BACKGROUND
recently a number of genome analysis methods have been developed that predict protein-protein interactions and functional associations between proteins based primarily on genome context and not directly relying on sequence homology  <cit> .
the context of a gene in a complete genome relates to its location on the genome and also its phylogenetic distribution across multiple genomes  <cit> .
such methods include the detection of gene clusters that are conserved across multiple genomes  <cit> , the detection of gene sets which exhibit similar presence or absence patterns called phylogenetic profiles  <cit>  and finally the detection of gene fusion events  <cit> , all indicative of protein interaction or general functional association of the corresponding gene products.
the gene-fusion approach relies on the observation that pairs of genes encoding proteins of known function  tend to be found in other species as a fused composite gene encoding a single multifunctional protein.
this event had been previously noted in protein evolution but not explicitly used for the prediction of protein function  <cit> .
the fusion of two genes, which interact or are closely functionally linked, appears to decrease the regulational load in the cell, for a particular process  <cit>  and may hence be advantageous under specific circumstances.
therefore, the detection of a gene fusion in one  genome allows the prediction of functional association between corresponding homologous genes that remain separate in another  genome.
typically, we refer to the fused gene as a 'composite' protein, while the un-fused counterpart genes in the reference organism are referred to as 'component' proteins  <cit> .
the accuracy of this approach has previously been demonstrated  <cit> , however the presence of so-called 'promiscuous domains' in eukaryotic species has made it problematic to apply this method across a broad phylogenetic spectrum.
these widespread domains  are present in a multitude of combinations in many eukaryotic proteins  <cit>  and can confound gene-fusion detection by appearing to be multiple conserved examples of gene-fusion components  <cit> .
for this reason, we have improved our detection method to filter highly promiscuous domains from predictions.
previously, we used sequence homology and clustering to attempt resolving this issue, however this approach is computationally intensive.
for this analysis, we take a simpler approach based on the pfam domain database  <cit> .
by delineating the domain architecture of each protein involved in a fusion event, we are able to locate and filter those domains that appear to link an inordinate number of proteins together based on domain interaction graph connectivity analysis .
this approach has only recently been made feasible due to the increasing coverage of the pfam domain database  and the availability of large-scale computational resources.
in order to further explore the evolution and dynamics of gene fusion events in complete genomes, we have applied the approach to a set of  <dig> genomes.
this represents the largest analysis of its type undertaken thus far.
as we have previously stated, the fidelity of functional predictions based on genome context methods greatly improves with larger numbers of available genomes.
hence, we use the cogent database  <cit>  as our source for genome sequences, as it is constantly updated with new genomes and uses a consistent naming scheme for protein identifiers.
the availability of a large number of genomes allows us to explore various aspects of fusion and function.
in this work, we explore the distribution of both fusion events and of composite and component proteins across each of the  <dig> genomes and their taxa.
we also quantify the cumulative effect of how access to multiple genomes allows more predictions of functional association, and assess whether we are approaching the limits of prediction with larger numbers of reference genomes.
finally, we automatically assign proteins involved in fusion events with gene ontology   <cit>  classifiers and show that certain classes of genes tend to be more frequently involved in fusion events than those of other classes, previously shown for individual classes  <cit> , and that genes involved in fusions tend to be of the same functional class, an observation that has been previously reported   <cit> .
we also compare these functional categories with interactions obtained from an experimental protein-protein interaction database.
these results are further validated using a robust randomized trial.
