Expansion of signaling genes for adaptive immune system evolution in early vertebrates
© Okada and Asai; licensee BioMed Central Ltd. 2008
Received: 09 November 2007
Accepted: 14 May 2008
Published: 14 May 2008
The adaptive immune system (AIS) of jawed vertebrates is a sophisticated system mediated by numerous genes in specialized cells. Phylogenetic analysis indicates that emergence of the AIS followed the occurrence of two rounds of whole-genome duplication (2R-WGD) in early vertebrates, but little direct evidence linking these two events is available.
We examined the relationship between 2R-WGD and the gain of AIS-related functions by numerous genes. To analyze the evolution of the many genes related to signal transduction in the AIS (defined as AIS genes), we identified groups of genes (defined as AIS subfamilies) that included at least one human AIS gene, its paralogs (if any), and its Drosophila ortholog(s). Genomic mapping revealed that numerous pairs of AIS genes and their paralogs were part of paralogons – series of paralogous regions that derive from a common ancestor – throughout the human genome, indicating that the genes were retained as duplicates after 2R-WGD. Outgroup comparison analysis revealed that subfamilies in which human and fly genes shared a nervous system-related function were significantly enriched among AIS subfamilies, as compared with the overall incidence of shared nervous system-related functions among all subfamilies in bilaterians. This finding statistically supports the hypothesis that AIS-related signaling genes were ancestrally involved in the nervous system of urbilaterians.
The current results suggest that 2R-WGD played a major role in the duplication of many signaling genes, ancestrally used in nervous system development and function, that were later co-opted for new functions during evolution of the AIS.
The AIS in jawed vertebrates is a sophisticated system mediated by numerous genes in specialized cells . Because the AIS is conserved widely among jawed vertebrates but not invertebrates , it is widely held that the AIS appeared suddenly, as an immunologic "big bang," in the common ancestor of jawed vertebrates . The recently sequenced genome of Stringylocentrotus purpuratus (purple sea urchin), one of the closest relatives of chordates, has revealed that although they lack an AIS, sea urchins have almost all of the vertebrate gene repertoire, including many genes involved in the AIS [4, 5]. This situation indicates that many of the genes involved in the AIS arose long before the emergence of jawed vertebrates (or at least that of the common ancestor of jawed vertebrates and sea urchins) and thereafter evolved concurrently to gain new functions in the AIS at the immunologic big bang.
Gene duplications are important evolutionary paths for the acquisition of new functions, because one copy of a duplicated gene can accumulate mutations and acquire novel functions while the other retains the original function. Such duplications can involve individual genes, genomic segments, or whole genomes. Because they generate a large number of gene duplicates concurrently, whole-genome duplications (WGDs) are considered particularly important evolutionary events . It has long been hypothesized that a WGD occurred twice in early vertebrates (two rounds of whole-genome duplication, 2R-WGD). This hypothesis has recently been supported by clear patterns of four-way paralogous regions occurring throughout the human genome [7, 8].
Phylogenetic analysis indicates that the occurrence of 2R-WGD preceded emergence of the AIS ; therefore, 2R-WGD may have been important in the acquisition of AIS-related functions by numerous genes at immunologic big bang. However, 2R-WGD has been directly linked to limited AIS-related genes that are located in only a few paralogons in the human genome [2, 9, 10], indicating that the genes arose from 2R-WGD. These currently available examples are too limited to reveal the precise relationship between 2R-WGD and the acquisition of AIS-related functions by the numerous genes involved in this system.
We focus here on many signaling genes in the AIS and investigate the extent to which 2R-WGD contributed to their gains of function in the AIS. In addition, to provide insight into the ancestral status of the AIS-related genes before 2R-WGD, we compared these genes with their orthologs in an invertebrate (Drosophila) that lacks an AIS.
