Biological factors in the synthetic construction of overlapping genes.

BACKGROUND: Overlapping genes (OLGs) with long protein-coding overlapping sequences are disallowed by standard genome annotation programs, outside of viruses. Recently however they have been discovered in Archaea, diverse Bacteria, and Mammals. The biological factors underlying life's ability to create overlapping genes require more study, and may have important applications in understanding evolution and in biotechnology. A previous study claimed that protein domains from viruses were much better suited to forming overlaps than those from other cellular organisms - in this study we assessed this claim, in order to discover what might underlie taxonomic differences in the creation of gene overlaps. RESULTS: After overlapping arbitrary Pfam domain pairs and evaluating them with Hidden Markov Models we find OLG construction to be much less constrained than expected. For instance, close to 10% of the constructed sequences cannot be distinguished from typical sequences in their protein family. Most are also indistinguishable from natural protein sequences regarding identity and secondary structure. Surprisingly, contrary to a previous study, virus domains were much less suitable for designing OLGs than bacterial or eukaryotic domains were. In general, the amount of amino acid change required to force a domain to overlap is approximately equal to the variation observed within a typical domain family. The resulting high similarity between natural sequences and those altered so as to overlap is mostly due to the combination of high redundancy in the genetic code and the evolutionary exchangeability of many amino acids. CONCLUSIONS: Synthetic overlapping genes which closely resemble natural gene sequences, as measured by HMM profiles, are remarkably easy to construct, and most arbitrary domain pairs can be altered so as to overlap while retaining high similarity to the original sequences. Future work however will need to assess important factors not considered such as intragenic interactions which affect protein folding. While the analysis here is not sufficient to guarantee functional folding proteins, further analysis of constructed OLGs will improve our understanding of the origin of these remarkable genetic elements across life and opens up exciting possibilities for synthetic biology.

Optimality in the standard genetic code is robust with respect to comparison code sets.

The genetic code and its evolution have been studied by many different approaches. One approach is to compare the properties of the standard genetic code (SGC) to theoretical alternative codes in order to determine how optimal it is and from this infer whether or not it is likely that it has undergone a selective evolutionary process. Many different properties have been studied in this way in the literature. Less focus has been put on the alternative code sets which are used as a comparison to the standard code. Each implicitly represents an evolutionary hypothesis and the sets used differ greatly across the literature. Here we determine the influence of the comparison set on the results of the optimality calculation by using codes based upon different sub-structures of the SGC. With these results we can generalize the results to different evolutionary hypotheses. We find that the SGC's optimality is very robust, as no code set with no optimised properties is found. We therefore conclude that the optimality of the SGC is a robust feature across all evolutionary hypotheses. Our results provide important information for any future studies on the evolution of the standard genetic code. We also studied properties of the SGC concerning overlapping genes, which have recently been found to be more widespread than often believed. Although our results are not conclusive yet we find additional intriguing structures in the SGC that need explanation.