BACKGROUND
for proper axon guidance during neuronal development, it is of critical importance that neurons can distinguish self-connection from non-self connection.
for example, neurons must avoid fasciculating or connecting to themselves, in order to spread efficiently into a large area.
it has has previously been proposed that specific cell surface molecules provide “labels” for different neurons to distinguish self from non-self, thus allowing the formation of functional neuronal connections .
given the diverse types of neurons in the developing nervous system and the number of genes expressed in the brain, the self-recognition of a single neuron is likely to involve multiple genes that encode cell surface molecules.
alternatively, neurons can rely on a large set of diverse molecules derived from a single gene, such as dscam <dig>  in drosophila  <cit> .
the dscam <dig> gene was shown previously to code for thousands of protein isoforms, namely by way of alternative splicing.
three extracellular ig domains of dscam <dig>  are encoded by three variable exons , which are very similar in their amino acid sequences  <cit> .
each variable domain is encoded by a corresponding cluster of multiple alternative exons.
the numbers of alternative exons in the clusters are  <dig> ,  <dig>  and  <dig>   <cit> .
only one exon from each cluster is used through the stochastic expression process of alternative splicing, to express thouthands of dscam <dig> isoform at a time.
therefore, exon combinations from  <dig> exons  can form potentially as many as  <dig>   kinds of isoforms with domains with different binding affinity  <cit> .
earlier biochemical in vitro studies suggest that each dscam <dig> isoform has extracellular domains that prefer to bind to itself , while heterophilic binding  tends to be weak or below the detection limit of the assays used  <cit> .
importantly, in vivo studies with fly mutant forms with reduced dscam <dig> expression suggested that the diversity of the dscam <dig> isoform population, rather than the specific individual isoforms, is critical for proper neuronal connectivity in vivo  <cit> , although allele-specific phenotypes raised from few isoforms were observed for a small number of specific dscam <dig> mutants  <cit> .
great diversity of dscam <dig> isoforms have been observed across all arthropods  <cit> , and was found to be highly conserved in genomes spanning at least  <dig> million years of evolutionary distance.
thus, the question arises as to how variable exon usage contributes to the enormous diversity of dscam <dig> isoforms in arthropods?
several recent investigations have addressed this question .
comparative sequence analysis using fruit fly, mosquito and honeybee revealed that although the sequence diversity of dscam <dig> is high, the underlying mechanisms for generating thousands of isoforms appears to be shared among all three species  <cit> .
the main route to generate these exons was believed to be through reiterative exon duplication and deletion  <cit> .
a survey of  <dig> arthropod as well as non-arthropod genomes further suggested that these tandem exons are limited to arthropods only  <cit> .
the largest study on this topic so far was based on  <dig> duplicated exons across  <dig> arthropods, revealed that the evolutionary occurrence of newly-derived  exons is continuing in the exon  <dig> and  <dig> clusters to this day  <cit> .
together, these reports suggest that dscam <dig> diversity plays a critical role in arthropod biology, and more importantly, highlights its unique evolutionary properties comparing to other cell surface molecules and their families.
although those studies shed light on how such complex gene regulation evolved in arthropods, the precise role of a preference for homophilic binding and its development throughout evolution remains to be elucidated.
it is still unclear as to whether the dscam <dig> exons were duplicated randomly and retained indiscriminately, until the isoform population reached a threshold level of diversity.
nd-exons might then have been further selected based on properties such as the functional or expressional differences of different isoforms.
for instance, although dscam <dig> is broadly expressed in the nervous systems, there is evidence for r <dig> cells of the drosophila eye that suggests that not all isoforms are truly randomly expressed, and some isoforms preferably express certain exons of ig <dig>  <cit> .
both in vitro and in vivo experiments for drosophila dscam <dig> suggest that homophilic binding preference is tightly correlated with its functions  <cit> .
in this study, we explored the connection between the evolution of alternative exons on the one hand, and the self-binding affinities of the resulting isoforms on the other.
by extracting sequence features of isoforms using available biochemical data, we established a model to predict with high confidence the homophilic binding affinities of these isoforms.
additionally, an ancestor dscam <dig> sequence was constructed using genomic information from  <dig> drosophila species that was approximately 40– <dig> million year old.
comparative analysis of the ancient and current dscam <dig> on their homophilic binding affinities revealed that the current dscam isoforms have higher homophilic binding affinities than their ancestor.
furthermore, the same conclusion was reached using data from another phylogenetic reconstruction of the exon  <dig> and  <dig> clusters  <cit> , verifying the robustness of our analysis.
together, these results highlight a coherent driving force underlying the extensive exon diversification processes of dscam in drosophila species.
