Why is rrna used

The copy contributing part of the genome may be acquired by horizontal transfer. Further understanding of concerted evolution of rrs when in multiple copies in the genome such as the exact mechanism of recombination, the rate of erasing or spreading of the original base change occurring in one rrs , and the possible difference on the rate of non-reciprocal recombination of the different rrs in the genome will help to detail its effect on the evolution of the 16S rRNA.

RE reviewed the literature and wrote the manuscript. NP extended revision of literature, revised data and drew figures, and collaborated in the writing of the manuscript. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acinas, S. Divergence and redundancy of 16S rRNA sequences in genomes with multiple rrn operons. Alberts, B. Molecular Biology of the Cell , 4th edn. Google Scholar. Anda, M. Bacterial clade with the ribosomal RNA operon on a small plasmid rather than the chromosome.

Apirion, D. RNA processing in prokaryotic cells. BioEssays 15, — Asai, T. Construction and initial characterization of Escherichia coli strains with few or no intact chromosomal rRNA operons. Battermann, A. A functional plasmid-borne rrn operon in soil isolates belonging to the genus Paracoccus.

Microbiology , — Battistuzzi, F. A genomic timescale of prokaryote evolution: insights into the origin of methanogenesis, phototrophy, and the colonization of land. BMC Evol. Bodilis, J. Variable copy number, intra-genomic heterogeneities and lateral transfers of the 16S rRNA gene in Pseudomonas.

PLoS One 7:e Cilia, V. Sequence heterogeneities among 16S ribosomal RNA sequences, and their effect on phylogenetic analyses at the species level. Feil, E. The relative contributions of recombination and mutation to the divergence of clones of Neisseria meningitidis.

Galimand, M. RNA 17, — FEMS Microbiol. Harth, E. Intragenomic heterogeneity and intergenomic recombination among Vibrio parahaemolyticus 16S rRNA genes. Hashimoto, J. Rates and consequences of recombination between ribosomal RNA operons. Hastings, P. Mechanisms of ectopic gene conversion. Genes Basel. Ira, G. Srs2 and Sgs1-Top3 suppress crossovers during double-strand break repair in yeast.

Cell , — Jain, R. Horizontal gene transfer among genomes: the complexity hypothesis. Johansen, J. PLoS One e Kaneko, T. DNA Res. Kim, J. Kiss, A. The interspecific differences of the information contained in the variable regions of 16S rRNA make the detection specific. With the emergence of PCR technology and the continuous improvement of nucleic acid research technology, 16S rRNA gene detection technology has become a powerful tool for pathogen detection and identification.

With the continuous improvement of the database, the technology can be applied to classify, identify, and detect pathogens quickly, accurately, and accurately. RRNA gene fragment in the microorganism sample by cloning, sequencing or enzyme cutting and probe hybridization, and then comparing with the sequence data or other data in the 16S rRNA database to determine its position in the evolutionary tree, thus identifying the possible samples.

The species of microbes that exist. The information obtained by this method is the most comprehensive, but in the sample Complex sequencing requires extensive sequencing. In addition, the probe can be directly detected by in situ hybridization with the sample. The underlying cause of the correlation between different sub-regions in terms of phylogenetic resolution remains unknown.

Because 16S rRNA itself carries out the process of gene translation, it is quite interesting to potentially connect these regions with the 3D structure and functioning sites Fig. The hairpin is a highly conserved loop in all three phylogenetic domains located at the V4 region of 16S rRNA [ 34 , 38 ].

The decoding center is also involved in V9, but it was not considered in the present study. Therefore, whether the positions in the decoding center determine the phylogenetic resolution could not be confirmed herein.

Important functional roles have not yet been confirmed. They may serve as structural stabilizers of the 16S rRNA, but no functional importance has been reported to date. This observation is similar to the debate over the association between the evolutionary rate and gene dispensability [ 47 — 49 ]. According to this theory, genes with a high dispensability may have evolved slowly. In contrast, the differences in less important regions, such as Class II, may occur at lower taxonomic levels.

