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Abstract Background The study of biological networks and how they have evolved is fundamental to our understanding of the cell. By investigating how proteins of different ages are connected in the protein interaction network, one can infer how that network has expanded in evolution, without the need for explicit reconstruction of ancestral networks. Studies that implement this approach show that proteins are often connected to proteins of a similar age, suggesting a simultaneous emergence of interacting proteins. There are several theories explaining this phenomenon, but despite the importance of gene duplication in genome evolution, none consider protein family dynamics as a contributing factor. Results In an S. cerevisiae protein interaction network we investigate to what extent edges that arise from duplication events contribute to the observed tendency to interact with proteins of a similar age. We find that part of this tendency is explained by interactions between paralogs. Age is usually defined on the level of protein families, rather than individual proteins, hence paralogs have the same age. The major contribution however, is from interaction partners that are shared between paralogs. These interactions have most likely been conserved after a duplication event. To investigate to what extent a nearly neutral process of network growth can explain these results, we adjust a well-studied network growth model to incorporate protein families. Our model shows that the number of edges between paralogs can be amplified by subsequent duplication events, thus explaining the overrepresentation of interparalog edges in the data. The fact that interaction partners shared by paralogs are often of the same age as the paralogs does not arise naturally from our model and needs further investigation. Conclusion We amend previous theories that explain why proteins of a similar age prefer to interact by demonstrating that this observation can be partially explained by gene duplication events. There is an ongoing debate on whether the protein interaction network is predominantly shaped by duplication and subfunctionalization or whether network rewiring is most important. Our analyses of S. cerevisiae protein interaction networks demonstrate that duplications have influenced at least one property of the protein interaction network: how proteins of different ages are connected.

Abstract Background Homology is a crucial concept in comparative genomics. The algorithm probably most widely used for homology detection in comparative genomics, is BLAST. Usually a stringent score cutoff is applied to distinguish putative homologs from possible false positive hits. As a consequence, some BLAST hits are discarded that are in fact homologous. Results Analogous to the use of the genomics context in genome alignments, we test whether conserved functional context can be used to select candidate homologs from insignificant BLAST hits. We make a co-complex network alignment between complex subunits in yeast and human and find that proteins with an insignificant BLAST hit that are part of homologous complexes, are likely to be homologous themselves. Further analysis of the distant homologs we recovered using the co-complex network alignment, shows that a large majority of these distant homologs are in fact ancient paralogs. Conclusions Our results show that, even though evolution takes place at the sequence and genome level, co-complex networks can be used as circumstantial evidence to improve confidence in the homology of distantly related sequences.

Abstract Background Thanks to recent high coverage mass-spectrometry studies and reconstructed protein complexes, we are now in an unprecedented position to study the evolution of biological systems. Gene duplications, known to be a major source of innovation in evolution, can now be readily examined in the context of protein complexes. Results We observe that paralogs operating in the same complex fulfill different roles: mRNA dosage increase for more than a hundred cytosolic ribosomal proteins, mutually exclusive participation of at least 54 paralogs resulting in alternative forms of complexes, and 24 proteins contributing to bona fide structural growth. Inspection of paralogous proteins participating in two independent complexes shows that an ancient, pre-duplication protein functioned in both multi-protein assemblies and a gene duplication event allowed the respective copies to specialize and split their roles. Conclusion Variants with conditionally assembled, paralogous subunits likely have played a role in yeast's adaptation to anaerobic conditions. In a number of cases the gene duplication has given rise to one duplicate that is no longer part of a protein complex and shows an accelerated rate of evolution. Such genes could provide the raw material for the evolution of new functions.

Abstract Background Homology is a key concept in both evolutionary biology and genomics. Detection of homology is crucial in fields like the functional annotation of protein sequences and the identification of taxon specific genes. Basic homology searches are still frequently performed by pairwise search methods such as BLAST. Vast improvements have been made in the identification of homologous proteins by using more advanced methods that use sequence profiles. However additional improvement could be made by exploiting sources of genomic information other than the primary sequence or tertiary structure. Results We test the hypothesis that extrinsic gene properties gene length and gene order can be of help in differentiating spurious sequence similarity from homology in the gray zone. Sharing gene order and similarity in size dramatically increase the chance of a query-hit pair being homologous: gray zone query-hit pairs of similar size and with conserved gene order are homologous in 99% of all cases, while for query-hit pairs without gene order conservation and with different sizes this is only 55%. Conclusion We have shown that using gene length and gene order drastically improves the detection of homologs within the BLAST gray zone. Our findings suggest that the use of such extrinsic gene properties can also improve the performance of homology detection by more advanced methods, and our study thereby underscores the importance of true data integration for fully exploiting genomic information.