RESULTS
the homophilic binding affinity of dscam <dig> isoforms can be confidently predicted following sequence analysis
it was shown previously that alternative splicing of the three variable exons  of dscam <dig> can generate as many as  <dig>  ecto-domain isoforms, and those isoforms assist neuronal cells to distinguish self from non-self through homophilic binding  <cit> .
despite such a large number of possible isoforms, the binding affinity between the dscam <dig> proteins of the same isoform is particularly high compared to different isofroms  <cit> .
previous studies on dscam <dig> suggested that the observed homophilic binding is mainly determined by the primary protein sequences  <cit> .
thus, it should be possible to analyze the sequence information of all possible isoforms to obtain their homophilic binding affinities relative to heterophilic binding, which would be a time and resource-consuming task if performed using experimental approaches.
estimating the binding affinities of every possible dscam <dig> isoform may help to further investigate quantitatively the behavior of neurons expressing combinations of various dscam <dig> isoforms.
we identified a total of  <dig> dscam <dig> isoforms from published biochemical studies, for which the self-binding affinities were measured experimentally, and then selected the sequence features that correlated strongly with the homophilic binding affinities of the isoforms .
based on these sequence features and the motif conservation information, the binding affinities of dscam <dig> isoforms were predicted using a support vector regression  model, coupled with feature selection performed via relieff attributes algorithm  .
to assess our models, we measured the pearson correlation coefficient  and root mean square error  from our predictions, which were performed on separate datasets not used to train our models.
the correlation coefficient r indicates the level of correlation between the binding affinity predicted by our models and the affinity measured by biochemical experiments.
the results are shown in table  <dig>  where r and rmse were obtained as the average of a 10-fold cross-validation.
note that the prediction of binding affinity in our model comes from the combination of sequence features from the entire lg <dig>  lg <dig> and lg <dig> domain, rather than individual variable domain, as the synergistic binding of all these domains is likely higher than the sum of the individual binding affinity of lg2-lg <dig>  lg3-lg <dig> and lg7-lg <dig> table  <dig>
performance on independent test sets varies with different features
features
pearson correlation coefficient
root mean square error
initial feature size
filtered feature size
best correlation coefficient  and related root mean squared error  for datasets based on the  <dig> types of features alone and their combinations with  <dig> fold cross-validations.
the feature size indicates the number of features obtained by juxtaposing the different descriptors  and the one after ra algorithm .
the best prediction, r =  <dig>  and rmse =  <dig> , was achieved with a combination of using pseudo-amino acids, sequence composition and exon labels  constituting  <dig> encoding features .
of these parameters,  <dig> features were pseudo-amino acids,  <dig> were composition and  <dig> was exon label.
the ranked attributes and their descriptions are presented in additional file 1: table s <dig>
the mean absolute error  on test data unknown to the model with our best parameter combination was  <dig>  .
as the affinity values were normalized in the  <cit>  interval, this means the average error was less than 10% on average, indicating that our model can predicate self-binding affinities of dscam <dig> isoforms with high confidence on cross-validated data.
therefore, we re-trained the model on all available data, and then applied it again to calculate the self-binding profiles of all dscam <dig> isoforms.
the predicted binding profiles for dscam <dig> isoforms are consistent with the experimental data
the binding profiles predicted by our model were consistent with the values measured experimentally.
firstly, there is a highly significant correlation between the measured binding data and the predicted homophilic binding strength .
secondly, biochemical studies chose the isoforms containing exons  <dig> ,  <dig>  and  <dig>  as a general example, have shown that the contributions of the variable exons is not equal , revealing that the isoforms of x.
<dig>  had the highest average self-binding affinities, while  <dig> x.
<dig> isoforms showed lower affinities, with  <dig> .x exhibiting the lowest self-binding affinities  <cit> .
our calculation on the dscam <dig> isoform population generated a ranking of contributions of the different exons to self-binding affinity: exon 4 > exon 6 > exon  <dig>  therefore, the model predicted the order of self-binding affinity of the above case as x.
<dig>  >  <dig> x.25 >  <dig> .x, matching well with previously published biochemical studies  <cit> .
furthermore, the overall predicted binding affinity for the isoform  <dig> .
<dig>  was found to be  <dig> , which is in agreement with experimental data published earlier   <cit> .
in addition, the earlier experiments on the variable domain binding specificity based on two different contexts also indicated that the binding domain of exon  <dig> has the highest binding fold over the assay background, and that exon  <dig> has the lowest binding affinity  <cit> , which is precisely the order we obtained by prediction .
furthermore, of the  <dig> isoforms with the highest self-binding affinities, all contain exon  <dig> , and eight contain either exon  <dig>  or  <dig> .
this strongly suggests that the distribution of isoforms with high affinity to self is non-random among the duplicated exons present in the drosophila genome.figure  <dig>
profiles of the self-binding affinities of dscam1isoforms.
a: binding affinities of the  <dig> isoforms experimentally measured by wojtowicz et al.
; b: predicted binding affinities for all possible  <dig>  isoforms.
reconstruction of the drosophila ancestor dscam <dig> sequence reveals that isoforms carrying nd-exons have higher self-binding affinities
the complex structure of dscam <dig> gene may have evolved along two possible evolutionary pathways: 1) changing the number of alternative exons by exon duplication and deletion; 2) changing the composition of individual exons by point mutations .
the first path generates nd-exons without clear orthologs, while in the second pathway exons persist throughout evolution , preserving identifiable ancient orthologs.
whilst the evolutionary process of exon duplication is primarily responsible for the generation of the vast number of alternative exons of dscam <dig>  the actual driving force responsible for this extensive duplication remains unknown  <cit> .
as self-binding is an integral part of the control processes involved in cellular recognition during neuronal development, we hypothesized that the dscam protein evolved in such way in order to improve the homophilic binding affinity of its isoforms.
testing this hypothesis requires a comparison between the current and the ancient forms of the dscam <dig> protein.
to this end, we first reconstructed a phylogenetic tree for dscam <dig>  and based on the alignment of the protein sequences of  <dig> drosophila species, we then rebuilt the ancestral genomic sequence of dscam <dig> originating from approximately 40– <dig> million years ago  <cit> .
