in general.
Identification of Tnig-GPCRs
Sequences of the Tetraodon nigroviridis are obtained from NCBI and Genoscope Tetraodon Genome Browser . HumanGPCR sequences were identified using GPCRDB  (Release 8.1) and based on earlier studies [7, 19, 23, 31]. GPCRs were identified using comprehensive approach (Figure 1) that includes RPS-BLAST  (using CDD v2.01 : SMART , Pfam  and COG Databases; E-value cut-off 10-5), Hmmpfam of HMMER 2.3.2  (using Pfam15; E-value cut-off 0.01) and BLASTP  homology comparisons against GPCRDB. Putative GPCR sequences were manually checked for GPCR specific patterns and presence of 7TM domain (at least 70% or more of Pfam 7TM should be aligned with each of the sequence). This is followed by secondary structure (transmembrane helix(TMH)) predictions using one or more methods like HMMTOP , SOSUI , MEMSTAT  and TMHMM2 . A range of 6–8 predicted TM helices acquired maximum coverage (96 percent; please see Additional data file 4 for details) when tested on a dataset of 327 annotated human GPCRs. A similar range was set to recognize acceptable tetraodon protein sequences containing transmembrane domain. Other examples, that either have under predicted or over predicted number of TM helices are earmarked separately ('#' symbol) in the current analysis. Splice variants, polymorphism and duplicates were eliminated by applying 90% sequence identity cut-off using CD-hit  and also checked manually. The corresponding genomic DNA sequences were also searched against the EST database at NCBI using BLASTN with a cutoff E-value of 1e12 . We could not obtain any Tetraodon nigroviridis EST hits, as there were few or no Tetraodon nigroviridis EST sequences available in the database.
Two genes, A from genome GA and B from GB, were considered orthologs if B is the best match of gene A in GB and A is the best match of B in GA using BLASTP .
Preliminary phylogenetic analysis  was performed using neighbor joining method with fewer number of bootstrap replicas and no randomization of sequence order. This was sufficient to separate GPCR sequences into rhodopsin like receptors and non rhodopsin like receptors. Rhodopsin like receptor and non-rhodopsin like receptor sequence datasets (separately full length and 7TM domain only), along with respective human GPCRs, were separately randomized twenty times with regard to sequence input order using a script called RandSeq (available upon request). These twenty datasets of different sequence order were aligned using clustalX 1.83  using multiple sequence alignment parameters with protein weight matrix BLOSUM series, gap opening penalty 10.0 and gap extension penalty 0.05 and delay divergence of 35 percent. To obtain unrooted trees, each alignment was bootstrapped 50 times and neighbor joining method (NEIGHBOR; Phylip package ) was employed to obtain tree topology using distance matrices obtained from alignments by PRODIST . Consensus tree was obtained from 1000 neighbor trees using CONSENSE . Only 500 boot strap replicas were used for rhodopsin like receptors due to limitations in the CONSENSE program and the trees were generated using Treeview . Maximum-likelihood tree of non-rhodopsin like receptors were also inferred from the alignment using TREE-PUZZLE . 10,000 quartet-puzzling steps were performed to obtain support values (reliability) for each internal branch.
R.S. is a Senior Research Fellow of the Wellcome Trust, UK. M.R.P.R. is a Senior Research Fellow of the Council of Scientific & Industrial Research (CSIR), India. We thank Ms. G. Mahima (BITs, Pilani) for GPCR pattern work and Mr. Nitin Gupta (UCSD) for coding a Java script to generate figure 2. We thank Tetraodon Sequencing Project for public availability of sequencing data. We also thank NCBS-TIFR for infrastructural support.
