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      A reference genome for common bean and genome-wide analysis of dual domestications

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      1 , 2 , , 3 , , 3 , 1 , 4 , 2 , 2 , 1 , 5 , 6 , 6 , 7 , 8 , 3 , 6 , 6 , 1 , 9 , 10 , 1 ,   11 , 1 , 6 , 1 ,   5 , 16 , 5 , 12 , 13 , 3 , 7 , 14 , 3 , 5 , 16 , 7 , 15 , 1 , 13 , 1 , 13 , 5 , 1 , 6 ,
      Nature Genetics
      Nature Publishing Group US
      Plant genetics

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          Abstract

          Scott Jackson, Jeremy Schmutz, Phillip McClean and colleagues report the genome sequence of the common bean ( Phaseolus vulgaris) and resequenced wild individuals and landraces from Mesoamerican and Andean gene pools, showing that common bean underwent two independent domestications.

          Supplementary information

          The online version of this article (doi:10.1038/ng.3008) contains supplementary material, which is available to authorized users.

          Abstract

          Common bean ( Phaseolus vulgaris L.) is the most important grain legume for human consumption and has a role in sustainable agriculture owing to its ability to fix atmospheric nitrogen. We assembled 473 Mb of the 587-Mb genome and genetically anchored 98% of this sequence in 11 chromosome-scale pseudomolecules. We compared the genome for the common bean against the soybean genome to find changes in soybean resulting from polyploidy. Using resequencing of 60 wild individuals and 100 landraces from the genetically differentiated Mesoamerican and Andean gene pools, we confirmed 2 independent domestications from genetic pools that diverged before human colonization. Less than 10% of the 74 Mb of sequence putatively involved in domestication was shared by the two domestication events. We identified a set of genes linked with increased leaf and seed size and combined these results with quantitative trait locus data from Mesoamerican cultivars. Genes affected by domestication may be useful for genomics-enabled crop improvement.

          Supplementary information

          The online version of this article (doi:10.1038/ng.3008) contains supplementary material, which is available to authorized users.

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          Most cited references46

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          The Sorghum bicolor genome and the diversification of grasses.

          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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            A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase.

            We present a statistical model for patterns of genetic variation in samples of unrelated individuals from natural populations. This model is based on the idea that, over short regions, haplotypes in a population tend to cluster into groups of similar haplotypes. To capture the fact that, because of recombination, this clustering tends to be local in nature, our model allows cluster memberships to change continuously along the chromosome according to a hidden Markov model. This approach is flexible, allowing for both "block-like" patterns of linkage disequilibrium (LD) and gradual decline in LD with distance. The resulting model is also fast and, as a result, is practicable for large data sets (e.g., thousands of individuals typed at hundreds of thousands of markers). We illustrate the utility of the model by applying it to dense single-nucleotide-polymorphism genotype data for the tasks of imputing missing genotypes and estimating haplotypic phase. For imputing missing genotypes, methods based on this model are as accurate or more accurate than existing methods. For haplotype estimation, the point estimates are slightly less accurate than those from the best existing methods (e.g., for unrelated Centre d'Etude du Polymorphisme Humain individuals from the HapMap project, switch error was 0.055 for our method vs. 0.051 for PHASE) but require a small fraction of the computational cost. In addition, we demonstrate that the model accurately reflects uncertainty in its estimates, in that probabilities computed using the model are approximately well calibrated. The methods described in this article are implemented in a software package, fastPHASE, which is available from the Stephens Lab Web site.
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              Artemis: sequence visualization and annotation

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                Author and article information

                Contributors
                jschmutz@hudsonalpha.org
                phillip.mcclean@ndsu.edu
                sjackson@uga.edu
                Journal
                Nat Genet
                Nat. Genet
                Nature Genetics
                Nature Publishing Group US (New York )
                1061-4036
                1546-1718
                8 June 2014
                8 June 2014
                2014
                : 46
                : 7
                : 707-713
                Affiliations
                [1 ]GRID grid.451309.a, ISNI 0000 0004 0449 479X, US Department of Energy Joint Genome Institute, ; Walnut Creek, California USA
                [2 ]GRID grid.417691.c, ISNI 0000 0004 0408 3720, HudsonAlpha Institute for Biotechnology, ; Huntsville, Alabama USA
                [3 ]GRID grid.261055.5, ISNI 0000 0001 2293 4611, Department of Plant Sciences, , North Dakota State University, ; Fargo, North Dakota USA
                [4 ]GRID grid.463419.d, ISNI 0000 0004 0404 0958, US Department of Agriculture–Agricultural Research Service, , Corn Insects and Crop Genetics Research Unit, ; Ames, Iowa USA
                [5 ]GRID grid.463419.d, ISNI 0000 0004 0404 0958, US Department of Agriculture–Agricultural Research Service, , Soybean Genomics and Improvement Laboratory, ; Beltsville, Maryland USA
                [6 ]GRID grid.213876.9, ISNI 0000 0004 1936 738X, Center for Applied Genetic Technologies, University of Georgia, ; Athens, Georgia USA
                [7 ]GRID grid.5842.b, ISNI 0000 0001 2171 2558, CNRS, Université Paris–Sud, Institut de Biologie des Plantes, UMR 8618, Saclay Plant Sciences (SPS), ; Orsay, France
                [8 ]Institut National de la Recherche Agronomique (INRA), Université Paris–Sud, Unité Mixte de Recherche de Génétique Végétale, Gif-sur-Yvette, France
                [9 ]GRID grid.280741.8, ISNI 0000 0001 2284 9820, Department of Agricultural and Natural Sciences, , Tennessee State University, ; Nashville, Tennessee USA
                [10 ]GRID grid.47894.36, ISNI 0000 0004 1936 8083, Department of Soil and Crop Sciences, , Colorado State University, ; Fort Collins, Colorado USA
                [11 ]GRID grid.27860.3b, ISNI 0000 0004 1936 9684, Department of Plant Sciences, , University of California, Davis, ; Davis, California USA
                [12 ]GRID grid.17088.36, ISNI 0000 0001 2150 1785, Department of Plant, , Soil and Microbial Sciences, Michigan State University, ; East Lansing, Michigan USA
                [13 ]GRID grid.134563.6, ISNI 0000 0001 2168 186X, Arizona Genomics Institute, University of Arizona, ; Tucson, Arizona USA
                [14 ]US Department of Agriculture–Agricultural Research Service, Vegetable and Forage Crop Research Unit, Prosser, Washington USA
                [15 ]Panhandle Research and Extension Center, University of Nebraska, Scottsbluff, Nebraska USA
                [16 ]Present Address: Present addresses: Pioneer Hi-Bred International, Inc., Johnston, Iowa, USA (D.L.H.) and Genética e Melhoramento, Federal University of Viçosa, Viçosa, Brazil (J.R.)., ,
                Author information
                http://orcid.org/0000-0003-2777-8034
                http://orcid.org/0000-0002-1056-4665
                Article
                BFng3008
                10.1038/ng.3008
                7048698
                24908249
                41c5df87-b167-4da8-a3aa-633774fc5023
                © The Author(s) 2014

                This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/.

                History
                : 8 November 2013
                : 15 May 2014
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                Genetics
                plant genetics
                Genetics
                plant genetics

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