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      Insights into angiosperm evolution, floral development and chemical biosynthesis from the Aristolochia fimbriata genome

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          Abstract

          Aristolochia, a genus in the magnoliid order Piperales, has been famous for centuries for its highly specialized flowers and wide medicinal applications. Here, we present a new, high-quality genome sequence of Aristolochia fimbriata, a species that, similar to Amborella trichopoda, lacks further whole-genome duplications since the origin of extant angiosperms. As such, the A. fimbriata genome is an excellent reference for inferences of angiosperm genome evolution, enabling detection of two novel whole-genome duplications in Piperales and dating of previously reported whole-genome duplications in other magnoliids. Genomic comparisons between A. fimbriata and other angiosperms facilitated the identification of ancient genomic rearrangements suggesting the placement of magnoliids as sister to monocots, whereas phylogenetic inferences based on sequence data we compiled yielded ambiguous relationships. By identifying associated homologues and investigating their evolutionary histories and expression patterns, we revealed highly conserved floral developmental genes and their distinct downstream regulatory network that may contribute to the complex flower morphology in A. fimbriata. Finally, we elucidated the genetic basis underlying the biosynthesis of terpenoids and aristolochic acids in A. fimbriata.

          Abstract

          A high-quality genome of Aristolochia fimbriata illuminates its unique history of whole-genome duplication similar to Amborella, the genomic basis of its complex flower morphology and chemical biosynthesis, and the phylogenetic placement of magnoliids.

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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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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              MUSCLE: multiple sequence alignment with high accuracy and high throughput.

              We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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                Author and article information

                Contributors
                jiaoyn@ibcas.ac.cn
                Journal
                Nat Plants
                Nat Plants
                Nature Plants
                Nature Publishing Group UK (London )
                2055-0278
                2 September 2021
                2 September 2021
                2021
                : 7
                : 9
                : 1239-1253
                Affiliations
                [1 ]GRID grid.9227.e, ISNI 0000000119573309, State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, , the Chinese Academy of Sciences, ; Beijing, China
                [2 ]GRID grid.410726.6, ISNI 0000 0004 1797 8419, University of Chinese Academy of Sciences, ; Beijing, China
                [3 ]GRID grid.440734.0, ISNI 0000 0001 0707 0296, School of Life Sciences and Center for Genomics and Computational Biology, , North China University of Science and Technology, ; Tangshan, China
                [4 ]GRID grid.4488.0, ISNI 0000 0001 2111 7257, Institute of Botany, , Dresden University of Technology, ; Dresden, Germany
                [5 ]GRID grid.213876.9, ISNI 0000 0004 1936 738X, Department of Plant Biology, , University of Georgia, ; Athens, GA USA
                [6 ]GRID grid.213876.9, ISNI 0000 0004 1936 738X, Plant Genome Mapping Laboratory, , University of Georgia, ; Athens, GA USA
                [7 ]GRID grid.29857.31, ISNI 0000 0001 2097 4281, Department of Biology and Huck Institutes of the Life Sciences, , The Pennsylvania State University, ; University Park, PA USA
                [8 ]GRID grid.15276.37, ISNI 0000 0004 1936 8091, Florida Museum of Natural History, , University of Florida, ; Gainesville, FL USA
                [9 ]GRID grid.15276.37, ISNI 0000 0004 1936 8091, Department of Biology, , University of Florida, ; Gainesville, FL USA
                Author information
                http://orcid.org/0000-0003-3471-3511
                http://orcid.org/0000-0001-5405-5216
                http://orcid.org/0000-0001-8465-1342
                http://orcid.org/0000-0001-9310-8659
                http://orcid.org/0000-0001-8638-4137
                http://orcid.org/0000-0002-0034-0510
                http://orcid.org/0000-0002-8987-2782
                Article
                990
                10.1038/s41477-021-00990-2
                8445822
                34475528
                451923f3-627d-4519-9268-67eab40a5864
                © The Author(s) 2021

                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
                : 24 December 2020
                : 22 July 2021
                Funding
                Funded by: Strategic Priority Research Program of the Chinese Academy of Sciences (XDA23080000) K.C.Wong Education Foundation (GJTD-2020-05)
                Funded by: K.C.Wong Education Foundation (GJTD-2020-05)
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                © The Author(s), under exclusive licence to Springer Nature Limited 2021

                genome evolution,plant evolution,genome duplication,secondary metabolism

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