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Methods

Identification of genomic features using microsyntenies of domains: Domain teams

¹ Laboratoire Génome et Informatique, CNRS/UEVE, 91034 Evry cedex, France ² Infobiogen, 91034 Evry cedex, France ³ LacIM, Université du Québec à Montréal, Montréal, Québec, Canada ⁴ Soluscience, Biopôle Clermont-Limagne, 63360 Saint-Beauzire, France

	ABSTRACT

Top ABSTRACT DomainTeam The number of teams... Results and Discussion Methods REFERENCES WEB SITE REFERENCES

 
The detection, across several genomes, of local conservation of gene content and proximity considerably helps the prediction of features of interest, such as gene fusions or physical and functional interactions. Here, we want to process realistic models of chromosomes, in which genes (or genomic segments of several genes) can be duplicated within a chromosome, or be absent from some other chromosome(s). Our approach adopts the technique of temporarily forgetting genes and working directly with protein "domains" such as those found in Pfam. This allows the detection of strings of domains that are conserved in their content, but not necessarily in their order, which we refer to as domain teams. The prominent feature of the method is that it relaxes the rigidity of the orthology criterion and avoids many of the pitfalls of gene-families identification methods, often hampered by multidomain proteins or low levels of sequence similarity. This approach, that allows both inter- and intrachromosomal comparisons, proves to be more sensitive than the classical methods based on pairwise sequence comparisons, particularly in the simultaneous treatment of many species. The automated and fast detection of domain teams, together with its increased sensitivity at identifying segments of identical (protein-coding) gene contents as well as gene fusions, should prove a useful complement to other existing methods.

Although the term "synteny" originally referred to gene loci on the same chromosome, it is now widely used to refer to gene loci in different organisms, located on a chromosomal region of common evolutionary ancestry (Passarge et al. 1999). Thus, like many others, we shall use the word synteny to mean "local conservation of gene content and proximity across several organisms." This conservation probably points out, in many cases, to a selection pressure that tends to preserve the very proximity of the genes (Overbeek et al. 1999). As a consequence, the detection, across several genomes, of local conservation of gene content and proximity considerably helps the prediction of features of interest such as the physical interaction of proteins or their participation in common metabolic/regulatory networks (Marcotte et al. 1999a,b; Sali 1999; Galperin and Koonin 2000; Enright and Ouzounis 2001; Suyama and Bork 2001; von Mering et al. 2003; Korbel et al. 2004; Suhre and Claverie 2004). It also enables phylogenetic reconstructions through the identification of some of the numerous rearrangements events that can affect a genome, i.e., transpositions, deletions, insertions, inversions, fusions, and fissions (for review, see Sankoff 2003; Tang and Moret 2003).

Syntenic regions in eucaryotic genomes are generally defined as groups of two or more genes in one species that possess an ortholog on the same chromosome in another species, irrespective of their orientation or order (Pevzner and Tesler 2003; Jaillon et al. 2004). Here, one can speak of macrosynteny. Among prokaryotic genomes, the definition often adds the constraint of gene proximity—not necessarily contiguity—on both of the compared chromosomes (Bergeron et al. 2002; Luc et al. 2003; von Mering et al. 2003). The addition of this constraint results in much shorter conserved regions, in which case, one speaks of microsynteny. In the search for microsyntenies, one can insist on the conservation of gene order (Overbeek et al. 1999), but generally the order, contiguity, and even strandeness of the genes are relaxed to some extent (Fujibuchi et al. 2000; Tamames 2001; Bergeron et al. 2002; Calabrese et al. 2003; Durand and Sankoff 2003; Luc et al. 2003). Such relaxed microsyntenies were formally defined as gene teams by Bergeron et al. (2002).