RESULTS
gene fusions
a total of  <dig> complete genomes from the cogent database  <cit>  were analyzed for fusion events .
this set comprises  <dig> bacterial,  <dig> archaeal and  <dig> eukaryotic genomes, representing a total of  <dig>  proteins.
from these genomes, a total of  <dig> , <dig> possible distinct fusion events were detected involving  <dig>  proteins.
in total,  <dig>  composite and  <dig>  component proteins were detected.
these fusion events were filtered to remove those containing promiscuous domains using a threshold measure based on graph connectivity of protein domains .
filtering the most promiscuous domains , in this fashion, removes a total of  <dig> , <dig> interactions, leaving  <dig> , <dig> potential interactions for further analysis.
since interaction data for all these genomes are not available, in order to validate this approach, we aim at high specificity , and low sensitivity .
the two million unique pairwise interactions that can be detected form a high-quality dataset upon which further analyses can be performed.
phylogenetic distribution of gene fusion events
across different genomes the pattern of detection of gene fusion events is very different.
as has been observed previously  <cit> , eukaryota exhibit the largest numbers of predicted interactions  because they represent the largest genomes and total number of detected interactions relates strongly to genome size .
however, a number of exceptions to this observation exist.
for example; plasmodium falciparum exhibits a larger number of detected interactions, than one might expect , for its genome size; similarly, shigella flexneri  has the largest number of detected interactions  of any bacterium , yet its genome is only about half the size of the largest bacterial genome .
interestingly, the other strain of s. flexneri  does not exhibit such a large number of detected interactions .
both of these serotypes are pathogenic strains isolated from infected patients, and their genomes possess large numbers of rearrangements  <cit> , however the exact reason for such a striking difference is, as yet, undetermined.
when one examines the distribution of the fraction of detected composite  proteins in each genome, compared with its genome size, a similar pattern across taxa emerges  .
the larger eukaryotic genomes tend to have a larger proportion of fused composite proteins, than smaller genomes, with human and mouse the largest, at 29% apiece.
once again, the p. falciparum genome is an exception to this rule with a far greater proportion of composite genes  than one might expect for its genome size, perhaps due to its role as an obligate intracellular parasite.
the bordetella pertussis genome possesses the largest proportion of composites of any other bacterial genome studied .
in general, the archaea appear to contribute the fewest composite proteins in the analysis, even in relation to their small genome sizes, although this may be due to the fact that there were only  <dig> archaeal genomes available .
as expected, a similar pattern emerges between the number of unique components versus composites , irrespective of genome size.
the distribution of the fraction of proteins involved in predicted interactions for the three major taxonomic domains illustrates the major differences between each domain .
for archaea and bacteria, the distribution is unimodal with a median between 12–14% of proteins involved in interactions for archaea and 16–18% for bacteria.
the distribution for eukaryota is manifestly bimodal with many genomes at 14–16% and a separate set of outliers at 30–42%.
inspection of the latter set indicates that it represents multicellular species, while the set with the smaller median value represents unicellular species.
all of the above percentages are markedly higher than those obtained in a previous analysis involving  <dig> genomes  <cit> , where on average 9% of proteins of the total encoded in a genome were found to correspond to unique components involved in gene fusion.
cumulative effect of multiple genomes
in order to assess the effect of an increasing number of genomes for fusion analysis, we analyzed the number of detected individual interactions for each genome based on fused genes detected in each of the reference genomes.
the reference genomes are displayed in terms of the number of interactions they may contribute for each query genome.
for those genomes with good correlation coefficients between the relative rank order of reference species and number of contributed interactions , these data are virtually linear , with  <dig> such genomes having slopes greater than  <dig>  .
these data indicate that there does not appear to be a saturation effect and increasing numbers of genomes might still give rise to novel protein interaction predictions .
in particular, certain reference genomes generate a large number of novel interactions, e.g.
eukaryotic genomes, typically in a non-monotonic fashion.
this indicates that detection of protein interactions based on gene fusion will continue to be a powerful tool for genome analysis.
a small number of genomes did appear to exhibit saturation effects, where new reference genomes did not significantly boost the number of initially obtained interactions .
one striking case being that of the wolbachia pipientis genome .
this result is not surprising as w. pipientis is an endosymbiont of insect species and possesses a minimal genome necessary for transmission and survival  <cit> .
in fact, many other species with similar slopes also possess small genomes and/or are endosymbionts and obligate intracellular parasites e.g.
