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      The genome sequences of Arachis duranensis and Arachis ipaensis, the diploid ancestors of cultivated peanut.

      1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 6 , 2 , 9 , 7 , 10 , 11 , 12 , 13 , 1 , 11 , 2 , 14 , 15 , 7 , 11 , 4 , 2 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 11 , 12 , 23 , 24 , 25 , 15 ,   26 , 2 , 11 , 6 , 2 , 4 , 5 , 9 , 14
      Nature genetics

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          Abstract

          Cultivated peanut (Arachis hypogaea) is an allotetraploid with closely related subgenomes of a total size of ∼2.7 Gb. This makes the assembly of chromosomal pseudomolecules very challenging. As a foundation to understanding the genome of cultivated peanut, we report the genome sequences of its diploid ancestors (Arachis duranensis and Arachis ipaensis). We show that these genomes are similar to cultivated peanut's A and B subgenomes and use them to identify candidate disease resistance genes, to guide tetraploid transcript assemblies and to detect genetic exchange between cultivated peanut's subgenomes. On the basis of remarkably high DNA identity of the A. ipaensis genome and the B subgenome of cultivated peanut and biogeographic evidence, we conclude that A. ipaensis may be a direct descendant of the same population that contributed the B subgenome to cultivated peanut.

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          Basic Local Alignment Search Tool

          S Altschul (1990)
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            DAGchainer: a tool for mining segmental genome duplications and synteny.

            Given the positions of protein-coding genes along genomic sequence and probability values for protein alignments between genes, DAGchainer identifies chains of gene pairs sharing conserved order between genomic regions, by identifying paths through a directed acyclic graph (DAG). These chains of collinear gene pairs can represent segmentally duplicated regions and genes within a single genome or syntenic regions between related genomes. Automated mining of the Arabidopsis genome for segmental duplications illustrates the use of DAGchainer.
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              Genome-wide genetic changes during modern breeding of maize.

              The success of modern maize breeding has been demonstrated by remarkable increases in productivity over the last four decades. However, the underlying genetic changes correlated with these gains remain largely unknown. We report here the sequencing of 278 temperate maize inbred lines from different stages of breeding history, including deep resequencing of 4 lines with known pedigree information. The results show that modern breeding has introduced highly dynamic genetic changes into the maize genome. Artificial selection has affected thousands of targets, including genes and non-genic regions, leading to a reduction in nucleotide diversity and an increase in the proportion of rare alleles. Genetic changes during breeding happen rapidly, with extensive variation (SNPs, indels and copy-number variants (CNVs)) occurring, even within identity-by-descent regions. Our genome-wide assessment of genetic changes during modern maize breeding provides new strategies as well as practical targets for future crop breeding and biotechnology.
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                Author and article information

                Journal
                Nat. Genet.
                Nature genetics
                1546-1718
                1061-4036
                Apr 2016
                : 48
                : 4
                Affiliations
                [1 ] Institute of Biological Sciences, University of Brasília, Brasília, Brazil.
                [2 ] Center for Applied Genetic Technologies, University of Georgia, Athens, Georgia, USA.
                [3 ] Corn Insects and Crop Genetics Research Unit, US Department of Agriculture-Agricultural Research Service, Ames, Iowa, USA.
                [4 ] Genome Center, University of California, Davis, Davis, California, USA.
                [5 ] Department of Plant Sciences, University of California, Davis, Davis, California, USA.
                [6 ] BGI-Shenzhen, Shenzhen, China.
                [7 ] National Center for Genome Resources, Santa Fe, New Mexico, USA.
                [8 ] Department of Computer Science, Iowa State University, Ames, Iowa, USA.
                [9 ] Institute of Plant Breeding, Genetics and Genomics, University of Georgia, Tifton, Georgia, USA.
                [10 ] Interdepartmental Genetics Graduate Program, Iowa State University, Ames, Iowa, USA.
                [11 ] Embrapa Genetic Resources and Biotechnology, Brasília, Brazil.
                [12 ] Kazusa DNA Research Institute, Department of Frontier Research, Kisarazu, Japan.
                [13 ] Department of Agronomy, Iowa State University, Ames, Iowa, USA.
                [14 ] Department of Horticulture, University of Georgia, Tifton, Georgia, USA.
                [15 ] Department of Genetics, University of Georgia, Athens, Georgia, USA.
                [16 ] Texas A&M AgriLife Research, Lubbock, Texas, USA.
                [17 ] Department of Plant and Soil Science, Texas Tech University, Lubbock, Texas, USA.
                [18 ] International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India.
                [19 ] Shandong Academy of Agricultural Sciences, Biotechnology Research Center, Jinan, China.
                [20 ] Henan Academy of Agricultural Sciences, Zhengzhou, China.
                [21 ] Plant Genetic Resources Conservation Unit, US Department of Agriculture-Agricultural Research Service, Griffin, Georgia, USA.
                [22 ] International Potato Center, Lima, Peru.
                [23 ] Crop Protection and Management Research Unit, US Department of Agriculture-Agricultural Research Service, Tifton, Georgia, USA.
                [24 ] Chinese Academy of Agricultural Sciences, Oil Crops Research Institute, Wuhan, China.
                [25 ] Department of Crop Science, North Carolina State University, Raleigh, North Carolina, USA.
                [26 ] Middle Southern Area Genomics Laboratory, US Department of Agriculture-Agricultural Research Service, Stoneville, Mississippi, USA.
                Article
                ng.3517
                10.1038/ng.3517
                26901068
                62eaad9d-6ffe-4d82-b6a0-593864e310d8
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