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1er février 2018

Russulaceae : a new genomic dataset to study ecosystem function and evolutionary diversification of ectomycorrhizal fungi with their tree associates [New Phytologist]

Keywords : decomposition, functional diversity, fungal niche, secondary metabolism, symbiosis

The family Russulaceae is considered an iconic lineage of mostly mushroom-forming basidiomycetes due to their importance as edible mushrooms in many parts of the world, and their ubiquity as ectomycorrhizal symbionts in both temperate and tropical forested biomes. Although much research has been focused on this group, a comprehensive or cohesive synthesis by which to understand the functional diversity of the group has yet to develop. Interest in ectomycorrhizal fungi, of which Russulaceae is a key lineage, is prodigious due to the important roles they play as plant root mutualists in ecosystem functioning, global carbon sequestration, and a potential role in technology development toward environmental sustainability.(...)

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31 janvier 2018

A genome for gnetophytes and early evolution of seed plants [Nature Plants]

Keywords : plant evolution, plant genetics

Gnetophytes are an enigmatic gymnosperm lineage comprising three genera, Gnetum, Welwitschia and Ephedra, which are morphologically distinct from all other seed plants. Their distinctiveness has triggered much debate as to their origin, evolution and phylogenetic placement among seed plants. To increase our understanding of the evolution of gnetophytes, and their relation to other seed plants, we report here a high-quality draft genome sequence for Gnetum montanum, the first for any gnetophyte. By using a novel genome assembly strategy to deal with high levels of heterozygosity, we assembled >4 Gb of sequence encoding 27,491 protein-coding genes.(...)

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31 janvier 2018

Building adaptive capacity to climate change in tropical coastal communities [Nature Climate Change]

Keywords : developing world, interdisciplinary studies, social sciences

To minimize the impacts of climate change on human wellbeing, governments, development agencies, and civil society organizations have made substantial investments in improving people’s capacity to adapt to change. Yet to date, these investments have tended to focus on a very narrow understanding of adaptive capacity. Here, we propose an approach to build adaptive capacity across five domains : the assets that people can draw upon in times of need ; the flexibility to change strategies ; the ability to organize and act collectively ; learning to recognize and respond to change ; and the agency to determine whether to change or not.

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31 janvier 2018

Cloud computing for genomic data analysis and collaboration [Nature Reviews Genetics]

Keywords : computational biology and bioinformatics, genetic databases, genomics, next-generation sequencing, research data

Next-generation sequencing has made major strides in the past decade. Studies based on large sequencing data sets are growing in number, and public archives for raw sequencing data have been doubling in size every 18 months. Leveraging these data requires researchers to use large-scale computational resources. Cloud computing, a model whereby users rent computers and storage from large data centres, is a solution that is gaining traction in genomics research. Here, we describe how cloud computing is used in genomics for research and large-scale collaborations, and argue that its elasticity, reproducibility and privacy features make it ideally suited for the large-scale reanalysis of publicly available archived data, including privacy-protected data.

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31 janvier 2018

The state of software for evolutionary biology [Molecular Biology and Evolution]

Keywords : software engineering quality, scientific computing, data analysis, numerical analysis, policy issues, evolutionary inference software

With Next Generation Sequencing data being routinely used, evolutionary biology is transforming into a computational science. Thus, researchers have to rely on a growing number of increasingly complex software. All widely used core tools in the field have grown considerably, in terms of the number of features as well as lines of code and consequently, also with respect to software complexity. A topic that has received little attention is the software engineering quality of widely used core analysis tools. Software developers appear to rarely assess the quality of their code, and this can have potential negative consequences for end-users. To this end, we assessed the code quality of 16 highly cited and compute-intensive tools mainly written in C/C ++ (e.g., MrBayes, MAFFT, SweepFinder etc.) and JAVA (BEAST) from the broader area of evolutionary biology that are being routinely used in current data analysis pipelines.(...)

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