nanoarchaeum equitans , mycoplasma genitalium , and a number of chlamydia strains such as chlamydia trachomatis   – .
another such example is the extremophile methanopyrus kandleri  which is a rod-shaped gram-positive methanogen that grows chemolithoautotrophically at 80–110°c in the h2co <dig> atmosphere of a deep water geothermal chimney  <cit> .
these results appear to indicate that it might be more difficult to detect protein interactions for genomes from poorly represented taxonomic classes, i.e.
most gene fusion events are detected between large groups of related species.
this result is borne out when one examines the genomes with the largest slopes.
the top ten such genomes are all proteobacteria, actinobacteria or firmicutes, classes of bacteria highly over-represented in cogent .
biological diversity of gene fusion events
in order to delineate the functional diversity of proteins predicted to interact by virtue of gene fusion events, we infer functional classes for each component of a fusion event , based on go  <cit>  annotations derived from their domains .
a number of functional classes relating to both the 'biological process' and 'molecular function' ontologies appear to be highly over-represented in components of gene fusion events .
the most highly over-represented molecular function classes, overall, are for receptors and protein transporters, both occurring more than ten times than expected .
small protein conjugating enzymes are the third most over-represented class, occurring eight times more than expected.
these three classes represent excellent targets for gene fusion, as they involve proteins that either form structural complexes or facilitate the channeling of various small-molecule and macromolecular substrates  <cit> .
transcription factors, and pore/channel transporters are also highly over-represented  .
we compared this breakdown of functional classes for gene-fusion based predictions of interaction against a set of experimentally determined interacting proteins from the dip database  <cit> , to determine whether the detected classes are representative of interacting proteins in general, or only those involved in gene fusion events .
the breakdown of go classes for dip interactions is significantly different than those obtained by gene fusion analysis , consistent with previous findings that certain classes of genes are more likely to be involved in fusion events, previously shown in certain cases  <cit> , thus, these sets of interactions appear to contain functionally diverse sets of proteins.
finally, we evaluate the performance of gene fusion based prediction of protein-protein interaction and functional association, using these derived functional classes.
we expect that if the method performs accurately, then predicted interactions should, in most cases, link proteins of the same or similar functional class  <cit> .
in order to test this hypothesis, we calculated the number of interactions for which both sets of proteins had matching functional classes .
we then generate  <dig> randomized trials and performed the same evaluation .
when the distribution of matches is compared for the real and randomized data, we find that the observed pairs are significantly more likely to link genes of the same functional class, than randomized pairs  with  <dig> % of real interactions having matching classes, compared to an average of  <dig> % for the randomized trials .
examples of protein interactions for validated annotations in chlamydia
to further exemplify the validity of our predictions, we validated all detected pairs of interacting proteins against a high-quality, manually curated set of functional annotations from the genome of chlamydia trachomatis serovar d  <cit> .
this set consists of  <dig> pairs .
of the  <dig> instances,  <dig>  are well-known interactions , evident from the associated annotations .
another  <dig>  instances  are probably false, due to paralogy between one of the proteins and the genuine interacting partner .
there are  <dig>  instances  where at least one of the partners is not functionally characterized .
in cases where one protein is characterized, this analysis provides an indication for the association of the other partner in a similar process .
the remaining  <dig> instances  represent interactions, ranging from the highly likely, supported by annotation , to reasonable predictions , to highly surprising  .
a network of protein interactions in the model plant species arabidopsis
finally, a question that typically arises in this type of analysis relates to the efficacy of this method for the delineation of protein interactions in eukaryotic species.
in fact, a large part of the predicted interactions occurs in a relatively small group of eukaryotes .
for instance, about a fifth of the total number of detected interactions occur in arabidopsis thaliana.
the analysis of this network is of particular interest, since there have not been yet any high-throughput protein interaction detection experiments for this important model plant species.
