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      Complete mitochondrial genome of the lappet moth, Kunugia undans (Lepidoptera: Lasiocampidae): genomic comparisons among macroheteroceran superfamilies

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          Abstract

          The mitochondrial genome (mitogenome) characteristics of the monotypic Lasiocampoidea are largely unknown, because only limited number of mitogenomes is available from this superfamily. In this study, we sequenced the complete mitogenome of the lappet moth, Kunugia undans (Lepidoptera: Lasiocampidae) and compared it to those of Lasiocampoidea and macroheteroceran superfamilies (59 species in six superfamilies). The 15,570-bp K. undans genome had one additional trnR that was located between trnA and trnN loci and this feature was unique in Macroheterocera, including Lasiocampoidea. Considering that the two trnR copies are located in tandem with proper secondary structures and identical anticodons, a gene duplication event might be responsible for the presence of the two tRNAs. Nearly all macroheteroceran species, excluding Lasiocampoidea, have a spacer sequence (1–34 bp) at the trnS 2 and ND1 junction, but most lasiocampid species, including K. undans, have an overlap at the trnS 2 and ND1 junction, which represents a different genomic feature in Lasiocampoidea. Nevertheless, a TTAGTAT motif, which is typically detected in Macroheterocera at the trnS 2 and ND1 junction, was also detected in all Lasiocampoidea. In summary, the general mitogenome characteristics of Lasiocampoidea did not differ greatly from the remaining macroheteroceran superfamilies, but it did exhibit some unique features.

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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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            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: a program for improved detection of transfer RNA genes in genomic sequence.

              We describe a program, tRNAscan-SE, which identifies 99-100% of transfer RNA genes in DNA sequence while giving less than one false positive per 15 gigabases. Two previously described tRNA detection programs are used as fast, first-pass prefilters to identify candidate tRNAs, which are then analyzed by a highly selective tRNA covariance model. This work represents a practical application of RNA covariance models, which are general, probabilistic secondary structure profiles based on stochastic context-free grammars. tRNAscan-SE searches at approximately 30 000 bp/s. Additional extensions to tRNAscan-SE detect unusual tRNA homologues such as selenocysteine tRNAs, tRNA-derived repetitive elements and tRNA pseudogenes.
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                Author and article information

                Journal
                Genet Mol Biol
                Genet. Mol. Biol
                gmb
                Genetics and Molecular Biology
                Sociedade Brasileira de Genética
                1415-4757
                1678-4685
                31 July 2017
                Jul-Sep 2017
                : 40
                : 3
                : 717-723
                Affiliations
                [1]Department of Applied Biology, College of Agriculture & Life Sciences, Chonnam National University, Gwangju, Republic of Korea
                Author notes
                Send correspondence to Iksoo Kim. Department of Applied Biology, College of Agriculture & Life Sciences, Chonnam National University, Gwangju 61186, Republic of Korea. E-mail: ikkim81@ 123456chonnam.ac.kr .
                Article
                S1415-47572017005019103
                10.1590/1678-4685-GMB-2016-0298
                5596373
                28767123
                88f37042-e4a5-4274-9492-97f7ab4231f7
                Copyright © 2017, Sociedade Brasileira de Genética.

                License information: This is an open-access article distributed under the terms of the Creative Commons Attribution License (type CC-BY), which permits unrestricted use, distribution and reproduction in any medium, provided the original article is properly cited.

                History
                : 17 November 2016
                : 25 February 2017
                Page count
                Figures: 4, Tables: 4, Equations: 0, References: 50, Pages: 10
                Categories
                Genomics and Bioinformatics

                Molecular biology
                kunugia undans,mitochondrial genome,lasiocampoidea,macroheterocera
                Molecular biology
                kunugia undans, mitochondrial genome, lasiocampoidea, macroheterocera

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