Detection of functional overlapping genes: simulation and case studies

OLGenie: Estimating Natural Selection to Predict Functional Overlapping Genes

Purifying (negative) natural selection is a hallmark of functional biological sequences, and can be detected in protein-coding genes using the ratio of nonsynonymous to synonymous substitutions per site (d_N/d_S). However, when two genes overlap the same nucleotide sites in different frames, synonymous changes in one gene may be nonsynonymous in the other, perturbing d_N/d_S. Thus, scalable methods are needed to estimate functional constraint specifically for overlapping genes (OLGs). We propose OLGenie, which implements a modification of the Wei–Zhang method. Assessment with simulations and controls from viral genomes (58 OLGs and 176 non-OLGs) demonstrates low false-positive rates and good discriminatory ability in differentiating true OLGs from non-OLGs. We also apply OLGenie to the unresolved case of HIV-1’s putative antisense protein gene, showing significant purifying selection. OLGenie can be used to study known OLGs and to predict new OLGs in genome annotation. Software and example data are freely available at https://github.com/chasewnelson/OLGenie (last accessed April 10, 2020).

Overlapping genes and the proteins they encode differ significantly in their sequence composition from non-overlapping genes

Overlapping genes represent a fascinating evolutionary puzzle, since they encode two functionally unrelated proteins from the same DNA sequence. They originate by a mechanism of overprinting, in which point mutations in an existing frame allow the expression (the "birth") of a completely new protein from a second frame. In viruses, in which overlapping genes are abundant, these new proteins often play a critical role in infection, yet they are frequently overlooked during genome annotation. This results in erroneous interpretation of mutational studies and in a significant waste of resources. Therefore, overlapping genes need to be correctly detected, especially since they are now thought to be abundant also in eukaryotes. Developing better detection methods and conducting systematic evolutionary studies require a large, reliable benchmark dataset of known cases. We thus assembled a high-quality dataset of 80 viral overlapping genes whose expression is experimentally proven. Many of them were not present in databases. We found that overall, overlapping genes differ significantly from non-overlapping genes in their nucleotide and amino acid composition. In particular, the proteins they encode are enriched in high-degeneracy amino acids and depleted in low-degeneracy ones, which may alleviate the evolutionary constraints acting on overlapping genes. Principal component analysis revealed that the vast majority of overlapping genes follow a similar composition bias, despite their heterogeneity in length and function. Six proven mammalian overlapping genes also followed this bias. We propose that this apparently near-universal composition bias may either favour the birth of overlapping genes, or/and result from selection pressure acting on them.

New tools to analyze overlapping coding regions

Background

Retroviruses transcribe messenger RNA for the overlapping Gag and Gag-Pol polyproteins, by using a programmed -1 ribosomal frameshift which requires a slippery sequence and an immediate downstream stem-loop secondary structure, together called frameshift stimulating signal (FSS). It follows that the molecular evolution of this genomic region of HIV-1 is highly constrained, since the retroviral genome must contain a slippery sequence (sequence constraint), code appropriate peptides in reading frames 0 and 1 (coding requirements), and form a thermodynamically stable stem-loop secondary structure (structure requirement).

Results

We describe a unique computational tool, RNAsampleCDS, designed to compute the number of RNA sequences that code two (or more) peptides p,q in overlapping reading frames, that are identical (or have BLOSUM/PAM similarity that exceeds a user-specified value) to the input peptides p,q. RNAsampleCDS then samples a user-specified number of messenger RNAs that code such peptides; alternatively, RNAsampleCDS can exactly compute the position-specific scoring matrix and codon usage bias for all such RNA sequences. Our software allows the user to stipulate overlapping coding requirements for all 6 possible reading frames simultaneously, even allowing IUPAC constraints on RNA sequences and fixing GC-content.

We generalize the notion of codon preference index (CPI) to overlapping reading frames, and use RNAsampleCDS to generate control sequences required in the computation of CPI. Moreover, by applying RNAsampleCDS, we are able to quantify the extent to which the overlapping coding requirement in HIV-1 [resp. HCV] contribute to the formation of the stem-loop [resp. double stem-loop] secondary structure known as the frameshift stimulating signal. Using our software, we confirm that certain experimentally determined deleterious HCV mutations occur in positions for which our software RNAsampleCDS and RNAiFold both indicate a single possible nucleotide. We generalize the notion of codon preference index (CPI) to overlapping coding regions, and use RNAsampleCDS to generate control sequences required in the computation of CPI for the Gag-Pol overlapping coding region of HIV-1. These applications show that RNAsampleCDS constitutes a unique tool in the software arsenal now available to evolutionary biologists.

Conclusion

Source code for the programs and additional data are available at http://bioinformatics.bc.edu/clotelab/RNAsampleCDS/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1389-7) contains supplementary material, which is available to authorized users.

