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      Multiplex sequencing of pooled mitochondrial genomes—a crucial step toward biodiversity analysis using mito-metagenomics

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          Abstract

          The advent in high-throughput-sequencing (HTS) technologies has revolutionized conventional biodiversity research by enabling parallel capture of DNA sequences possessing species-level diagnosis. However, polymerase chain reaction (PCR)-based implementation is biased by the efficiency of primer binding across lineages of organisms. A PCR-free HTS approach will alleviate this artefact and significantly improve upon the multi-locus method utilizing full mitogenomes. Here we developed a novel multiplex sequencing and assembly pipeline allowing for simultaneous acquisition of full mitogenomes from pooled animals without DNA enrichment or amplification. By concatenating assemblies from three de novo assemblers, we obtained high-quality mitogenomes for all 49 pooled taxa, with 36 species >15 kb and the remaining >10 kb, including 20 complete mitogenomes and nearly all protein coding genes (99.6%). The assembly quality was carefully validated with Sanger sequences, reference genomes and conservativeness of protein coding genes across taxa. The new method was effective even for closely related taxa, e.g. three Drosophila spp., demonstrating its broad utility for biodiversity research and mito-phylogenomics. Finally, the in silico simulation showed that by recruiting multiple mito-loci, taxon detection was improved at a fixed sequencing depth. Combined, these results demonstrate the plausibility of a multi-locus mito-metagenomics approach as the next phase of the current single-locus metabarcoding method.

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          Most cited references30

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

          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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            TIGR Gene Indices clustering tools (TGICL): a software system for fast clustering of large EST datasets.

            TGICL is a pipeline for analysis of large Expressed Sequence Tags (EST) and mRNA databases in which the sequences are first clustered based on pairwise sequence similarity, and then assembled by individual clusters (optionally with quality values) to produce longer, more complete consensus sequences. The system can run on multi-CPU architectures including SMP and PVM.
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              A DNA barcode for land plants.

              DNA barcoding involves sequencing a standard region of DNA as a tool for species identification. However, there has been no agreement on which region(s) should be used for barcoding land plants. To provide a community recommendation on a standard plant barcode, we have compared the performance of 7 leading candidate plastid DNA regions (atpF-atpH spacer, matK gene, rbcL gene, rpoB gene, rpoC1 gene, psbK-psbI spacer, and trnH-psbA spacer). Based on assessments of recoverability, sequence quality, and levels of species discrimination, we recommend the 2-locus combination of rbcL+matK as the plant barcode. This core 2-locus barcode will provide a universal framework for the routine use of DNA sequence data to identify specimens and contribute toward the discovery of overlooked species of land plants.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                16 December 2014
                07 October 2014
                07 October 2014
                : 42
                : 22
                : e166
                Affiliations
                [1 ]China National GeneBank, BGI-Shenzhen, Beishan Road, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong Province 518083, China
                [2 ]University of Chinese Academy of Sciences, 19A Yuquan Road, Shijingshan District, Beijing 100094, China
                [3 ]China University of Geosciences, 388 Lumo Road, Wuhan 430074, China
                [4 ]Capital Normal University, Beijing 100094, China
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +86 0755 25273620; Fax: +86 0755 25273620; Email: xinzhou@ 123456genomics.cn
                Article
                10.1093/nar/gku917
                4267667
                25294837
                87243abe-1b15-4188-b78d-39c021d3dd13
                © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution 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@ 123456oup.com

                History
                : 22 September 2014
                : 16 September 2014
                : 10 June 2014
                Page count
                Pages: 13
                Categories
                7
                Methods Online
                Custom metadata
                16 December 2014

                Genetics
                Genetics

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