Molecular functions of paralogs in paralogons formed in early vertebrates
Top five Gene Ontology (GO) slim terms of BV paralogous genes
Observed number of BV paralogous genes (%)
regulation of biological process
698 (25% = 698/2842)
4.05 × 10-14
634 (22% = 634/2842)
9.52 × 10-24
multicellular organismal development
397 (14% = 397/2842)
1.59 × 10-24
388 (14% = 388/2842)
4.49 × 10-10
protein modification process
326 (11% = 326/2842)
1.65 × 10-27
Detection of AIS subfamilies
In the AIS, signal transduction machineries play indispensable roles as mediators between the diverse extracellular stimuli received by membrane-bound receptors and various induced biological processes. We focused on an antigen-recognition receptor pathway, chemokine receptor pathway, and cytokine receptor pathway as representatives of the various signal transduction machineries in the AIS. We prepared a list of the 61 families of human genes (defined as AIS families) that comprise these three signaling pathways (see Additional File 1) and that include many genes essential to the AIS .
If the genes in an AIS family have emerged at or before the divergence of protostomes and deuterostomes, then the AIS family will encompass one or more subfamilies, each of which will include all the descendants of a single ancestral gene in the common ancestor of protostomes and deuterostomes (i.e., the ancestral bilaterian). We comprehensively identified such subfamilies by applying a clustering algorithm to the complete gene sets of one invertebrate (Drosophila) and three vertebrates (human, mouse, and medaka) and investigated whether any of the AIS families contained one or more resulting subfamilies. Consequently, 93% (57 of 61) of the AIS families encompassed at least one subfamily (see Additional File 1), indicating that their ancestral genes existed in the ancestral bilaterian.
However, in the case of AIS families with multiple subfamilies, one or more subfamilies may not contain any AIS-related genes, because each AIS family can include genes that are not involved in the AIS. By using published information on the AIS-related functions of each gene in the subfamilies of all AIS families, we identified 50 subfamilies that each included at least one member gene involved in the AIS (defined as an AIS gene); the 50 subfamilies were defined as "AIS subfamilies" (see Additional Files 2, 3). Because each subfamily included all the descendants of a single ancestral gene in the common ancestor of protostomes (i.e., Drosophila) and deuterostomes (i.e., human, mouse, and medaka), an AIS subfamily included at least one human AIS gene, its paralog(s) (if any), and its Drosophila ortholog(s).
Timing of gene duplications in AIS subfamilies
We found that 84% (42 of 50) of the AIS subfamilies included multiple human genes (Additional Files 2, 3), indicating that the numbers of subfamily members increased through gene duplication after the divergence of protostomes and deuterostomes. To clarify the timing of the duplications, we conducted phylogenetic analyses of the AIS subfamilies. Examination of the resulting phylogenetic trees showed that 88% of the total duplications (65 of 74) in the AIS subfamilies occurred in the early vertebrate lineage (i.e., before the divergence of fish and tetrapods; see Additional Files 4, 5).
Genomic mapping analysis
Use of large-scale microarray analysis to detect tissues and organs in which the genes in AIS subfamilies are expressed at high levels
Outgroup comparison for inferring the ancestral functions of genes in AIS subfamilies
System-level function categories that are shared between Drosophila and human genes in AIS subfamilies
System-level function category
Number of AIS subfamilies (%)
2 (4% = 2/48)
4.26 × 10-2
7 (15% = 7/48)
2.17 × 10-10
6 (13% = 6/48)
1.11 × 10-9
28 (58% = 28/48)
9.26 × 10-15
Gene usage of AIS subfamilies in the NS and AIS
Large-scale microarray data  enabled us to examine the statistical significance of the enrichment of the system-level function categories among the AIS subfamilies and revealed that the most significantly enriched category among the AIS subfamilies was NS. To precisely assess gene usage in the NS and AIS among the AIS subfamilies, we listed the NS- and AIS-related functions of the human genes in the AIS subfamilies according to data in the published literature (see Additional File 11). Most of the human genes in the AIS families (43%, 56 of 129) were used in either the NS or AIS, suggesting that the functions of these genes are specialized for the respective system (see Additional File 11). In contrast, 44 genes (34%, 44 of 129) were used in both the NS and AIS (see Additional File 11), although whether the genes have different or similar functions in each system is unclear.
