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  • A nuclear phylogenomic study of the angiosperm order Myrtales, exploring the potential and limitations of the universal Angiosperms353 probe set

    Maurin, Olivier; Anest, Artemis; Bellot, Sidonie; Biffin, Edward; Brewer, Grace E.; Charles-Dominique, Tristan; Cowan, Robyn S.; Dodsworth, Steven; Epitawalage, Niroshini; Gallego, Berta; et al. (Wiley, 2021-07-31)
    To further advance the understanding of the species-rich, economically and ecologically important angiosperm order Myrtales in the rosid clade, comprising nine families, approximately 400 genera and almost 14,000 species occurring on all continents (except Antarctica), we tested the Angiosperms353 probe kit. We combined high-throughput sequencing and target enrichment with the Angiosperms353 probe kit to evaluate a sample of 485 species across 305 genera (76% of all genera in the order). Results provide the most comprehensive phylogenetic hypothesis for the order to date. Relationships at all ranks, such as the relationship of the early-diverging families, often reflect previous studies, but gene conflict is evident, and relationships previously found to be uncertain often remain so. Technical considerations for processing HTS data are also discussed. High-throughput sequencing and the Angiosperms353 probe kit are powerful tools for phylogenomic analysis, but better understanding of the genetic data available is required to identify genes and gene trees that account for likely incomplete lineage sorting and/or hybridization events.
  • Exploring Angiosperms353: an open, community toolkit for collaborative phylogenomic research on flowering plants

    Baker, William J.; Dodsworth, Steven; Forest, Felix; Graham, Sean W.; Johnson, Matthew G.; McDonnell, Angela J.; Pokorny, Lisa; Tate, Jennifer; Wicke, Susann; Wickett, Norman J.; et al. (Wiley, 2021-07-22)
    The unveiling of the angiosperm (flowering plant) tree of life over the past three decades has been one of the great success stories of modern plant biology. Flowering plants underpin most terrestrial biomes: they fix vast amounts of terrestrial carbon, in turn producing a substantial fraction of planetary oxygen, and drive major biogeochemical cycles. The bulk of human calories are derived either directly (crops) or indirectly (fodder) from angiosperms, as are many medicines, fuel, dyes, beverages, timber, fibers, and other materials. Countless indispensable and mundane items that impact human existence find their origins in flowering plants, and without them, life would be decidedly drearier—imagine a world without herbs, spices, or garden flowers, for example. In this context, the importance of a comprehensive understanding of the angiosperm tree of life cannot be overstated. The tree of life is the fundamental, biological roadmap to the evolution and properties of plants (e.g., Wong et al., 2020). For evolutionary biologists, phylogenies allow us to better understand the spectacular rise of the flowering plants to dominance over the past 140 million or so years (e.g., Lutzoni et al., 2018; Ramírez-Barahona et al., 2020). Information about angiosperm phylogenetic relationships also underpins modern angiosperm classification (e.g., APG IV, 2016), and helps us to better understand species origins and boundaries (e.g., Fazekas et al., 2009). Today, tree of life research is undergoing a renaissance due to the development of powerful, new phylogenomic methods (Dodsworth et al., 2019). In this special issue of the American Journal of Botany, together with a companion issue of Applications in Plant Sciences, we gather a set of papers that focus on a new, common phylogenomic toolkit, the Angiosperms353 probe set (Johnson et al., 2019), and illustrate its potential for evolutionary synthesis by promoting open collaboration across our community.
  • Exploring Angiosperms353: developing and applying a universal toolkit for flowering plant phylogenomics

