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      Jellyfish genomes reveal distinct homeobox gene clusters and conservation of small RNA processing

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          Abstract

          The phylum Cnidaria represents a close outgroup to Bilateria and includes familiar animals including sea anemones, corals, hydroids, and jellyfish. Here we report genome sequencing and assembly for true jellyfish Sanderia malayensis and Rhopilema esculentum. The homeobox gene clusters are characterised by interdigitation of Hox, NK, and Hox-like genes revealing an alternate pathway of ANTP class gene dispersal and an intact three gene ParaHox cluster. The mitochondrial genomes are linear but, unlike in Hydra, we do not detect nuclear copies, suggesting that linear plastid genomes are not necessarily prone to integration. Genes for sesquiterpenoid hormone production, typical for arthropods, are also now found in cnidarians. Somatic and germline cells both express piwi-interacting RNAs in jellyfish revealing a conserved cnidarian feature, and evidence for tissue-specific microRNA arm switching as found in Bilateria is detected. Jellyfish genomes reveal a mosaic of conserved and divergent genomic characters evolved from a shared ancestral genetic architecture.

          Abstract

          Jellyfish plays an important ecological role in surface waters and the deep sea. Here the authors report genome sequences of two true jellyfish, Sanderia malayensis and Rhopilema esculentum, showing distinct homeobox gene clusters and sesquiterpenoid pathway.

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          LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons

          Background Transposable elements are abundant in eukaryotic genomes and it is believed that they have a significant impact on the evolution of gene and chromosome structure. While there are several completed eukaryotic genome projects, there are only few high quality genome wide annotations of transposable elements. Therefore, there is a considerable demand for computational identification of transposable elements. LTR retrotransposons, an important subclass of transposable elements, are well suited for computational identification, as they contain long terminal repeats (LTRs). Results We have developed a software tool LTRharvest for the de novo detection of full length LTR retrotransposons in large sequence sets. LTRharvest efficiently delivers high quality annotations based on known LTR transposon features like length, distance, and sequence motifs. A quality validation of LTRharvest against a gold standard annotation for Saccharomyces cerevisae and Drosophila melanogaster shows a sensitivity of up to 90% and 97% and specificity of 100% and 72%, respectively. This is comparable or slightly better than annotations for previous software tools. The main advantage of LTRharvest over previous tools is (a) its ability to efficiently handle large datasets from finished or unfinished genome projects, (b) its flexibility in incorporating known sequence features into the prediction, and (c) its availability as an open source software. Conclusion LTRharvest is an efficient software tool delivering high quality annotation of LTR retrotransposons. It can, for example, process the largest human chromosome in approx. 8 minutes on a Linux PC with 4 GB of memory. Its flexibility and small space and run-time requirements makes LTRharvest a very competitive candidate for future LTR retrotransposon annotation projects. Moreover, the structured design and implementation and the availability as open source provides an excellent base for incorporating novel concepts to further improve prediction of LTR retrotransposons.
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            Toward almost closed genomes with GapFiller

            De novo assembly is a commonly used application of next-generation sequencing experiments. The ultimate goal is to puzzle millions of reads into one complete genome, although draft assemblies usually result in a number of gapped scaffold sequences. In this paper we propose an automated strategy, called GapFiller, to reliably close gaps within scaffolds using paired reads. The method shows good results on both bacterial and eukaryotic datasets, allowing only few errors. As a consequence, the amount of additional wetlab work needed to close a genome is drastically reduced. The software is available at http://www.baseclear.com/bioinformatics-tools/.
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              Sea anemone genome reveals ancestral eumetazoan gene repertoire and genomic organization.