Because most traces of 2R-WGD have been deleted by subsequent gene loss and genomic rearrangement [8, 20], direct evidence linking 2R-WGD and expansion of AIS subfamilies is difficult to obtain by analyzing the membership of AIS subfamilies. A 4:1 ratio in the number of vertebrate to invertebrate genes in a family (e.g., Hox clusters ) is considered to reflect an effect of 2R-WGD. However, because of massive gene loss after 2R-WGD, few AIS subfamilies include four human genes (see Additional File 3). Likewise, the phylogenetic timing of duplications in AIS subfamilies is inconclusive, because duplications can occur on every branch. Although the number of duplications was increased somewhat in the early vertebrate lineage (Additional File 5 and as found previously ), this increase may simply indicate that this evolutionary period was associated with accelerated small-scale gene duplication or a reduced rate of gene loss, rather than WGD. However, the genomic mapping analysis, which examined the relationship between the genomic map positions of members in AIS subfamilies and those of BV paralogous genes in paralogons, yielded conclusive evidence of the role of 2R-WGD in the expansion of the AIS subfamilies. This analysis revealed that most of the paralogous pairs in AIS subfamilies were part of paralogons in the human genome (Fig. 1 and see Additional File 7), indicating that most AIS genes were retained as duplicates from 2R-WGD.
Our outgroup comparison analysis suggested the category NS as the ancestral function of most AIS genes (Table 2), as in a previous study . Although suggested by several previous studies [22–25], the apparent association between the AIS and NS may have arisen simply because the number of genes involved in the NS is larger than that of genes involved in other systems. We therefore examined the relative enrichment of assigned categories among AIS subfamilies as compared with the overall distribution of these categories among all subfamilies. This analysis revealed that the NS category was significantly over-represented as an ancestral function among AIS subfamilies, supporting statistically the hypothesis  that AIS-related signaling genes were ancestrally involved in the development and/or function of the NS in urbilaterians.
Our study did not address the specific evolutionary roles of each round of 2R-WGD. Because of the unavailability of the genome sequence of jawless vertebrates, which presumably diverged from jawed vertebrates before the second round of 2R-WGD , it is difficult to differentiate the effect of the first round of 2R-WGD in vertebrate genomes from the second. It has recently been shown that jawless vertebrates evolved their own AIS, which is different from the AIS of jawed vertebrates [27, 28]. We anticipate that the ongoing genome project (Washington University, St Louis, MO, USA) of a jawless vertebrate (lamprey) will clarify the individual roles of each round of 2R-WGD in the evolution of the different AISs of these organisms.
To date, studies using small-scale gene sets have hinted at relationships between the AIS and 2R-WGD [2, 10, 22] and between the AIS and NS [22–25]. Although such studies are informative, they cannot yield conclusions that are broadly applicable to the role of 2R-WGD. However, our use of large-scale data sets (i.e., genomic sequence information, microarray-based expression data, and functional annotation) enabled us to address these relationships in a genome-wide fashion. In future research, integration of other large-scale data sets (e.g., other types of data and from additional species) into similar analyses will facilitate efforts to describe the evolution of the AIS precisely and in detail and will help to further unravel the biologic significance of 2R-WGD in that process.
The occurrence of 2R-WGD preceding emergence of the AIS enhances our understanding of the biologic significance of WGD. Comprehensive identification of the paralogons in the human genome enabled us to conduct a genomic mapping analysis to examine the relationship between 2R-WGD and the evolution of many of the genes involved in the AIS. This analysis revealed that numerous pairs of signaling genes in the AIS (i.e., AIS genes) and their paralogs were part of paralogons, indicating that the genes were retained as duplicates from 2R-WGD.
The large-scale biologic data enabled us to examine the statistical significance of enrichment of system-level function categories among the AIS subfamilies as compared with the overall distribution of these categories among all subfamilies. This examination revealed that the category NS was significantly over-represented among AIS subfamilies, supporting statistically the hypothesis that the AIS-related signaling genes were involved in the nervous system of ancestral bilaterians. Our analysis uncovered the evolutionary role of 2R-WGD in duplicating numerous signaling genes used in the ancestral NS and thereafter in leading to the coordinated evolution of the resulting duplicates to gain new functions in the AIS. We believe that our findings provide a basis for further detailed exploration of the diverse roles of 2R-WGD in the evolutionary success of the vertebrate lineage.
