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      Phylogenomics reveals multiple losses of nitrogen-fixing root nodule symbiosis

      Author(s): , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
      Publication date (Electronic):
      Journal: Science
      Publisher: American Association for the Advancement of Science (AAAS)

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          Abstract

          The root nodule symbiosis of plants with nitrogen-fixing bacteria impacts global nitrogen cycles and food production but is restricted to a subset of genera within a single clade of flowering plants. To explore the genetic basis for this scattered occurrence, we sequenced the genomes of ten plant species covering the diversity of nodule morphotypes, bacterial symbionts and infection strategies. In a genome-wide comparative analysis of a total of 37 plant species, we discovered signatures of multiple independent loss-of-function events in the indispensable symbiotic regulator NODULE INCEPTION (NIN) in ten out of 13 genomes of non-nodulating species within this clade. The discovery that multiple independent losses shaped the present day distribution of nitrogen-fixing root nodule symbiosis in plants reveals a phylogenetically wider distribution in evolutionary history and a so far underestimated selection pressure against this symbiosis.

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          ETE 3: Reconstruction, Analysis, and Visualization of Phylogenomic Data

          Jaime Huerta-Cepas, François Serra, Peer Bork (2016)
          The Environment for Tree Exploration (ETE) is a computational framework that simplifies the reconstruction, analysis, and visualization of phylogenetic trees and multiple sequence alignments. Here, we present ETE v3, featuring numerous improvements in the underlying library of methods, and providing a novel set of standalone tools to perform common tasks in comparative genomics and phylogenetics. The new features include (i) building gene-based and supermatrix-based phylogenies using a single command, (ii) testing and visualizing evolutionary models, (iii) calculating distances between trees of different size or including duplications, and (iv) providing seamless integration with the NCBI taxonomy database. ETE is freely available at http://etetoolkit.org
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            LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons

            David Ellinghaus, Stefan Kurtz, Ute Willhoeft (2008)
            Background Transposable elements are abundant in eukaryotic genomes and it is believed that they have a significant impact on the evolution of gene and chromosome structure. While there are several completed eukaryotic genome projects, there are only few high quality genome wide annotations of transposable elements. Therefore, there is a considerable demand for computational identification of transposable elements. LTR retrotransposons, an important subclass of transposable elements, are well suited for computational identification, as they contain long terminal repeats (LTRs). Results We have developed a software tool LTRharvest for the de novo detection of full length LTR retrotransposons in large sequence sets. LTRharvest efficiently delivers high quality annotations based on known LTR transposon features like length, distance, and sequence motifs. A quality validation of LTRharvest against a gold standard annotation for Saccharomyces cerevisae and Drosophila melanogaster shows a sensitivity of up to 90% and 97% and specificity of 100% and 72%, respectively. This is comparable or slightly better than annotations for previous software tools. The main advantage of LTRharvest over previous tools is (a) its ability to efficiently handle large datasets from finished or unfinished genome projects, (b) its flexibility in incorporating known sequence features into the prediction, and (c) its availability as an open source software. Conclusion LTRharvest is an efficient software tool delivering high quality annotation of LTR retrotransposons. It can, for example, process the largest human chromosome in approx. 8 minutes on a Linux PC with 4 GB of memory. Its flexibility and small space and run-time requirements makes LTRharvest a very competitive candidate for future LTR retrotransposon annotation projects. Moreover, the structured design and implementation and the availability as open source provides an excellent base for incorporating novel concepts to further improve prediction of LTR retrotransposons.
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              NITROGEN LIMITATION OF NET PRIMARY PRODUCTIVITY IN TERRESTRIAL ECOSYSTEMS IS GLOBALLY DISTRIBUTED

              Kathleen K. Treseder, David LeBauer (2008)
              Our meta-analysis of 126 nitrogen addition experiments evaluated nitrogen (N) limitation of net primary production (NPP) in terrestrial ecosystems. We tested the hypothesis that N limitation is widespread among biomes and influenced by geography and climate. We used the response ratio (R approximately equal ANPP(N)/ANPP(ctrl)) of aboveground plant growth in fertilized to control plots and found that most ecosystems are nitrogen limited with an average 29% growth response to nitrogen (i.e., R = 1.29). The response ratio was significant within temperate forests (R = 1.19), tropical forests (R = 1.60), temperate grasslands (R = 1.53), tropical grasslands (R = 1.26), wetlands (R = 1.16), and tundra (R = 1.35), but not deserts. Eight tropical forest studies had been conducted on very young volcanic soils in Hawaii, and this subgroup was strongly N limited (R = 2.13), which resulted in a negative correlation between forest R and latitude. The degree of N limitation in the remainder of the tropical forest studies (R = 1.20) was comparable to that of temperate forests, and when the young Hawaiian subgroup was excluded, forest R did not vary with latitude. Grassland response increased with latitude, but was independent of temperature and precipitation. These results suggest that the global N and C cycles interact strongly and that geography can mediate ecosystem response to N within certain biome types.
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                Author and article information

                Journal
                Title: Science
                Abbreviated Title: Science
                Publisher: American Association for the Advancement of Science (AAAS)
                ISSN (Print): 0036-8075
                ISSN (Electronic): 1095-9203
                Publication date (Electronic): May 24 2018
                Page: eaat1743
                Article
                DOI: 10.1126/science.aat1743
                PubMed ID: 29794220
                SO-VID: 2440df34-daad-4866-ac20-914c9d148466
                Copyright © © 2018
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