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      Origin of marine planktonic cyanobacteria

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      Scientific Reports
      Nature Publishing Group

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          Abstract

          Marine planktonic cyanobacteria contributed to the widespread oxygenation of the oceans towards the end of the Pre-Cambrian and their evolutionary origin represents a key transition in the geochemical evolution of the Earth surface. Little is known, however, about the evolutionary events that led to the appearance of marine planktonic cyanobacteria. I present here phylogenomic (135 proteins and two ribosomal RNAs), Bayesian relaxed molecular clock (18 proteins, SSU and LSU) and Bayesian stochastic character mapping analyses from 131 cyanobacteria genomes with the aim to unravel key evolutionary steps involved in the origin of marine planktonic cyanobacteria. While filamentous cell types evolved early on at around 2,600–2,300 Mya and likely dominated microbial mats in benthic environments for most of the Proterozoic (2,500–542 Mya), marine planktonic cyanobacteria evolved towards the end of the Proterozoic and early Phanerozoic. Crown groups of modern terrestrial and/or benthic coastal cyanobacteria appeared during the late Paleoproterozoic to early Mesoproterozoic. Decrease in cell diameter and loss of filamentous forms contributed to the evolution of unicellular planktonic lineages during the middle of the Mesoproterozoic (1,600–1,000 Mya) in freshwater environments. This study shows that marine planktonic cyanobacteria evolved from benthic marine and some diverged from freshwater ancestors during the Neoproterozoic (1,000–542 Mya).

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          ProtTest: selection of best-fit models of protein evolution.

          Using an appropriate model of amino acid replacement is very important for the study of protein evolution and phylogenetic inference. We have built a tool for the selection of the best-fit model of evolution, among a set of candidate models, for a given protein sequence alignment. ProtTest is available under the GNU license from http://darwin.uvigo.es
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            SequenceMatrix: concatenation software for the fast assembly of multi-gene datasets with character set and codon information

            We present SequenceMatrix, software that is designed to facilitate the assembly and analysis of multi-gene datasets. Genes are concatenated by dragging and dropping FASTA, NEXUS, or TNT files with aligned sequences into the program window. A multi-gene dataset is concatenated and displayed in a spreadsheet; each sequence is represented by a cell that provides information on sequence length, number of indels, the number of ambiguous bases ("Ns"), and the availability of codon information. Alternatively, GenBank numbers for the sequences can be displayed and exported. Matrices with hundreds of genes and taxa can be concatenated within minutes and exported in TNT, NEXUS, or PHYLIP formats, preserving both character set and codon information for TNT and NEXUS files. SequenceMatrix also creates taxon sets listing taxa with a minimum number of characters or gene fragments, which helps assess preliminary datasets. Entire taxa, whole gene fragments, or individual sequences for a particular gene and species can be excluded from export. Data matrices can be re-split into their component genes and the gene fragments can be exported as individual gene files. SequenceMatrix also includes two tools that help to identify sequences that may have been compromised through laboratory contamination or data management error. One tool lists identical or near-identical sequences within genes, while the other compares the pairwise distance pattern of one gene against the pattern for all remaining genes combined. SequenceMatrix is Java-based and compatible with the Microsoft Windows, Apple MacOS X and Linux operating systems. The software is freely available from http://code.google.com/p/sequencematrix/. © The Willi Hennig Society 2010.
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              Present and future global distributions of the marine Cyanobacteria Prochlorococcus and Synechococcus.

              The Cyanobacteria Prochlorococcus and Synechococcus account for a substantial fraction of marine primary production. Here, we present quantitative niche models for these lineages that assess present and future global abundances and distributions. These niche models are the result of neural network, nonparametric, and parametric analyses, and they rely on >35,000 discrete observations from all major ocean regions. The models assess cell abundance based on temperature and photosynthetically active radiation, but the individual responses to these environmental variables differ for each lineage. The models estimate global biogeographic patterns and seasonal variability of cell abundance, with maxima in the warm oligotrophic gyres of the Indian and the western Pacific Oceans and minima at higher latitudes. The annual mean global abundances of Prochlorococcus and Synechococcus are 2.9 ± 0.1 × 10(27) and 7.0 ± 0.3 × 10(26) cells, respectively. Using projections of sea surface temperature as a result of increased concentration of greenhouse gases at the end of the 21st century, our niche models projected increases in cell numbers of 29% and 14% for Prochlorococcus and Synechococcus, respectively. The changes are geographically uneven but include an increase in area. Thus, our global niche models suggest that oceanic microbial communities will experience complex changes as a result of projected future climate conditions. Because of the high abundances and contributions to primary production of Prochlorococcus and Synechococcus, these changes may have large impacts on ocean ecosystems and biogeochemical cycles.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                01 December 2015
                2015
                : 5
                : 17418
                Affiliations
                [1 ]School of Geographical Sciences, University of Bristol , Bristol BS8 1SS, UK
                Author notes
                Article
                srep17418
                10.1038/srep17418
                4665016
                26621203
                e9274de3-03dd-4b9c-a5f2-f76d571f301e
                Copyright © 2015, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 28 May 2015
                : 29 October 2015
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