Protein-coding sequences for Homo sapiens (human; version 42.36d), Mus musculus (mouse; version 42.36c), Oryzias latipes (medaka; version 44.1a), and Drosophila melanogaster (fly; version 42.43) were obtained from the Ensembl project website , and those for Ciona intestinalis came from the JGI website . For genes with multiple transcripts, only the longest sequence was retrieved, resulting in 15 852 Ciona, 24 125 mouse, 19 938 medaka, 13 545 Drosophila, and 22 102 human protein-coding genes (total, 95 562 genes).
Clustering for detecting subfamilies of chordates
The objective of gene clustering was to reconstruct groups of genes such that each included all of (and only) the descendents of a single gene in the ancestral chordate. The underlying assumption was that all of the vertebrate genes in such a group were more similar to each other than to their ortholog in Ciona, because they arose by either gene duplication or lineage splitting after the urochordate-vertebrate divergence. We generated the translated protein sequences for all genes, conducted all-to-all BLASTP analysis using the default parameters , and identified reciprocal best-hit pairs between Ciona and vertebrate protein sequences (C and V, respectively). Such a pair recursively recruited other vertebrate sequences of which the best hit in Ciona was C if they were more similar to each other than C was to V; this constraint ensured that genes with similarity due to duplication before the urochordate-vertebrate divergence were allocated appropriately into separate groups. The resulting groups of genes were defined as subfamilies. We consequently generated 7109 subfamilies that included 39 407 (48%) of the 82 017 total chordate genes.
Phylogenetic analysis for subfamilies
For multiple sequence alignment of each subfamily, MAFFT 5.852  was run using the parameters: global alignment option; model, BLOSUM62; maximal iteration, 1000. This alignment then was trimmed by eliminating all positions with gap characters. Only a multiple alignment with a remaining length of at least 100 amino acids was used for further analysis. Phylogenetic trees were inferred by a maximum likelihood method as implemented in TREE-PUZZLE 5.2  with the JTT model of amino acid substitution  and a gamma distribution of rates over eight rate categories; 10 000 puzzling steps were used to assess reliability. Any trees with nodes that did not bifurcate strictly were eliminated.
Paralogon detection and genomic mapping analysis
By using strictly bifurcating trees, we retrieved gene duplications that occurred before the divergence of fish and tetrapods and identified 2774 paralogous pairs of genes in humans. Paralogous pairs duplicated at the base of the vertebrate branch were defined as BV paralogous pairs. A paralogon was defined as two separate regions in the same genome, each having one gene of each of two (or more) BV paralogous pairs, with a maximum of 100 unduplicated genes between the two BV paralogous genes. Through a sliding window analysis (for details, see ), we comprehensively identified paralogons in the human genome. For any paralogous gene pair P, we examined whether the genomic map position of P was part of one of the paralogons.
Clustering for detecting subfamilies of bilaterians
Although the general procedure was similar to the algorithm for detecting subfamilies of chordate genes, two additional modifications were incorporated. First, we used genes of flies instead of those of Ciona. Second, we took account of paralogous genes in Drosophila that were duplicated in the lineage leading to Drosophila. After clustering groups with complete gene sets of one invertebrate (Drosophila) and three vertebrates in the same way as for detecting subfamilies of chordate genes, we obtained singleton Drosophila sequences that were not included in any subfamily. For any singleton Drosophila sequence S, if S was more similar to the Drosophila sequence D in a subfamily than D was to any vertebrate sequences in the subfamily, then S was re-recruited into the subfamily.
GO terms  assigned to human genes were downloaded from the Ensembl project website  (Dec 2006). By mapping the GO terms into the more general parent GO Slim terms (Generic GO Slim; obtained from the website of the Gene Ontology consortium ), we assigned GO Slim terms to each human gene. We focused on the descendant terms of "biological process" (GO: 0008150).