In this study, we reinvestigate the search for microsyntenies by temporarily forgetting genes and working directly with protein domains, such as those found in Pfam (Bateman et al. 2004). We define chromosomal regions of conserved protein domains as domain teams. This choice has many interesting consequences. First, it allows us to process simultaneously intrachromosomal and interchromosomal comparisons. Indeed, since all of the protein-coding genes are decomposed into the domains of the proteins they code for, the usual step of finding the "bidirectional best hits" (e.g., Overbeek et al. 1999) is avoided, as well as the problem of partitioning sequences into nonoverlapping and biologically coherent clusters when multidomain proteins are present (see, for example, Yona et al. 1999). As a consequence, the rigidity of the orthology criterion is relaxed, and this approach allows us to process more realistic models of chromosomes, in which genes or segments of genes can be duplicated or even be absent from some chromosomes. Moreover, considering genes from the domain point of view enables us to integrate multiple-sequence alignments information; the position-sensitive scoring matrices (Gribskov et al. 1987) or the hidden Markov model profiles (Eddy 1998) that are stored in the Pfam database (Bateman et al. 2004) are known to be more sensitive than pairwise sequence alignments (e.g., Altschul et al. 1997). Finally, this model allows the detection of events such as fusions and duplications that would not be otherwise obvious.

We implemented this concept in a software named DomainTeam, freely available on request for academic purposes. The strength and limitations of this approach are discussed in detail in this work.

	DomainTeam

Top ABSTRACT DomainTeam The number of teams... Results and Discussion Methods REFERENCES WEB SITE REFERENCES

 
For reasons that will be made clear in the Results section, we shall here interest ourselves only in prokaryotic organisms. From a computational point of view, a chromosome can be defined as a collection of genes. Focusing on protein-coding genes, we want to define a chromosome as an ordered sequence of genes, where a unique coding sequence is associated with the nucleic acid sequence of a gene. In addition, we will divide each gene into one or more consecutive domains, each domain having a label. In the present case, the domains will be the Pfam domains of the encoded proteins (Pfam imposes a nonoverlapping rule on domains). In those few cases where a domain is inserted within another one (Bateman et al. 2004), the two domains are considered as adjacent. Overlapping genes (e.g., Fukuda et al. 1999) are similarly noted as contiguous (see Supplemental material, part 1).

The distance between two domains on the same chromosome is the difference between their positions. The position of a domain is defined using the order in which the domains appear on the chromosome (considering both DNA strands). Given a set S of domain labels, and a fixed distance , the labels of S divide a set of chromosomes in -chains. These are maximal runs of domains whose labels belong to S, such that the distance between two consecutive domains in a run is less than or equal to . For example, consider the domains A, B, and C (S ={A, B, C}) and the following set C of chromosomes in which these domains have been underlined:

C = ABD EFBCAGH IJAKBCLM NOPCAQARS

With = 2, the set S induces four -chains on the chromosomes of C: AB, BCA, AKBC, and CAQA. Note that the domains in different -chains can appear in different orders, and are not necessarily contiguous in a given -chain.

The content of a -chain is the subset of S of the labels that appear in the domains of the run. Each -chain that contains all of the labels of a set S is called an occurrence of the set S. A set of labels T is an extension of a set S if S is contained in T, and each occurrence of S is contained in an occurrence of T.

Definition 1
Given , a set S of labels is a -team of a set of chromosomes C if there is at least one occurrence of the set S in C, and S has no extension.

For example, in the above set C of chromosomes, the set S ={A, B, C} is a -team with = 2. It has two occurrences: BCA and AKBC. On the other hand, the set {B} is not a -team, since the set T ={A, B} is an extension of {B}, which means that each occurrence of label B implies a nearby occurrence of label A (the reverse is not true). Note that for = 2, the set T ={A, B} is also a -team, even if S contains T because T is not an extension of S. In this case, it has three occurrences: AB, BCA and AKB, which means that teams can be nested. Thus, in a set of n chromosomes, a set {A, B, C} can be a team conserved in m n chromosomes, but the shorter nested set {A, B} can be conserved in k > m chromosomes. DomainTeam will report both sets. In other words, DomainTeam does not report only those teams conserved in all of the chromosomes. Definition 1 is a direct generalization of the notion of gene teams introduced by Bergeron et al. (2002), which addressed the case of chromosomes containing a unique copy of each gene. He and Goldwasser (2004) also defined an extension of gene teams that allows multiple copies of a gene in a chromosome. However, the number of chromosomes must be restricted to two in order to achieve polynomial time complexity of their algorithm.