we compared the predicted self-binding affinities of different isoforms based on the information derived from both the ancestral and current genomes.
the reconstructed ancestral sequence of dscam <dig> contains  <dig>  nucleotides , resulting in a total of  <dig>  ancestor isoforms.
the gc content of the ancestral and current dscam <dig> sequences were found to be similar .
however, we found several differences related to their exon variants.
notably, no orthologs were found in the ancestral genome for several current exons, including exon  <dig> , exon  <dig> , and exon  <dig> .
therefore, those exons would have been generated more recently, probably within the past 40 ~  <dig> million years, by exon duplication, while the other exons would already have existed, and would have continued to evolve by point mutations.
here we define “new” isoforms as recently evolved variable domains  and “ancient” isoforms as those containing conserved domains .
we set out to investigate as to whether the recently generated isoforms  display enhanced self-binding affinities relative to the ancient isoforms .
we found that all of the isoforms carrying recently duplicated exons have significantly higher predicted self-binding affinities than those with ancient exon orthologs .
the mean self-binding affinity is  <dig>  ±  <dig>  for the new isoforms containing recently appeared exons in exon  <dig>   <dig> or  <dig>  with a mean self-binding affinity of  <dig>  ±  <dig>  for the conserved isoforms .
furthermore, the isoforms containing a recently duplicated exon  <dig> or exon  <dig> have greater self-binding affinities than the isoforms containing corresponding ancient exon  <dig> or exon  <dig> .
together, these results suggest that recent exon duplications strongly correlate with improved self-binding affinities of the resultant dscam <dig> isoforms.figure  <dig>
comparison of self-binding affinities of isoforms containing current and ancient exons.
a: distributions of self-binding affinities of isoforms containing exons originating from ancient exon  <dig> or  <dig>  and those containing exons without such ancient origins .
isoforms containing recently gained exons display higher self-binding affinities than conserved isoforms; b: distributions of self-binding affinities of the ancient and current isoforms.
the self-binding affinities of current isoforms are higher than those of ancient isoforms.
we next tested whether these results could be reproduced by using an independent dataset.
the evolutionary history of all of the exons  <dig>   <dig> and  <dig> clusters in  <dig> arthropods had been independently reconstructed previously  <cit> , and it was reported that nine forms of exon  <dig>  and thirteen of exon  <dig>  originated approximately  <dig> million years ago.
using this data set, we found a similar trend to that observed in the dataset described above, namely that all isoforms carrying the recently duplicated exons  <dig> or  <dig> display significantly higher self-binding affinities compared to those carrying conserved forms of exon  <dig> or  <dig> .
moreover, the isoforms containing both of the recently duplicated exons  <dig> and  <dig> have higher self-binding affinities than the isoforms with ancient exons  <dig> as well as ancient exon  <dig> .
taken together, these results indicate that dscam <dig> isoforms containing evolutionarily newer exons tend have higher homophilic binding affinities than ancient forms.
ancestral dscam proteins display lower self-binding affinities than recent forms
after investigating the self-binding affinities of dscam isoforms containing exons that have emerged 40– <dig> million years ago, we analyzed the self-binding profiles of the more conserved isoforms whose exons evolved by point mutations, and for which current-ancestor orthologs exist.
the mean self-binding affinities of all ancestor isoforms was shown to be  <dig>  ±  <dig> , which is significantly lower than that of the current isoforms derived from those ancestor isoforms, which was shown to be  <dig>  ±  <dig>  .
these results indicate that the self-binding affinities have increased considerably in this particular isoform population during the last 40 ~  <dig> million years of evolution.
upon further analysis of each pair of the current-ancestor orthologs it was revealed that there is a strong and significant correlation of self-binding affinities between the ancestor and current isoforms: isoforms with higher binding affinity in the past also have higher self-binding affinity at present .
this suggests that any point mutations that might have rendered self-binding to be of lower affinities were either suppressed or eliminated during evolution.figure  <dig>
correlation of self-binding affinities of current isoforms with those of their ancestral forms.
<dig> dscam <dig> isoforms were grouped together: in the figure.
the number of isoforms at each data point is presented in pseudo-color as indicated by the color bar below.
the dotted purple line indicates a positive correlation of self-binding affinities between time points.
the fact that higher homophilic binding affinity was observed in the current and newly evolved isoforms appears to contradict a neutral evolutionary model of dscam evolution.
if evolving towards a more diverse population were the only selective pressure, and homophilic binding affinity played no role in the evolution of dscam isoforms, what would happen?
a neutral evolutionary model would suggests that, assuming the mean binding affinity of all the isoforms is x in the ancestor dscam isoforms 40– <dig> million years ago, the mean binding affinity should be unchanged in both the isoforms containing newly duplicated exons and the conserved isoforms , and there would be no differences between them and their ancestral isoforms.
our data suggest that this is not the case for dscam <dig> evolution.
thus, this neutral evolutionary model is rejected.
discussion
both in vivo and in vitro studies of dscam have revealed that highly specific homophilic binding, which may arise from high binding affinities, is a general property of these cell surface proteins, and that this property is crucial for its proper physiological function  <cit> .
however, it is not feasible to assess experimentally the binding characteristics of all the possible isoforms.
similarily, structure prediction and modeling of all dscam <dig> isoforms for which crystal structures are available would be tremendously labor-intensive and time-consuming.