Similarly, in our study, the functions associated with Class I regions might evolve at a lower rate and be more stable than the other variable regions. As a result, these regions could allow the realization of a more stable phylogenetic topology among the diverse bacterial phyla. Class II and Class III regions are less conserved and display more polymorphisms that may occur only at lower taxonomic levels. Thus, these sub-regions are less sensitive as markers for the phylogenetic resolution of a novel lineage within a community at the phylum level.

However, the functioning sites are usually quite short in comparison with the whole sub-region and thus, it is questionable whether the several conserved sites determine the topology of a phylogenetic tree consisting of 32 different phyla.

Individual regions are identified by the same color in both the 2D and 3D structures. Some important structures are colored with blocks. In the present study, we evaluated the sensitivity of different 16S rRNA sub-regions as biomarkers of different bacterial phyla using the geodesic distance method and the consensus AHC method.

A combination of V4-V6 was determined to represent the optimal sub-regions for the bacterial phylogenetic study of new phyla. Furthermore, for the first time, we briefly evaluated the correlation of different sub-regions of 16S rRNA in terms of the phylogenetic resolution, which might suggest a relationship between the function and evolution of 16S rRNA genes.

Insights into the phylogeny and coding potential of microbial dark matter. Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA.

Appl Environ Microbiol. Characterization of microbial diversity by determining terminal restriction fragment length polymorphisms of genes encoding 16S rRNA.

Combining fluorescent in situ hybridization FISH with cultivation and mathematical modeling to study population structure and function of ammonia-oxidizing bacteria in activated sludge. Water Sci Technol. Applications of functional gene microarrays for profiling microbial communities. Curr Opin Biotech. Comparison of two next-generation sequencing technologies for resolving highly complex microbiota composition using tandem variable 16S rRNA gene regions.

Nucleic Acids Res. PLoS One. Bennett S. Solexa Ltd. Article PubMed Google Scholar. Rapid determination of 16S ribosomal RNA sequences for phylogenetic analyses.

Tringe SG, Hugenholtz P. A renaissance for the pioneering 16S rRNA gene. Curr Opin Microbiol. Review and re-analysis of domain-specific 16S primers. J Microbiol Methods. Wang Y, Qian P-Y. Yu Z, Morrison M. Comparisons of different hypervariable regions of rrs genes for use in fingerprinting of microbial communities by PCR-denaturing gradient gel electrophoresis. Hamady M, Knight R. Microbial community profiling for human microbiome projects: Tools, techniques, and challenges.

Genome Res. Evaluation of different partial 16S rRNA gene sequence regions for phylogenetic analysis of microbiomes. Evaluations of different hypervariable regions of archaeal 16S rRNA genes in profiling of methanogens by Archaea-specific PCR and denaturing gradient gel electrophoresis.

Direct analysis of genes encoding 16S rRNA from complex communities reveals many novel molecular species within the human gut. Phylogenetic analysis of the 16S rDNA of the cytoplasmic bacterium Wolbachia from the novel host Folsomia candida Hexapoda, Collembola and its implications for wolbachial taxonomy. J Bacteriol. Geometry of the Space of Phylogenetic Trees. Adv Appl Math. Article Google Scholar. Owen M. Computing Geodesic Distances in Tree Space. Owen M, Provan JS.

The other defined a collection of highly unusual and little studied organisms. This group, originally named Archaeabacteria, is now known as Archaea. Very soon after Woese and colleagues outlined the three domains of life, researchers started reading the sequences of ribosomal RNA genes from a larger number of organisms. Researchers studying microbes initially focused on microbes that they could grow in the lab i.

However, a few researchers, especially Norman Pace , realized that they might be able to use this general approach to study microbes in the environment without ever growing them in the lab. Pace sampled environments where there were thought to be only a few types of organisms present, isolated ribosomal RNA from the samples, and read the sequences. He showed that he could determine the types of organisms present in a sample by building evolutionary trees of rRNA sequences, even if he had never grown, or even seen, the organisms.

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