Figure 1 shows an example of a domain team found in four different organisms, exhibiting significant rearrangements. The five domains present in Yersima pestis are transposed, reversed, and duplicated in Salmonella typhi, Escherichia coli, and Vibrio cholerae. Another example is shown in the Supplemental material (part 2), depicting a team found in a set of 10 pathogenic bacteria.

View larger version (37K): [in this window] [in a new window]   Figure 1. A domain team ( = 3) of five domains with occurrences in four different organisms, with two occurrences in S. typhi. The first occurrence in S. typhi has the same domain order and content as the occurrence in Y. pestis, except that the whole segment is reversed. In the second occurrence in S. typhi, domain 294 is duplicated in reverse, sandwiching an insertion of a new domain. There is also a transposition of domain 294 and a duplication of domain 359, with respect to the four other occurrences. V. cholerae has a duplication of domain 2379 and E. coli a duplication of domain 294.

	The number of teams can be exponential

Top ABSTRACT DomainTeam The number of teams... Results and Discussion Methods REFERENCES WEB SITE REFERENCES

In order to show the exponential nature of Definition 1, consider a set L of n labels. Construct n chromosomes, each containing n-1 different labels obtained by removing one different label from L. Then, for = n-2, each proper subset of L is a -team. For example, with n = 5 and L ={A, B, C, D, E}, one gets the following five chromosomes:

ABCD ABCE ABDE ACDE BCDE

Each proper subset S of L has at least one occurrence, since S is contained in at least one chromosome, and the distance between two labels in a chromosome is always less than = n-2. For any domain d not in S, there is an occurrence of S that is not contained in , namely, the chromosome in which d was removed, therefore, S has no extension. Thus, S is a -team.

	Results and Discussion

Top ABSTRACT DomainTeam The number of teams... Results and Discussion Methods REFERENCES WEB SITE REFERENCES

 
Sensitivity of DomainTeam as viewed from three closely related genomes
As a way to test the sensitivity of our approach, we compared the results obtained by GeneTeam (Luc et al. 2003) and DomainTeam on a set of three chromosomes from closely related species. Both algorithms implement the same notion of microsynteny, but GeneTeam searches for regions of conserved orthologous protein-coding genes, while DomainTeam looks for regions of conserved protein domains content. The comparison was performed by mapping the chromosome of E. coli according to the syntenic regions it shares with both the S. typhi and Y. pestis chromosomes. In both programs, the parameter was set to 3 (allowing gaps of two consecutive genes or domains).

The results are summarized in Figure 2. The first obvious observation is that, for both programs, there are no huge teams that would encompass almost all of the genome. Rather, these three closely related species share a lot of microsyntenic regions (red color in Fig. 2). As expected, the teams obtained by DomainTeam (inner circle) and GeneTeam (outer circle) most often coincide. However, DomainTeam identifies larger and more numerous microsyntenies, as large nonsyntenic regions reported by GeneTeam are broken into several domain teams. The largest teams (green in Fig. 2) contain 31 and 26 genes for DomainTeam and GeneTeam, respectively. On the whole, the domain teams harbor 2207 genes (52% of the E. coli genes) and the gene teams 1662 (40%). This difference can be explained by at least three reasons, i.e., the use of the domain criterion (1) relaxes the need for strict homology, (2) permits various rearrangements of domains such as duplications or fusions, and (3) allows one to take paralogs into account; thus, the identification of duplicated regions. These three points are discussed in the next sections.

View larger version (50K): [in this window] [in a new window]   Figure 2. Map of the E. coli chromosome where genes colored red are those genes of E. coli that belong to a team also found in S. typhi and Y. pestis. Genes colored blue do not belong to a microsyntenic region shared by the three species. The inner circle shows the results of DomainTeam ( = 3). The outer circle shows those of GeneTeam ( = 3), based on the set of 2106 triplets of orthologous proteins obtained by the bidirectional best hit method. Syntenic regions reported by DomainTeam and GeneTeam coincide, but DomainTeam finds larger syntenic regions and identifies 2207 syntenic genes (52% of the E. coli genes) versus 1662 (40%) for GeneTeam. Green regions indicate the largest teams (31 and 26 genes) for DomainTeam and GeneTeam respectively. Figure 2 was drawn using GenomeViz (Ghai et al. 2004).