in total, we are able to predict  <dig>  interactions in a. thaliana, encompassing  <dig>  unique proteins and forming  <dig> distinct network components.
the structure of the a. thaliana interaction network is representative of those found in other eukaryotes, with a giant component dominating the picture, and smaller peripheral interaction clusters .
an analysis of such network presents a challenge, for two main reasons: first, complex eukaryotic species undergo various developmental stages, thus any protein complement analysis has to take into account sub-cellular, cell type, tissue, organ and developmental stage co-ordinates, something that is certainly not always possible; second, the paralogous nature of eukaryotic genomes obscures potential protein interactions, usually by over-predicting possible, not necessarily false, functional associations  .
in order to perform an analysis of the functional network in this model plant species, we focus on the functional significance of one-to-one interactions only, i.e.
these interactions where the two members are found to interact with each other, on the basis of a composite protein elsewhere.
our survey reveals a few examples of well-annotated interactions, as well as predictions for novel cases of interacting proteins.
known cases include a multitude of self-evident protein pairs, as assessed by the corresponding gene descriptions.
this fact provides further reassurance for the relevance of this approach.
such examples include the detection of interactions between components of the nadh-ubiquinone oxidoreductase complex, components of the l-arginine biosynthesis pathway, and components of the glycerophospholipid metabolism pathway .
less evident examples include interactions between proteins that are less well characterized, with partial annotations that can be used to shed a light on the biological process in which these proteins participate.
one such case is the interaction between at4g <dig>   and at2g <dig>  , which provides further reassurance that at2g <dig> is indeed a component of the molybdopterin synthase complex .
another less clear case is the interaction between at2g <dig>   and at5g <dig>  , which suggests that the latter protein might also be involved in spliceosome activity .
a particularly striking example is the interaction between at1g <dig>  and at1g <dig> , both hypothetical proteins: the former containing a noc3p domain  <cit>  and the latter containing a cbf domain, a domain found in the yeast noc <dig> protein  <cit>   .
in yeast, noc1p and noc3p are required for ribosome maturation and transport, where mutation of each noc protein impairs intranuclear transport of 60s subunits at different stages and inhibits pre-rrna processing  <cit> .
since homologs for each of the noc1-3p proteins exist in higher eukaryotes, it is likely that their functions in ribosome synthesis are conserved in evolution  <cit> .
the inferred interaction between the two a. thaliana proteins provides some preliminary evidence for the existence of an homologous complex and molecular process in a. thaliana.
CONCLUSIONS
we present the largest analysis, as yet undertaken, toward the computational detection of protein-protein interactions and functional associations based on gene fusion events.
we illustrate that gene fusion events are widespread across the different domains of life and are present in intricate patterns across various genomes, both in terms of their phylogenetic distribution and in terms of the biological diversity of proteins involved in these events.
the fact that we have by no means saturated the predictive power of this approach with  <dig> genomes is encouraging, since previous research has already shown that the fidelity of these predictions increases as more genomes are considered.
unlike other genome context methods, such as phylogenetic profiles which perform best with non-eukaryotic genomes  <cit> , the gene fusion approach benefits from the multi-domain nature of eukaryotic proteins for the prediction of protein interactions, if properly implemented.
as more genomes become available, particularly for taxonomic groups that are currently not well represented, we expect that gene fusion analysis will continue to be a valuable tool for the rigorous exploration of protein function in entire genome sequences  <cit> .

