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      Reference-based RADseq resolves robust relationships among closely related species of lichen-forming fungi using metagenomic DNA

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          Abstract

          Despite increasing availability of phylogenomic datasets, strategies to generate genome-scale data from organisms involved in symbiotic relationships remains challenging. Restriction site-associated DNA sequencing (RADseq) can effectively generated reduced representation genomic loci. However, when using metagenomic DNA from inseparable symbiotic organisms, RADseq loci may belong to any number of the organisms involved in these intimate associations. In this study, we explored the potential for a reference-based RADseq approach to generate data for lichen-forming fungi from metagenomic DNA extracted from intact lichens. We simulated RAD data from draft genomes of closely related lichenized fungi to test if RADseq can reconstruct robust evolutionary relationships. Subsequently, we generated empirical RADseq data from metagenomic lichen DNA, with RADseq loci mapped back to a reference genome to exclude loci from other lichen symbionts that are represented in metagenomic libraries. In all cases, phylogenetic reconstructions using RADseq loci recovered diversification histories consistent with a previous study based on more comprehensive genome sampling. Furthermore, RADseq loci were found to resolve relationships among closely related species, which were otherwise indistinguishable using a phylogenetic species recognition criterion. Our studies revealed that a modified, reference-based RADseq approach can successfully be implemented to generate symbiont-specific phylogenomic data from metagenomic reads.

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          Ray Meta: scalable de novo metagenome assembly and profiling

          Voluminous parallel sequencing datasets, especially metagenomic experiments, require distributed computing for de novo assembly and taxonomic profiling. Ray Meta is a massively distributed metagenome assembler that is coupled with Ray Communities, which profiles microbiomes based on uniquely-colored k-mers. It can accurately assemble and profile a three billion read metagenomic experiment representing 1,000 bacterial genomes of uneven proportions in 15 hours with 1,024 processor cores, using only 1.5 GB per core. The software will facilitate the processing of large and complex datasets, and will help in generating biological insights for specific environments. Ray Meta is open source and available at http://denovoassembler.sf.net.
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            Automated Reconstruction of Whole-Genome Phylogenies from Short-Sequence Reads

            Studies of microbial evolutionary dynamics are being transformed by the availability of affordable high-throughput sequencing technologies, which allow whole-genome sequencing of hundreds of related taxa in a single study. Reconstructing a phylogenetic tree of these taxa is generally a crucial step in any evolutionary analysis. Instead of constructing genome assemblies for all taxa, annotating these assemblies, and aligning orthologous genes, many recent studies 1) directly map raw sequencing reads to a single reference sequence, 2) extract single nucleotide polymorphisms (SNPs), and 3) infer the phylogenetic tree using maximum likelihood methods from the aligned SNP positions. However, here we show that, when using such methods to reconstruct phylogenies from sets of simulated sequences, both the exclusion of nonpolymorphic positions and the alignment to a single reference genome, introduce systematic biases and errors in phylogeny reconstruction. To address these problems, we developed a new method that combines alignments from mappings to multiple reference sequences and show that this successfully removes biases from the reconstructed phylogenies. We implemented this method as a web server named REALPHY (Reference sequence Alignment-based Phylogeny builder), which fully automates phylogenetic reconstruction from raw sequencing reads.
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              HybPiper: Extracting coding sequence and introns for phylogenetics from high-throughput sequencing reads using target enrichment1

              Premise of the study: Using sequence data generated via target enrichment for phylogenetics requires reassembly of high-throughput sequence reads into loci, presenting a number of bioinformatics challenges. We developed HybPiper as a user-friendly platform for assembly of gene regions, extraction of exon and intron sequences, and identification of paralogous gene copies. We test HybPiper using baits designed to target 333 phylogenetic markers and 125 genes of functional significance in Artocarpus (Moraceae). Methods and Results: HybPiper implements parallel execution of sequence assembly in three phases: read mapping, contig assembly, and target sequence extraction. The pipeline was able to recover nearly complete gene sequences for all genes in 22 species of Artocarpus. HybPiper also recovered more than 500 bp of nontargeted intron sequence in over half of the phylogenetic markers and identified paralogous gene copies in Artocarpus. Conclusions: HybPiper was designed for Linux and Mac OS X and is freely available at https://github.com/mossmatters/HybPiper.
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                Author and article information

                Contributors
                fgrewe@fieldmuseum.org
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                29 August 2017
                29 August 2017
                2017
                : 7
                : 9884
                Affiliations
                [1 ]ISNI 0000 0001 0476 8496, GRID grid.299784.9, Integrative Research Center, , Science and Education, Field Museum of Natural History, 1400S Lake Shore Drive, ; Chicago, IL 60605 USA
                [2 ]ISNI 0000 0004 1936 9115, GRID grid.253294.b, Department of Biology & M. L. Bean Life Science Museum, , Brigham Young University, ; Provo, UT 84602 USA
                Article
                9906
                10.1038/s41598-017-09906-7
                5575168
                28852019
                27a01b9b-9727-468b-93c0-f0a523a35dba
                © The Author(s) 2017

                Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 8 May 2017
                : 31 July 2017
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