Figure 3 displays a schematic representation of a conserved team between E. coli and S. typhi, in which the proteins share five domains. The proteins encoded by pgtA and pgtB in S. typhi are known to be the members of a two-component regulatory system (Kadner 1996). As shown in the STRING database (von Mering et al. 2003), genes encoding two-component systems are often adjacent. The pairs YfhA/YfhK and Sty2809/Sty2811 are putative proteins that were assigned the same function (two-component regulatory system) by homology with proteins from other bacteria. However, sequence comparisons of PgtB with both YfhK and Sty2811 resulted in high BLAST2 E-values (10 and 0.17, respectively). As a consequence, the teams YfhA/YfhK and Sty2809/Sty2811 are not reported in STRING (they appear, however, in the KEGG database [Kanehisa et al. 2004] which is maintained through considerable manual expertise). Similarly, the probable duplication of pgtA and pgtB in S. typhi would not have been detected by an automated procedure based on pairwise comparisons. Note that the two inserted genes yfhG and sty2810 code for highly similar (hypothetical) proteins, which reinforces the probability that the two teams yfhA/yfhG/yfhK and STY2809/STY2810/STY2811 are genuine orthologous conserved segments whose proteins share the same functions in the two species.

View larger version (12K): [in this window] [in a new window]   Figure 3. An example of a team ( = 3) found in E. coli and S. typhi, corresponding to proteins that belong to the so-called "two-components regulatory system." The figures near the arrows are the BLAST E-values corresponding to the pairwise alignments of the proteins. It can be seen that the proteins YfhK and PgtB share but little sequence similarity, preventing this team from being detected by automated methods based on sequence comparisons. Similarly, PgtB and STY2811 are poorly similar, but the use of their Pfam labels led to pinpointing the duplication in S. typhi.

An example is given in Figure 4, which results from the search for conserved teams across five bacteria. This team is part of the tryptophan operon. While trpC is a stand-alone gene in Bacteroides thetaiotaomicron and Anabaena, it is fused with trpF in E. coli, S. typhi, and Y. pestis. As to trpG, it is fused with trpD in E. coli and S. typhi, but with trpE in Anabaena. These fusions are also detected by other methods based on sequence comparisons and are reported in FusionDB (Suhre and Claverie 2004) and AllFuse (Enright and Ouzounis 2001). However, the simultaneous comparison of several chromosomes by DomainTeam enables an immediate synthetic view of all the domain rearrangements.

View larger version (44K): [in this window] [in a new window]   Figure 4. Part of the tryptophan operon as identified in five bacteria ( = 3), exhibiting rearrangements and fusions of domains. Genes are labeled with their "ordered locus name" and, for E.coli and B. thetaiotaomicron, by their names.

View this table: [in this window] [in a new window]   Table 1. Some otherwise undetected composite genes reported by Domain Teams

Sensitivity of DomainTeam in massive comparisons
The simultaneous detection of a local conservation of orthologous genes in a number of chromosomes is a difficult task, since the sequence similarities can be weak in distant species. As a way to explore the sensitivity of DomainTeam across many genomes, we took as a test case the collection of E. coli operons stored in the RegulonDB database (Salgado et al. 2004; J. Collado-Vides, pers. comm.) and searched for their being conserved in a set of 14 other Gram-negative bacteria. From the set of 309 E. coli operons, 245 (79%) were fully recovered by at least one domain team. The conserved regions, hence, the teams, were always larger than the operons per se. In some cases, one or more genes within a team encompassing an operon were considered as insertions as they corresponded to proteins that had no Pfam label (an example is given in Fig. 5). The fifty operons that could not be entirely recovered as a single domain team were operons that contained too many consecutive Pfam unlabeled genes. They were thus broken into several partial segments. Fourteen operons in E. coli have no counterpart in any of the 14 other bacteria.