thus, to extract the principle relationship between biochemical binding data and sequence features, we used machine-learning methods to develop a computational model to predict dscam <dig> self-binding affinities with high confidence.
the self-binding affinities of all isoforms in drosophila genome and those of an ancestral genome, which diverged  <dig> million years ago, were calculated, and detailed computational comparisons were made to examine a) the binding affinities of the isoforms carrying recently generated exons and ancient exons, and b) the self-binding affinities of those current isoforms that are orthologs of ancient isoforms.
both comparisons revealed that the self-binding affinity of dscam <dig> became significantly enhanced over evolutionary time scales, suggesting that the dscam <dig> protein evolved to improve the its self-binding affinities, by sequence mutation and/or exon duplication .figure  <dig>
a schematic model depicting the evolution of dscam <dig> in arthropods.
nd-exons were created by exon duplication and/or sequence mutation.
over time, all isoforms containing old and nd-exons were under selection pressures for higher homophilic binding.
only those exons contributing to higher homophilic binding affinities were retained throughout evolution, and can be found in current genome.
a fascinating feature of dscam <dig> is its enormous isoform diversity, which was shown experimentally to be crucial for proper neural development and functioning immune responses in arthropods.
our results presented here suggest that diversity generated simply by exon duplication and sequence mutation may not be adequate, and that a neutral evolutionary model based solely on isoform diversity cannot explain this phenomenon.
even the molecular diversity  and biochemical diversity  together are likely not sufficient.
it appears that out of the pool of possible dscam <dig> isoforms that existed in the past, the evolutionary process selected only those isoforms that displayed enhanced self-binding affinities .
therefore, diverse isoforms are distinguished from each other not just by composition, but also by their increasingly specialized and progressively enhanced interactions.
we also noticed that the binding affinity we studied here does not equal to binding specificity, and both of them may play important roles in the evolution of dscam.
one may argue that a small improvement in the self-binding affinity would be not sufficient for generating visible benefit in the current drosophila genome.
as the discrimination between self and non-self neurons needs thousands of dscam isoforms, even a small change in the self-binding affinity of each dscam isoform would lead to significant differences at the population level of these isoforms, likely causing adequate biological effects as a consequence.
lastly, because of accumulation effects, it would be reasonable to suggest that the 15% increase in self-binding affinity in each isoform when compared to its own ancient isoforms might be crucial for the insect brain to avoid mistakes in the self-recognition process.
our computational predictions of the self-binding affinities of all possible dscam <dig> isoforms demonstrated the potential machine learning methods have for the rapid extraction of key molecular features, as well as for the systematic prediction of biological effects, which is crucial for the accurate large-scale analysis of complex molecular and cellular systems.
because so far, only a small fraction of dscam <dig> isoforms has been measured experimentally, the experimental datasets available for our analysis were relatively small.
however, the high correlation between measured binding affinities and predicted binding affinities illustrated the power of using such methods of support vector machines on small sample sizes.
profiling the homophilic binding characteristics of just 50% of dscam <dig> isoforms would require almost  <dig>  experimental measurements, even more if duplications were to be included, a scale that would require facilities for robotic liquid handling of cell transfections as well as automatic binding assays.
it needs to be stressed that careful acquisition of experimental data is vital for obtaining accurate and meaningful modeling results.
in this context, we recently became aware of a high-throughput domain docking method, which has the potential of simulating self-binding affinities  <cit> .
however, this method requires detailed structural information for each protein, and thus is far more time-consuming when compared to computational modeling.
so far, there is no indication as to whether other methods will become available soon for large-scale evolutionary studies like the one discussed here.
it is well-established that homophilic binding of dscam <dig> isoforms is crucial for proper functioning in a physiological setting.
therefore, evolutionary selection towards higher affinities towards self is likely to be crucial.
through random processes such as exon duplication and sequence mutation, newly evolved dscam <dig> isoforms would have acquired higher self-binding affinities over old isoforms.
selective pressure would then have acted upon these newer dscam <dig> isoforms to retain those with higher affinities for self.
we speculate that strong self-interactions would provide higher signal-to-noise ratios for cell-cell recognition, which might be just one event among many simultaneous molecular interactions on the cell surface.
such enhanced contrast for meaningful cell-to-cell signaling might ensure that neurons in the developing brain recognize and connect only to appropriate cell partners, in a correct manner.
as dscam <dig> is also critical during the launch of innate immune responses in insects, self-binding may also play a role in the proper functioning of the immune system.
as one of the most complex molecules in the genome of arthropods, dscam <dig> has been studied in great detail using biochemical, genetic and structure modeling approaches.
our comparative profiling of the self-binding affinities of the vast number of dscam <dig> isoforms at different time points throughout evolution demonstrates that an evolutionary approach is a powerful and complementary tool to gain novel insights into the mechanistic details of a complex biological system.
CONCLUSIONS
the mechanisms behind the great diversity of arthropod dscam <dig> forms containing new variable domains consistently emerging is not just a challenging question in neurobiology, but is equally important for our understanding of evolutionary processes in general.
the extensive diversity, in combination with the observed specific homophilic interactions of dscam <dig> isoforms provides an unique opportunity for biologists not only to trace the process of its evolution, but also to understand the driving forces behind the evolution of a specific gene at the molecular level.
in this study we demonstrated that those dscam <dig> isoforms generally evolved to gain higher hemophilic binding affinity during the evolution of arthropod.

