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      The gene-rich genome of the scallop Pecten maximus

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          Abstract

          Background

          The king scallop, Pecten maximus, is distributed in shallow waters along the Atlantic coast of Europe. It forms the basis of a valuable commercial fishery and plays a key role in coastal ecosystems and food webs. Like other filter feeding bivalves it can accumulate potent phytotoxins, to which it has evolved some immunity. The molecular origins of this immunity are of interest to evolutionary biologists, pharmaceutical companies, and fisheries management.

          Findings

          Here we report the genome assembly of this species, conducted as part of the Wellcome Sanger 25 Genomes Project. This genome was assembled from PacBio reads and scaffolded with 10X Chromium and Hi-C data. Its 3,983 scaffolds have an N50 of 44.8 Mb (longest scaffold 60.1 Mb), with 92% of the assembly sequence contained in 19 scaffolds, corresponding to the 19 chromosomes found in this species. The total assembly spans 918.3 Mb and is the best-scaffolded marine bivalve genome published to date, exhibiting 95.5% recovery of the metazoan BUSCO set. Gene annotation resulted in 67,741 gene models. Analysis of gene content revealed large numbers of gene duplicates, as previously seen in bivalves, with little gene loss, in comparison with the sequenced genomes of other marine bivalve species.

          Conclusions

          The genome assembly of P. maximus and its annotated gene set provide a high-quality platform for studies on such disparate topics as shell biomineralization, pigmentation, vision, and resistance to algal toxins. As a result of our findings we highlight the sodium channel gene Nav1, known to confer resistance to saxitoxin and tetrodotoxin, as a candidate for further studies investigating immunity to domoic acid.

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          Most cited references69

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          Fast and accurate long-read assembly with wtdbg2

          Existing long-read assemblers require thousands of CPU hours to assemble a human genome and are being outpaced by sequencing technologies in terms of both throughput and cost. We developed a long-read assembler wtdbg2 (https://github.com/ruanjue/wtdbg2) that is 2–17 times as fast as published tools while achieving comparable contiguity and accuracy. It paves the way for population-scale long-read assembly in future.
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            The Network of Cancer Genes (NCG): a comprehensive catalogue of known and candidate cancer genes from cancer sequencing screens

            The Network of Cancer Genes (NCG) is a manually curated repository of 2372 genes whose somatic modifications have known or predicted cancer driver roles. These genes were collected from 275 publications, including two sources of known cancer genes and 273 cancer sequencing screens of more than 100 cancer types from 34,905 cancer donors and multiple primary sites. This represents a more than 1.5-fold content increase compared to the previous version. NCG also annotates properties of cancer genes, such as duplicability, evolutionary origin, RNA and protein expression, miRNA and protein interactions, and protein function and essentiality. NCG is accessible at http://ncg.kcl.ac.uk/. Electronic supplementary material The online version of this article (10.1186/s13059-018-1612-0) contains supplementary material, which is available to authorized users.
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              GenomeScope 2.0 and Smudgeplot for reference-free profiling of polyploid genomes

              An important assessment prior to genome assembly and related analyses is genome profiling, where the k-mer frequencies within raw sequencing reads are analyzed to estimate major genome characteristics such as size, heterozygosity, and repetitiveness. Here we introduce GenomeScope 2.0 (https://github.com/tbenavi1/genomescope2.0), which applies combinatorial theory to establish a detailed mathematical model of how k-mer frequencies are distributed in heterozygous and polyploid genomes. We describe and evaluate a practical implementation of the polyploid-aware mixture model that quickly and accurately infers genome properties across thousands of simulated and several real datasets spanning a broad range of complexity. We also present a method called Smudgeplot (https://github.com/KamilSJaron/smudgeplot) to visualize and estimate the ploidy and genome structure of a genome by analyzing heterozygous k-mer pairs. We successfully apply the approach to systems of known variable ploidy levels in the Meloidogyne genus and the extreme case of octoploid Fragaria  ×  ananassa.
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                Author and article information

                Journal
                Gigascience
                Gigascience
                gigascience
                GigaScience
                Oxford University Press
                2047-217X
                30 April 2020
                May 2020
                30 April 2020
                : 9
                : 5
                : giaa037
                Affiliations
                [1 ] Natural History Museum, Department of Life Sciences, Cromwell Road, London SW7 5BD, UK
                [3 ] University of Cambridge, Department of Genetics, Cambridge CB2 3EH, UK
                [4 ] The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine , Houston, TX 77030, USA
                [5 ] The Center for Theoretical Biological Physics, Rice University , 6100 Main St, Houston, TX 77005-1827, USA
                [7 ] Wellcome Sanger Institute , Cambridge CB10 1SA, UK
                [9 ] School of Computing, Newcastle University , Newcastle upon Tyne NE1 7RU, UK
                [10 ] Institute of Infection and Global Health, Liverpool University , iC2, 146 Brownlow Hill, Liverpool L3 5RF, UK
                [11 ] Shanghai Institute for Advanced Immunochemical Studies, Shanghai Tech University , Shanghai, China
                [12 ] School of Agriculture and Environment, University of Western Australia , Perth, Australia
                Author notes
                Correspondence address. Suzanne T. Williams, Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD, UK. E-mail: s.williams@ 123456nhm.ac.uk

                Present address: Oxford Brookes University, Headington Road, Oxford OX3 0BP, UK

                Present address: Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK

                Present address: Freeline Therapeutics Limited, Stevenage Bioscience Catalyst, Gunnels Wood Road, Stevenage, Hertfordshire, SG1 2FX, UK

                Author information
                http://orcid.org/0000-0003-2995-5823
                Article
                giaa037
                10.1093/gigascience/giaa037
                7191990
                32352532
                edd72002-732d-4ce7-9a36-1e957b5bc7ff
                © The Author(s) 2020. Published by Oxford University Press.

                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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 18 January 2020
                : 26 February 2020
                : 24 March 2020
                Page count
                Pages: 13
                Funding
                Funded by: Horizon 2020, DOI 10.13039/100010661;
                Funded by: National Science Foundation, DOI 10.13039/100000001;
                Award ID: PHY1427654
                Funded by: Welch Foundation, DOI 10.13039/100000928;
                Award ID: Q-1866
                Funded by: National Institutes of Health, DOI 10.13039/100000002;
                Award ID: U01HL130010
                Categories
                Data Note
                AcademicSubjects/SCI00960
                AcademicSubjects/SCI02254

                scallop,bivalve,mollusc,genome,domoic,neurotoxin
                scallop, bivalve, mollusc, genome, domoic, neurotoxin

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