View larger version (50K): [in this window] [in a new window]   Figure 5. An example of a team ( = 3) found in four bacteria. This team corresponds to the "superoperon" yjeFE-amiB-mutL-miaA-hfq-hflXKC in the RegulonDB database, from b4167 to b4175 in E. coli. The conserved team thus extends beyond this operon. Some proteins do not contain a Pfam label (arrowheads). However, DomainTeams could retrieve the entire operon (and more) because these proteins are considered as insertions. The proteins are labeled by the "ordered locus name" of their genes.

View larger version (45K): [in this window] [in a new window]   Figure 6. Diagram of the phylogenetic distribution of 245 E. coli operons (of 309) fully recovered by at least one domain team in the set of 15 Gram-negative bacteria. The figure shows the distribution of the operons as a function of the number of chromosomes in which the operons were identified as syntenic. Each class has been divided into three categories, depending on the species where the teams were found, i.e., only in gammaproteobacteria or only in proteobacteria, or also in other taxons. Thus 96 operons (gray) were recovered only within close species (gammaproteobacteria), but the diagram shows that 149 other operons are conserved in more distant bacteria. Fourteen operons (class 1) were found only in E. coli.

The DomainTeam algorithm relies on pre-existing Pfam annotations of proteomes. As of December 2004, the Pfam library covers 74% of the proteins in SWISS-PROT/TrEMBL. This means that, on average, one protein in four is not (so far) labeled with a Pfam domain. As shown in Table 2, the Pfam coverage of complete proteomes is heterogeneous and varies from 96% for Buchnera aphidicola (a symbiotic bacterium endowed with a small genome) down to 40% for the archaebacterium Aeropyrum pernix. Obviously, DomainTeam will inevitably miss these unlabeled proteins and their corresponding genes. Most of the time, however, they will simply be considered as insertions within the teams (a false negative will be obtained when n consecutive genes are unlabeled, with n ). In order to apply DomainTeam to a newly sequenced genome, one would have first to annotate the proteins with the HMMER series of programs (http://hmmer.wustl.edu/), which may not be trivial. Since the aim of DomainTeam is not to supercede other tools dedicated to the search of microsyntenies, but to allow a more sensitive approach, we would rather advise using GeneTeam (Luc et al. 2003) as a first global approach for the study of a genome devoid of Pfam annotations.

View this table: [in this window] [in a new window]   Table 2. Coverage of the Pfam database

Some "promiscuous domains," such as DNA-binding domains, increase the number of small uninteresting teams. We addressed this problem through the use of a simple and empirical score, aimed at ranking the observed sets of teams as a function of the number of different domains they contain and the number of different chromosomes they belong to. For one set of a given -team, let np be the number of proteins in the team (not counting those proteins having one or more orphan Pfam label[s]), nd the number of different domains, no the number of occurrences of the team, and m the weighted mean of the frequencies of the domains in the set (m = _i n_i ^* f_i with n_i the number of times the domain i appears in the team and f_i the frequency of the domain i in the set). The score S is defined as

The best ranks are for those teams having a high number of proteins per chromosome (np/no) with a high number of different domains (nd) and a low number of promiscuous domains (1/m). It is our experience that teams with S > 90 are potentially interesting. See Supplemental material, part 4, as an example of the average number of proteins per occurrence in those teams having a score 90.

Practical computing considerations
The computation time required to compare a set of chromosomes is a function of the number of chromosomes, the number of proteins in the set, the value of , and the degree of conservation between the organisms under study. We tested the efficiency of DomainTeam on a 1 Ghz Sun ultrasparc III+ processor. The comparison with = 3 was performed in 5 min for the set of 16 Archaebacteria, 320 min for the set of 15 Gram-negative bacteria (containing very close species), and 29 min for the set of 13 Gram-positive bacteria. Thus, DomainTeam can compare a large number of chromosomes in a reasonable time. See Supplemental material, part 5, for more information about computing considerations.

Conclusions
Most of the methods aimed at detecting chromosomal regions of conserved gene content are based on the sequence similarities between the encoded proteins. We have shown that labeling the genes with the Pfam domain(s) of the proteins they code for, coupled with the notion of teams, adds an extra sensitivity to the process and makes it possible to compare simultaneously more than 10 chromosomes in a reasonable time. In addition, the program DomainTeam performs both inter- and intrachromosomal comparisons at the same time. It should prove a useful complement to other existing methods.