 for proper axon guidance during neuronal development, it is of critical importance that neurons can distinguish self-connection from non-self connection. for example, neurons must avoid fasciculating or connecting to themselves, in order to spread efficiently into a large area. it has has previously been proposed that specific cell surface molecules provide “labels” for different neurons to distinguish self from non-self, thus allowing the formation of functional neuronal connections. given the diverse types of neurons in the developing nervous system and the number of genes expressed in the brain, the self-recognition of a single neuron is likely to involve multiple genes that encode cell surface molecules. alternatively, neurons can rely on a large set of diverse molecules derived from a single gene, such as dscam in drosophila. the dscam gene was shown previously to code for thousands of protein isoforms, namely by way of alternative splicing. three extracellular ig domains of dscam are encoded by three variable exons, which are very similar in their amino acid sequences. each variable domain is encoded by a corresponding cluster of multiple alternative exons. the numbers of alternative exons in the clusters are, and. only one exon from each cluster is used through the stochastic expression process of alternative splicing, to express thouthands of dscam isoform at a time. therefore, exon combinations from exons can form potentially as many as kinds of isoforms with domains with different binding affinity. earlier biochemical in vitro studies suggest that each dscam isoform has extracellular domains that prefer to bind to itself, while heterophilic binding tends to be weak or below the detection limit of the assays used. importantly, in vivo studies with fly mutant forms with reduced dscam expression suggested that the diversity of the dscam isoform population, rather than the specific individual isoforms, is critical for proper neuronal connectivity in vivo, although allele-specific phenotypes raised from few isoforms were observed for a small number of specific dscam mutants. great diversity of dscam isoforms have been observed across all arthropods, and was found to be highly conserved in genomes spanning at least million years of evolutionary distance. thus, the question arises as to how variable exon usage contributes to the enormous diversity of dscam isoforms in arthropods? several recent investigations have addressed this question. comparative sequence analysis using fruit fly, mosquito and honeybee revealed that although the sequence diversity of dscam is high, the underlying mechanisms for generating thousands of isoforms appears to be shared among all three species. the main route to generate these exons was believed to be through reiterative exon duplication and deletion. a survey of arthropod as well as non-arthropod genomes further suggested that these tandem exons are limited to arthropods only. the largest study on this topic so far was based on duplicated exons across arthropods, revealed that the evolutionary occurrence of newly-derived exons is continuing in the exon and clusters to this day. together, these reports suggest that dscam diversity plays a critical role in arthropod biology, and more importantly, highlights its unique evolutionary properties comparing to other cell surface molecules and their families. although those studies shed light on how such complex gene regulation evolved in arthropods, the precise role of a preference for homophilic binding and its development throughout evolution remains to be elucidated. it is still unclear as to whether the dscam exons were duplicated randomly and retained indiscriminately, until the isoform population reached a threshold level of diversity. nd-exons might then have been further selected based on properties such as the functional or expressional differences of different isoforms. for instance, although dscam is broadly expressed in the nervous systems, there is evidence for r cells of the drosophila eye that suggests that not all isoforms are truly randomly expressed, and some isoforms preferably express certain exons of ig. both in vitro and in vivo experiments for drosophila dscam suggest that homophilic binding preference is tightly correlated with its functions. in this study, we explored the connection between the evolution of alternative exons on the one hand, and the self-binding affinities of the resulting isoforms on the other. by extracting sequence features of isoforms using available biochemical data, we established a model to predict with high confidence the homophilic binding affinities of these isoforms. additionally, an ancestor dscam sequence was constructed using genomic information from drosophila species that was approximately 40– million year old. comparative analysis of the ancient and current dscam on their homophilic binding affinities revealed that the current dscam isoforms have higher homophilic binding affinities than their ancestor. furthermore, the same conclusion was reached using data from another phylogenetic reconstruction of the exon and clusters, verifying the robustness of our analysis. together, these results highlight a coherent driving force underlying the extensive exon diversification processes of dscam in drosophila species.  the homophilic binding affinity of dscam isoforms can be confidently predicted following sequence analysis it was shown previously that alternative splicing of the three variable exons of dscam can generate as many as ecto-domain isoforms, and those isoforms assist neuronal cells to distinguish self from non-self through homophilic binding. despite such a large number of possible isoforms, the binding affinity between the dscam proteins of the same isoform is particularly high compared to different isofroms. previous studies on dscam suggested that the observed homophilic binding is mainly determined by the primary protein sequences. thus, it should be possible to analyze the sequence information of all possible isoforms to obtain their homophilic binding affinities relative to heterophilic binding, which would be a time and resource-consuming task if performed using experimental approaches. estimating the binding affinities of every possible dscam isoform may help to further investigate quantitatively the behavior of neurons expressing combinations of various dscam isoforms. we identified a total of dscam isoforms from published biochemical studies, for which the self-binding affinities were measured experimentally, and then selected the sequence features that correlated strongly with the homophilic binding affinities of the isoforms. based on these sequence features and the motif conservation information, the binding affinities of dscam isoforms were predicted using a support vector regression model, coupled with feature selection performed via relieff attributes algorithm. to assess our models, we measured the pearson correlation coefficient and root mean square error from our predictions, which were performed on separate datasets not used to train our models. the correlation coefficient r indicates the level of correlation between the binding affinity predicted by our models and the affinity measured by biochemical experiments. the results are shown in