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      Extensive chromosomal reshuffling drives evolution of virulence in an asexual pathogen

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          Abstract

          Sexual recombination drives genetic diversity in eukaryotic genomes and fosters adaptation to novel environmental challenges. Although strictly asexual microorganisms are often considered as evolutionary dead ends, they comprise many devastating plant pathogens. Presently, it remains unknown how such asexual pathogens generate the genetic variation that is required for quick adaptation and evolution in the arms race with their hosts. Here, we show that extensive chromosomal rearrangements in the strictly asexual plant pathogenic fungus Verticillium dahliae establish highly dynamic lineage-specific (LS) genomic regions that act as a source for genetic variation to mediate aggressiveness. We show that such LS regions are greatly enriched for in planta-expressed effector genes encoding secreted proteins that enable host colonization. The LS regions occur at the flanks of chromosomal breakpoints and are enriched for retrotransposons and other repetitive sequence elements. Our results suggest that asexual pathogens may evolve by prompting chromosomal rearrangements, enabling rapid development of novel effector genes. Likely, chromosomal reshuffling can act as a general mechanism for adaptation in asexually propagating organisms.

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          BEDTools: a flexible suite of utilities for comparing genomic features

          Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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            The variant call format and VCFtools

            Summary: The variant call format (VCF) is a generic format for storing DNA polymorphism data such as SNPs, insertions, deletions and structural variants, together with rich annotations. VCF is usually stored in a compressed manner and can be indexed for fast data retrieval of variants from a range of positions on the reference genome. The format was developed for the 1000 Genomes Project, and has also been adopted by other projects such as UK10K, dbSNP and the NHLBI Exome Project. VCFtools is a software suite that implements various utilities for processing VCF files, including validation, merging, comparing and also provides a general Perl API. Availability: http://vcftools.sourceforge.net Contact: rd@sanger.ac.uk
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              Transcript assembly and abundance estimation from RNA-Seq reveals thousands of new transcripts and switching among isoforms

              High-throughput mRNA sequencing (RNA-Seq) holds the promise of simultaneous transcript discovery and abundance estimation 1-3 . We introduce an algorithm for transcript assembly coupled with a statistical model for RNA-Seq experiments that produces estimates of abundances. Our algorithms are implemented in an open source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed more than 430 million paired 75bp RNA-Seq reads from a mouse myoblast cell line representing a differentiation time series. We detected 13,692 known transcripts and 3,724 previously unannotated ones, 62% of which are supported by independent expression data or by homologous genes in other species. Analysis of transcript expression over the time series revealed complete switches in the dominant transcription start site (TSS) or splice-isoform in 330 genes, along with more subtle shifts in a further 1,304 genes. These dynamics suggest substantial regulatory flexibility and complexity in this well-studied model of muscle development.
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                Author and article information

                Journal
                Genome Res
                Genome Res
                GENOME
                Genome Research
                Cold Spring Harbor Laboratory Press
                1088-9051
                1549-5469
                August 2013
                August 2013
                : 23
                : 8
                : 1271-1282
                Affiliations
                [1 ]Laboratory of Phytopathology, Wageningen University, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands;
                [2 ]United States Department of Agriculture, Agricultural Research Service, Northern Crop Science Laboratory, Fargo, North Dakota 58102-2765, USA;
                [3 ]Centre for BioSystems Genomics, 6700 AB Wageningen, The Netherlands
                Author notes
                [4]

                These authors contributed equally to this work.

                Present addresses: 5Department of Plant Pathology, University of California, Davis, CA 95616, USA;

                [6]

                VIB Department of Plant Systems Biology, Ghent University, Bioinformatics and Evolutionary Genomics Division, Technologiepark 927, B-9052 Ghent, Belgium.

                [7 ]Corresponding author E-mail bart.thomma@ 123456wur.nl
                Article
                9518021
                10.1101/gr.152660.112
                3730101
                23685541
                e3e6644e-e74b-4dd4-859c-027a3bda35cb
                © 2013, Published by Cold Spring Harbor Laboratory Press

                This article, published in Genome Research, is available under a Creative Commons License (Attribution-NonCommercial 3.0 Unported), as described at http://creativecommons.org/licenses/by-nc/3.0/.

                History
                : 26 November 2012
                : 14 May 2013
                Page count
                Pages: 12
                Categories
                Research

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