Origin and length distribution of unidirectional prokaryotic overlapping genes

Prokaryotic unidirectional overlapping genes can be originated by disrupting and replacing of the start or stop codon of one protein-coding gene with another start or stop codon within the adjacent gene. However, the probability of disruption and replacement of a start or stop codon may differ significantly depending on the number and redundancy of the start and stop codons sets. Here, we performed a simulation study of the formation of unidirectional overlapping genes using a simple model of nucleotide change and contrasted it with empirical data. Our results suggest that overlaps originated by an elongation of the 3′-end of the upstream gene are significantly more frequent than those originated by an elongation of the 5′-end of the downstream gene. According to this, we propose a model for the creation of unidirectional overlaps that is based on the disruption probabilities of start codon and stop codon sets and on the different probabilities of phase 1 and phase 2 overlaps. Additionally, our results suggest that phase 2 overlaps are formed at higher rates than phase 1 overlaps, given the same evolutionary time. Finally, we propose that there is no need to invoke selection to explain the prevalence of long phase 1 unidirectional overlaps. Rather, the overrepresentation of long phase 1 relative to long phase 2 overlaps might occur because it is highly probable that phase 2 overlaps are retained as short overlaps by chance. Such a pattern is stronger if selection against very long overlaps is included in the model. Our model as a whole is able to explain to a large extent the empirical length distribution of unidirectional overlaps in prokaryotic genomes.

Phenotype of htgA (mbiA), a recently evolved orphan gene of Escherichia coli and Shigella, completely overlapping in antisense to yaaW

Overlapping embedded genes, such as htgA/yaaW, are assumed to be rare in prokaryotes. In Escherichia coli O157:H7, gfp fusions of both promoter regions revealed activity and transcription start sites could be determined for both genes. Both htgA and yaaW were inactivated strand specifically by introducing a stop codon. Both mutants exhibited differential phenotypes in biofilm formation and metabolite levels in a nontargeted analysis, suggesting that both are functional despite YaaW but not HtgA could be expressed. While yaaW is distributed all over the Gammaproteobacteria, an overlapping htgA-like sequence is restricted to the Escherichia-Klebsiella clade. Full-length htgA is only present in Escherichia and Shigella, and htgA showed evidence for purifying selection. Thus, htgA is an interesting case of a lineage-specific, nonessential and young orphan gene.

Viral proteins originated de novo by overprinting can be identified by codon usage: application to the "gene nursery" of Deltaretroviruses

A well-known mechanism through which new protein-coding genes originate is by modification of pre-existing genes, e.g. by duplication or horizontal transfer. In contrast, many viruses generate protein-coding genes de novo, via the overprinting of a new reading frame onto an existing (“ancestral”) frame. This mechanism is thought to play an important role in viral pathogenicity, but has been poorly explored, perhaps because identifying the de novo frames is very challenging. Therefore, a new approach to detect them was needed. We assembled a reference set of overlapping genes for which we could reliably determine the ancestral frames, and found that their codon usage was significantly closer to that of the rest of the viral genome than the codon usage of de novo frames. Based on this observation, we designed a method that allowed the identification of de novo frames based on their codon usage with a very good specificity, but intermediate sensitivity. Using our method, we predicted that the Rex gene of deltaretroviruses has originated de novo by overprinting the Tax gene. Intriguingly, several genes in the same genomic region have also originated de novo and encode proteins that regulate the functions of Tax. Such “gene nurseries” may be common in viral genomes. Finally, our results confirm that the genomic GC content is not the only determinant of codon usage in viruses and suggest that a constraint linked to translation must influence codon usage.

How does novelty originate in nature? It is commonly thought that new genes are generated mainly by modifications of existing genes (the “tinkering” model). In contrast, we have shown recently that in viruses, numerous genes are generated entirely de novo (“from scratch”). The role of these genes remains underexplored, however, because they are difficult to identify. We have therefore developed a new method to detect genes originated de novo in viral genomes, based on the observation that each viral genome has a unique “signature”, which genes originated de novo do not share. We applied this method to analyze the genes of Human T-Lymphotropic Virus 1 (HTLV1), a relative of the HIV virus and also a major human pathogen that infects about twenty million people worldwide. The life cycle of HTLV1 is finely regulated – it can stay dormant for long periods and can provoke blood cancers (leukemias) after a very long incubation. We discovered that several of the genes of HTLV1 have originated de novo. These novel genes play a key role in regulating the life cycle of HTLV1, and presumably its pathogenicity. Our investigations suggest that such “gene nurseries” may be common in viruses.

Predicting statistical properties of open reading frames in bacterial genomes

An analytical model based on the statistical properties of Open Reading Frames (ORFs) of eubacterial genomes such as codon composition and sequence length of all reading frames was developed. This new model predicts the average length, maximum length as well as the length distribution of the ORFs of 70 species with GC contents varying between 21% and 74%. Furthermore, the number of annotated genes is predicted with high accordance. However, the ORF length distribution in the five alternative reading frames shows interesting deviations from the predicted distribution. In particular, long ORFs appear more often than expected statistically. The unexpected depletion of stop codons in these alternative open reading frames cannot completely be explained by a biased codon usage in the +1 frame. While it is unknown if the stop codon depletion has a biological function, it could be due to a protein coding capacity of alternative ORFs exerting a selection pressure which prevents the fixation of stop codon mutations. The comparison of the analytical model with bacterial genomes, therefore, leads to a hypothesis suggesting novel gene candidates which can now be investigated in subsequent wet lab experiments.