table  where r and rmse were obtained as the average of a 10-fold cross-validation. note that the prediction of binding affinity in our model comes from the combination of sequence features from the entire lg lg and lg domain, rather than individual variable domain, as the synergistic binding of all these domains is likely higher than the sum of the individual binding affinity of lg2-lg lg3-lg and lg7-lg table performance on independent test sets varies with different features features pearson correlation coefficient root mean square error initial feature size filtered feature size best correlation coefficient and related root mean squared error for datasets based on the types of features alone and their combinations with fold cross-validations. the feature size indicates the number of features obtained by juxtaposing the different descriptors and the one after ra algorithm. the best prediction, r =  and rmse = , was achieved with a combination of using pseudo-amino acids, sequence composition and exon labels constituting encoding features. of these parameters, features were pseudo-amino acids, were composition and was exon label. the ranked attributes and their descriptions are presented in additional file 1: table s the mean absolute error on test data unknown to the model with our best parameter combination was. as the affinity values were normalized in the interval, this means the average error was less than 10% on average, indicating that our model can predicate self-binding affinities of dscam isoforms with high confidence on cross-validated data. therefore, we re-trained the model on all available data, and then applied it again to calculate the self-binding profiles of all dscam isoforms. the predicted binding profiles for dscam isoforms are consistent with the experimental data the binding profiles predicted by our model were consistent with the values measured experimentally. firstly, there is a highly significant correlation between the measured binding data and the predicted homophilic binding strength. secondly, biochemical studies chose the isoforms containing exons, and as a general example, have shown that the contributions of the variable exons is not equal, revealing that the isoforms of x. had the highest average self-binding affinities, while x. isoforms showed lower affinities, with.x exhibiting the lowest self-binding affinities. our calculation on the dscam isoform population generated a ranking of contributions of the different exons to self-binding affinity: exon 4 > exon 6 > exon therefore, the model predicted the order of self-binding affinity of the above case as x.  >  x.25 > .x, matching well with previously published biochemical studies. furthermore, the overall predicted binding affinity for the isoform. was found to be, which is in agreement with experimental data published earlier. in addition, the earlier experiments on the variable domain binding specificity based on two different contexts also indicated that the binding domain of exon has the highest binding fold over the assay background, and that exon has the lowest binding affinity, which is precisely the order we obtained by prediction. furthermore, of the isoforms with the highest self-binding affinities, all contain exon, and eight contain either exon or. this strongly suggests that the distribution of isoforms with high affinity to self is non-random among the duplicated exons present in the drosophila genome.figure profiles of the self-binding affinities of dscam1isoforms. a: binding affinities of the isoforms experimentally measured by wojtowicz et al.; b: predicted binding affinities for all possible isoforms. reconstruction of the drosophila ancestor dscam sequence reveals that isoforms carrying nd-exons have higher self-binding affinities the complex structure of dscam gene may have evolved along two possible evolutionary pathways: 1) changing the number of alternative exons by exon duplication and deletion; 2) changing the composition of individual exons by point mutations. the first path generates nd-exons without clear orthologs, while in the second pathway exons persist throughout evolution, preserving identifiable ancient orthologs. whilst the evolutionary process of exon duplication is primarily responsible for the generation of the vast number of alternative exons of dscam the actual driving force responsible for this extensive duplication remains unknown. as self-binding is an integral part of the control processes involved in cellular recognition during neuronal development, we hypothesized that the dscam protein evolved in such way in order to improve the homophilic binding affinity of its isoforms. testing this hypothesis requires a comparison between the current and the ancient forms of the dscam protein. to this end, we first reconstructed a phylogenetic tree for dscam and based on the alignment of the protein sequences of drosophila species, we then rebuilt the ancestral genomic sequence of dscam originating from approximately 40– million years ago. we compared the predicted self-binding affinities of different isoforms based on the information derived from both the ancestral and current genomes. the reconstructed ancestral sequence of dscam contains nucleotides, resulting in a total of ancestor isoforms. the gc content of the ancestral and current dscam sequences were found to be similar. however, we found several differences related to their exon variants. notably, no orthologs were found in the ancestral genome for several current exons, including exon, exon, and exon. therefore, those exons would have been generated more recently, probably within the past 40 ~  million years, by exon duplication, while the other exons would already have existed, and would have continued to evolve by point mutations. here we define “new” isoforms as recently evolved variable domains and “ancient” isoforms as those containing conserved domains. we set out to investigate as to whether the recently generated isoforms display enhanced self-binding affinities relative to the ancient isoforms. we found that all of the isoforms carrying recently duplicated exons have significantly higher predicted self-binding affinities than those with ancient exon orthologs. the mean self-binding affinity is  ±  for the new isoforms containing recently appeared exons in exon or with a mean self-binding affinity of  ±  for the conserved isoforms. furthermore, the isoforms containing a recently duplicated exon or exon have greater self-binding affinities than the isoforms containing corresponding ancient exon or exon. together, these results suggest that recent exon duplications strongly correlate with improved self-binding affinities of the resultant dscam isoforms.figure comparison of self-binding affinities of isoforms containing current and ancient exons. a: distributions of self-binding affinities of isoforms containing exons originating from ancient exon or and those containing exons without such ancient origins. isoforms containing recently gained exons display higher self-binding affinities than conserved isoforms; b: distributions of self-binding affinities of the ancient and current isoforms. the self-binding affinities of current isoforms are higher than those of ancient isoforms. we next tested whether these results could