Abstract Background Orthology is one of the cornerstones of gene function prediction. Dividing the phylogenetic relations between genes into either orthologs or paralogs is however an oversimplification. Already in two-species gene-phylogenies, the complicated, non-transitive nature of phylogenetic relations results in inparalogs and outparalogs. For situations with more than two species we lack semantics to specifically describe the phylogenetic relations, let alone to exploit them. Published procedures to extract orthologous groups from phylogenetic trees do not allow identification of orthology at various levels of resolution, nor do they document the relations between the orthologous groups. Results We introduce "levels of orthology" to describe the multi-level nature of gene relations. This is implemented in a program LOFT (Levels of Orthology From Trees) that assigns hierarchical orthology numbers to genes based on a phylogenetic tree. To decide upon speciation and gene duplication events in a tree LOFT can be instructed either to perform classical species-tree reconciliation or to use the species overlap between partitions in the tree. The hierarchical orthology numbers assigned by LOFT effectively summarize the phylogenetic relations between genes. The resulting high-resolution orthologous groups are depicted in colour, facilitating visual inspection of (large) trees. A benchmark for orthology prediction, that takes into account the varying levels of orthology between genes, shows that the phylogeny-based high-resolution orthology assignments made by LOFT are reliable. Conclusion The "levels of orthology" concept offers high resolution, reliable orthology, while preserving the relations between orthologous groups. A Windows as well as a preliminary Java version of LOFT is available from the LOFT website http://www.cmbi.ru.nl/LOFT.

Abstract Background Peroxisomes are ubiquitous eukaryotic organelles involved in various oxidative reactions. Their enzymatic content varies between species, but the presence of common protein import and organelle biogenesis systems support a single evolutionary origin. The precise scenario for this origin remains however to be established. The ability of peroxisomes to divide and import proteins post-translationally, just like mitochondria and chloroplasts, supports an endosymbiotic origin. However, this view has been challenged by recent discoveries that mutant, peroxisome-less cells restore peroxisomes upon introduction of the wild-type gene, and that peroxisomes are formed from the Endoplasmic Reticulum. The lack of a peroxisomal genome precludes the use of classical analyses, as those performed with mitochondria or chloroplasts, to settle the debate. We therefore conducted large-scale phylogenetic analyses of the yeast and rat peroxisomal proteomes. Results Our results show that most peroxisomal proteins (39–58%) are of eukaryotic origin, comprising all proteins involved in organelle biogenesis or maintenance. A significant fraction (13–18%), consisting mainly of enzymes, has an alpha-proteobacterial origin and appears to be the result of the recruitment of proteins originally targeted to mitochondria. Consistent with the findings that peroxisomes are formed in the Endoplasmic Reticulum, we find that the most universally conserved Peroxisome biogenesis and maintenance proteins are homologous to proteins from the Endoplasmic Reticulum Assisted Decay pathway. Conclusion Altogether our results indicate that the peroxisome does not have an endosymbiotic origin and that its proteins were recruited from pools existing within the primitive eukaryote. Moreover the reconstruction of primitive peroxisomal proteomes suggests that ontogenetically as well as phylogenetically, peroxisomes stem from the Endoplasmic Reticulum. Reviewers This article was reviewed by Arcady Mushegian, Gáspár Jékely and John Logsdon Open peer review Reviewed by Arcady Mushegian, Gáspar Jékely and John Logsdon. For the full reviews, please go to the Reviewers' comments section.

Abstract Background The massive scale of microarray derived gene expression data allows for a global view of cellular function. Thus far, comparative studies of gene expression between species have been based on the level of expression of the gene across corresponding tissues, or on the co-expression of the gene with another gene. Results To compare gene expression between distant species on a global scale, we introduce the "expression context". The expression context of a gene is based on the co-expression with all other genes that have unambiguous counterparts in both genomes. Employing this new measure, we show 1) that the expression context is largely conserved between orthologs, and 2) that sequence identity shows little correlation with expression context conservation after gene duplication and speciation. Conclusion This means that the degree of sequence identity has a limited predictive quality for differential expression context conservation between orthologs, and thus presumably also for other facets of gene function.