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      Genome Size Reduction and Transposon Activity Impact tRNA Gene Diversity While Ensuring Translational Stability in Birds

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          Abstract

          As a highly diverse vertebrate class, bird species have adapted to various ecological systems. How this phenotypic diversity can be explained genetically is intensively debated and is likely grounded in differences in the genome content. Larger and more complex genomes could allow for greater genetic regulation that results in more phenotypic variety. Surprisingly, avian genomes are much smaller compared to other vertebrates but contain as many protein-coding genes as other vertebrates. This supports the notion that the phenotypic diversity is largely determined by selection on non-coding gene sequences. Transfer RNAs (tRNAs) represent a group of non-coding genes. However, the characteristics of tRNA genes across bird genomes have remained largely unexplored. Here, we exhaustively investigated the evolution and functional consequences of these crucial translational regulators within bird species and across vertebrates. Our dense sampling of 55 avian genomes representing each bird order revealed an average of 169 tRNA genes with at least 31% being actively used. Unlike other vertebrates, avian tRNA genes are reduced in number and complexity but are still in line with vertebrate wobble pairing strategies and mutation-driven codon usage. Our detailed phylogenetic analyses further uncovered that new tRNA genes can emerge through multiplication by transposable elements. Together, this study provides the first comprehensive avian and cross-vertebrate tRNA gene analyses and demonstrates that tRNA gene evolution is flexible albeit constrained within functional boundaries of general mechanisms in protein translation.

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          Basic local alignment search tool.

          A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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            HISAT: a fast spliced aligner with low memory requirements.

            HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an indexing scheme based on the Burrows-Wheeler transform and the Ferragina-Manzini (FM) index, employing two types of indexes for alignment: a whole-genome FM index to anchor each alignment and numerous local FM indexes for very rapid extensions of these alignments. HISAT's hierarchical index for the human genome contains 48,000 local FM indexes, each representing a genomic region of ∼64,000 bp. Tests on real and simulated data sets showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method. Despite its large number of indexes, HISAT requires only 4.3 gigabytes of memory. HISAT supports genomes of any size, including those larger than 4 billion bases.
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              MEGA6: Molecular Evolutionary Genetics Analysis version 6.0.

              We announce the release of an advanced version of the Molecular Evolutionary Genetics Analysis (MEGA) software, which currently contains facilities for building sequence alignments, inferring phylogenetic histories, and conducting molecular evolutionary analysis. In version 6.0, MEGA now enables the inference of timetrees, as it implements the RelTime method for estimating divergence times for all branching points in a phylogeny. A new Timetree Wizard in MEGA6 facilitates this timetree inference by providing a graphical user interface (GUI) to specify the phylogeny and calibration constraints step-by-step. This version also contains enhanced algorithms to search for the optimal trees under evolutionary criteria and implements a more advanced memory management that can double the size of sequence data sets to which MEGA can be applied. Both GUI and command-line versions of MEGA6 can be downloaded from www.megasoftware.net free of charge.
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                Author and article information

                Contributors
                Role: Associate Editor
                Journal
                Genome Biol Evol
                Genome Biol Evol
                gbe
                Genome Biology and Evolution
                Oxford University Press
                1759-6653
                April 2021
                03 February 2021
                03 February 2021
                : 13
                : 4
                : evab016
                Affiliations
                [1 ] Department of Microbiology, Tumor and Cell Biology, Science for Life Laboratory, Karolinska Institute , Stockholm, Sweden
                [2 ] Department of Ecology and Genetics, Evolutionary Biology Centre, Science for Life Laboratory, Uppsala University , Sweden
                Author notes
                Corresponding author: E-mail: claudia.kutter@ 123456ki.se .
                Article
                evab016
                10.1093/gbe/evab016
                8044555
                33533905
                f076d36d-2475-447d-acee-2607df09e001
                © The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 22 January 2021
                Page count
                Pages: 16
                Categories
                Research Article
                AcademicSubjects/SCI01130
                AcademicSubjects/SCI01140

                Genetics
                trna annotation,trna gene usage,codon usage,transposons,vertebrate,comparative genomics
                Genetics
                trna annotation, trna gene usage, codon usage, transposons, vertebrate, comparative genomics

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