              Sea anemones are seemingly primitive animals that, along with corals, jellyfish, and hydras, constitute the oldest eumetazoan phylum, the Cnidaria. Here, we report a comparative analysis of the draft genome of an emerging cnidarian model, the starlet sea anemone Nematostella vectensis. The sea anemone genome is complex, with a gene repertoire, exon-intron structure, and large-scale gene linkage more similar to vertebrates than to flies or nematodes, implying that the genome of the eumetazoan ancestor was similarly complex. Nearly one-fifth of the inferred genes of the ancestor are eumetazoan novelties, which are enriched for animal functions like cell signaling, adhesion, and synaptic transmission. Analysis of diverse pathways suggests that these gene "inventions" along the lineage leading to animals were likely already well integrated with preexisting eukaryotic genes in the eumetazoan progenitor.
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                Author and article information

                Contributors
                peter.holland@zoo.ox.ac.uk
                jeromehui@cuhk.edu.hk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                19 June 2020
                19 June 2020
                2020
                : 11
                : 3051
                Affiliations
                [1 ]ISNI 0000 0004 1937 0482, GRID grid.10784.3a, School of Life Sciences, Simon F.S. Li Marine Science Laboratory, State Key Laboratory of Agrobiotechnology, , The Chinese University of Hong Kong, ; Shatin, Hong Kong
                [2 ]Department of Ocean Science, Division of Life Science and Hong Kong Branch of the Southern Marine Science and Engineering Guangdong Laboratory, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
                [3 ]GRID grid.504403.6, Dovetail Genomics, ; Scotts Valley, CA USA
                [4 ]ISNI 0000 0004 1764 5980, GRID grid.221309.b, Department of Biology, , Hong Kong Baptist University, ; Kowloon Tong, Hong Kong
                [5 ]ISNI 0000 0004 1937 0482, GRID grid.10784.3a, School of Life Sciences, , The Chinese University of Hong Kong, ; Shatin, Hong Kong
                [6 ]ISNI 0000 0004 1936 8331, GRID grid.410356.5, Department of Biology, , Queen’s University, ; Kingston, ON Canada
                [7 ]ISNI 0000 0001 2157 2938, GRID grid.17063.33, Department of Cell and Systems Biology, , University of Toronto, ; Toronto, ON Canada
                [8 ]ISNI 0000 0004 1937 0482, GRID grid.10784.3a, School of Life Sciences, State Key Laboratory of Agrobiotechnology, , The Chinese University of Hong Kong, ; Shatin, Hong Kong
                [9 ]ISNI 0000 0004 1937 0482, GRID grid.10784.3a, Department of Computer Science and Engineering, , The Chinese University of Hong Kong, ; Shatin, Hong Kong
                [10 ]ISNI 0000 0004 1937 0482, GRID grid.10784.3a, School of Life Sciences, Simon F.S. Li Marine Laboratory, , The Chinese University of Hong Kong, ; Shatin, Hong Kong
                [11 ]ISNI 0000 0004 1937 1450, GRID grid.24515.37, Division of Life Science, , Hong Kong University of Science and Technology, ; Clear Water Bay, Hong Kong
                [12 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Department of Zoology, , University of Oxford, ; Oxford, OX1 3SZ UK
                Author information
                http://orcid.org/0000-0002-3277-716X
                http://orcid.org/0000-0003-4074-9078
                http://orcid.org/0000-0002-1541-9627
                http://orcid.org/0000-0003-3874-4681
                http://orcid.org/0000-0002-5554-0966
                http://orcid.org/0000-0002-0489-3884
                http://orcid.org/0000-0001-5516-9944
                http://orcid.org/0000-0001-8107-5415
                http://orcid.org/0000-0003-1533-9376
                http://orcid.org/0000-0003-1355-8495
                Article
                16801
                10.1038/s41467-020-16801-9
                7305137
                32561724
                d40d99d1-0816-4275-8dfc-348d2b8886ae
                © The Author(s) 2020

                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
                : 21 December 2018
                : 22 May 2020
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                © The Author(s) 2020

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                evolution,evolutionary developmental biology
                Uncategorized
                evolution, evolutionary developmental biology

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