Normalization of microarray expression data
Large-scale microarray expression data for 79 human tissues and organs were obtained from the GEO website [37, 38] (GEO accession ID: GDS596). We excluded probes for control sequences and those with names that carried the suffix_x_at; such probes do not uniquely complement the target sequence and hence are likely to cross-hybridize. For resulting data, the arithmetic mean of the two replicates in the microarray data was calculated. Next, the data were normalized (Z-score normalization) according to sample to exclude differences associated with sample preparation, for example, and then further normalized (Z-score normalization) according to probe to exclude factors such as housekeeping genes, which are highly expressed in all tissues and organs. If the Z-score of a gene in a particular tissue or organ was greater than or equal to 2, we considered that the gene was expressed specifically in that tissue or organ.
Listing the NS- and AIS-related functions of human genes in the AIS subfamilies according to data in the literature
Information regarding the NS- and AIS-related functions of human genes in the AIS subfamilies was assigned on the basis of published literature (Dec 2006). Most of the literature data supporting the functions of human genes are based on analyses that have used their orthologs in other vertebrate species (e.g., mouse, chicken, rat). The assigned information regarding function reflected one of two types of data. The first type of assigned information was that concluded from phenotypical changes in experiments, including those involving gene mutation or knockout, overexpression or ectopic expression of wild-type or mutant genes, antisense RNA or RNAi, specific protein inhibitors, or gene interaction and rescue. However, for precise assignment, experiments involving multiple members of a single subfamily (e.g., double knockout experiments) were not considered. The second type of annotated information was that concluded from studies addressing causes of diseases.
Assignment of system-level function categories to human genes in the AIS subfamilies on the basis of microarray data
System-level function categories were assigned to the human genes in the subfamilies according to the following criterion: if, on the basis of microarray data (GEO accession ID: GDS596), a gene is specifically expressed in at least one of the tissues or organs represented in a system-level function category, then that system-level function category was assigned to the gene.
Assignment of system-level function categories to Drosophila genes on the basis of FlyBase annotation
To assign system-level function categories to Drosophila genes, we used allele phenotype data  that are manually curated with hierarchically structured controlled vocabularies (CVs) in the FlyBase database . The CV term "nervous system" (FBbt:00005093) corresponded to the system-level function category NS, that of "muscle system" (FBbt:00005069) corresponded to "muscle tissue", and that of "circulatory system" (FBbt:00005057) corresponded to "blood." The CV terms "lamellocyte" (FBbt:00001687), "crystal cell" (FBbt:00001690), and "hemocyte" (FBbt:00005063) corresponded to the system-level function category "innate immunity." If a Drosophila gene in a subfamily was annotated with the CV corresponding to a system-level function category or with any of the descendents of the CV, then the corresponding system-level function category was assigned to the gene.
adaptive immune system
two rounds of whole-genome duplication
We thank the members of the Computational Biology Research Center http://www.cbrc.jp for all of their support and helpful comments. This work was supported by KAKENHI (Grant-in-Aid for Scientific Research) on Priority Areas ("Comparative Genomics") from the Ministry of Education, Culture, Sports, Science, and Technology of Japan.
