The recent accumulation of genomic and structural data as well as improvements in homology detection algorithms has led to the reliable prediction of the protein domain content of all completed genomes using both SCOP and CATH domain definitions [21
]. These protein domain distributions are the starting point for the investigation of protein domain evolution in the genomic era [23
The work of assessing the distribution of domain content across the tree of life began shortly after the completion of the first genomes from each of the three superkingdoms [28
]. As the number of structures and the number of genomes accumulated a power law distribution of domains [29
] and domain combinations [30
] emerged. Several models have been proposed to explain this distribution [31
]. To illustrate this point, according to SCOP 1.73 which contains 1087 folds, 692 folds contain only one family (and hence one superfamily). Therefore, the majority of folds correspond to one homologous family that covers a very tiny portion of sequence space. Conversely, the ferredoxin-like fold (SCOP d.58) is found in 55 superfamilies, comprising 123 families. This imbalance is undoubtedly the result of evolution as can be seen by considering the power law relationship with respect to the complexity of the organism.
Two independent groups compared domain abundance to features representing complexity, namely genome size [33
] and numbers of cell types [34
]. Ranea et al. [33
] clustered domain families into three categories in terms of their relationship to genome size: unrelated (mainly translation and biosynthesis), linearly-related (mainly metabolism) and non-linearly-related (mainly involved in gene regulation). Vogel et al. [34
] compared domain family abundance with cell type numbers in different eukaryote species. About 10% of domain families have a strong correlation with complexity. Half of these superfamilies are involved in extracellular processes and regulation. Such results infer subtle structure-function relationships of protein domains during evolution leading to the current protein structure repertoire.
An important evolutionary consideration is not just the abundance of domains, but their organization. Over 70% of proteins in eukaryotes and over 50% of proteins in prokaryotes contain more than one domain [23
]. These multi-domain proteins are represented by linear combinations of domains; the domain architecture [35
]. Domain architectures arise through domain shuffling, domain duplication, and domain insertion and deletion (see [36
] for a review) leading to new functions [38
]. Baus et al. [39
] defined “promiscuous” domains as those that occur in diverse domain architectures. The authors provided a measurement of promiscuity of domains based on the frequency of their coexistence with different domain partners. A systematic comparative genomic analysis in 28 eukaryotes resulted in 215 strongly promiscuous domains. It is not surprising that most are involved in protein-protein interactions, especially in signal transduction pathways. Vogel et al. [40
] observed an over-representation of some two-domain or three-domain combinations in complete genomes and termed them “supra-domains.” Those supra-domains (described here as macrodomains) have stable internal domain architectures that are conserved over long evolutionary distances, acting like a single domain in combination with other domain partners. About 1400 macrodomains have been identified with diverse functions, indicating that the preferred association of certain domains is universal and evolutionarily advantageous. These two examples show that domain combinations are determined by functional constraints and evolutionary selection, not just random processes [29
]. As such, domain combinations are an important aspect of any protein classification scheme.
A logical extension of these findings is to map domain combinations to presumed phylogenetic relationships derived by other means as exemplified by Snell et al. [41
]. Kummerfeld et al. [42
] counted the distribution of various types of single domain and multi-domain proteins across the tree of life and predicted that fusion is four times more common than fission in domain combinations. Fong et al. [43
] viewed the domain architecture in multi-domain proteins as the rearrangement of existing architectures, acquisition of new domains or deletion of old domains, and proposed a parsimony model to derive the evolutionary pathways by which extant domain architectures may have evolved. Guided by the evolutionary information in phylogenetic trees, Ekman et al. [44
] studied the rate of multi-domain architecture formation across different branches of the phylogenetic tree and found that there are elevated rates of domain rearrangement in Metazoa, whereas creation of domains was more frequent in early evolution. Similarly, Itoh et al. [45
] observed a large number of group-specific domain combinations in animals and investigated the difference in domain combinations among different phylogenetic groups. Yang et al. [46
] aimed to derive the entire evolutionary history of each domain and domain combination throughout the tree of life by mapping current domain content onto the species trees. This approach reveals the origin of each protein domain as well as evolutionary processes such as horizontal gene transfer among more distant species.