A model for tool-use traditions in primates: implications for the coevolution of culture and cognition

Inspired by the demonstration that tool-use variants among wild chimpanzees and orangutans qualify as traditions (or cultures), we developed a formal model to predict the incidence of these acquired specializations among wild primates and to examine the evolution of their underlying abilities. We assumed that the acquisition of the skill by an individual in a social unit is crucially controlled by three main factors, namely probability of innovation, probability of socially biased learning, and the prevailing social conditions (sociability, or number of potential experts at close proximity). The model reconfirms the restriction of customary tool use in wild primates to the most intelligent radiation, great apes; the greater incidence of tool use in more sociable populations of orangutans and chimpanzees; and tendencies toward tool manufacture among the most sociable monkeys. However, it also indicates that sociable gregariousness is far more likely to produce the maintenance of invented skills in a population than solitary life, where the mother is the only accessible expert. We therefore used the model to explore the evolution of the three key parameters. The most likely evolutionary scenario is that where complex skills contribute to fitness, sociability and/or the capacity for socially biased learning increase, whereas innovative abilities (i.e., intelligence) follow indirectly. We suggest that the evolution of high intelligence will often be a byproduct of selection on abilities for socially biased learning that are needed to acquire important skills, and hence that high intelligence should be most common in sociable rather than solitary organisms. Evidence for increased sociability during hominin evolution is consistent with this new hypothesis. (C) 2003 Elsevier Science Ltd. All rights reserved.

The Evolution of Guanylyl Cyclases as Multidomain Proteins: Conserved Features of Kinase-Cyclase Domain Fusions

Guanylyl cyclases (GCs) are enzymes that generate cyclic GMP and regulate different physiologic and developmental processes in a number of organisms. GCs possess sequence similarity to class III adenylyl cyclases (ACs) and are present as either membrane-bound receptor GCs or cytosolic soluble GCs. We sought to determine the evolution of GCs using a large-scale bioinformatic analysis and found multiple lineage-specific expansions of GC genes in the genomes of many eukaryotes. Moreover, a few GC-like proteins were identified in prokaryotes, which come fused to a number of different domains, suggesting allosteric regulation of nucleotide cyclase activity Eukaryotic receptor GCs are associated with a kinase homology domain (KHD), and phylogenetic analysis of these proteins suggest coevolution of the KHD and the associated cyclase domain as well as a conservation of the sequence and the size of the linker region between the KHD and the associated cyclase domain. Finally, we also report the existence of mimiviral proteins that contain putative active kinase domains associated with a cyclase domain, which could suggest early evolution of the fusion of these two important domains involved in signa transduction.

The repertoire of protein kinases encoded in the draft version of the human genome: atypical variations and uncommon domain combinations

Background: Phosphorylation by protein kinases is central to cellular signal transduction. Abnormal functioning of kinases has been implicated in developmental disorders and malignancies. Their activity is regulated by second messengers and by the binding of associated domains, which are also influential in translocating the catalytic component to their substrate sites, in mediating interaction with other proteins and carrying out their biological roles. Results: Using sensitive profile-search methods and manual analysis, the human genome has been surveyed for protein kinases. A set of 448 sequences, which show significant similarity to protein kinases and contain the critical residues essential for kinase function, have been selected for an analysis of domain combinations after classifying the kinase domains into subfamilies. The unusual domain combinations in particular kinases suggest their involvement in ubiquitination pathways and alternative modes of regulation for mitogen-activated protein kinase kinases (MAPKKs) and cyclin-dependent kinase (CDK)-like kinases. Previously unexplored kinases have been implicated in osteoblast differentiation and embryonic development on the basis of homology with kinases of known functions from other organisms. Kinases potentially unique to vertebrates are involved in highly evolved processes such as apoptosis, protein translation and tyrosine kinase signaling. In addition to coevolution with the kinase domain, duplication and recruitment of non-catalytic domains is apparent in signaling domains such as the PH, DAG-PE, SH2 and SH3 domains. Conclusions: Expansion of the functional repertoire and possible existence of alternative modes of regulation of certain kinases is suggested by their uncommon domain combinations. Experimental verification of the predicted implications of these kinases could enhance our understanding of their biological roles.

The origins of the evolutionary signal used to predict protein-protein interactions

Background: The correlation of genetic distances between pairs of protein sequence alignments has been used to infer protein-protein interactions. It has been suggested that these correlations are based on the signal of co-evolution between interacting proteins. However, although mutations in different proteins associated with maintaining an interaction clearly occur (particularly in binding interfaces and neighbourhoods), many other factors contribute to correlated rates of sequence evolution. Proteins in the same genome are usually linked by shared evolutionary history and so it would be expected that there would be topological similarities in their phylogenetic trees, whether they are interacting or not. For this reason the underlying species tree is often corrected for. Moreover processes such as expression level, are known to effect evolutionary rates. However, it has been argued that the correlated rates of evolution used to predict protein interaction explicitly includes shared evolutionary history; here we test this hypothesis. Results: In order to identify the evolutionary mechanisms giving rise to the correlations between interaction proteins, we use phylogenetic methods to distinguish similarities in tree topologies from similarities in genetic distances. We use a range of datasets of interacting and non-interacting proteins from Saccharomyces cerevisiae. We find that the signal of correlated evolution between interacting proteins is predominantly a result of shared evolutionary rates, rather than similarities in tree topology, independent of evolutionary divergence. Conclusions: Since interacting proteins do not have tree topologies that are more similar than the control group of non-interacting proteins, it is likely that coevolution does not contribute much to, if any, of the observed correlations.