Expression of multiple horizontally acquired genes is a hallmark of both vertebrate and invertebrate genomes

Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.

Horizontal gene transfer (HGT; also known as lateral gene transfer) has had an important role in eukaryotic genome evolution, but its importance is often overshadowed by the greater prevalence and our more advanced understanding of gene transfer in prokaryotes. Recurrent endosymbioses and the generally poor sampling of most nuclear genes from diverse lineages have also complicated the search for transferred genes. Nevertheless, the number of well-supported cases of transfer from both prokaryotes and eukaryotes, many with significant functional implications, is now expanding rapidly. Major recent trends include the important role of HGT in adaptation to certain specialized niches and the highly variable impact of HGT in different lineages.

Detection of protein families in large databases is one of the principal research objectives in structural and functional genomics. Protein family classification can significantly contribute to the delineation of functional diversity of homologous proteins, the prediction of function based on domain architecture or the presence of sequence motifs as well as comparative genomics, providing valuable evolutionary insights. We present a novel approach called TRIBE-MCL for rapid and accurate clustering of protein sequences into families. The method relies on the Markov cluster (MCL) algorithm for the assignment of proteins into families based on precomputed sequence similarity information. This novel approach does not suffer from the problems that normally hinder other protein sequence clustering algorithms, such as the presence of multi-domain proteins, promiscuous domains and fragmented proteins. The method has been rigorously tested and validated on a number of very large databases, including SwissProt, InterPro, SCOP and the draft human genome. Our results indicate that the method is ideally suited to the rapid and accurate detection of protein families on a large scale. The method has been used to detect and categorise protein families within the draft human genome and the resulting families have been used to annotate a large proportion of human proteins.