Molecular evolution of rDNA in early diverging Metazoa: First comparative analysis and phylogenetic application of complete SSU rRNA secondary structures in Porifera

Background  

The cytoplasmic ribosomal small subunit (SSU, 18S) ribosomal RNA (rRNA) is the most frequently-used gene for molecular phylogenetic studies. However, information regarding its secondary structure is neglected in most phylogenetic analyses. Incorporation of this information is essential in order to apply specific rRNA evolutionary models to overcome the problem of co-evolution of paired sites, which violates the basic assumption of the independent evolution of sites made by most phylogenetic methods. Information about secondary structure also supports the process of aligning rRNA sequences across taxa. Both aspects have been shown to increase the accuracy of phylogenetic reconstructions within various taxa.     

Constraining ribosomal RNA conformational space

Despite the potential for many possible secondary-structure conformations, the native sequence of ribosomal RNA (rRNA) is able to find the correct and universally conserved core fold. This study reports a computational analysis investigating two mechanisms that appear to constrain rRNA secondary-structure conformational space: ribosomal proteins and rRNA sequence composition. The analysis was carried out by using rRNA–ribosomal protein interaction data for the Escherichia coli 16S rRNA and free energy minimization software for secondary-structure prediction. The results indicate that selection pressures on rRNA sequence composition and ribosomal protein–rRNA interaction play a key role in constraining the rRNA secondary structure to a single stable form.     

Introducing W.A.T.E.R.S.: a Workflow for the Alignment,Taxonomy, and Ecology of Ribosomal Sequences

Background  

For more than two decades microbiologists have used a highly conserved microbial gene as a phylogenetic marker for bacteria and archaea. The small-subunit ribosomal RNA gene, also known as 16 S rRNA, is encoded by ribosomal DNA, 16 S rDNA, and has provided a powerful comparative tool to microbial ecologists. Over time, the microbial ecology field has matured from small-scale studies in a select number of environments to massive collections of sequence data that are paired with dozens of corresponding collection variables. As the complexity of data and tool sets have grown, the need for flexible automation and maintenance of the core processes of 16 S rDNA sequence analysis has increased correspondingly.     

Sequence and characterisation of a ribosomal RNA operon fromAgrobacterium vitis

One of the four ribosomal RNA operons (rrnA) from theAgrobacterium vitis vitopine strain S4 was sequenced.rrnA is most closely related to therrn operons ofBradyrhizobium japonicum andRhodobacter sphaeroides and carries an fMet-tRNA gene downstream of its 5S gene, as in the case ofR. sphaeroides. The 16S rRNA sequence of S4 differs from theA. vitis K309 type strain sequence by only one nucleotide, in spite of the fact that S4 and K309 have very different Ti plasmids. The predicted secondary structure of the S4 23S rRNA shows several features that are specific for the alpha proteobacteria, and an unusual branched structure in the universal B8 stem. The 3 ends of the three otherrrn copies of S4 were also cloned and sequenced. Sequence comparison delimits the 3 ends of the four repeats and defines two groups:rrnA/rrnB andrrnC/rrnD.     

The 18S and 5S ribosomal RNA genes in Oenothera mitochondria: Sequence rearrangments in the 18S and 5S rRNA genes of higher plants

Summary The 18S and 5S ribosomal RNA genes are separated by a 582-nucleotide-long spacer region in the Oenothera mitochondrial genome. The 5S rRNA gene is 7 bp shorter than the maize and 3 bp shorter than the wheat sequences due to a 4 bp deletion in a side arm of the secondary structure model. The 18S rRNA molecule can be folded analogously to the maize and wheat mitochondrial and Escherichia coli models for this rRNA. Most of the sequence variations between the wheat and Oenothera molecules are located in the variable domains identified for the wheat 18S rRNA.The comparison of the 18S rRNA from the mitochondria of Oenothera as a representative of dicotyledonous plants with that of the monocotyledons wheat and maize provides an indication of the rate of diversity in higher plant mitochondrial genes and gives direct evidence for sequence rearrangements within the 18 S rRNA genes.     

Repeated reunions and splits feature the highly dynamic evolution of 5S and 35S ribosomal RNA genes (rDNA) in the Asteraceae family

Background  

In flowering plants and animals the most common ribosomal RNA genes (rDNA) organisation is that in which 35S (encoding 18S-5.8S-26S rRNA) and 5S genes are physically separated occupying different chromosomal loci. However, recent observations established that both genes have been unified to a single 35S-5S unit in the genus Artemisia (Asteraceae), a genomic arrangement typical of primitive eukaryotes such as yeast, among others. Here we aim to reveal the origin, distribution and mechanisms leading to the linked organisation of rDNA in the Asteraceae by analysing unit structure (PCR, Southern blot, sequencing), gene copy number (quantitative PCR) and chromosomal position (FISH) of 5S and 35S rRNA genes in ~200 species representing the family diversity and other closely related groups.     