- Palczewski K, Kumasaka T, Hori T, Behnke CA, Motoshima H, Fox BA, Le Trong I, Teller DC, Okada T, Stenkamp RE, Yamamoto M, Miyano M: Crystal structure of rhodopsin: A G protein-coupled receptor. Science. 2000, 289: 739-745. 10.1126/science.289.5480.739.View ArticlePubMedGoogle Scholar
- Marinissen MJ, Gutkind JS: G-protein-coupled receptors and signaling networks: emerging paradigms. Trends Pharmacol Sci. 2001, 22: 368-376. 10.1016/S0165-6147(00)01678-3.View ArticlePubMedGoogle Scholar
- Wise A, Gearing K, Rees S: Target validation of G-protein coupled receptors. Drug Discovery Today. 2002, 7: 235-246. 10.1016/S1359-6446(01)02131-6.View ArticlePubMedGoogle Scholar
- Flower DR: Modelling G-protein-coupled receptors for drug design. Biochim Biophys Acta. 1999, 1422: 207-234.View ArticlePubMedGoogle Scholar
- Drews J: Drug discovery: a historical perspective. Science. 2000, 287: 1960-1964. 10.1126/science.287.5460.1960.View ArticlePubMedGoogle Scholar
- Lin SH, Civelli O: Orphan G protein-coupled receptors: targets for new therapeutic interventions. Ann Med. 2004, 36: 204-214. 10.1080/07853890310024668.View ArticlePubMedGoogle Scholar
- Metpally RPR, Sowdhamini R: Cross Genome Clustering of G-protein Coupled Receptor Sequences [Abstract]. Proceedings of the International Conference on Mathematical Biology: 19-21 Feb 2004; Kanpur;. 2004, BC-8.Google Scholar
- Marchese A, George SR, Kolakowski LFJ, Lynch KR, O'Dowd BF: Novel GPCRs and their endogenous ligands: expanding the boundaries of physiology and pharmacology. Trends Pharmacol Sci. 1999, 20: 370-375. 10.1016/S0165-6147(99)01366-8.View ArticlePubMedGoogle Scholar
- Meeusen T, Mertens I, De Loof A, Schoofs L: G protein-coupled receptors in invertebrates: a state of the art. Int Rev Cytol. 2003, 230: 189-261.View ArticlePubMedGoogle Scholar
- Herz JM, Thomsen WJ, Yarbrough GG: Molecular approaches to receptors as targets for drug discovery. J Recept Signal Transduct Res. 1997, 17: 671-776.View ArticlePubMedGoogle Scholar
- Attwood TK: A compendium of specific motifs for diagnosing GPCR subtypes. Trends Pharmacol Sci. 2001, 22: 162-165. 10.1016/S0165-6147(00)01658-8.View ArticlePubMedGoogle Scholar
- Lindemann L, Ebeling M, Kratochwil NA, Bunzow JR, Grandy DK, Hoener MC: Trace amine-associated receptors form structurally and functionally distinct subfamilies of novel G protein-coupled receptors. Genomics. 2005, 85: 372-385. 10.1016/j.ygeno.2004.11.010.View ArticlePubMedGoogle Scholar
- Bjarnadottir TK, Schioth HB, Fredriksson R: The phylogenetic relationship of the glutamate and pheromone g-protein-coupled receptors in different vertebrate species. Ann N Y Acad Sci. 2005, 1040: 230-233. 10.1196/annals.1327.031.View ArticlePubMedGoogle Scholar
- Jaillon O, Aury JM, Brunet F, Petit JL, Stange-Thomann N, Mauceli E, Bouneau L, Fischer C, Ozouf-Costaz C, Bernot A, Nicaud S, Jaffe D, Fisher S, Lutfalla G, Dossat C, Segurens B, Dasilva C, Salanoubat M, Levy M, Boudet N, Castellano S, Anthouard V, Jubin C, Castelli V, Katinka M, Vacherie B, Biemont C, Skalli Z, Cattolico L, Poulain J, De Berardinis V, Cruaud C, Duprat S, Brottier P, Coutanceau JP, Gouzy J, Parra G, Lardier G, Chapple C, McKernan KJ, McEwan P, Bosak S, Kellis M, Volff JN, Guigo R, Zody MC, Mesirov J, Lindblad-Toh K, Birren B, Nusbaum C, Kahn D, Robinson-Rechavi M, Laudet V, Schachter V, Quetier F, Saurin W, Scarpelli C, Wincker P, Lander ES, Weissenbach J, Roest Crollius H: Genome duplication in the teleost fish Tetraodon nigroviridis reveals the early vertebrate proto-karyotype. Nature. 2004, 431: 946-957. 10.1038/nature03025.View ArticlePubMedGoogle Scholar
