Genome-wide analysis of mammalian DNA segment fusion/fission

Systematic computational prediction of protein interaction networks

Determining the network of physical protein associations is an important first step in developing mechanistic evidence for elucidating biological pathways. Despite rapid advances in the field of high throughput experiments to determine protein interactions, the majority of associations remain unknown. Here we describe computational methods for significantly expanding protein association networks. We describe methods for integrating multiple independent sources of evidence to obtain higher quality predictions and we compare the major publicly available resources available for experimentalists to use.

Genome-wide detection of hybrid genes with multiple components in human

Background

Previous studies showed that gene hybrid is one of the principal processes for generating new genes. Although some gene hybrid events have been reported to be inter- or intra-species, there lacks a well-organized method for large scale detection of the events with multiple components. Hence in this study, we focus on building up an efficient method for exploring all candidates of gene hybrid events in human genome and provide useful results for further study.

Findings

We have developed a method designated Triad Comparison Algorithm (TCA) to detect all potential N-hybrid events (i.e., an N-hybrid gene and its N non-overlapping component regions derived from N different genes) in human genome. The results reveal that there are many convoluted N-hybrid events with multiple components (N > 2) and that the most complicated N-hybrid genes detected in human by TCA are composed of six component regions. Interestingly, our results show that most of the hybrid events belong to the 3-hybrid category. Furthermore, we observe that a single gene might participate in different events. Twelve genes were found to have dual identities contained in different N-hybrid events (i.e., they were identified as hybrid genes as well as component genes). This points out that to a certain extent the gene hybrid mechanism has generated new genes during the course of human genome evolutionary history.

Conclusion

An efficient method, TCA, is developed for exploring all candidates of hybrid genes in the human genome and provides useful results for the evolutionary analysis. The advantage of TCA is its power of detecting any kinds of hybrid events in any species with a large genome size.

Fusion and fission of genes define a metric between fungal genomes

Gene fusion and fission events are key mechanisms in the evolution of gene architecture, whose effects are visible in protein architecture when they occur in coding sequences. Until now, the detection of fusion and fission events has been performed at the level of protein sequences with a post facto removal of supernumerary links due to paralogy, and often did not include looking for events defined only in single genomes. We propose a method for the detection of these events, defined on groups of paralogs to compensate for the gene redundancy of eukaryotic genomes, and apply it to the proteomes of 12 fungal species. We collected an inventory of 1,680 elementary fusion and fission events. In half the cases, both composite and element genes are found in the same species. Per-species counts of events correlate with the species genome size, suggesting a random mechanism of occurrence. Some biological functions of the genes involved in fusion and fission events are slightly over- or under-represented. As already noted in previous studies, the genes involved in an event tend to belong to the same functional category. We inferred the position of each event in the evolution tree of the 12 fungal species. The event localization counts for all the segments of the tree provide a metric that depicts the “recombinational” phylogeny among fungi. A possible interpretation of this metric as distance in adaptation space is proposed.

One consequence of genome remodelling in evolution is the modification of genes, either by fusion with other genes, or by fission into several parts. By tracking the mathematical relations between groups of similar genes, rather than between individual genes, we can paint a global picture of remodelling across many species simultaneously. The strengths of our method are that it allows us to include highly redundant eukaryote genomes, and that it avoids alignment artifacts by representing each group of similar genes by a mathematical model. Applying our method to a set of fungal genomes, we confirmed first that the number of fusion/fission events is correlated with genome size, second that the fusion to fission ratio favors fusions, third that the set of events is not saturated, and fourth that while genes assembled in a fusion tend to have the same biochemical function, there appears to be little bias for the functions that are involved. Indeed, fusion and fission events are landmarks of random remodelling, independent of mutation rate: they define a metric of “recombination distance.” This distance lets us build a genome evolution history of species and may well be a better measure than mutation distance of the process of adaptation.