Daniel H. Huson

SplitsTree: analyzing and visualizing evolutionary data.

MOTIVATION Real evolutionary data often contain a number of different and sometimes conflicting phylogenetic signals, and thus do not always clearly support a unique tree. To address this problem, Bandelt and Dress (Adv. Math., 92, 47-05, 1992) developed the method of split decomposition. For ideal data, this method gives rise to a tree, whereas less ideal data are represented by a tree-like network that may indicate evidence for different and conflicting phylogenies. RESULTS SplitsTree is an interactive program, for analyzing and visualizing evolutionary data, that implements this approach. It also supports a number of distances transformations, the computation of parsimony splits, spectral analysis and bootstrapping.

Dendroscope: An interactive viewer for large phylogenetic trees

BackgroundResearch in evolution requires software for visualizing and editing phylogenetic trees, for increasingly very large datasets, such as arise in expression analysis or metagenomics, for example. It would be desirable to have a program that provides these services in an effcient and user-friendly way, and that can be easily installed and run on all major operating systems. Although a large number of tree visualization tools are freely available, some as a part of more comprehensive analysis packages, all have drawbacks in one or more domains. They either lack some of the standard tree visualization techniques or basic graphics and editing features, or they are restricted to small trees containing only tens of thousands of taxa. Moreover, many programs are diffcult to install or are not available for all common operating systems.ResultsWe have developed a new program, Dendroscope, for the interactive visualization and navigation of phylogenetic trees. The program provides all standard tree visualizations and is optimized to run interactively on trees containing hundreds of thousands of taxa. The program provides tree editing and graphics export capabilities. To support the inspection of large trees, Dendroscope offers a magnification tool. The software is written in Java 1.4 and installers are provided for Linux/Unix, MacOS X and Windows XP.ConclusionDendroscope is a user-friendly program for visualizing and navigating phylogenetic trees, for both small and large datasets.

Fast and sensitive protein alignment using DIAMOND

The alignment of sequencing reads against a protein reference database is a major computational bottleneck in metagenomics and data-intensive evolutionary projects. Although recent tools offer improved performance over the gold standard BLASTX, they exhibit only a modest speedup or low sensitivity. We introduce DIAMOND, an open-source algorithm based on double indexing that is 20,000 times faster than BLASTX on short reads and has a similar degree of sensitivity.

Dendroscope 3: An Interactive Tool for Rooted Phylogenetic Trees and Networks

Dendroscope 3 is a new program for working with rooted phylogenetic trees and networks. It provides a number of methods for drawing and comparing rooted phylogenetic networks, and for computing them from rooted trees. The program can be used interactively or in command-line mode. The program is written in Java, use of the software is free, and installers for all 3 major operating systems can be downloaded from www.dendroscope.org. [Phylogenetic trees; phylogenetic networks; software.].

Simultaneous Assessment of Soil Microbial Community Structure and Function through Analysis of the Meta-Transcriptome

Background Soil ecosystems harbor the most complex prokaryotic and eukaryotic microbial communities on Earth. Experimental approaches studying these systems usually focus on either the soil communitys taxonomic structure or its functional characteristics. Many methods target DNA as marker molecule and use PCR for amplification. Methodology/Principal Findings Here we apply an RNA-centered meta-transcriptomic approach to simultaneously obtain information on both structure and function of a soil community. Total community RNA is random reversely transcribed into cDNA without any PCR or cloning step. Direct pyrosequencing produces large numbers of cDNA rRNA-tags; these are taxonomically profiled in a binning approach using the MEGAN software and two specifically compiled rRNA reference databases containing small and large subunit rRNA sequences. The pyrosequencing also produces mRNA-tags; these provide a sequence-based transcriptome of the community. One soil dataset of 258,411 RNA-tags of ∼98 bp length contained 193,219 rRNA-tags with valid taxonomic information, together with 21,133 mRNA-tags. Quantitative information about the relative abundance of organisms from all three domains of life and from different trophic levels was obtained in a single experiment. Less frequent taxa, such as soil Crenarchaeota, were well represented in the data set. These were identified by more than 2,000 rRNA-tags; furthermore, their activity in situ was revealed through the presence of mRNA-tags specific for enzymes involved in ammonia oxidation and CO2 fixation. Conclusions/Significance This approach could be widely applied in microbial ecology by efficiently linking community structure and function in a single experiment while avoiding biases inherent in other methods.