- Brenner S, Elgar G, Sandford R, Macrae A, Venkatesh B, Aparicio S: Characterization of the pufferfish (Fugu) genome as a compact model vertebrate genome. Nature. 1993, 366: 265-268. 10.1038/366265a0.View ArticlePubMedGoogle Scholar
- Roest Crollius H, Jaillon O, Bernot A, Dasilva C, Bouneau L, Fischer C, Fizames C, Wincker P, Brottier P, Quetier F, Saurin W, Weissenbach J: Estimate of human gene number provided by genome-wide analysis using Tetraodon nigroviridis DNA sequence. Nat Genet. 2000, 25: 235-238. 10.1038/76118.View ArticlePubMedGoogle Scholar
- Venter JC, Adams MD, Myers EW, Li PW, Mural RJ, Sutton GG, Smith HO, Yandell M, Evans CA, Holt RA, Gocayne JD, Amanatides P, Ballew RM, Huson DH, Wortman JR, Zhang Q, Kodira CD, Zheng XH, Chen L, Skupski M, Subramanian G, Thomas PD, Zhang J, Gabor Miklos GL, Nelson C, Broder S, Clark AG, Nadeau J, McKusick VA, Zinder N, Levine AJ, Roberts RJ, Simon M, Slayman C, Hunkapiller M, Bolanos R, Delcher A, Dew I, Fasulo D, Flanigan M, Florea L, Halpern A, Hannenhalli S, Kravitz S, Levy S, Mobarry C, Reinert K, Remington K, Abu-Threideh J, Beasley E, Biddick K, Bonazzi V, Brandon R, Cargill M, Chandramouliswaran I, Charlab R, Chaturvedi K, Deng Z, Di Francesco V, Dunn P, Eilbeck K, Evangelista C, Gabrielian AE, Gan W, Ge W, Gong F, Gu Z, Guan P, Heiman TJ, Higgins ME, Ji RR, Ke Z, Ketchum KA, Lai Z, Lei Y, Li Z, Li J, Liang Y, Lin X, Lu F, Merkulov GV, Milshina N, Moore HM, Naik AK, Narayan VA, Neelam B, Nusskern D, Rusch DB, Salzberg S, Shao W, Shue B, Sun J, Wang Z, Wang A, Wang X, Wang J, Wei M, Wides R, Xiao C, Yan C, Yao A, Ye J, Zhan M, Zhang W, Zhang H, Zhao Q, Zheng L, Zhong F, Zhong W, Zhu S, Zhao S, Gilbert D, Baumhueter S, Spier G, Carter C, Cravchik A, Woodage T, Ali F, An H, Awe A, Baldwin D, Baden H, Barnstead M, Barrow I, Beeson K, Busam D, Carver A, Center A, Cheng ML, Curry L, Danaher S, Davenport L, Desilets R, Dietz S, Dodson K, Doup L, Ferriera S, Garg N, Gluecksmann A, Hart B, Haynes J, Haynes C, Heiner C, Hladun S, Hostin D, Houck J, Howland T, Ibegwam C, Johnson J, Kalush F, Kline L, Koduru S, Love A, Mann F, May D, McCawley S, McIntosh T, McMullen I, Moy M, Moy L, Murphy B, Nelson K, Pfannkoch C, Pratts E, Puri V, Qureshi H, Reardon M, Rodriguez R, Rogers YH, Romblad D, Ruhfel B, Scott R, Sitter C, Smallwood M, Stewart E, Strong R, Suh E, Thomas R, Tint NN, Tse S, Vech C, Wang G, Wetter J, Williams S, Williams M, Windsor S, Winn-Deen E, Wolfe K, Zaveri J, Zaveri K, Abril JF, Guigo R, Campbell MJ, Sjolander KV, Karlak B, Kejariwal A, Mi H, Lazareva B, Hatton T, Narechania A, Diemer K, Muruganujan A, Guo N, Sato S, Bafna V, Istrail S, Lippert R, Schwartz R, Walenz B, Yooseph S, Allen D, Basu A, Baxendale J, Blick L, Caminha M, Carnes-Stine J, Caulk P, Chiang YH, Coyne M, Dahlke C, Mays A, Dombroski M, Donnelly M, Ely D, Esparham S, Fosler C, Gire H, Glanowski S, Glasser K, Glodek A, Gorokhov M, Graham K, Gropman B, Harris M, Heil J, Henderson S, Hoover J, Jennings D, Jordan C, Jordan J, Kasha J, Kagan L, Kraft C, Levitsky A, Lewis M, Liu X, Lopez J, Ma D, Majoros W, McDaniel J, Murphy S, Newman M, Nguyen T, Nguyen N, Nodell M, Pan S, Peck J, Peterson M, Rowe W, Sanders R, Scott J, Simpson M, Smith T, Sprague A, Stockwell T, Turner R, Venter E, Wang M, Wen M, Wu D, Wu M, Xia A, Zandieh A, Zhu X: The sequence of the human genome. Science. 2001, 291: 1304-1351. 10.1126/science.1058040.View ArticlePubMedGoogle Scholar
