Dataset Information

Loss of matK RNA editing in seed plant chloroplasts.

ABSTRACT:

Background

RNA editing in chloroplasts of angiosperms proceeds by C-to-U conversions at specific sites. Nuclear-encoded factors are required for the recognition of cis-elements located immediately upstream of editing sites. The ensemble of editing sites in a chloroplast genome differs widely between species, and editing sites are thought to evolve rapidly. However, large-scale analyses of the evolution of individual editing sites have not yet been undertaken.

Results

Here, we analyzed the evolution of two chloroplast editing sites, matK-2 and matK-3, for which DNA sequences from thousands of angiosperm species are available. Both sites are found in most major taxa, including deep-branching families such as the nymphaeaceae. However, 36 isolated taxa scattered across the entire tree lack a C at one of the two matK editing sites. Tests of several exemplary species from this in silico analysis of matK processing unexpectedly revealed that one of the two sites remain unedited in almost half of all species examined. A comparison of sequences between editors and non-editors showed that specific nucleotides co-evolve with the C at the matK editing sites, suggesting that these nucleotides are critical for editing-site recognition.

Conclusion

(i) Both matK editing sites were present in the common ancestor of all angiosperms and have been independently lost multiple times during angiosperm evolution.(ii) The editing activities corresponding to matK-2 and matK-3 are unstable.(iii) A small number of third-codon positions in the vicinity of editing sites are selectively constrained independent of the presence of the editing site, most likely because of interacting RNA-binding proteins.

SUBMITTER: Tillich M

PROVIDER: S-EPMC2744683 | biostudies-literature | 2009 Aug

REPOSITORIES: biostudies-literature

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Publications

Loss of matK RNA editing in seed plant chloroplasts.

Tillich Michael M Sy Vinh Le VL Schulerowitz Katrin K von Haeseler Arndt A Maier Uwe G UG Schmitz-Linneweber Christian C

BMC evolutionary biology 20090813

<h4>Background</h4>RNA editing in chloroplasts of angiosperms proceeds by C-to-U conversions at specific sites. Nuclear-encoded factors are required for the recognition of cis-elements located immediately upstream of editing sites. The ensemble of editing sites in a chloroplast genome differs widely between species, and editing sites are thought to evolve rapidly. However, large-scale analyses of the evolution of individual editing sites have not yet been undertaken.<h4>Results</h4>Here, we anal ...[more]

PMID: 19678945

Similar Datasets

Project description:BACKGROUND:DNA barcoding is widely used and most efficient approach that facilitates rapid and accurate identification of plant species based on the short standardized segment of the genome. The nucleotide sequences of maturaseK (matK) and ribulose-1, 5-bisphosphate carboxylase (rbcL) marker loci are commonly used in plant species identification. Here, we present a new and highly efficient approach for identifying a unique set of discriminating nucleotide patterns to generate a signature (i.e. regular expression) for plant species identification. METHODS:In order to generate molecular signatures, we used matK and rbcL loci datasets, which encompass 125 plant species in 52 genera reported by the CBOL plant working group. Initially, we performed Multiple Sequence Alignment (MSA) of all species followed by Position Specific Scoring Matrix (PSSM) for both loci to achieve a percentage of discrimination among species. Further, we detected Discriminating Patterns (DP) at genus and species level using PSSM for the matK dataset. Combining DP and consecutive pattern distances, we generated molecular signatures for each species. Finally, we performed a comparative assessment of these signatures with the existing methods including BLASTn, Support Vector Machines (SVM), Jrip-RIPPER, J48 (C4.5 algorithm), and the Naïve Bayes (NB) methods against NCBI-GenBank matK dataset. RESULTS:Due to the higher discrimination success obtained with the matK as compared to the rbcL, we selected matK gene for signature generation. We generated signatures for 60 species based on identified discriminating patterns at genus and species level. Our comparative assessment results suggest that a total of 46 out of 60 species could be correctly identified using generated signatures, followed by BLASTn (34 species), SVM (18 species), C4.5 (7 species), NB (4 species) and RIPPER (3 species) methods As a final outcome of this study, we converted signatures into QR codes and developed a software matK-QR Classifier (http://www.neeri.res.in/matk_classifier/index.htm), which search signatures in the query matK gene sequences and predict corresponding plant species. CONCLUSIONS:This novel approach of employing pattern-based signatures opens new avenues for the classification of species. In addition to existing methods, we believe that matK-QR Classifier would be a valuable tool for molecular taxonomists enabling precise identification of plant species.

Dataset Information

Loss of matK RNA editing in seed plant chloroplasts.

Background

Results

Conclusion

Publications

Loss of matK RNA editing in seed plant chloroplasts.

Similar Datasets

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