- Abbas AK, Lichtman AH: Cellular and molecular immunology. 2003, Philadelphia, Pennsylvania: Saunders, 5Google Scholar
- Kasahara M, Suzuki T, Pasquier LD: On the origins of the adaptive immune system: novel insights from invertebrates and cold-blooded vertebrates. Trends Immunol. 2004, 25 (2): 105-111. 10.1016/j.it.2003.11.005.PubMedView ArticleGoogle Scholar
- Bernstein RM, Schluter SF, Bernstein H, Marchalonis JJ: Primordial emergence of the recombination activating gene 1 (RAG1): sequence of the complete shark gene indicates homology to microbial integrases. Proc Natl Acad Sci USA. 1996, 93 (18): 9454-9459. 10.1073/pnas.93.18.9454.PubMedPubMed CentralView ArticleGoogle Scholar
- Sodergren E, Weinstock GM, Davidson EH, Cameron RA, Gibbs RA, Angerer RC, Angerer LM, Arnone MI, Burgess DR, Burke RD: The genome of the sea urchin Strongylocentrotus purpuratus. Science. 2006, 314 (5801): 941-952. 10.1126/science.1133609.PubMedView ArticleGoogle Scholar
- Rast JP, Smith LC, Loza-Coll M, Hibino T, Litman GW: Genomic insights into the immune system of the sea urchin. Science. 2006, 314 (5801): 952-956. 10.1126/science.1134301.PubMedPubMed CentralView ArticleGoogle Scholar
- Ohno S: Evolution by gene duplication. 1970, Heidelberg: Springer-VerlagView ArticleGoogle Scholar
- Nakatani Y, Takeda H, Kohara Y, Morishita S: Reconstruction of the vertebrate ancestral genome reveals dynamic genome reorganization in early vertebrates. Genome Res. 2007, 17 (9): 1254-1265. 10.1101/gr.6316407.PubMedPubMed CentralView ArticleGoogle Scholar
- Dehal P, Boore JL: Two rounds of whole genome duplication in the ancestral vertebrate. PLoS Biol. 2005, 3 (10): e314-10.1371/journal.pbio.0030314.PubMedPubMed CentralView ArticleGoogle Scholar
- Du Pasquier L, Zucchetti I, De Santis R: Immunoglobulin superfamily receptors in protochordates: before RAG time. Immunol Rev. 2004, 198: 233-248. 10.1111/j.0105-2896.2004.00122.x.PubMedView ArticleGoogle Scholar
- Kasahara M: The 2R hypothesis: an update. Curr Opin Immunol. 2007, 19 (5): 547-552. 10.1016/j.coi.2007.07.009.PubMedView ArticleGoogle Scholar
- Blanc G, Wolfe KH: Functional divergence of duplicated genes formed by polyploidy during Arabidopsis evolution. Plant Cell. 2004, 16 (7): 1679-1691. 10.1105/tpc.021410.PubMedPubMed CentralView ArticleGoogle Scholar
- Maere S, De Bodt S, Raes J, Casneuf T, Van Montagu M, Kuiper M, Peer Van de Y: Modeling gene and genome duplications in eukaryotes. Proc Natl Acad Sci USA. 2005, 102 (15): 5454-5459. 10.1073/pnas.0501102102.PubMedPubMed CentralView ArticleGoogle Scholar
- Kellis M, Birren BW, Lander ES: Proof and evolutionary analysis of ancient genome duplication in the yeast Saccharomyces cerevisiae. Nature. 2004, 428 (6983): 617-624. 10.1038/nature02424.PubMedView ArticleGoogle Scholar
- Brunet FG, Crollius HR, Paris M, Aury JM, Gibert P, Jaillon O, Laudet V, Robinson-Rechavi M: Gene loss and evolutionary rates following whole-genome duplication in teleost fishes. Mol Biol Evol. 2006, 23 (9): 1808-1816. 10.1093/molbev/msl049.PubMedView ArticleGoogle Scholar
- Blomme T, Vandepoele K, De Bodt S, Simillion C, Maere S, Peer Van de Y: The gain and loss of genes during 600 million years of vertebrate evolution. Genome Biol. 2006, 7 (5): R43-10.1186/gb-2006-7-5-r43.PubMedPubMed CentralView ArticleGoogle Scholar
- Su AI, Wiltshire T, Batalov S, Lapp H, Ching KA, Block D, Zhang J, Soden R, Hayakawa M, Kreiman G: A gene atlas of the mouse and human protein-encoding transcriptomes. Proc Natl Acad Sci USA. 2004, 101 (16): 6062-6067. 10.1073/pnas.0400782101.PubMedPubMed CentralView ArticleGoogle Scholar
