scholarly journals Analysis of Messenger RNA Secondary Structures in Rhodobacter sphaeroides

2020 ◽  
Author(s):  
Damilola Omotajo ◽  
Hyuk Cho ◽  
Madhusudan Choudhary
Keyword(s):  
Secondary Structure ◽  
Rhodobacter Sphaeroides ◽  
Translation Initiation ◽  
Messenger Rna ◽  
Gc Content ◽  
Secondary Structures ◽  
Inhibitory Effect ◽  
Nucleotide Composition ◽  
Protein Coding ◽  
Secondary Structure Analysis

Abstract Background: The Shine-Dalgarno (SD) sequence, when present, is known to promote translation initiation in a bacterial cell. However, the thermodynamic stability of the messenger RNA (mRNA) through its secondary structures has an inhibitory effect on the efficiency of translation. This poses the question of whether bacterial mRNAs with SD have low secondary structure formation or not. Results: About 3500 protein-coding genes in Rhodobacter sphaeroides were analyzed and a sliding window analysis of the last 100 nucleotides of the 5’ UTR and the first 100 nucleotides of ORFs was performed using RNAfold, a software for RNA secondary structure analysis. It was shown that mRNAs with SD are less stable than those without SD for genes located on the primary chromosome, but not for the plasmid encoded genes. Furthermore, mRNA stability is similar for genes within each chromosome except those encoded by the accessory chromosome (second chromosome). Conclusions: Results highlight the possible contribution of other factors like replicon- specific nucleotide composition (GC content), codon bias, and protein stability in determining the efficiency of translation initiation in both SD-dependent and SD-independent translation systems.

scholarly journals Widespread selection for extremely high and low levels of secondary structure in coding sequences across all domains of life

Open Biology ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 190020 ◽  
Author(s):  
Daniel Gebert ◽  
Julia Jehn ◽  
David Rosenkranz
Keyword(s):  
Secondary Structure ◽  
Gc Content ◽  
Secondary Structures ◽  
Coding Sequences ◽  
Rna Secondary Structures ◽  
Synonymous Mutations ◽  
Codon Composition ◽  
Domains Of Life ◽  
Low Levels ◽  
Selection For

Codon composition, GC content and local RNA secondary structures can have a profound effect on gene expression, and mutations affecting these parameters, even though they do not alter the protein sequence, are not neutral in terms of selection. Although evidence exists that, in some cases, selection favours more stable RNA secondary structures, we currently lack a concrete idea of how many genes are affected within a species, and whether this is a universal phenomenon in nature. We searched for signs of structural selection in a global manner, analysing a set of 1 million coding sequences from 73 species representing all domains of life, as well as viruses, by means of our newly developed software PACKEIS. We show that codon composition and amino acid identity are main determinants of RNA secondary structure. In addition, we show that the arrangement of synonymous codons within coding sequences is non-random, yielding extremely high, but also extremely low, RNA structuredness significantly more often than expected by chance. Taken together, we demonstrate that selection for high and low levels of secondary structure is a widespread phenomenon. Our results provide another line of evidence that synonymous mutations are less neutral than commonly thought, which is of importance for many evolutionary models.

scholarly journals Mutations designed to modify the NS gene mRNA secondary structure affect influenza A pathogenicity in vivo

2021 ◽  
Vol 8 (1) ◽  
pp. 1-9
Author(s):  
I. L. Baranovskaya ◽  
M. V. Sergeeva ◽  
A. S. Taraskin ◽  
A. A. Lozhkov ◽  
A. V. Vasin
Keyword(s):  
Secondary Structure ◽  
Viral Replication ◽  
Influenza A Virus ◽  
Messenger Rna ◽  
Influenza A ◽  
Early Stage ◽  
Secondary Structures ◽  
Mrna Secondary Structure ◽  
Splice Sites ◽  
Ns Gene

