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      Evolution and structural variations in chloroplast tRNAs in gymnosperms

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          Abstract

          Background

          Chloroplast transfer RNAs (tRNAs) can participate in various vital processes. Gymnosperms have important ecological and economic value, and they are the dominant species in forest ecosystems in the Northern Hemisphere. However, the evolution and structural changes in chloroplast tRNAs in gymnosperms remain largely unclear.

          Results

          In this study, we determined the nucleotide evolution, phylogenetic relationships, and structural variations in 1779 chloroplast tRNAs in gymnosperms. The numbers and types of tRNA genes present in the chloroplast genomes of different gymnosperms did not differ greatly, where the average number of tRNAs was 33 and the frequencies of occurrence for various types of tRNAs were generally consistent. Nearly half of the anticodons were absent. Molecular sequence variation analysis identified the conserved secondary structures of tRNAs. About a quarter of the tRNA genes were found to contain precoded 3′ CCA tails. A few tRNAs have undergone novel structural changes that are closely related to their minimum free energy, and these structural changes affect the stability of the tRNAs. Phylogenetic analysis showed that tRNAs have evolved from multiple common ancestors. The transition rate was higher than the transversion rate in gymnosperm chloroplast tRNAs. More loss events than duplication events have occurred in gymnosperm chloroplast tRNAs during their evolutionary process.

          Conclusions

          These findings provide novel insights into the molecular evolution and biological characteristics of chloroplast tRNAs in gymnosperms.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12864-021-08058-3.

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          Most cited references80

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          Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

          Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl. Contact: peter@biomatters.com
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            MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform.

            K Katoh (2002)
            A multiple sequence alignment program, MAFFT, has been developed. The CPU time is drastically reduced as compared with existing methods. MAFFT includes two novel techniques. (i) Homo logous regions are rapidly identified by the fast Fourier transform (FFT), in which an amino acid sequence is converted to a sequence composed of volume and polarity values of each amino acid residue. (ii) We propose a simplified scoring system that performs well for reducing CPU time and increasing the accuracy of alignments even for sequences having large insertions or extensions as well as distantly related sequences of similar length. Two different heuristics, the progressive method (FFT-NS-2) and the iterative refinement method (FFT-NS-i), are implemented in MAFFT. The performances of FFT-NS-2 and FFT-NS-i were compared with other methods by computer simulations and benchmark tests; the CPU time of FFT-NS-2 is drastically reduced as compared with CLUSTALW with comparable accuracy. FFT-NS-i is over 100 times faster than T-COFFEE, when the number of input sequences exceeds 60, without sacrificing the accuracy.
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              tRNAscan-SE On-line: integrating search and context for analysis of transfer RNA genes

              High-throughput genome sequencing continues to grow the need for rapid, accurate genome annotation and tRNA genes constitute the largest family of essential, ever-present non-coding RNA genes. Newly developed tRNAscan-SE 2.0 has advanced the state-of-the-art methodology in tRNA gene detection and functional prediction, captured by rich new content of the companion Genomic tRNA Database. Previously, web-server tRNA detection was isolated from knowledge of existing tRNAs and their annotation. In this update of the tRNAscan-SE On-line resource, we tie together improvements in tRNA classification with greatly enhanced biological context via dynamically generated links between web server search results, the most relevant genes in the GtRNAdb and interactive, rich genome context provided by UCSC genome browsers. The tRNAscan-SE On-line web server can be accessed at http://trna.ucsc.edu/tRNAscan-SE/.
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                Author and article information

                Contributors
                lizhonghu@nwu.edu.cn
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                18 October 2021
                18 October 2021
                2021
                : 22
                : 750
                Affiliations
                [1 ]GRID grid.412262.1, ISNI 0000 0004 1761 5538, Key Laboratory of Resource Biology and Biotechnology in Western China (Ministry of Education), College of Life Sciences, , Northwest University, ; Xi’an, 710069 China
                [2 ]GRID grid.412262.1, ISNI 0000 0004 1761 5538, State Key Laboratory of Continental Dynamics, Department of Geology, , Early Life Institute, Northwest University, ; Xi’an, 710069 China
                Article
                8058
                10.1186/s12864-021-08058-3
                8524817
                34663228
                b6441e15-e80b-4e80-82b0-bb136e9e2786
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 20 October 2020
                : 6 October 2021
                Funding
                Funded by: the National Natural Science Foundation of China
                Award ID: 31970359
                Funded by: the Shaanxi Science and Technology Innovation Team
                Award ID: 2019TD‐012
                Funded by: the Public health specialty in the Department of Traditional Chinese Medicine
                Award ID: 2019-68
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2021

                Genetics
                chloroplast trna,conservation,evolution,minimum free energy,phylogenetic relationship
                Genetics
                chloroplast trna, conservation, evolution, minimum free energy, phylogenetic relationship

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