Evolution of viral proteins originated de novo by overprinting

New protein-coding genes can originate either through modification of existing genes or de novo. Recently, the importance of de novo origination has been recognized in eukaryotes, although eukaryotic genes originated de novo are relatively rare and difficult to identify. In contrast, viruses contain many de novo genes, namely those in which an existing gene has been “overprinted” by a new open reading frame, a process that generates a new protein-coding gene overlapping the ancestral gene. We analyzed the evolution of 12 experimentally validated viral genes that originated de novo and estimated their relative ages. We found that young de novo genes have a different codon usage from the rest of the genome. They evolve rapidly and are under positive or weak purifying selection. Thus, young de novo genes might have strain-specific functions, or no function, and would be difficult to detect using current genome annotation methods that rely on the sequence signature of purifying selection. In contrast to young de novo genes, older de novo genes have a codon usage that is similar to the rest of the genome. They evolve slowly and are under stronger purifying selection. Some of the oldest de novo genes evolve under stronger selection pressure than the ancestral gene they overlap, suggesting an evolutionary tug of war between the ancestral and the de novo gene.

Is there a twelfth protein-coding gene in the genome of influenza A? A selection-based approach to the detection of overlapping genes in closely related sequences

Protein-coding genes often contain long overlapping open-reading frames (ORFs), which may or may not be functional. Current methods that utilize the signature of purifying selection to detect functional overlapping genes are limited to the analysis of sequences from divergent species, thus rendering them inapplicable to genes found only in closely related sequences. Here, we present a method for the detection of selection signatures on overlapping reading frames by using closely related sequences, and apply the method to several known overlapping genes, and to an overlapping ORF on the negative strand of segment 8 of influenza A virus (NEG8), for which the suggestion has been made that it is functional. We find no evidence that NEG8 is under selection, suggesting that the intact reading frame might be non-functional, although we cannot fully exclude the possibility that the method is not sensitive enough to detect the signature of selection acting on this gene. We present the limitations of the method using known overlapping genes and suggest several approaches to improve it in future studies. Finally, we examine alternative explanations for the sequence conservation of NEG8 in the absence of selection. We show that overlap type and genomic context affect the conservation of intact overlapping ORFs and should therefore be considered in any attempt of estimating the signature of selection in overlapping genes.

Probable presence of an ubiquitous cryptic mitochondrial gene on the antisense strand of the cytochrome oxidase I gene

BACKGROUND

Mitochondria mediate most of the energy production that occurs in the majority of eukaryotic organisms. These subcellular organelles contain a genome that differs from the nuclear genome and is referred to as mitochondrial DNA (mtDNA). Despite a disparity in gene content, all mtDNAs encode at least two components of the mitochondrial electron transport chain, including cytochrome c oxidase I (Cox1).

PRESENTATION OF THE HYPOTHESIS

A positionally conserved ORF has been found on the complementary strand of the cox1 genes of both eukaryotic mitochondria (protist, plant, fungal and animal) and alpha-proteobacteria. This putative gene has been named gau for gene antisense ubiquitous in mtDNAs. The length of the deduced protein is approximately 100 amino acids. In vertebrates, several stop codons have been found in the mt gau region, and potentially functional gau regions have been found in nuclear genomes. However, a recent bioinformatics study showed that several hypothetical overlapping mt genes could be predicted, including gau; this involves the possible import of the cytosolic AGR tRNA into the mitochondria and/or the expression of mt antisense tRNAs with anticodons recognizing AGR codons according to an alternative genetic code that is induced by the presence of suppressor tRNAs. Despite an evolutionary distance of at least 1.5 to 2.0 billion years, the deduced Gau proteins share some conserved amino acid signatures and structure, which suggests a possible conserved function. Moreover, BLAST analysis identified rare, sense-oriented ESTs with poly(A) tails that include the entire gau region. Immunohistochemical analyses using an anti-Gau monoclonal antibody revealed strict co-localization of Gau proteins and a mitochondrial marker.

TESTING THE HYPOTHESIS

This hypothesis could be tested by purifying the gau gene product and determining its sequence. Cell biological experiments are needed to determine the physiological role of this protein.

IMPLICATIONS OF THE HYPOTHESIS

Studies of the gau ORF will shed light on the origin of novel genes and their functions in organelles and could also have medical implications for human diseases that are caused by mitochondrial dysfunction. Moreover, this strengthens evidence for mitochondrial genes coded according to an overlapping genetic code.