The influenza A virus genome consists of eight segments of negative-sense RNA that encode up to 18 proteins. During the process of viral replication, positive-sense (+)RNA (cRNA) or messenger RNA (mRNA) is synthesized. Today, there is only a partial understanding of the function of several secondary structures within vRNA and cRNA promoters, and splice sites in the M and NS genes. The most precise secondary structure of (+)RNA has been determined for the NS segment of influenza A virus.  The influenza A virus NS gene features two regions with a conserved mRNA secondary structure located near splice sites. Here, we compared 4 variants of the A/Puerto Rico/8/1934 strain featuring different combinations of secondary structures at the NS segment (+)RNA regions 82-148 and 497-564. We found that RNA structures did not affect viral replication in cell culture. However, one of the viruses demonstrated lower NS1 and NEP expression levels during early stage cell infection as well as reduced pathogenicity in mice compared to other variants. In particular, this virus is characterized by an RNA hairpin in the 82-148 region and a stable hairpin in the 497-564 region.

scholarly journals Making ends meet: new functions of mRNA secondary structure

2020 ◽  
Author(s):  
Dmitri N. Ermolenko ◽  
David Mathews
Keyword(s):  
Secondary Structure ◽  
Translation Initiation ◽  
Protein Complexes ◽  
Experimental Studies ◽  
Mrna Translation ◽  
Low Complexity ◽  
Mrna Secondary Structure ◽  
Protein Coding ◽  
Random Coils ◽  
Non Coding Rnas

AbstractThe 5’ cap and 3’ poly(A) tail of mRNA are known to synergistically regulate mRNA translation and stability. Recent computational and experimental studies revealed that both protein-coding and non-coding RNAs will fold with extensive intramolecular secondary structure, which will result in close distances between the sequence ends. This proximity of the ends is a sequence-independent, universal property of most RNAs. Only low-complexity sequences without guanosines are without secondary structure and exhibit end-to-end distances expected for RNA random coils. The innate proximity of RNA ends might have important biological implications that remain unexplored. In particular, the inherent compactness of mRNA might regulate translation initiation by facilitating the formation of protein complexes that bridge mRNA 5’ and 3’ ends. Additionally, the proximity of mRNA ends might mediate coupling of 3′ deadenylation to 5′ end mRNA decay.

scholarly journals Splicing buffers suboptimal codon usage in human cells

2019 ◽  
Author(s):  
Christine Mordstein ◽  
Rosina Savisaar ◽  
Robert S Young ◽  
Jeanne Bazile ◽  
Lana Talmane ◽  
...  
Keyword(s):  
Codon Usage ◽  
Human Genome ◽  
Selective Pressure ◽  
Gc Content ◽  
Nucleotide Composition ◽  
Mrna Splicing ◽  
Mrna Levels ◽  
Cytoplasmic Localization ◽  
Protein Coding ◽  
Positive Effect

Although multiple studies have addressed the effects of codon usage on gene expression, such studies were typically performed in unspliced model genes. In the human genome, most genes undergo splicing and patterns of codon usage are splicing-dependent: guanine and cytosine (GC) content is highest within single-exon genes and within first exons of multi-exon genes. Intrigued by this observation, we measured the effects of splicing on expression in a panel of synonymous variants of GFP and mKate2 reporter genes that varied in nucleotide composition. We found that splicing promotes the expression of adenine and thymine (AT)-rich variants by increasing their steady-state protein and mRNA levels, in part through promoting cytoplasmic localization of mRNA. Splicing had little or no effect on the expression of GC-rich variants. In the absence of splicing, high GC content at the 5' end, but not at the 3' end of the coding sequence positively correlated with expression. Among endogenous human protein-coding transcripts, GC content has a more positive effect on various expression measures of unspliced, relative to spliced mRNAs. We propose that splicing promotes the expression of AT-rich genes, leading to selective pressure for the retention of introns in the human genome.

scholarly journals Widespread selection for high and low secondary structure in coding sequences across all domains of life

2019 ◽  
Author(s):  
Daniel Gebert ◽  
Julia Jehn ◽  
David Rosenkranz
Keyword(s):  
Secondary Structure ◽  
Gc Content ◽  
Secondary Structures ◽  
Amino Acid Identity ◽  
Coding Sequences ◽  
Rna Secondary Structures ◽  
Synonymous Mutations ◽  
Codon Composition ◽  
Domains Of Life ◽  
Selection For