	Methods

Top ABSTRACT DomainTeam The number of teams... Results and Discussion Methods REFERENCES WEB SITE REFERENCES

 
Chromosome tables and Pfam annotations
The chromosomal ordered lists (chromosome tables) of the bacterial genes and their products (together with their UniProt IDs) were downloaded from the EBI "proteome" site (http://www.ebi.ac.uk/integr8/EBI-Integr8-HomePage.do). The Pfam annotations pertaining to the above-mentioned proteomes were downloaded from ftp://ftp.sanger.ac.uk/pub/databases/Pfam/database-files.

Bacterial sets
The bacterial sets used in this study were as follows:

Set of 15 Gram-negative bacteria: Anabaena sp, Bacteroides thetaiotaomicron, Borrelia burgdorferi, Campylobacter jejuni NCTC 11168, Chlamydia muridarum, Escherichia coli K12, Haemophilus influenzae, Helicobacter pylori ATCC 700392, Pseudomonas aeruginosa, Rhizobium loti, Salmonella typhi, Thermotoga maritima, Vibrio cholerae, Xylella fastidiosa, Yersinia pestis CO-92.

Set of 13 Gram-positive bacteria: Bacillus subtilis, Bifidobacterium longum, Clostridium perfringens, Corynebacterium efficiens, Deinococcus radiodurans, Enterococcus faecalis, Lactococcus lactis, Lactobacillus plantarum, Listeria monocytogenes, Mycobacterium leprae, Oceanobacillus iheyensis, Staphylococcus aureus N315, Streptococcus agalactiae serotype V.

Set of 16 archaebacteria: Aeropyrum pernix, Archaeoglobus fulgidus, Halobacterium sp, Methanobacterium thermoautotrophicum, Methanococcus jannaschii, Methanopyrus kandleri, Methanosarcina acetivorans, Methanosarcina mazei, Pyrococcus abyssi, Pyrobaculum aerophilum, Pyrococcus furiosus, Pyrococcus horikoshii, Sulfolobus solfataricus, Sulfolobus tokodaii, Thermoplasma acidophilum, Thermoplasma volcanium.

DomainTeam
The program DomainTeam is written in standard ANSI C and was run under both the Linux kernel 2.4.21 (Intel Pentium III at 1.3 GHz) and Sun Solaris 9 (Ultrasparc III+ at 1 Ghz) operating systems. The full results of DomainTeam for the Gram-negative and Gram-positive and archaebacteria can be viewed and queried by gene name from http://lgi.infobiogen.fr/DomainTeams. The DomainTeam program is freely available on request for academic purposes. Binary codes and scripts to display graphical outputs can be obtained from the same URL (Downloads). See also the link `Overview of the software' for an explanation of the text output format of DomainTeam.

	Acknowledgements

 
We thank the Infobiogen team for their patience and understanding during very long runs and M. Marshall from the Pfam team for her help in retrieving the proper annotation files.

	Footnotes

 
⁵ Corresponding author.
E-mail pasek{at}genopole.cnrs.fr; fax 33-1-60-87-38-97.

[Supplemental material is available online at www.genome.org.]

Article and publication are at http://www.genome.org/cgi/doi/10.1101/gr.3638405. Article published online before print in May 2005.

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	WEB SITE REFERENCES

Top ABSTRACT DomainTeam The number of teams... Results and Discussion Methods REFERENCES WEB SITE REFERENCES

 

ftp://ftp.sanger.ac.uk/pub/databases/Pfam/database-files; The directory of the Pfam ftp server that contains the Pfam annotations of the proteins in UniProt.

http://hmmer.wustl.edu/; HMMER series of programs.

http://www.ebi.ac.uk/integr8/EBI-Integr8-HomePage.do; The proteome Home Page at EBI.

http://lgi.infobiogen.fr/DomainTeams; DomainTeams full results and code downloads.

Received January 3, 2005; accepted in revised format March 28, 2005.

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