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      Whole-genome resequencing reveals Brassica napus origin and genetic loci involved in its improvement

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          Abstract

          Brassica napus (2 n = 4 x = 38, AACC) is an important allopolyploid crop derived from interspecific crosses between Brassica rapa (2 n = 2 x = 20, AA) and Brassica oleracea (2 n = 2 x = 18, CC). However, no truly wild B. napus populations are known; its origin and improvement processes remain unclear. Here, we resequence 588 B. napus accessions. We uncover that the A subgenome may evolve from the ancestor of European turnip and the C subgenome may evolve from the common ancestor of kohlrabi, cauliflower, broccoli, and Chinese kale. Additionally, winter oilseed may be the original form of B. napus. Subgenome-specific selection of defense-response genes has contributed to environmental adaptation after formation of the species, whereas asymmetrical subgenomic selection has led to ecotype change. By integrating genome-wide association studies, selection signals, and transcriptome analyses, we identify genes associated with improved stress tolerance, oil content, seed quality, and ecotype improvement. They are candidates for further functional characterization and genetic improvement of B. napus.

          Abstract

          Brassica napus is a globally important oil crop, but the origin of the allotetraploid genome and its improvement process are largely unknown. Here, the authors take a population genetic approach to resolve its origin and evolutionary history, and identify candidate genes related to important agricultural traits.

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          Most cited references27

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          A uniform decimal code for growth stages of crops and weeds

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            Robust and scalable inference of population history from hundreds of unphased whole genomes

            Yun Song and colleagues present SMC++, a statistical method for population history inference capable of analyzing unphased whole genomes and sample sizes much larger than can be analyzed by current methods. The authors apply SMC++ to sequence data from human, Drosophila and finch populations.
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              Improving power and accuracy of genome-wide association studies via a multi-locus mixed linear model methodology

              Genome-wide association studies (GWAS) have been widely used in genetic dissection of complex traits. However, common methods are all based on a fixed-SNP-effect mixed linear model (MLM) and single marker analysis, such as efficient mixed model analysis (EMMA). These methods require Bonferroni correction for multiple tests, which often is too conservative when the number of markers is extremely large. To address this concern, we proposed a random-SNP-effect MLM (RMLM) and a multi-locus RMLM (MRMLM) for GWAS. The RMLM simply treats the SNP-effect as random, but it allows a modified Bonferroni correction to be used to calculate the threshold p value for significance tests. The MRMLM is a multi-locus model including markers selected from the RMLM method with a less stringent selection criterion. Due to the multi-locus nature, no multiple test correction is needed. Simulation studies show that the MRMLM is more powerful in QTN detection and more accurate in QTN effect estimation than the RMLM, which in turn is more powerful and accurate than the EMMA. To demonstrate the new methods, we analyzed six flowering time related traits in Arabidopsis thaliana and detected more genes than previous reported using the EMMA. Therefore, the MRMLM provides an alternative for multi-locus GWAS.
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                Author and article information

                Contributors
                wangxw@mail.caas.net.cn
                paterson@uga.edu
                ljn1950@swu.edu.cn
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                11 March 2019
                11 March 2019
                2019
                : 10
                : 1154
                Affiliations
                [1 ]GRID grid.263906.8, College of Agronomy and Biotechnology, , Southwest University, Beibei, ; 400715 Chongqing, China
                [2 ]GRID grid.263906.8, Academy of Agricultural Sciences, , Southwest University, Beibei, ; 400715 Chongqing, China
                [3 ]GRID grid.263906.8, State Cultivation Base of Crop Stress Biology for Southern Mountainous Land of Southwest University, Beibei, ; 400715 Chongqing, China
                [4 ]GRID grid.410751.6, Biomarker Technologies Corporation, ; 101300 Beijing, China
                [5 ]ISNI 0000 0001 0526 1937, GRID grid.410727.7, Institute of Vegetables and Flowers, , Chinese Academy of Agricultural Science, ; 100081 Beijing, China
                [6 ]ISNI 0000 0004 1936 738X, GRID grid.213876.9, Plant Genome Mapping Laboratory, , University of Georgia, ; Athens, Georgia 30605 USA
                Author information
                http://orcid.org/0000-0003-1370-8633
                http://orcid.org/0000-0003-2982-9675
                http://orcid.org/0000-0001-8633-6290
                http://orcid.org/0000-0002-9426-3615
                Article
                9134
                10.1038/s41467-019-09134-9
                6411957
                30858362
                67cd6135-1459-48a9-a23f-614fdbe26790
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 1 May 2018
                : 22 February 2019
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