be reproduced by using an independent dataset. the evolutionary history of all of the exons and clusters in arthropods had been independently reconstructed previously, and it was reported that nine forms of exon and thirteen of exon originated approximately million years ago. using this data set, we found a similar trend to that observed in the dataset described above, namely that all isoforms carrying the recently duplicated exons or display significantly higher self-binding affinities compared to those carrying conserved forms of exon or. moreover, the isoforms containing both of the recently duplicated exons and have higher self-binding affinities than the isoforms with ancient exons as well as ancient exon. taken together, these results indicate that dscam isoforms containing evolutionarily newer exons tend have higher homophilic binding affinities than ancient forms. ancestral dscam proteins display lower self-binding affinities than recent forms after investigating the self-binding affinities of dscam isoforms containing exons that have emerged 40– million years ago, we analyzed the self-binding profiles of the more conserved isoforms whose exons evolved by point mutations, and for which current-ancestor orthologs exist. the mean self-binding affinities of all ancestor isoforms was shown to be  ± , which is significantly lower than that of the current isoforms derived from those ancestor isoforms, which was shown to be  ± . these results indicate that the self-binding affinities have increased considerably in this particular isoform population during the last 40 ~  million years of evolution. upon further analysis of each pair of the current-ancestor orthologs it was revealed that there is a strong and significant correlation of self-binding affinities between the ancestor and current isoforms: isoforms with higher binding affinity in the past also have higher self-binding affinity at present. this suggests that any point mutations that might have rendered self-binding to be of lower affinities were either suppressed or eliminated during evolution.figure correlation of self-binding affinities of current isoforms with those of their ancestral forms. dscam isoforms were grouped together: in the figure. the number of isoforms at each data point is presented in pseudo-color as indicated by the color bar below. the dotted purple line indicates a positive correlation of self-binding affinities between time points. the fact that higher homophilic binding affinity was observed in the current and newly evolved isoforms appears to contradict a neutral evolutionary model of dscam evolution. if evolving towards a more diverse population were the only selective pressure, and homophilic binding affinity played no role in the evolution of dscam isoforms, what would happen? a neutral evolutionary model would suggests that, assuming the mean binding affinity of all the isoforms is x in the ancestor dscam isoforms 40– million years ago, the mean binding affinity should be unchanged in both the isoforms containing newly duplicated exons and the conserved isoforms, and there would be no differences between them and their ancestral isoforms. our data suggest that this is not the case for dscam evolution. thus, this neutral evolutionary model is rejected. discussion both in vivo and in vitro studies of dscam have revealed that highly specific homophilic binding, which may arise from high binding affinities, is a general property of these cell surface proteins, and that this property is crucial for its proper physiological function. however, it is not feasible to assess experimentally the binding characteristics of all the possible isoforms. similarily, structure prediction and modeling of all dscam isoforms for which crystal structures are available would be tremendously labor-intensive and time-consuming. thus, to extract the principle relationship between biochemical binding data and sequence features, we used machine-learning methods to develop a computational model to predict dscam self-binding affinities with high confidence. the self-binding affinities of all isoforms in drosophila genome and those of an ancestral genome, which diverged million years ago, were calculated, and detailed computational comparisons were made to examine a) the binding affinities of the isoforms carrying recently generated exons and ancient exons, and b) the self-binding affinities of those current isoforms that are orthologs of ancient isoforms. both comparisons revealed that the self-binding affinity of dscam became significantly enhanced over evolutionary time scales, suggesting that the dscam protein evolved to improve the its self-binding affinities, by sequence mutation and/or exon duplication.figure a schematic model depicting the evolution of dscam in arthropods. nd-exons were created by exon duplication and/or sequence mutation. over time, all isoforms containing old and nd-exons were under selection pressures for higher homophilic binding. only those exons contributing to higher homophilic binding affinities were retained throughout evolution, and can be found in current genome. a fascinating feature of dscam is its enormous isoform diversity, which was shown experimentally to be crucial for proper neural development and functioning immune responses in arthropods. our results presented here suggest that diversity generated simply by exon duplication and sequence mutation may not be adequate, and that a neutral evolutionary model based solely on isoform diversity cannot explain this phenomenon. even the molecular diversity and biochemical diversity together are likely not sufficient. it appears that out of the pool of possible dscam isoforms that existed in the past, the evolutionary process selected only those isoforms that displayed enhanced self-binding affinities. therefore, diverse isoforms are distinguished from each other not just by composition, but also by their increasingly specialized and progressively enhanced interactions. we also noticed that the binding affinity we studied here does not equal to binding specificity, and both of them may play important roles in the evolution of dscam. one may argue that a small improvement in the self-binding affinity would be not sufficient for generating visible benefit in the current drosophila genome. as the discrimination between self and non-self neurons needs thousands of dscam isoforms, even a small change in the self-binding affinity of each dscam isoform would lead to significant differences at the population level of these isoforms, likely causing adequate biological effects as a consequence. lastly, because of accumulation effects, it would be reasonable to suggest that the 15% increase in self-binding affinity in each isoform when compared to its own ancient isoforms might be crucial for the insect brain to avoid mistakes in the self-recognition process. our computational predictions of the self-binding affinities of all possible dscam isoforms demonstrated the potential machine learning methods have for the rapid extraction of key molecular features, as well as for the systematic prediction of biological effects, which is crucial for the accurate large-scale analysis of complex molecular and cellular systems. because so far, only a small fraction of dscam isoforms