Evidence of a Direct Evolutionary Selection for Strong Folding and Mutational Robustness Within HIV Coding Regions

Abstract

A large number of studies demonstrated the importance of different HIV RNA structural elements at all stages of the viral life cycle. Nevertheless, the significance of many of these structures is unknown, and plausibly new regions containing RNA structure-mediated regulatory signals remain to be identified. An important characteristic of genomic regions carrying functionally significant secondary structures is their mutational robustness, that is, the extent to which a sequence remains constant in spite of despite mutations in terms of its underlying secondary structure. Structural robustness to mutations is expected to be important in the case of functional RNA structures in viruses with high mutation rate; it may prevent fitness loss due to disruption of possibly functional conformations, pointing to the specific significance of the corresponding genomic region. In the current work, we perform a genome-wide computational analysis to detect signals of a direct evolutionary selection for strong folding and RNA structure-based mutational robustness within HIV coding sequences. We provide evidence that specific regions of HIV structural genes undergo an evolutionary selection for strong folding; in addition, we demonstrate that HIV Rev responsive element seems to undergo a direct evolutionary selection for increased secondary structure robustness to point mutations. We believe that our analysis may enable a better understanding of viral evolutionary dynamics at the RNA structural level and may benefit to practical efforts of engineering antiviral vaccines and novel therapeutic approaches.

Evidence of translation efficiency adaptation of the coding regions of the bacteriophage lambda

“…28 This model was initially introduced in the context of enumerative combinatorics and was used by us before for studying other viruses. 16,17 We used the original source code which can be found in http://csb.cs. mcgill.ca/sparcs (7 February 2017, date last accessed).…”

“…mRNA secondary structure is believed to be in the most stable conformation when minimum amount of free energy is exerted (the MFE obtains the most negative value). The local MFE-profiles were constructed by applying a 39 nt length sliding window to a genomic sequence: in each step the MFE of a local subsequence enclosed by the corresponding window was calculated by Vienna (v. 2.1.9) package RNAfold 31 function with default parameters (see, also 16,32 ). This function predicts the MFE and the associated secondary structure for the input RNA sequence using a dynamic programming based on the thermodynamic nearest-neighbor approach (the Zucker algorithm).…”

“…For each gene 100 randomized MFE-profiles variants were computed basing on randomized sequences generated by the dinucleotide preserving and codon preserving randomization models (both preserving also the encoded proteins, see section above). 16,17,28 We did not change the UTRs in the randomization as in this study we are interested in the coding regions.…”

“…For example, a recent study by Liu et al 9 employed ribosome profiling to study the progress of bacteriophage lambda gene expression during phage development and showed that the known genes are expressed in a predictable fashion; in addition many previously unknown potential open reading frames were detected. Other studies focused on different aspects of viral translation (and lifecycle in general) regulation that has a significant effect on shaping viral genomes, such as: secondary structures within viral transcripts (mainly in untranslated regions 16,17 but also within coding regions [18][19][20] ) and evolutionary pressure on synonymous codons usage bias. [21][22][23][24][25] However, to the best of our knowledge, this is the first study aiming to perform a comprehensive, large scale analysis of different types of genomic synonymous information related to regulation of translation efficiency in all coding regions of a bacteriophage lambda, during different stages of its development.…”

The Landscape of the Emergence of Life

“…and concluded that various “hidden” regulatory signals are encoded in the viral genome which naturally affect their evolution and replication rate. Codes analogous to the viral “hidden” codes may have appeared in the molecules prior to the origin of cellular life [35,36,37,38]. …”