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      The first Antechinus reference genome provides a resource for investigating the genetic basis of semelparity and age-related neuropathologies

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          Abstract

          Antechinus are a genus of mouse-like marsupials that exhibit a rare reproductive strategy known as semelparity and also naturally develop age-related neuropathologies similar to those in humans. We provide the first annotated antechinus reference genome for the brown antechinus ( Antechinus stuartii). The reference genome is 3.3 Gb in size with a scaffold N50 of 73Mb and 93.3% complete mammalian BUSCOs. Using bioinformatic methods we assign scaffolds to chromosomes and identify 0.78 Mb of Y-chromosome scaffolds. Comparative genomics revealed interesting expansions in the NMRK2 gene and the protocadherin gamma family, which have previously been associated with aging and age-related dementias respectively. Transcriptome data displayed expression of common Alzheimer’s related genes in the antechinus brain and highlight the potential of utilising the antechinus as a future disease model. The valuable genomic resources provided herein will enable future research to explore the genetic basis of semelparity and age-related processes in the antechinus.

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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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            The Sequence Alignment/Map format and SAMtools

            Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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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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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: ResourcesRole: Data curationRole: Writing - original draft
                Role: Data curationRole: Writing review & editing
                Role: ResourcesRole: Writing review & editing
                Role: Funding acquisitionRole: ConceptualizationRole: ResourcesRole: Writing review & editing
                Role: Funding acquisitionRole: ConceptualizationRole: Writing review & editing
                Journal
                GigaByte
                GigaByte
                Gigabyte
                GigaByte
                GigaScience Press (Sha Tin, New Territories, Hong Kong SAR )
                2709-4715
                05 November 2020
                2020
                : 2020
                : gigabyte7
                Affiliations
                [ 1 ] School of Life and Environmental Sciences, Faculty of Science, University of Sydney , Sydney, New South Wales, Australia
                [ 2 ] Zoologica: Veterinary and Zoological Consulting , Millthorpe, New South Wales, Australia
                Author notes
                [ * ] Corresponding author. E-mail: kathy.belov@ 123456sydney.edu.au
                [ † ]

                Contributed equally.

                Author information
                https://orcid.org/0000-0003-1702-2938
                https://orcid.org/0000-0002-6328-398X
                https://orcid.org/0000-0002-9762-5554
                Article
                7
                10.46471/gigabyte.7
                9631953
                36824596
                0a97b4f4-6827-4ca9-877a-81c5fc48ad70
                © The Author(s) 2020.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 September 2020
                : 04 November 2020
                Funding
                Funded by: Australasian Wildlife Genomics Group;
                This project was supported by the Australasian Wildlife Genomics Group at The University of Sydney.
                Categories
                Data Release
                Genetics and Genomics
                Animal Genetics
                Evolutionary Biology

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