 recently a number of genome analysis methods have been developed that predict protein-protein interactions and functional associations between proteins based primarily on genome context and not directly relying on sequence homology. the context of a gene in a complete genome relates to its location on the genome and also its phylogenetic distribution across multiple genomes. such methods include the detection of gene clusters that are conserved across multiple genomes, the detection of gene sets which exhibit similar presence or absence patterns called phylogenetic profiles and finally the detection of gene fusion events, all indicative of protein interaction or general functional association of the corresponding gene products. the gene-fusion approach relies on the observation that pairs of genes encoding proteins of known function tend to be found in other species as a fused composite gene encoding a single multifunctional protein. this event had been previously noted in protein evolution but not explicitly used for the prediction of protein function. the fusion of two genes, which interact or are closely functionally linked, appears to decrease the regulational load in the cell, for a particular process and may hence be advantageous under specific circumstances. therefore, the detection of a gene fusion in one genome allows the prediction of functional association between corresponding homologous genes that remain separate in another genome. typically, we refer to the fused gene as a'composite' protein, while the un-fused counterpart genes in the reference organism are referred to as'component' proteins. the accuracy of this approach has previously been demonstrated, however the presence of so-called'promiscuous domains' in eukaryotic species has made it problematic to apply this method across a broad phylogenetic spectrum. these widespread domains are present in a multitude of combinations in many eukaryotic proteins and can confound gene-fusion detection by appearing to be multiple conserved examples of gene-fusion components. for this reason, we have improved our detection method to filter highly promiscuous domains from predictions. previously, we used sequence homology and clustering to attempt resolving this issue, however this approach is computationally intensive. for this analysis, we take a simpler approach based on the pfam domain database. by delineating the domain architecture of each protein involved in a fusion event, we are able to locate and filter those domains that appear to link an inordinate number of proteins together based on domain interaction graph connectivity analysis. this approach has only recently been made feasible due to the increasing coverage of the pfam domain database and the availability of large-scale computational resources. in order to further explore the evolution and dynamics of gene fusion events in complete genomes, we have applied the approach to a set of genomes. this represents the largest analysis of its type undertaken thus far. as we have previously stated, the fidelity of functional predictions based on genome context methods greatly improves with larger numbers of available genomes. hence, we use the cogent database as our source for genome sequences, as it is constantly updated with new genomes and uses a consistent naming scheme for protein identifiers. the availability of a large number of genomes allows us to explore various aspects of fusion and function. in this work, we explore the distribution of both fusion events and of composite and component proteins across each of the genomes and their taxa. we also quantify the cumulative effect of how access to multiple genomes allows more predictions of functional association, and assess whether we are approaching the limits of prediction with larger numbers of reference genomes. finally, we automatically assign proteins involved in fusion events with gene ontology classifiers and show that certain classes of genes tend to be more frequently involved in fusion events than those of other classes, previously shown for individual classes, and that genes involved in fusions tend to be of the same functional class, an observation that has been previously reported. we also compare these functional categories with interactions obtained from an experimental protein-protein interaction database. these results are further validated using a robust randomized trial.  gene fusions a total of complete genomes from the cogent database were analyzed for fusion events. this set comprises bacterial, archaeal and eukaryotic genomes, representing a total of proteins. from these genomes, a total of, possible distinct fusion events were detected involving proteins. in total, composite and component proteins were detected. these fusion events were filtered to remove those containing promiscuous domains using a threshold measure based on graph connectivity of protein domains. filtering the most promiscuous domains, in this fashion, removes a total of, interactions, leaving, potential interactions for further analysis. since interaction data for all these genomes are not available, in order to validate this approach, we aim at high specificity, and low sensitivity. the two million unique pairwise interactions that can be detected form a high-quality dataset upon which further analyses can be performed. phylogenetic distribution of gene fusion events across different genomes the pattern of detection of gene fusion events is very different. as has been observed previously, eukaryota exhibit the largest numbers of predicted interactions