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.