- Hill CA, Fox AN, Pitts RJ, Kent LB, Tan PL, Chrystal MA, Cravchik A, Collins FH, Robertson HM, Zwiebel LJ: G protein-coupled receptors in Anopheles gambiae. Science. 2002, 298: 176-178. 10.1126/science.1076196.View ArticlePubMedGoogle Scholar
- Fredriksson R, Schioth HB: The repertoire of G-protein-coupled receptors in fully sequenced genomes. Mol Pharmacol. 2005, 67: 1414-1425. 10.1124/mol.104.009001.View ArticlePubMedGoogle Scholar
- Gloriam DE, Bjarnadottir TK, Yan YL, Postlethwait JH, Schioth HB, Fredriksson R: The repertoire of trace amine G-protein-coupled receptors: large expansion in zebrafish. Mol Phylogenet Evol. 2005, 35: 470-482. 10.1016/j.ympev.2004.12.003.View ArticlePubMedGoogle Scholar
- Taylor JS, Braasch I, Frickey T, Meyer A, Van de Peer Y: Genome duplication, a trait shared by 22000 species of ray-finned fish. Genome Res. 2003, 13: 382-390. 10.1101/gr.640303.PubMed CentralView ArticlePubMedGoogle Scholar
- Van de Peer Y: Tetraodon genome confirms Takifugu findings: most fish are ancient polyploids. Genome Biol. 2004, 5: 250-10.1186/gb-2004-5-12-250.PubMed CentralView ArticlePubMedGoogle Scholar
- Fredriksson R, Lagerstrom MC, Lundin LG, Schioth HB: The G-protein-coupled receptors in the human genome form five main families. Phylogenetic analysis, paralogon groups, and fingerprints. Mol Pharmacol. 2003, 63: 1256-1272. 10.1124/mol.63.6.1256.View ArticlePubMedGoogle Scholar
- Schioth HB, Fredriksson R: The GRAFS classification system of G-protein coupled receptors in comparative perspective. Gen Comp Endocrinol. 2005, 142: 94-101. 10.1016/j.ygcen.2004.12.018.View ArticlePubMedGoogle Scholar
- Fredriksson R, Lagerstrom MC, Schioth HB: Expansion of the superfamily of g-protein-coupled receptors in chordates. Ann N Y Acad Sci. 2005, 1040: 89-94. 10.1196/annals.1327.011.View ArticlePubMedGoogle Scholar
- Kratz E, Dugas JC, Ngai J: Odorant receptor gene regulation: implications from genomic organization. Trends Genet. 2002, 18: 29-34. 10.1016/S0168-9525(01)02579-3.View ArticlePubMedGoogle Scholar
- Li X, Staszewski L, Xu H, Durick K, Zoller M, Adler E: Human receptors for sweet and umami taste. Proc Natl Acad Sci U S A. 2002, 99: 4692-4696. 10.1073/pnas.072090199.PubMed CentralView ArticlePubMedGoogle Scholar
- Zhao GQ, Zhang Y, Hoon MA, Chandrashekar J, Erlenbach I, Ryba NJ, Zuker CS: The receptors for mammalian sweet and umami taste. Cell. 2003, 115: 255-266. 10.1016/S0092-8674(03)00844-4.View ArticlePubMedGoogle Scholar
- Tetraodon Genome Browser, http://www.genoscope.cns.fr/externe/tetranew/. 2004Google Scholar
- Horn F, Weare J, Beukers MW, Horsch S, Bairoch A, Chen W, Edvardsen O, Campagne F, Vriend G: GPCRDB: an information system for G protein-coupled receptors. Nucleic Acids Res. 1998, 26: 275-279. 10.1093/nar/26.1.275.PubMed CentralView ArticlePubMedGoogle Scholar
- Metpally RPR, Sowdhamini R: Genome wide survey of Drosophila G protein-coupled receptors [Abstract]. Proceedings of the European Conference on Computational Biology in conjunction with the French National Conference on Bioinformatics. 2003, PSA-13.Google Scholar
- Marchler-Bauer A, Anderson JB, DeWeese-Scott C, Fedorova ND, Geer LY, He S, Hurwitz DI, Jackson JD, Jacobs AR, Lanczycki CJ, Liebert CA, Liu C, Madej T, Marchler GH, Mazumder R, Nikolskaya AN, Panchenko AR, Rao BS, Shoemaker BA, Simonyan V, Song JS, Thiessen PA, Vasudevan S, Wang Y, Yamashita RA, Yin JJ, Bryant SH: CDD: a curated Entrez database of conserved domain alignments. Nucleic Acids Res. 2003, 31: 383-387. 10.1093/nar/gkg087.PubMed CentralView ArticlePubMedGoogle Scholar
