The complete mitochondrial genome of oceanic puffer ( Lagocephalus lagocephalus ) from South China Sea

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Abstract

Lagocephalus lagocephalus is one of genus Lagocephalus and widely distributed in tropical and temperate oceans. In this study, we described the complete mitochondrial genome of L. lagocephalus. The genome is 166,443 bp in length, encoding the standard set of 13 protein-coding genes (PCGs), 22 transfer RNA genes, 2 ribosomal RNA genes, and a non-coding D-loop, with circular organization. The overall base composition of the whole mitochondrial genome was A (27.95%), T (25.07%), G (16.14%), and C (30.83%) with an AT bias of 53.03%. The longest PCG of these species was ND5, whereas the shortest ATP8.

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Most cited references 7

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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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Reconstructing mitochondrial genomes directly from genomic next-generation sequencing reads—a baiting and iterative mapping approach

Christoph Hahn, Lutz Bachmann, Bastien Chevreux (2013)

We present an in silico approach for the reconstruction of complete mitochondrial genomes of non-model organisms directly from next-generation sequencing (NGS) data—mitochondrial baiting and iterative mapping (MITObim). The method is straightforward even if only (i) distantly related mitochondrial genomes or (ii) mitochondrial barcode sequences are available as starting-reference sequences or seeds, respectively. We demonstrate the efficiency of the approach in case studies using real NGS data sets of the two monogenean ectoparasites species Gyrodactylus thymalli and Gyrodactylus derjavinoides including their respective teleost hosts European grayling (Thymallus thymallus) and Rainbow trout (Oncorhynchus mykiss). MITObim appeared superior to existing tools in terms of accuracy, runtime and memory requirements and fully automatically recovered mitochondrial genomes exceeding 99.5% accuracy from total genomic DNA derived NGS data sets in <24 h using a standard desktop computer. The approach overcomes the limitations of traditional strategies for obtaining mitochondrial genomes for species with little or no mitochondrial sequence information at hand and represents a fast and highly efficient in silico alternative to laborious conventional strategies relying on initial long-range PCR. We furthermore demonstrate the applicability of MITObim for metagenomic/pooled data sets using simulated data. MITObim is an easy to use tool even for biologists with modest bioinformatics experience. The software is made available as open source pipeline under the MIT license at https://github.com/chrishah/MITObim.

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Author and article information

Journal

Journal ID (nlm-ta): Mitochondrial DNA B Resour

Journal ID (iso-abbrev): Mitochondrial DNA B Resour

Title: Mitochondrial DNA. Part B, Resources

Publisher: Taylor & Francis

ISSN (Electronic): 2380-2359

Publication date (Electronic, pub): 12 November 2019

Publication date (Electronic, collection): 2019

Volume: 4

Issue: 2

Pages: 3996-3997

Affiliations

[a ]South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences , Guangzhou, China;

[b ]Guangdong Provincial Key Laboratory of Fishery Ecology and Environment, Chinese Academy of Fishery Sciences , Guangzhou, China

Author notes

CONTACT Feiyan Du feiyanegg@ 123456163.com South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences , Guangzhou510300, China

Article

Publisher ID: 1688098

DOI: 10.1080/23802359.2019.1688098

PMC ID: 7707739

SO-VID: a65eb2d0-b45d-45aa-a4f9-959b383112fd

License:

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Figures: 1, Tables: 0, Pages: 2, Words: 1089

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