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Amino acid repeats avert mRNA folding through conservative substitutions and synonymous codons, regardless of codon bias

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Heliyon

Elsevier

Genetics, Computational biology, Structural biology, Bioinformatics

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      Abstract

      A significant number of proteins in all living species contains amino acid repeats (AARs) of various lengths and compositions, many of which play important roles in protein structure and function. Here, I have surveyed select homopolymeric single [(A)n] and double [(AB)n] AARs in the human proteome. A close examination of their codon pattern and analysis of RNA structure propensity led to the following set of empirical rules: (1) One class of amino acid repeats (Class I) uses a mixture of synonymous codons, some of which approximate the codon bias ratio in the overall human proteome; (2) The second class (Class II) disregards the codon bias ratio, and appears to have originated by simple repetition of the same codon (or just a few codons); and finally, (3) In all AARs (including Class I, Class II, and the in-betweens), the codons are chosen in a manner that precludes the formation of RNA secondary structure. It appears that the AAR genes have evolved by orchestrating a balance between codon usage and mRNA secondary structure. The insights gained here should provide a better understanding of AAR evolution and may assist in designing synthetic genes.

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      Most cited references 27

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      Mfold web server for nucleic acid folding and hybridization prediction.

       M Zuker (2003)
      The abbreviated name, 'mfold web server', describes a number of closely related software applications available on the World Wide Web (WWW) for the prediction of the secondary structure of single stranded nucleic acids. The objective of this web server is to provide easy access to RNA and DNA folding and hybridization software to the scientific community at large. By making use of universally available web GUIs (Graphical User Interfaces), the server circumvents the problem of portability of this software. Detailed output, in the form of structure plots with or without reliability information, single strand frequency plots and 'energy dot plots', are available for the folding of single sequences. A variety of 'bulk' servers give less information, but in a shorter time and for up to hundreds of sequences at once. The portal for the mfold web server is http://www.bioinfo.rpi.edu/applications/mfold. This URL will be referred to as 'MFOLDROOT'.
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        Incorporating chemical modification constraints into a dynamic programming algorithm for prediction of RNA secondary structure.

        A dynamic programming algorithm for prediction of RNA secondary structure has been revised to accommodate folding constraints determined by chemical modification and to include free energy increments for coaxial stacking of helices when they are either adjacent or separated by a single mismatch. Furthermore, free energy parameters are revised to account for recent experimental results for terminal mismatches and hairpin, bulge, internal, and multibranch loops. To demonstrate the applicability of this method, in vivo modification was performed on 5S rRNA in both Escherichia coli and Candida albicans with 1-cyclohexyl-3-(2-morpholinoethyl) carbodiimide metho-p-toluene sulfonate, dimethyl sulfate, and kethoxal. The percentage of known base pairs in the predicted structure increased from 26.3% to 86.8% for the E. coli sequence by using modification constraints. For C. albicans, the accuracy remained 87.5% both with and without modification data. On average, for these sequences and a set of 14 sequences with known secondary structure and chemical modification data taken from the literature, accuracy improves from 67% to 76%. This enhancement primarily reflects improvement for three sequences that are predicted with <40% accuracy on the basis of energetics alone. For these sequences, inclusion of chemical modification constraints improves the average accuracy from 28% to 78%. For the 11 sequences with <6% pseudoknotted base pairs, structures predicted with constraints from chemical modification contain on average 84% of known canonical base pairs.
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          RNAstructure: software for RNA secondary structure prediction and analysis

          Background To understand an RNA sequence's mechanism of action, the structure must be known. Furthermore, target RNA structure is an important consideration in the design of small interfering RNAs and antisense DNA oligonucleotides. RNA secondary structure prediction, using thermodynamics, can be used to develop hypotheses about the structure of an RNA sequence. Results RNAstructure is a software package for RNA secondary structure prediction and analysis. It uses thermodynamics and utilizes the most recent set of nearest neighbor parameters from the Turner group. It includes methods for secondary structure prediction (using several algorithms), prediction of base pair probabilities, bimolecular structure prediction, and prediction of a structure common to two sequences. This contribution describes new extensions to the package, including a library of C++ classes for incorporation into other programs, a user-friendly graphical user interface written in JAVA, and new Unix-style text interfaces. The original graphical user interface for Microsoft Windows is still maintained. Conclusion The extensions to RNAstructure serve to make RNA secondary structure prediction user-friendly. The package is available for download from the Mathews lab homepage at http://rna.urmc.rochester.edu/RNAstructure.html.
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            Author and article information

            Affiliations
            EonBio, 3780 Pelham Drive, Mobile, AL 36619, USA
            Author notes
            [* ]Corresponding author. barikfamily@ 123456gmail.com
            Contributors
            Journal
            Heliyon
            Heliyon
            Heliyon
            Elsevier
            2405-8440
            28 December 2017
            December 2017
            28 December 2017
            : 3
            : 12
            5772840
            S2405-8440(17)33548-X
            10.1016/j.heliyon.2017.e00492
            e00492
            © 2017 The Authors

            This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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