- Marchler-Bauer A, Anderson JB, Cherukuri PF, DeWeese-Scott C, Geer LY, Gwadz M, He S, Hurwitz DI, Jackson JD, Ke Z, Lanczycki CJ, Liebert CA, Liu C, Lu F, Marchler GH, Mullokandov M, Shoemaker BA, Simonyan V, Song JS, Thiessen PA, Yamashita RA, Yin JJ, Zhang D, Bryant SH: CDD: a Conserved Domain Database for protein classification. Nucleic Acids Res. 2005, 33 (Database Issue): D192-6. 10.1093/nar/gki069.PubMed CentralView ArticlePubMedGoogle Scholar
- Letunic I, Copley RR, Schmidt S, Ciccarelli FD, Doerks T, Schultz J, Ponting CP, Bork P: SMART 4.0: towards genomic data integration. Nucleic Acids Res. 2004, 32 Database issue: D142-4. 10.1093/nar/gkh088.View ArticleGoogle Scholar
- Bateman A, Coin L, Durbin R, Finn RD, Hollich V, Griffiths-Jones S, Khanna A, Marshall M, Moxon S, Sonnhammer EL, Studholme DJ, Yeats C, Eddy SR: The Pfam protein families database. Nucleic Acids Res. 2004, 32 (Database issue): D138-41. 10.1093/nar/gkh121.PubMed CentralView ArticlePubMedGoogle Scholar
- Eddy SR: Profile hidden Markov models. Bioinformatics. 1998, 14: 755-763. 10.1093/bioinformatics/14.9.755.View ArticlePubMedGoogle Scholar
- Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ: Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997, 25: 3389-3402. 10.1093/nar/25.17.3389.PubMed CentralView ArticlePubMedGoogle Scholar
- Tusnady GE, Simon I: The HMMTOP transmembrane topology prediction server. Bioinformatics. 2001, 17: 849-850. 10.1093/bioinformatics/17.9.849.View ArticlePubMedGoogle Scholar
- Hirokawa T, Boon-Chieng S, Mitaku S: SOSUI: classification and secondary structure prediction system for membrane proteins. Bioinformatics. 1998, 14: 378-379. 10.1093/bioinformatics/14.4.378.View ArticlePubMedGoogle Scholar
- Jones DT, Taylor WR, Thornton JM: A model recognition approach to the prediction of all-helical membrane protein structure and topology. Biochemistry. 1994, 33: 3038-3049. 10.1021/bi00176a037.View ArticlePubMedGoogle Scholar
- Krogh A, Larsson B, von Heijne G, Sonnhammer EL: Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J Mol Biol. 2001, 305: 567-580. 10.1006/jmbi.2000.4315.View ArticlePubMedGoogle Scholar
- Li W, Jaroszewski L, Godzik A: Clustering of highly homologous sequences to reduce the size of large protein databases. Bioinformatics. 2001, 17: 282-283. 10.1093/bioinformatics/17.3.282.View ArticlePubMedGoogle Scholar
- Baldauf SL: Phylogeny for the faint of heart: a tutorial. Trends Genet. 2003, 19: 345-351. 10.1016/S0168-9525(03)00112-4.View ArticlePubMedGoogle Scholar
- Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG: The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res. 1997, 25: 4876-4882. 10.1093/nar/25.24.4876.PubMed CentralView ArticlePubMedGoogle Scholar
- Felsenstein J: PHYLIP -- Phylogeny Inference Package (Version 3.2). Cladistics. 1989, 5: 164-166.Google Scholar
- Page RD: TreeView: an application to display phylogenetic trees on personal computers. Comput Appl Biosci. 1996, 12: 357-358.PubMedGoogle Scholar
- Schmidt HA, Strimmer K, Vingron M, von Haeseler A: TREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing. Bioinformatics. 2002, 18: 502-504. 10.1093/bioinformatics/18.3.502.View ArticlePubMedGoogle Scholar
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