Nucleotide sequence of the rrnB 16S ribosomal RNA gene from Mycoplasma capricolum

Summary The nucleotide sequences of the rrnB 16S ribosomal RNA gene and its 5-and 3-flanking regions from Mycoplasma capricolum have been determined. The coding sequence is 1521 base pairs long, being 21 base pairs shorter than that of the Scherichia coli 16S rRNA gene. The 16S rRNA sequence of M. capricolum reveals 74% and 76% identity with that of E. coli and Anacystis nidulans, respectively. The secondary structure model constructed from the M. capricolum 16S rRNA.gene sequence resembles that proposed for E. coli 16S rRNA. A large stem structure can be constructed between the 5- and 3-flanking sequences of the 16S rRNA gene. The flanking regions are extremely rich in AT.     

Two accurate sequence,structure, and phylogenetic template-based RNA alignment systems

Background

The analysis of RNA sequences, once a small niche field for a small collection of scientists whose primary emphasis was the structure and function of a few RNA molecules, has grown most significantly with the realizations that 1) RNA is implicated in many more functions within the cell, and 2) the analysis of ribosomal RNA sequences is revealing more about the microbial ecology within all biological and environmental systems. The accurate and rapid alignment of these RNA sequences is essential to decipher the maximum amount of information from this data.

Methods

Two computer systems that utilize the Gutell lab's RNA Comparative Analysis Database (rCAD) were developed to align sequences to an existing template alignment available at the Gutell lab's Comparative RNA Web (CRW) Site. Multiple dimensions of cross-indexed information are contained within the relational database - rCAD, including sequence alignments, the NCBI phylogenetic tree, and comparative secondary structure information for each aligned sequence. The first program, CRWAlign-1 creates a phylogenetic-based sequence profile for each column in the alignment. The second program, CRWAlign-2 creates a profile based on phylogenetic, secondary structure, and sequence information. Both programs utilize their profiles to align new sequences into the template alignment.

Results

The accuracies of the two CRWAlign programs were compared with the best template-based rRNA alignment programs and the best de-novo alignment programs. We have compared our programs with a total of eight alternative alignment methods on different sets of 16S rRNA alignments with sequence percent identities ranging from 50% to 100%. Both CRWAlign programs were superior to these other programs in accuracy and speed.

Conclusions

Both CRWAlign programs can be used to align the very extensive amount of RNA sequencing that is generated due to the rapid next-generation sequencing technology. This latter technology is augmenting the new paradigm that RNA is intimately implicated in a significant number of functions within the cell. In addition, the use of bacterial 16S rRNA sequencing in the identification of the microbiome in many different environmental systems creates a need for rapid and highly accurate alignment of bacterial 16S rRNA sequences.

     

Nucleotide sequence of Citrus limon 26S rRNA gene and secondary structure model of its RNA

The complete nucleotide sequence of Citrus limon 26S rDNA has been determined. The sequence has been aligned with large ribosomal RNA (L-rRNA) sequences of Escherichia coli, Saccharomyces cerevisiae and Oryza sativa. Nine extensive expansion segments in dicot 26S rRNA relative to E. coli 23S rRNA have been identified and compared with analogous segments of monocot, yeast, amphibian and human L-rRNAs. A secondary structure model for lemon 26S rRNA has been derived based on the refined model of E. coli 23S rRNA. It has been compared with other eukaryotic L-rRNAs models in terms of location of functionally important regions. Origin and evolution of L-rRNA expansion segments are discussed.     

RibAlign: a software tool and database for eubacterial phylogeny based on concatenated ribosomal protein subunits

Background  

Until today, analysis of 16S ribosomal RNA (rRNA) sequences has been the de-facto gold standard for the assessment of phylogenetic relationships among prokaryotes. However, the branching order of the individual phlya is not well-resolved in 16S rRNA-based trees. In search of an improvement, new phylogenetic methods have been developed alongside with the growing availability of complete genome sequences. Unfortunately, only a few genes in prokaryotic genomes qualify as universal phylogenetic markers and almost all of them have a lower information content than the 16S rRNA gene. Therefore, emphasis has been placed on methods that are based on multiple genes or even entire genomes. The concatenation of ribosomal protein sequences is one method which has been ascribed an improved resolution. Since there is neither a comprehensive database for ribosomal protein sequences nor a tool that assists in sequence retrieval and generation of respective input files for phylogenetic reconstruction programs, RibAlign has been developed to fill this gap.     