because they represent the largest genomes and total number of detected interactions relates strongly to genome size. however, a number of exceptions to this observation exist. for example; plasmodium falciparum exhibits a larger number of detected interactions, than one might expect, for its genome size; similarly, shigella flexneri has the largest number of detected interactions of any bacterium, yet its genome is only about half the size of the largest bacterial genome. interestingly, the other strain of s. flexneri does not exhibit such a large number of detected interactions. both of these serotypes are pathogenic strains isolated from infected patients, and their genomes possess large numbers of rearrangements, however the exact reason for such a striking difference is, as yet, undetermined. when one examines the distribution of the fraction of detected composite proteins in each genome, compared with its genome size, a similar pattern across taxa emerges. the larger eukaryotic genomes tend to have a larger proportion of fused composite proteins, than smaller genomes, with human and mouse the largest, at 29% apiece. once again, the p. falciparum genome is an exception to this rule with a far greater proportion of composite genes than one might expect for its genome size, perhaps due to its role as an obligate intracellular parasite. the bordetella pertussis genome possesses the largest proportion of composites of any other bacterial genome studied. in general, the archaea appear to contribute the fewest composite proteins in the analysis, even in relation to their small genome sizes, although this may be due to the fact that there were only archaeal genomes available. as expected, a similar pattern emerges between the number of unique components versus composites, irrespective of genome size. the distribution of the fraction of proteins involved in predicted interactions for the three major taxonomic domains illustrates the major differences between each domain. for archaea and bacteria, the distribution is unimodal with a median between 12–14% of proteins involved in interactions for archaea and 16–18% for bacteria. the distribution for eukaryota is manifestly bimodal with many genomes at 14–16% and a separate set of outliers at 30–42%. inspection of the latter set indicates that it represents multicellular species, while the set with the smaller median value represents unicellular species. all of the above percentages are markedly higher than those obtained in a previous analysis involving genomes, where on average 9% of proteins of the total encoded in a genome were found to correspond to unique components involved in gene fusion. cumulative effect of multiple genomes in order to assess the effect of an increasing number of genomes for fusion analysis, we analyzed the number of detected individual interactions for each genome based on fused genes detected in each of the reference genomes. the reference genomes are displayed in terms of the number of interactions they may contribute for each query genome. for those genomes with good correlation coefficients between the relative rank order of reference species and number of contributed interactions, these data are virtually linear, with such genomes having slopes greater than. these data indicate that there does not appear to be a saturation effect and increasing numbers of genomes might still give rise to novel protein interaction predictions. in particular, certain reference genomes generate a large number of novel interactions, e.g. eukaryotic genomes, typically in a non-monotonic fashion. this indicates that detection of protein interactions based on gene fusion will continue to be a powerful tool for genome analysis. a small number of genomes did appear to exhibit saturation effects, where new reference genomes did not significantly boost the number of initially obtained interactions. one striking case being that of the wolbachia pipientis genome. this result is not surprising as w. pipientis is an endosymbiont of insect species and possesses a minimal genome necessary for transmission and survival. in fact, many other species with similar slopes also possess small genomes and/or are endosymbionts and obligate intracellular parasites e.g. nanoarchaeum equitans, mycoplasma genitalium, and a number of chlamydia strains such as chlamydia trachomatis –. another such example is the extremophile methanopyrus kandleri which is a rod-shaped gram-positive methanogen that grows chemolithoautotrophically at 80–110°c in the h2co atmosphere of a deep water geothermal chimney. these results appear to indicate that it might be more difficult to detect protein interactions for genomes from poorly represented taxonomic classes, i.e. most gene fusion events are detected between large groups of related species. this result is borne out when one examines the genomes with the largest slopes. the top ten such genomes are all proteobacteria, actinobacteria or firmicutes, classes of bacteria highly over-represented in cogent. biological diversity of gene fusion events in order to delineate the functional diversity of proteins predicted to interact by virtue of gene fusion events, we infer functional classes for each component of a fusion event, based on go annotations derived from their domains. a number of functional classes relating to both the'biological process' and'molecular function' ontologies appear to be highly over-represented in components of gene fusion events. the most highly over-represented molecular function classes, overall, are for receptors and protein