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      Complex archaea that bridge the gap between prokaryotes and eukaryotes

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          Abstract

          The origin of the eukaryotic cell remains one of the most contentious puzzles in modern biology. Recent studies have provided support for the emergence of the eukaryotic host cell from within the archaeal domain of life, but the identity and nature of the putative archaeal ancestor remain a subject of debate. Here we describe the discovery of ‘Lokiarchaeota’, a novel candidate archaeal phylum, which forms a monophyletic group with eukaryotes in phylogenomic analyses, and whose genomes encode an expanded repertoire of eukaryotic signature proteins that are suggestive of sophisticated membrane remodelling capabilities. Our results provide strong support for hypotheses in which the eukaryotic host evolved from a bona fide archaeon, and demonstrate that many components that underpin eukaryote-specific features were already present in that ancestor. This provided the host with a rich genomic ‘starter-kit’ to support the increase in the cellular and genomic complexity that is characteristic of eukaryotes.

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          Most cited references107

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            Fast and accurate short read alignment with Burrows–Wheeler transform

            Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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              MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

              We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                21 May 2015
                06 May 2015
                14 May 2015
                14 November 2015
                : 521
                : 7551
                : 173-179
                Affiliations
                [1 ]Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University, SE-75123 Uppsala, Sweden.
                [2 ]Department of Biology, Centre for Geobiology, University of Bergen, N-5020 Bergen, Norway.
                [3 ]Division of Archaea Biology and Ecogenomics, Department of Ecogenomics and Systems Biology, University of Vienna, A-1090 Vienna, Austria.
                [4 ]Department of Medical Biochemistry and Microbiology, Uppsala University, SE-75123 Uppsala, Sweden.
                Author notes
                Correspondence and requests for materials should be addressed to T.J.G.E. ( thijs.ettema@ 123456icm.uu.se ) or L.G. ( lionel.guy@ 123456imbim.uu.se )
                [†]

                Present address: Groningen Institute for Evolutionary Life Sciences, University of Groningen, NL-9747AG Groningen, The Netherlands.

                Author Contributions T.J.G.E., S.L.J. and C.S. conceived the study. S.L.J. provided deep-sea sediments and isolated community DNA. R.v.E., J.H.S. and A.E.L. prepared sequencing libraries. A.E.L., J.H.S., S.L.J. and J.M. analysed environmental sequence data. L.G., K.Z.-N. and J.H.S. performed, optimised and analysed metagenomic sequence assemblies. L.G., J.H.S., A.S., K.Z.-N. and T.J.G.E. analysed genomic data and performed phylogenetic analyses. A.S., L.G., S.L.J. and T.J.G.E analysed genomic signatures of DSAG. T.J.G.E., A.S., S.L.J. and L.G. wrote, and all authors edited and approved the manuscript.

                Article
                EMS63446
                10.1038/nature14447
                4444528
                25945739
                d4b4284b-827b-44bd-8e8b-319a827cdcb8
                ©2015 Macmillan Publishers Limited. All rights reserved

                Reprints and permissions information is available at www.nature.com/reprints.

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