0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Genomic insights into the evolutionary history and diversification of bulb traits in garlic

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Garlic is an entirely sterile crop with important value as a vegetable, condiment, and medicine. However, the evolutionary history of garlic remains largely unknown.

          Results

          Here we report a comprehensive map of garlic genomic variation, consisting of amazingly 129.4 million variations. Evolutionary analysis indicates that the garlic population diverged at least 100,000 years ago, and the two groups cultivated in China were domesticated from two independent routes. Consequently, 15.0 and 17.5% of genes underwent an expression change in two cultivated groups, causing a reshaping of their transcriptomic architecture. Furthermore, we find independent domestication leads to few overlaps of deleterious substitutions in these two groups due to separate accumulation and selection-based removal. By analysis of selective sweeps, genome-wide trait associations and associated transcriptomic analysis, we uncover differential selections for the bulb traits in these two garlic groups during their domestication.

          Conclusions

          This study provides valuable resources for garlic genomics-based breeding, and comprehensive insights into the evolutionary history of this clonal-propagated crop.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13059-022-02756-1.

          Related collections

          Most cited references61

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            The Sequence Alignment/Map format and SAMtools

            Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              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
                Bookmark

                Author and article information

                Contributors
                jgsu@vip.163.com
                chengzh@nwafu.edu.cn
                tianshilin@novogene.com
                liutouming@caas.cn
                Journal
                Genome Biol
                Genome Biol
                Genome Biology
                BioMed Central (London )
                1474-7596
                1474-760X
                7 September 2022
                7 September 2022
                2022
                : 23
                : 188
                Affiliations
                [1 ]GRID grid.464342.3, ISNI 0000 0004 1764 0485, Institute of Bast Fiber Crops, Chinese Academy of Agricultural Sciences, ; Changsha, 410205 China
                [2 ]GRID grid.440622.6, ISNI 0000 0000 9482 4676, Shandong Agricultural University, ; Tai’an, 271018 China
                [3 ]GRID grid.410753.4, Novogene Bioinformatics Institute, ; Beijing, 100083 China
                [4 ]GRID grid.268415.c, Yangzhou University, ; Yangzhou, 225009 China
                [5 ]Industrial Research Institute of garlic (IBFC-Jinxiang), Jinxiang, 272200 China
                [6 ]GRID grid.448798.e, ISNI 0000 0004 1765 3577, Changsha University, ; Changsha, 410003 China
                [7 ]Shandong Dongyun Research Center of garlic Engineering, JinXiang, 272200 China
                [8 ]GRID grid.144022.1, ISNI 0000 0004 1760 4150, Northwest A&F University, ; Yangling, 712100 China
                [9 ]GRID grid.410445.0, ISNI 0000 0001 2188 0957, University of Hawaii at Manoa, ; Honolulu, 96822 USA
                Author information
                http://orcid.org/0000-0003-0599-7527
                Article
                2756
                10.1186/s13059-022-02756-1
                9450234
                36071507
                00bec34a-c065-43bd-8d5d-55bff198d3b7
                © The Author(s) 2022

                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.

                History
                : 4 March 2022
                : 22 August 2022
                Funding
                Funded by: Shandong Provincial Key Research and Development Program (Major Science and Technology Innovation Project) - Boost Plan for Rural Vitalization Science and Technology Innovation
                Award ID: 2021TZXD001
                Funded by: National Agricultural Science and Technology Innovation Program of China
                Award ID: CAAS-ASTIP-IBFC
                Award Recipient :
                Funded by: Central Public-interest Scientific Institution Basal Research Fund
                Award ID: 1610242021002
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 31972000, 31772323
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Genetics
                Genetics

                Comments

                Comment on this article