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      MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity

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          Abstract

          MCScan is an algorithm able to scan multiple genomes or subgenomes in order to identify putative homologous chromosomal regions, and align these regions using genes as anchors. The MCScanX toolkit implements an adjusted MCScan algorithm for detection of synteny and collinearity that extends the original software by incorporating 14 utility programs for visualization of results and additional downstream analyses. Applications of MCScanX to several sequenced plant genomes and gene families are shown as examples. MCScanX can be used to effectively analyze chromosome structural changes, and reveal the history of gene family expansions that might contribute to the adaptation of lineages and taxa. An integrated view of various modes of gene duplication can supplement the traditional gene tree analysis in specific families. The source code and documentation of MCScanX are freely available at http://chibba.pgml.uga.edu/mcscan2/.

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          New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

          Stéphane Guindon, Jean-François Dufayard, Vincent Lefort … (2010)
          PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.
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            The grapevine genome sequence suggests ancestral hexaploidization in major angiosperm phyla.

            Alberto Casagrande (2007)
            The analysis of the first plant genomes provided unexpected evidence for genome duplication events in species that had previously been considered as true diploids on the basis of their genetics. These polyploidization events may have had important consequences in plant evolution, in particular for species radiation and adaptation and for the modulation of functional capacities. Here we report a high-quality draft of the genome sequence of grapevine (Vitis vinifera) obtained from a highly homozygous genotype. The draft sequence of the grapevine genome is the fourth one produced so far for flowering plants, the second for a woody species and the first for a fruit crop (cultivated for both fruit and beverage). Grapevine was selected because of its important place in the cultural heritage of humanity beginning during the Neolithic period. Several large expansions of gene families with roles in aromatic features are observed. The grapevine genome has not undergone recent genome duplication, thus enabling the discovery of ancestral traits and features of the genetic organization of flowering plants. This analysis reveals the contribution of three ancestral genomes to the grapevine haploid content. This ancestral arrangement is common to many dicotyledonous plants but is absent from the genome of rice, which is a monocotyledon. Furthermore, we explain the chronology of previously described whole-genome duplication events in the evolution of flowering plants.
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              The Sorghum bicolor genome and the diversification of grasses.

              Andrew Paterson, John Bowers, Rémy Bruggmann … (2009)
              Sorghum, an African grass related to sugar cane and maize, is grown for food, feed, fibre and fuel. We present an initial analysis of the approximately 730-megabase Sorghum bicolor (L.) Moench genome, placing approximately 98% of genes in their chromosomal context using whole-genome shotgun sequence validated by genetic, physical and syntenic information. Genetic recombination is largely confined to about one-third of the sorghum genome with gene order and density similar to those of rice. Retrotransposon accumulation in recombinationally recalcitrant heterochromatin explains the approximately 75% larger genome size of sorghum compared with rice. Although gene and repetitive DNA distributions have been preserved since palaeopolyploidization approximately 70 million years ago, most duplicated gene sets lost one member before the sorghum-rice divergence. Concerted evolution makes one duplicated chromosomal segment appear to be only a few million years old. About 24% of genes are grass-specific and 7% are sorghum-specific. Recent gene and microRNA duplications may contribute to sorghum's drought tolerance.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (iso-abbrev): Nucleic Acids Res
                Journal ID (publisher-id): nar
                Journal ID (hwp): nar
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date Collection: April 2012
                Publication date (Print): April 2012
                Publication date (Electronic): 4 January 2012
                Publication date PMC-release: 4 January 2012
                Volume: 40
                Issue: 7
                Page: e49
                Affiliations
                1Plant Genome Mapping Laboratory, 2Institute of Bioinformatics, 3Department of Plant Biology, University of Georgia, Athens, GA 30602, 4J. Craig Venter Institute, 9704 Medical Center Drive, Rockville, MD 20850, 5Center for Tropical and Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, 6Center for Genomics and Computational Biology, School of Life Sciences and School of Sciences, Hebei United University, Tangshan, Hebei 063009, China, 7Department of Genetics and 8Department of Crop and Soil Sciences, University of Georgia, Athens, GA 30602, USA
                Author notes
                *To whom correspondence should be addressed. Tel: +1 706 583 0162; Fax: +1 706 583 0160; Email: paterson@ 123456plantbio.uga.edu

                The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Author.

                Article
                Publisher ID: gkr1293
                DOI: 10.1093/nar/gkr1293
                PMC ID: 3326336
                PubMed ID: 22217600
                SO-VID: 0d026cf9-229f-41b7-be32-f3c5c001e094
                Copyright © © The Author(s) 2012. Published by Oxford University Press.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 22 September 2011
                Date revision received : 11 December 2011
                Date accepted : 15 December 2011
                Page count
                Pages: 14
                Categories
                Subject: Methods Online

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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