Secondary structure maps of ribosomal RNA. II. Processing of mouse L-cell ribosomal RNA and variations in the processing pathway

Secondary structure mapping in the electron microscope was applied to ribosomal RNA and precusor ribosomal RNA molecules isolated from nucleoli and the cytoplasm of mouse L-cells. Highly reproducible loop patterns were observed in these molecules. The polarity of L-cell rRNA was determined by partial digestion with 3′-exonuclease. The 28 S region is located at the 5′-end of the 45 S rRNA precursor. Together with earlier experiments on labeling kinetics, these observations established a processing pathway for L-cell rRNA. The 45 S rRNA precursor is cleaved at the 3′-end of the 18 S RNA sequence to produce a 41 S molecule and a spacer-containing fragment (24 S RNA). The 41 S rRNA is cleaved forming mature 18 S rRNA and a 36 S molecule. The 36 S molecule is processed through a 32 S intermediate to the mature 28 S rRNA. This pathway is similar to that found in HeLa cells, except that in L-cells a 36 S molecule occurs in the major pathway and no 20 S precusor to 18 S RNA is found. The processing pathway and its intermediates in L-cells are analogous to those in Xenopus laevis, except for a considerable size difference in all rRNAs except 18 S rRNA.The arrangement of gene and transcribed spacer regions and of secondary structure loops, as well as the shape of the major loops were compared in L-cells, HeLa cell and Xenopus rRNA. The over-all arrangement of regions and loop patterns is very similar in the RNA from these three organisms. The shapes of loops in mature 28 S RNA are also highly conserved in evolution, but the shapes of loops in the transcribed spacer regions vary greatly. These observations suggest that the sequence complementarity that gives rise to this highly conserved secondary structure pattern may have some functional importance.     

Evaluation of the suitability of free-energy minimization using nearest-neighbor energy parameters for RNA secondary structure prediction

Background

A detailed understanding of an RNA's correct secondary and tertiary structure is crucial to understanding its function and mechanism in the cell. Free energy minimization with energy parameters based on the nearest-neighbor model and comparative analysis are the primary methods for predicting an RNA's secondary structure from its sequence. Version 3.1 of Mfold has been available since 1999. This version contains an expanded sequence dependence of energy parameters and the ability to incorporate coaxial stacking into free energy calculations. We test Mfold 3.1 by performing the largest and most phylogenetically diverse comparison of rRNA and tRNA structures predicted by comparative analysis and Mfold, and we use the results of our tests on 16S and 23S rRNA sequences to assess the improvement between Mfold 2.3 and Mfold 3.1.

Results

The average prediction accuracy for a 16S or 23S rRNA sequence with Mfold 3.1 is 41%, while the prediction accuracies for the majority of 16S and 23S rRNA structures tested are between 20% and 60%, with some having less than 20% prediction accuracy. The average prediction accuracy was 71% for 5S rRNA and 69% for tRNA. The majority of the 5S rRNA and tRNA sequences have prediction accuracies greater than 60%. The prediction accuracy of 16S rRNA base-pairs decreases exponentially as the number of nucleotides intervening between the 5' and 3' halves of the base-pair increases.

Conclusion

Our analysis indicates that the current set of nearest-neighbor energy parameters in conjunction with the Mfold folding algorithm are unable to consistently and reliably predict an RNA's correct secondary structure. For 16S or 23S rRNA structure prediction, Mfold 3.1 offers little improvement over Mfold 2.3. However, the nearest-neighbor energy parameters do work well for shorter RNA sequences such as tRNA or 5S rRNA, or for larger rRNAs when the contact distance between the base-pairs is less than 100 nucleotides.     

