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      Genomic insights into the origin, domestication and genetic basis of agronomic traits of castor bean

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          Abstract

          Background

          Castor bean ( Ricinus communis L.) is an important oil crop, which belongs to the Euphorbiaceae family. The seed oil of castor bean is currently the only commercial source of ricinoleic acid that can be used for producing about 2000 industrial products. However, it remains largely unknown regarding the origin, domestication, and the genetic basis of key traits of castor bean.

          Results

          Here we perform a de novo chromosome-level genome assembly of the wild progenitor of castor bean. By resequencing and analyzing 505 worldwide accessions, we reveal that the accessions from East Africa are the extant wild progenitors of castor bean, and the domestication occurs ~ 3200 years ago. We demonstrate that significant genetic differentiation between wild populations in Kenya and Ethiopia is associated with past climate fluctuation in the Turkana depression ~ 7000 years ago. This dramatic change in climate may have caused the genetic bottleneck in wild castor bean populations. By a genome-wide association study, combined with quantitative trait locus analysis, we identify important candidate genes associated with plant architecture and seed size.

          Conclusions

          This study provides novel insights of domestication and genome evolution of castor bean, which facilitates genomics-based breeding of this important oilseed crop and potentially other tree-like crops in future.

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          Most cited references 106

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          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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            RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

            Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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              Fast and accurate short read alignment with Burrows–Wheeler transform

              Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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                Author and article information

                Contributors
                liuaizhong@mail.kib.ac.cn
                dzl@mail.kib.ac.cn
                Journal
                Genome Biol
                Genome Biol
                Genome Biology
                BioMed Central (London )
                1474-7596
                1474-760X
                20 April 2021
                20 April 2021
                2021
                : 22
                Affiliations
                [1 ]GRID grid.9227.e, ISNI 0000000119573309, Department of Economic Plants and Biotechnology, Yunnan Key Laboratory for Wild Plant Resources, Kunming Institute of Botany, , Chinese Academy of Sciences, ; Kunming, 650201 China
                [2 ]GRID grid.412720.2, ISNI 0000 0004 1761 2943, Key Laboratory for Forest Resource Conservation and Utilization in the Southwest Mountains of China, Ministry of Education, , Southwest Forestry University, ; Kunming, 650224 China
                [3 ]GRID grid.5491.9, ISNI 0000 0004 1936 9297, Biological Sciences and Centre for Underutilised Crops, , University of Southampton, ; Southampton, SO17 1BJ UK
                [4 ]Shanghai OE Biotech Co., Ltd, Shanghai, 201114 China
                [5 ]GRID grid.9227.e, ISNI 0000000119573309, Germplasm Bank of Wild Species, Kunming Institute of Botany, , Chinese Academy of Sciences, ; Kunming, 650201 China
                Article
                2333
                10.1186/s13059-021-02333-y
                8056531
                © The Author(s) 2021

                Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 31661143002, 31771839 and 31970341
                Award Recipient :
                Funded by: the Large-scale Scientific Facilities of the Chinese Academy of Sciences
                Award ID: 2017-LSF-GBOWS-02
                Funded by: FundRef http://dx.doi.org/10.13039/501100004739, Youth Innovation Promotion Association of the Chinese Academy of Sciences;
                Award ID: 2020389
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Genetics

                castor bean, population genetics, domestication, genomic evolution, gwas

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