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Na H.,University of Aarhus | Lever M.A.,University of Aarhus | Lever M.A.,Universitatsstrasse 16 | Kjeldsen K.U.,University of Aarhus | And 2 more authors.
Environmental Microbiology Reports | Year: 2015

Stable isotope probing (SIP) of deoxyribonucleic acid (DNA) was used to identify microbes incorporating 13C-labeled acetate in sulfate-reducing sediment from Aarhus Bay, Denmark. Sediment was incubated in medium containing 10mM sulfate and different 13C-acetate (10, 1, 0.1mM) concentrations. The resultant changes in microbial community composition were monitored in total and SIP-fractionated DNA during long-term incubations. Chemical analyses demonstrated metabolic activity in all sediment slurries, with sulfate-reducing activity largely determined by initial acetate concentrations. Sequencing of 16S rRNA gene PCR amplicons showed that the incubations shifted the bacterial but not the archaeal community composition. After 3 months of incubation, only sediment slurries incubated with 10mM 13C-acetate showed detectable 13C-DNA labeling. Based on 16S rRNA and dsrB gene PCR amplicon sequencing, the 13C-labeled DNA pool was dominated by a single type of sulfate reducer representing a novel genus in the family Desulfobacteraceae. In addition, members of the uncultivated Crenarchaeotal group C3 were enriched in the 13C-labeled DNA. Our results were reproducible across biological replicate experiments and provide new information about the identities of uncultured acetate-consuming bacteria and archaea in marine sediments. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd. Source

Hartmann K.,University of Tasmania | Wong D.,Dalhousie University | Stadler T.,Universitatsstrasse 16
Systematic Biology | Year: 2010

A wide range of evolutionary models for species-level (and higher) diversification have been developed. These models can be used to test evolutionary hypotheses and provide comparisons with phylogenetic trees constructed from real data. To carry out these tests and comparisons, it is often necessary to sample, or simulate, trees from the evolutionary models. Sampling trees from these models is more complicated than it may appear at first glance, necessitating careful consideration and mathematical rigor. Seemingly straightforward sampling methods may produce trees that have systematically biased shapes or branch lengths. This is particularly problematic as there is no simple method for determining whether the sampled trees are appropriate. In this paper, we show why a commonly used simple sampling approach (SSA)-simulating trees forward in time until n species are first reached-should only be applied to the simplest pure birth model, the Yule model. We provide an alternative general sampling approach (GSA) that can be applied to most other models. Furthermore, we introduce the constant-rate birth-death model sampling approach, which samples trees very efficiently from a widely used class of models. We explore the bias produced by SSA and identify situations in which this bias is particularly pronounced. We show that using SSA can lead to erroneous conclusions: When using the inappropriate SSA, the variance of a gradually evolving trait does not correlate with the age of the tree; when the correct GSA is used, the trait variance correlates with tree age. The algorithms presented here are available in the Perl Bio:Phylo package, as a stand-alone program TreeSample, and in the R TreeSim package. © The Author(s) 2010. Source

Richner N.,Agroscope Institute for Sustainability science ISS | Holderegger R.,Swiss Federal Institute of forest | Holderegger R.,Universitatsstrasse 16 | Linder H.P.,University of Zurich | Walter T.,Agroscope Institute for Sustainability science ISS
Weed Research | Year: 2015

Changing agricultural practices have dramatically altered the arable flora of Europe since the Second World War. We conducted a meta-analysis of the available literature to assess the dynamics of species richness and species traits in the arable flora across Europe during this time period. We found a total of 32 publications, yielding 53 data sets with an average number of 252 studied plots per data set. Average species number per plot of arable plants across all data sets declined by about 20%. However, twelve data sets showed an increase in average species number per plot, including all studies starting after 1980. Plant species preferring nutrient-rich sites, neophytes and monocotyledons generally increased since 1980, while characteristic or threatened species of arable weed communities further declined. This temporal development of the European arable flora suggests that the changes happening in agricultural management since the 1980s, such as organic farming and reduced pesticide input, may have helped slow the decline of the arable flora in terms of species number, but not in terms of characteristic or threatened arable weeds. Hence, more specific measures are necessary to stop decline of the latter, making sure that these measures are advantageous for rare and characteristic arable species, but not for harmful weeds. Weed Research © 2015 European Weed Research Society. Source

Stadler T.,Universitatsstrasse 16 | Degnan J.H.,University of Canterbury | Degnan J.H.,National Institute of Mathematical and Biological Synthesis
Algorithms for Molecular Biology | Year: 2012

Background: The ancestries of genes form gene trees which do not necessarily have the same topology as the species tree due to incomplete lineage sorting. Available algorithms determining the probability of a gene tree given a species tree require exponential computational runtime.Results: In this paper, we provide a polynomial time algorithm to calculate the probability of a ranked gene tree topology for a given species tree, where a ranked tree topology is a tree topology with the internal vertices being ordered. The probability of a gene tree topology can thus be calculated in polynomial time if the number of orderings of the internal vertices is a polynomial number. However, the complexity of calculating the probability of a gene tree topology with an exponential number of rankings for a given species tree remains unknown.Conclusions: Polynomial algorithms for calculating ranked gene tree probabilities may become useful in developing methodology to infer species trees based on a collection of gene trees, leading to a more accurate reconstruction of ancestral species relationships. © 2012 Stadler and Degnan; licensee BioMed Central Ltd. Source

Herrmann M.,Swiss Federal Institute of forest | Holderegger R.,Swiss Federal Institute of forest | Holderegger R.,Universitatsstrasse 16 | Van Strien M.J.,Swiss Federal Institute of forest | Van Strien M.J.,Universitatsstrasse 16
Molecular Ecology Resources | Year: 2013

The use of procedures for the automated scoring of amplified fragment length polymorphisms (AFLP) fragments has recently increased. Corresponding software does not only automatically score the presence or absence of AFLP fragments, but also allows an evaluation of how different settings of scoring parameters influence subsequent population genetic analyses. In this study, we used the automated scoring package rawgeno to evaluate how five scoring parameters influence the number of polymorphic bins and estimates of pairwise genetic differentiation between populations (Fst). Steps were implemented in r to automatically run the scoring process in rawgeno for a set of different parameter combinations. While we found the scoring parameters minimum bin width and minimum number of samples per bin to have only weak influence on pairwise Fst values, maximum bin width and bin reproducibility had much stronger effects. The minimum average bin fluorescence scoring parameter affected Fst values in an only moderate way. At a range of scoring parameters around the default settings of rawgeno, the number of polymorphic bins as well as pairwise Fst values stayed rather constant. This study thus shows the particularities of AFLP scoring, be it either manual or automatical, can have profound effects on subsequent population genetic analysis. © 2012 Blackwell Publishing Ltd. Source

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