has been measured experimentally, the experimental datasets available for our analysis were relatively small. however, the high correlation between measured binding affinities and predicted binding affinities illustrated the power of using such methods of support vector machines on small sample sizes. profiling the homophilic binding characteristics of just 50% of dscam isoforms would require almost experimental measurements, even more if duplications were to be included, a scale that would require facilities for robotic liquid handling of cell transfections as well as automatic binding assays. it needs to be stressed that careful acquisition of experimental data is vital for obtaining accurate and meaningful modeling results. in this context, we recently became aware of a high-throughput domain docking method, which has the potential of simulating self-binding affinities. however, this method requires detailed structural information for each protein, and thus is far more time-consuming when compared to computational modeling. so far, there is no indication as to whether other methods will become available soon for large-scale evolutionary studies like the one discussed here. it is well-established that homophilic binding of dscam isoforms is crucial for proper functioning in a physiological setting. therefore, evolutionary selection towards higher affinities towards self is likely to be crucial. through random processes such as exon duplication and sequence mutation, newly evolved dscam isoforms would have acquired higher self-binding affinities over old isoforms. selective pressure would then have acted upon these newer dscam isoforms to retain those with higher affinities for self. we speculate that strong self-interactions would provide higher signal-to-noise ratios for cell-cell recognition, which might be just one event among many simultaneous molecular interactions on the cell surface. such enhanced contrast for meaningful cell-to-cell signaling might ensure that neurons in the developing brain recognize and connect only to appropriate cell partners, in a correct manner. as dscam is also critical during the launch of innate immune responses in insects, self-binding may also play a role in the proper functioning of the immune system. as one of the most complex molecules in the genome of arthropods, dscam has been studied in great detail using biochemical, genetic and structure modeling approaches. our comparative profiling of the self-binding affinities of the vast number of dscam isoforms at different time points throughout evolution demonstrates that an evolutionary approach is a powerful and complementary tool to gain novel insights into the mechanistic details of a complex biological system.  the mechanisms behind the great diversity of arthropod dscam forms containing new variable domains consistently emerging is not just a challenging question in neurobiology, but is equally important for our understanding of evolutionary processes in general. the extensive diversity, in combination with the observed specific homophilic interactions of dscam isoforms provides an unique opportunity for biologists not only to trace the process of its evolution, but also to understand the driving forces behind the evolution of a specific gene at the molecular level. in this study we demonstrated that those dscam isoforms generally evolved to gain higher hemophilic binding affinity during the evolution of arthropod. 
as thousands of dscam isoforms are needed for the self-avoidance of the neuron, we propose that an increase in self-binding affinity provides the basis for the successful evolution of the arthropod brain. our data presented here provide an excellent model for future experimental studies of the binding behavior of dscam isoforms. it is known that thousands of isoforms bind themselves through specific homophilic interactions, a process which provides the basis for cellular self-recognition. on the basis of this sequence, we established a working model to predict the self-binding affinities of all isoforms in both the current and the ancestral genome, using machine-learning methods. our results revealed that 1) isoforms containing newly derived variable domains exhibit higher self-binding affinities than those with conserved domains, and 2) current isoforms display higher self-binding affinities than their counterparts in the ancient genome. the results of our analysis indicate that evolution favored the rise of novel variable domains thanks to their higher self-binding affinities, rather than selection merely on the basis of simple expansion of isoform diversity, as that this particular selection process would have established the powerful mechanisms required for neuronal self-avoidance. drosophila dscam is a cell-surface protein that plays important roles in neural development and axon tiling of neurons. detailed biochemical studies of specific isoforms strongly suggest that homophilic binding, i.e.
 drosophila dscam is a cell-surface protein that plays important roles in neural development and axon tiling of neurons. it is known that thousands of isoforms bind themselves through specific homophilic interactions, a process which provides the basis for cellular self-recognition. detailed biochemical studies of specific isoforms strongly suggest that homophilic binding, i.e. the formation of homodimers by identical dscam isomers, is of great importance for the self-avoidance of neurons. due to experimental limitations, it is currently impossible to measure the homophilic binding affinities for all potential isoforms.  here we reconstructed the dna sequences of an ancestral dscam form using a comparative genomic approach. on the basis of this sequence, we established a working model to predict the self-binding affinities of all isoforms in both the current and the ancestral genome, using machine-learning methods. detailed computational analysis was performed to compare the self-binding affinities of all isoforms present in these two genomes. our results revealed that 1) isoforms containing newly derived variable domains exhibit higher self-binding affinities than those with conserved domains, and 2) current isoforms display higher self-binding affinities than their counterparts in the ancient genome. as thousands of dscam isoforms are needed for the self-avoidance of the neuron, we propose that an increase in self-binding affinity provides the basis for the successful evolution of the arthropod brain.  our data presented here provide an excellent model for future experimental studies of the binding behavior of dscam isoforms. the results of our analysis indicate that evolution favored the rise of novel variable domains thanks to their higher self-binding affinities, rather than selection merely on the basis of simple expansion of isoform diversity, as that this particular selection process would have established the powerful mechanisms required for neuronal self-avoidance. thus, we reveal here a new molecular mechanism for the successful evolution of arthropod brains. electronic supplementary material the online version of this article contains supplementary material, which is available to authorized users. keywords dscamhomophilic bindingevolution of arthropodsissue-copyright-statement© the author 2014 