transporters, both occurring more than ten times than expected. small protein conjugating enzymes are the third most over-represented class, occurring eight times more than expected. these three classes represent excellent targets for gene fusion, as they involve proteins that either form structural complexes or facilitate the channeling of various small-molecule and macromolecular substrates. transcription factors, and pore/channel transporters are also highly over-represented. we compared this breakdown of functional classes for gene-fusion based predictions of interaction against a set of experimentally determined interacting proteins from the dip database, to determine whether the detected classes are representative of interacting proteins in general, or only those involved in gene fusion events. the breakdown of go classes for dip interactions is significantly different than those obtained by gene fusion analysis, consistent with previous findings that certain classes of genes are more likely to be involved in fusion events, previously shown in certain cases, thus, these sets of interactions appear to contain functionally diverse sets of proteins. finally, we evaluate the performance of gene fusion based prediction of protein-protein interaction and functional association, using these derived functional classes. we expect that if the method performs accurately, then predicted interactions should, in most cases, link proteins of the same or similar functional class. in order to test this hypothesis, we calculated the number of interactions for which both sets of proteins had matching functional classes. we then generate randomized trials and performed the same evaluation. when the distribution of matches is compared for the real and randomized data, we find that the observed pairs are significantly more likely to link genes of the same functional class, than randomized pairs with % of real interactions having matching classes, compared to an average of % for the randomized trials. examples of protein interactions for validated annotations in chlamydia to further exemplify the validity of our predictions, we validated all detected pairs of interacting proteins against a high-quality, manually curated set of functional annotations from the genome of chlamydia trachomatis serovar d. this set consists of pairs. of the instances, are well-known interactions, evident from the associated annotations. another instances are probably false, due to paralogy between one of the proteins and the genuine interacting partner. there are instances where at least one of the partners is not functionally characterized. in cases where one protein is characterized, this analysis provides an indication for the association of the other partner in a similar process. the remaining instances represent interactions, ranging from the highly likely, supported by annotation, to reasonable predictions, to highly surprising. a network of protein interactions in the model plant species arabidopsis finally, a question that typically arises in this type of analysis relates to the efficacy of this method for the delineation of protein interactions in eukaryotic species. in fact, a large part of the predicted interactions occurs in a relatively small group of eukaryotes. for instance, about a fifth of the total number of detected interactions occur in arabidopsis thaliana. the analysis of this network is of particular interest, since there have not been yet any high-throughput protein interaction detection experiments for this important model plant species. in total, we are able to predict interactions in a. thaliana, encompassing unique proteins and forming distinct network components. the structure of the a. thaliana interaction network is representative of those found in other eukaryotes, with a giant component dominating the picture, and smaller peripheral interaction clusters. an analysis of such network presents a challenge, for two main reasons: first, complex eukaryotic species undergo various developmental stages, thus any protein complement analysis has to take into account sub-cellular, cell type, tissue, organ and developmental stage co-ordinates, something that is certainly not always possible; second, the paralogous nature of eukaryotic genomes obscures potential protein interactions, usually by over-predicting possible, not necessarily false, functional associations. in order to perform an analysis of the functional network in this model plant species, we focus on the functional significance of one-to-one interactions only, i.e. these interactions where the two members are found to interact with each other, on the basis of a composite protein elsewhere. our survey reveals a few examples of well-annotated interactions, as well as predictions for novel cases of interacting proteins. known cases include a multitude of self-evident protein pairs, as assessed by the corresponding gene descriptions. this fact provides further reassurance for the relevance of this approach. such examples include the detection of interactions between components of the nadh-ubiquinone oxidoreductase complex, components of the l-arginine biosynthesis pathway, and components of the glycerophospholipid metabolism pathway. less evident examples include interactions between proteins that are less well characterized, with partial annotations that can be used to shed a light on the biological process in which these proteins participate. one such case is the interaction between at4g and at2g, which provides further reassurance that at2g is indeed a component of the molybdopterin