Intraspecific nucleotide divergence in Saccharomycodes ludwigii,and proposal of Saccharomycodes pseudoludwigii sp. nov,a new apiculate yeast isolated from China

The six synonyms currently accepted under Saccharomycodes ludwigii were investigated for by phenotypic properties, however, the sequence diversity of the rRNA and protein coding genes have not yet been determined. Nine strains including the type strains of synonyms of S. ludwigii deposited in the CBS yeast collection, Westerdijk Fungal Biodiversity Institute, Utrecht, The Netherlands, were analyzed using a multi-locus sequence analysis (MLSA) approach that included sequences of 18S ribosomal RNA (rRNA), the D1/D2 domains of the 26S rRNA, the ITS region (including the 5.8S rRNA) and fragments of genes encoding the largest subunit of the RNA polymerase II (RPB1 and RPB2) and translation elongation factor 1-α (TEF1). Our results showed that the nine strains have identical D1/D2, 18S and RPB2 sequences and similar ITS, RPB1 and TEF1 sequences, which indicated that they are conspecific. In addition, a novel species of Saccharomycodes, S. pseudoludwigii sp. nov. (type CGMCC 2.4526 ^T) that was isolated from fruit and tree bark in China, is proposed. The MycoBank number of this new species is MB 811,650.

     

Sequence studies on the soybean chloroplast 16S–23S rDNA spacer region

The sequence of the ribosomal spacer region of soybean chloroplast DNA including the 3 end of the 16S rRNA gene, the tRNA^Ala and tRNA^Ile genes (but not their introns), the three intergenic regions and the 5 end of the 23S rRNA gene, has been determined. This sequence has been compared to corresponding regions of other angiosperm chloroplast DNAs. Secondary structure models are proposed for the entirety of the intergenic regions a, b and c and for the flanking rRNA regions. A model for a common secondary structure of the ribosomal spacer intergenic regions from chloroplasts of higher plants is proposed, which is supported by comparative evidence.     

Visualization of ribosomal RNA operon copy number distribution

Background  

Results of microbial ecology studies using 16S rRNA sequence information can be deceiving due to differences in rRNA operon copy number and genome size of the detected organisms. It therefore will be useful for investigators to have a better understanding of how these two parameters differ in various organism types. In this study, the number of ribosomal operons and genome size were separately mapped onto a Bacterial phylogenetic tree.     

A memory-efficient dynamic programming algorithm for optimal alignment of a sequence to an RNA secondary structure

Background  

Covariance models (CMs) are probabilistic models of RNA secondary structure, analogous to profile hidden Markov models of linear sequence. The dynamic programming algorithm for aligning a CM to an RNA sequence of length N is O(N ³) in memory. This is only practical for small RNAs.     

Can Clustal-style progressive pairwise alignment of multiple sequences be used in RNA secondary structure prediction?

Background  

In ribonucleic acid (RNA) molecules whose function depends on their final, folded three-dimensional shape (such as those in ribosomes or spliceosome complexes), the secondary structure, defined by the set of internal basepair interactions, is more consistently conserved than the primary structure, defined by the sequence of nucleotides.     

What an rRNA Secondary Structure Tells about Phylogeny of Fungi in Ascomycota with Emphasis on Evolution of Major Types of Ascus

Background

RNA secondary structure is highly conserved throughout evolution. The higher order structure is fundamental in establishing important structure-function relationships. Nucleotide sequences from ribosomal RNA (rRNA) genes have made a great contribution to our understanding of Ascomycota phylogeny. However, filling the gaps between molecular phylogeny and morphological assumptions based on ascus dehiscence modes and type of fruitbodies at the higher level classification of the phylum remains an unfulfilled task faced by mycologists.

Methodology/Principal Findings

We selected some major groups of Ascomycota to view their phylogenetic relationships based on analyses of rRNA secondary structure. Using rRNA secondary structural information, here, we converted nucleotide sequences into the structure ones over a 20-symbol code. Our structural analyses together with ancestral character state reconstruction produced reasonable phylogenetic position for the class Geoglossomycetes as opposed to the classic nucleotide analyses. Judging from the secondary structure analyses with consideration of mode of ascus dehiscence and the ability of forming fruitbodies, we draw a clear picture of a possible evolutionary route for fungal asci and some major groups of fungi in Ascomycota. The secondary structure trees show a more reasonable phylogenetic position for the class Geoglossomycetes.

Conclusions

Our results illustrate that asci lacking of any dehiscence mechanism represent the most primitive type. Passing through the operculate and Orbilia-type asci, bitunicate asci occurred. The evolution came to the most advanced inoperculate type. The ascus-producing fungi might be derived from groups lacking of the capacity to form fruitbodies, and then evolved multiple times. The apothecial type of fruitbodies represents the ancestral state, and the ostiolar type is advanced. The class Geoglossomycetes is closely related to Leotiomycetes and Sordariomycetes having a similar ascus type other than it was originally placed based on nucleotide sequence analyses.