    McDonnell, Angela J.; Baker, William J.; Dodsworth, Steven; Forest, Felix; Graham, Sean W.; Johnson, Matthew G.; Pokorny, Lisa; Tate, Jennifer; Wickett, Norman J.; Wicke, Susann; et al. (Wiley, 2021-07-26)
    Special Issue Introduction. Target enrichment represents a useful, cost-effective method for researchers working on the phylogenomics of non-model organisms (e.g., Cronn et al., 2012; Hale et al., 2020). The ability to sequence a customizable predefined genomic subset for several dozens or even hundreds of taxa allows in-depth analyses and the testing of phylogenetic hypotheses in ways that were not previously possible (reviewed in McKain et al., 2018). The most popular methods for targeted sequencing of genomic loci in phylogenomics include (long-)amplicon sequencing (Rothfels et al., 2017) and hybridization capture (Mandel et al., 2014; Weitemier et al., 2014). Targeted amplicon sequencing is based on single-fragment PCR amplification or by using multiplexing methods such as a microfluidic PCR-based amplification of multiple pre-selected genomic regions (e.g., Zhang and Ozdemir, 2009; Ho et al., 2014), which can then be pooled and sequenced. Massively parallel amplicon sequencing was first used in medical diagnostics (Turner et al., 2009) and was later applied to metazoan phylogenetics (Bybee et al., 2011; O’Neill et al., 2013). Microfluidic PCR and long-amplicon sequencing were subsequently applied in plant systematics (Uribe-Convers et al., 2014, 2016; Gostel et al., 2015). Amplicon-based methods can be time consuming as they require careful optimization and validation of primers. These methods are also susceptible to many of the common problems in PCR (such as nonspecific products, inability to amplify large loci in their entirety, or simply no products). Recently, amplicon approaches have been largely supplanted by hybridization-based targeted enrichment, which allows for relatively rapid probe design with reference to a few related transcriptomes or genomes, and allows simultaneous and efficient recovery of many hundreds of genes.
  • Safety knowledge sharing on Twitter: a social network analysis

    Yao, Qi; Li, Rita Yi Man; Song, Lingxi; Crabbe, M. James C.; Chongqing Technology and Business University; Hong Kong Shue Yan University; Rajamangala University of Technology Tawan-Ok; Oxford University; University of Bedfordshire (Elsevier, 2021-07-28)
    Many studies show that unsafe behavior is the main cause of construction accidents. Safety education and training are effective means to minimise people’s unsafe behaviors. Apart from traditional face-to-face construction knowledge sharing, social media is a good tool because it is convenient, efficient, and widely used. We applied both social network analysis and sentiment analysis to investigate knowledge sharing on Twitter. Our study is a novel attempt to understand social structure of “construction safety”- related twitter networks and the opinion leaders. We selected and analyzed 6561 tweets of three users’ networks on Twitter – “construction safety”, “construction health” and “construction accident”. We found that three networks had low density and many isolated vertices, which showed that users did not actively interact with each other. The opinion leaders in this study were mostly organizations or government agencies. The top one is “cif_ireland”, the Irish construction industry’s representative body, the Construction Industry Federation. 3200 Tweets of the top opinion leader were analyzed through graph metrics calculation, cluster analysis, sentiment analysis, and correlation analysis. The opinion leader used Twitter as a medium to disseminate the latest safety news. Thus, we may use Twitter to stimulate people’s interest on construction safety topics, share construction safety knowledge, opinions and ideas. Besides, our results showed that sentiment valence had no correlation with number of favorites or retweets. Nevertheless, there was a positive correlation between favorites and retweets.
  • Management of environmental streaming data to optimize Arctic shipping routes.

    Zhang, Zhihua; Crabbe, M. James C.; University of Bedfordshire; Shandong University (Springer Nature, 2021-07-20)
    Dynamic accurate predictions of Arctic sea ice, ocean, atmosphere, and ecosystem are necessary for safe and efficient Arctic maritime transportation; however a related technical roadmap has not yet been established. In this paper, we propose a management system for trans-Arctic maritime transportation supported by near real-time streaming data from air-space-ground-sea integrated monitoring networks and high spatio-temporal sea ice modeling. As the core algorithm of integrated monitoring networks, a long short-term memory (LSTM) neural network is embedded to improve Arctic sea ice mapping algorithms.Since the LSTM is localized in time and space, it can make full use of streaming data characteristics. The sea ice–related parameters from satellite remote sensing raw data are used as the input of the LSTM, while streaming data from shipborne radar networks and/or buoy measurements are used as training datasets to enhance the accuracy and resolution of environmental streaming data from outputs of LSTM. Due to large size of streaming data, the proposed management system of trans-Arctic shipping should be built on a cloud distribution platform using existing wireless communications networks among vessels and ports. Our management system will be used by the ongoing European Commission Horizon 2020 Programme “ePIcenter.”

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