synthase complex. another less clear case is the interaction between at2g and at5g, which suggests that the latter protein might also be involved in spliceosome activity. a particularly striking example is the interaction between at1g and at1g, both hypothetical proteins: the former containing a noc3p domain and the latter containing a cbf domain, a domain found in the yeast noc protein. in yeast, noc1p and noc3p are required for ribosome maturation and transport, where mutation of each noc protein impairs intranuclear transport of 60s subunits at different stages and inhibits pre-rrna processing. since homologs for each of the noc1-3p proteins exist in higher eukaryotes, it is likely that their functions in ribosome synthesis are conserved in evolution. the inferred interaction between the two a. thaliana proteins provides some preliminary evidence for the existence of an homologous complex and molecular process in a. thaliana.  we present the largest analysis, as yet undertaken, toward the computational detection of protein-protein interactions and functional associations based on gene fusion events. we illustrate that gene fusion events are widespread across the different domains of life and are present in intricate patterns across various genomes, both in terms of their phylogenetic distribution and in terms of the biological diversity of proteins involved in these events. the fact that we have by no means saturated the predictive power of this approach with genomes is encouraging, since previous research has already shown that the fidelity of these predictions increases as more genomes are considered. unlike other genome context methods, such as phylogenetic profiles which perform best with non-eukaryotic genomes, the gene fusion approach benefits from the multi-domain nature of eukaryotic proteins for the prediction of protein interactions, if properly implemented. as more genomes become available, particularly for taxonomic groups that are currently not well represented, we expect that gene fusion analysis will continue to be a valuable tool for the rigorous exploration of protein function in entire genome sequences. 
we investigate the cumulative effect of increasing numbers of genomes on the fidelity and quantity of predictions, and show that, for large numbers of genomes, predictions do not become saturated but continue to grow linearly, for the majority of the species. by analyzing interaction graphs and applying a threshold that limits the maximum number of possible interactions within the largest graph components, we show that we can reduce the number of implausible interactions due to the detection of promiscuous domains. we illustrate the phylogenetic and functional diversity of gene fusion events across genomes, and their usefulness for accurate prediction of protein interaction and function. in order to explore the usefulness and scope of this approach for protein interaction prediction and generate a high-quality, non-redundant set of interacting pairs of proteins across a wide taxonomic range, we have exhaustively performed gene fusion analysis for genomes using an efficient variant of a previously developed protocol. gene fusion detection – also known as the'rosetta stone' method – involves the identification of fused composite genes in a set of reference genomes, which indicates potential interactions between its un-fused counterpart genes in query genomes. the precision of this method typically improves with an ever-increasing number of reference genomes. we also examine the percentage of component proteins with relation to the number of genes and further validate the functional categories that are highly represented in this robust set of detected genome-wide interactions.
 gene fusion detection – also known as the'rosetta stone' method – involves the identification of fused composite genes in a set of reference genomes, which indicates potential interactions between its un-fused counterpart genes in query genomes. the precision of this method typically improves with an ever-increasing number of reference genomes.  in order to explore the usefulness and scope of this approach for protein interaction prediction and generate a high-quality, non-redundant set of interacting pairs of proteins across a wide taxonomic range, we have exhaustively performed gene fusion analysis for genomes using an efficient variant of a previously developed protocol. by analyzing interaction graphs and applying a threshold that limits the maximum number of possible interactions within the largest graph components, we show that we can reduce the number of implausible interactions due to the detection of promiscuous domains. with this generally applicable approach, we generate a robust set of over million distinct and testable interactions encompassing proteins in species or strains, most of which have never been the subject of high-throughput experimental proteomics. we investigate the cumulative effect of increasing numbers of genomes on the fidelity and quantity of predictions, and show that, for large numbers of genomes, predictions do not become saturated but continue to grow linearly, for the majority of the species. we also examine the percentage of component proteins with relation to the number of genes and further validate the functional categories that are highly represented in this robust set of detected genome-wide interactions.  we illustrate the phylogenetic and functional diversity of gene fusion events across genomes, and their usefulness for accurate prediction of protein interaction and function. 