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Detection of Functional Overlapping Genes: Simulation and Case Studies

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Abstract

As far as protein-coding genes are concerned, there is a non-zero probability that at least one of the five possible overlapping sequences of any gene will contain an open-reading frame (ORF) of a length that may be suitable for coding a functional protein. It is, however, very difficult to determine whether or not such an ORF is functional. Recently, we proposed a method that predicts functionality of an overlapping ORF if it can be shown that it has been subject to purifying selection during its evolution. Here, we use simulation to test this method under several conditions and compare it with the method of Firth and Brown. We found that under most conditions, our method detects functional overlapping genes with higher sensitivity than Firth and Brown’s method, while maintaining high specificity. Further, we tested the hypothesis that the two aminoacyl tRNA synthetase classes have originated from a pair of overlapping genes. A central piece of evidence ostensibly supporting this hypothesis is the assertion that an overlapping ORF of a heat-shock protein-70 gene, which exhibits some similarity to class 2 aminoacyl tRNA synthetases, is functional. We found signature of purifying selection only in highly divergent sequences, suggesting that the method yields false-positives in high sequence divergence and that the overlapping ORF is not a functional gene. Finally, we examined three cases of overlap in the human genome. We find varying signatures of purifying selection acting on these overlaps, raising the possibility that two of the overlapping genes may not be functional.

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Acknowledgments

We thank Dr. Anton Nekrutenko and an anonymous reviewer for their useful comments. This work was supported in part by US National Library of Medicine Grant LM010009-01 to Dan Graur and Giddy Landan.

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  1. Department of Biology and Biochemistry, University of Houston, Houston, TX, 77204, USA

    Niv Sabath & Dan Graur

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  1. Niv Sabath
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  2. Dan Graur
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Correspondence to Niv Sabath.

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Supplementary Fig. 1

Detection of selection by the SLG (solid lines, P < 0.01) and FB (dashed lines) methods on simulated genes with different levels of GC contents (blue, green, and red, for 30, 50, and 70%, respectively). Each data point is the percentage of runs for which the methods detected selection. We used same-strand phase 1 overlaps, length of 300 codons, t = 0.4, ω k was set to 0.2, and ω h varied between 0.2 and 1 (JPEG 304 kb)

Supplementary Fig. 2

Amino acid alignment of GNAS1 genes from human and mouse. The overlap region with ARF is highlighted in red. multiple_alignments.txt: Multiple alignments used in the study in FASTA format (JPEG 120 kb)

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Sabath, N., Graur, D. Detection of Functional Overlapping Genes: Simulation and Case Studies. J Mol Evol 71, 308–316 (2010). https://doi.org/10.1007/s00239-010-9386-3

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