AbstractCodon composition, GC-content and local RNA secondary structures can have a profound effect on gene expression and mutations affecting these parameters, even though they do not alter the protein sequence, are not neutral in terms of selection. Although evidence exists that in some cases selection favors more stable RNA secondary structures, we currently lack a concrete idea of how many genes are affected within a species, and if this is a universal phenomenon in nature.We searched for signs of structural selection in a global manner, analyzing a set of one million coding sequences from 73 species representing all domains of life, as well as viruses, by means of our newly developed software PACKEIS. We show that codon composition and amino acid identity are main determinants of RNA secondary structure. In addition, we show that the arrangement of synonymous codons within coding sequences is non-random, yielding extremely high, but also extremely low secondary structures significantly more often than expected by chance.Together, we demonstrate that selection for high and low secondary structure is a widespread phenomenon. Our results provide another line of evidence that synonymous mutations are less neutral than commonly thought, which is of importance for many evolutionary models.

scholarly journals How Codon Usage Bias Affects Our Ability to Recover the Tree of Life

2019 ◽  
Author(s):  
Justin B. Miller ◽  
Michael F. Whiting ◽  
John S.K. Kauwe ◽  
Perry G. Ridge
Keyword(s):  
Gene Expression ◽  
Secondary Structure ◽  
Codon Usage ◽  
Primary Structure ◽  
Gc Content ◽  
Nucleotide Composition ◽  
Evolutionary Patterns ◽  
Tree Inference ◽  
Differential Gene ◽  
Affect Gene Expression

Phylogenies depict shared evolutionary patterns and structures on a tree topology, enabling the identification of hierarchical and historical relationships. Recent analyses indicate that phylogenetic signals extend beyond the primary structure of protein or DNA, and various aspects of codon usage biases are phylogenetically conserved. Several functional biases exist within genes, including the number of codons that are used, the position of the codons, and the overall nucleotide composition of the genome. Codon usage biases can significantly affect transcription and translational efficiencies, leading to differential gene expression. Although systematic codon usage biases originate from the overall GC content of a species, ramp sequences, codon aversion, codon pairing, and tRNA competition also significantly affect gene expression and are phylogenetically conserved. We review recent advances in analyzing codon usage biases and their implications in phylogenomics. We first outline common phylogenomic techniques. Next, we identify several codon usage biases and their effects on secondary structure, gene expression, and implications in phylogenetics. Finally, we suggest how codon usage biases can be included in phylogenomics. By incorporating various codon usage biases in common phylogenomic algorithms, we propose that we can significantly improve tree inference. Since codon usage biases have significant biological implications, they should be considered in conjunction with other phylogenetic algorithms.

scholarly journals Cross-linked RNA Secondary Structure Analysis using Network Techniques

2019 ◽  
Author(s):  
Irena Fischer-Hwang ◽  
Zhipeng Lu ◽  
James Zou ◽  
Tsachy Weissman
Keyword(s):  
Network Analysis ◽  
Secondary Structure ◽  
Structure Analysis ◽  
Rna Secondary Structure ◽  
Secondary Structures ◽  
Rna Structures ◽  
Secondary Structure Analysis ◽  
Automated Method ◽  
Analysis Package ◽  
Generation Sequencing

AbstractNext generation sequencing and biochemical cross-linking methods have been combined into powerful tools to probe RNA secondary structure. One such method, known as PARIS, has been used to produce near base-pair maps of long-range and alternative RNA structures in living cells. However, the procedure for generating these maps typically relies on laborious manual analysis. We developed an automated method for producing RNA secondary structure maps using network analysis techniques. We produced an analysis pipeline, dubbed cross-linked RNA secondary structure analysis using network techniques (CRSSANT), which automates the grouping of gapped RNA sequencing reads produced using the PARIS assay, and tests the validity of secondary structures implied by the groups. We validated the clusters and secondary structures produced by CRSSANT using manually-produced grouping maps and known secondary structures. We implemented CRSSANT in Python using the network analysis package NetworkX and RNA folding software package ViennaRNA. CRSSANT is fast and efficient, and is available as Python source code at https://github.com/ihwang/CRSSANT.

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