- Fujibuchi W, Kiseleva L, Taniguchi T, Harada H, Horton P: CellMontage: similar expression profile search server. Bioinformatics. 2007, 23 (22): 3103-3104. 10.1093/bioinformatics/btm462.PubMedView ArticleGoogle Scholar
- Crosby MA, Goodman JL, Strelets VB, Zhang P, Gelbart WM: FlyBase: genomes by the dozen. Nucl Acids Res. 2007, D486-491. 10.1093/nar/gkl827. 35 Database
- Maddison WP, Donoghue MJ, Maddison DR: Outgroup analysis and parsimony. Syst Zool. 1984, 33 (1): 88-103. 10.2307/2413134.View ArticleGoogle Scholar
- McLysaght A, Hokamp K, Wolfe KH: Extensive genomic duplication during early chordate evolution. Nat Genet. 2002, 31 (2): 200-204. 10.1038/ng884.PubMedView ArticleGoogle Scholar
- Popovici C, Leveugle M, Birnbaum D, Coulier F: Homeobox gene clusters and the human paralogy map. FEBS letters. 2001, 491 (3): 237-242. 10.1016/S0014-5793(01)02187-1.PubMedView ArticleGoogle Scholar
- Kudo M: Molecular evolutionary study of the vertebrate adaptive immune system. Master thesis. 2005, Nara Institute of Science and TechnologyGoogle Scholar
- Yamamori T, Sarai A: Coevolution of cytokine receptor families in the immune and nervous systems. Neurosci Res. 1992, 15 (3): 151-161. 10.1016/0168-0102(92)90001-S.PubMedView ArticleGoogle Scholar
- Khan AA, Bose C, Yam LS, Soloski MJ, Rupp F: Physiological regulation of the immunological synapse by agrin. Science. 2001, 292 (5522): 1681-1686. 10.1126/science.1056594.PubMedView ArticleGoogle Scholar
- Kikutani H, Kumanogoh A: Semaphorins in interactions between T cells and antigen-presenting cells. Nat Rev Immunol. 2003, 3 (2): 159-167. 10.1038/nri1003.PubMedView ArticleGoogle Scholar
- Escriva H, Manzon L, Youson J, Laudet V: Analysis of lamprey and hagfish genes reveals a complex history of gene duplications during early vertebrate evolution. Mol Biol Evol. 2002, 19 (9): 1440-1450.PubMedView ArticleGoogle Scholar
- Pancer Z, Saha NR, Kasamatsu J, Suzuki T, Amemiya CT, Kasahara M, Cooper MD: Variable lymphocyte receptors in hagfish. Proc Natl Acad Sci USA. 2005, 102 (26): 9224-9229. 10.1073/pnas.0503792102.PubMedPubMed CentralView ArticleGoogle Scholar
- Pancer Z, Amemiya CT, Ehrhardt GR, Ceitlin J, Gartland GL, Cooper MD: Somatic diversification of variable lymphocyte receptors in the agnathan sea lamprey. Nature. 2004, 430 (6996): 174-180. 10.1038/nature02740.PubMedView ArticleGoogle Scholar
- The Ensembl website. [http://www.ensembl.org]
- The JGI website. [http://www.jgi.doe.gov/]
- Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ: Basic local alignment search tool. Jour Mol Biol. 1990, 215 (3): 403-410.View ArticleGoogle Scholar
- Katoh K, Kuma K, Toh H, Miyata T: MAFFT version 5: improvement in accuracy of multiple sequence alignment. Nucl Acids Res. 2005, 33 (2): 511-518. 10.1093/nar/gki198.PubMedPubMed CentralView ArticleGoogle Scholar
- Schmidt HA, Strimmer K, Vingron M, von Haeseler A: TREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing. Bioinformatics. 2002, 18 (3): 502-504. 10.1093/bioinformatics/18.3.502.PubMedView ArticleGoogle Scholar
- Jones DT, Taylor WR, Thornton JM: The rapid generation of mutation data matrices from protein sequences. Comput Appl Biosci. 1992, 8 (3): 275-282.PubMedGoogle Scholar
- Harris MA, Clark J, Ireland A, Lomax J, Ashburner M, Foulger R, Eilbeck K, Lewis S, Marshall B, Mungall C: The Gene Ontology (GO) database and informatics resource. Nucl Acids Res. 2004, D258-261. 32 Database
- The Gene Ontology consortium. [http://www.geneontology.org/]
- Barrett T, Troup DB, Wilhite SE, Ledoux P, Rudnev D, Evangelista C, Kim IF, Soboleva A, Tomashevsky M, Edgar R: NCBI GEO: mining tens of millions of expression profiles – database and tools update. Nucl Acids Res. 2007, D760-765. 10.1093/nar/gkl887. 35 Database
- The GEO website. [http://www.ncbi.nlm.nih.gov/geo/]
- The Flybase database. [http://www.flybase.bio.indiana.edu/]