MetaSim—A Sequencing Simulator for Genomics and Metagenomics

Background The new research field of metagenomics is providing exciting insights into various, previously unclassified ecological systems. Next-generation sequencing technologies are producing a rapid increase of environmental data in public databases. There is great need for specialized software solutions and statistical methods for dealing with complex metagenome data sets. Methodology/Principal Findings To facilitate the development and improvement of metagenomic tools and the planning of metagenomic projects, we introduce a sequencing simulator called MetaSim. Our software can be used to generate collections of synthetic reads that reflect the diverse taxonomical composition of typical metagenome data sets. Based on a database of given genomes, the program allows the user to design a metagenome by specifying the number of genomes present at different levels of the NCBI taxonomy, and then to collect reads from the metagenome using a simulation of a number of different sequencing technologies. A population sampler optionally produces evolved sequences based on source genomes and a given evolutionary tree. Conclusions/Significance MetaSim allows the user to simulate individual read datasets that can be used as standardized test scenarios for planning sequencing projects or for benchmarking metagenomic software.

Specificity prediction of adenylation domains in nonribosomal peptide synthetases (NRPS) using transductive support vector machines (TSVMs)

We present a new support vector machine (SVM)-based approach to predict the substrate specificity of subtypes of a given protein sequence family. We demonstrate the usefulness of this method on the example of aryl acid-activating and amino acid-activating adenylation domains (A domains) of nonribosomal peptide synthetases (NRPS). The residues of gramicidin synthetase A that are 8 Å around the substrate amino acid and corresponding positions of other adenylation domain sequences with 397 known and unknown specificities were extracted and used to encode this physico-chemical fingerprint into normalized real-valued feature vectors based on the physico-chemical properties of the amino acids. The SVM software package SVMlight was used for training and classification, with transductive SVMs to take advantage of the information inherent in unlabeled data. Specificities for very similar substrates that frequently show cross-specificities were pooled to the so-called composite specificities and predictive models were built for them. The reliability of the models was confirmed in cross-validations and in comparison with a currently used sequence-comparison-based method. When comparing the predictions for 1230 NRPS A domains that are currently detectable in UniProt, the new method was able to give a specificity prediction in an additional 18% of the cases compared with the old method. For 70% of the sequences both methods agreed, for <6% they did not, mainly on low-confidence predictions by the existing method. None of the predictive methods could infer any specificity for 2.4% of the sequences, suggesting completely new types of specificity.

Sequence and Expression Differences Underlie Functional Specialization of Arabidopsis MicroRNAs miR159 and miR319

Many microRNAs (miRNAs) are encoded by small gene families. In a third of all conserved Arabidopsis miRNA families, members vary at two or more nucleotide positions. We have focused on the related miR159 and miR319 families, which share sequence identity at 17 of 21 nucleotides, yet affect different developmental processes through distinct targets. MiR159 regulates MYB mRNAs, while miR319 predominantly acts on TCP mRNAs. In the case of miR319, MYB targeting plays at most a minor role because miR319 expression levels and domain limit its ability to affect MYB mRNAs. In contrast, in the case of miR159, the miRNA sequence prevents effective TCP targeting. We complement these observations by identifying nucleotide positions relevant for miRNA activity with mutants recovered from a suppressor screen. Together, our findings reveal that functional specialization of miR159 and miR319 is achieved through both expression and sequence differences.

Systematic enumeration of crystalline networks

The systematic enumeration of all possible networks of atoms ininorganic structures is of considerable interest. Of particular importance are the 4-connected networks (those in which each atom is connected to exactly four neighbours), which are relevant to a wide range of systems — crystalline elements, hydrates, covalently bonded crystals, silicates and many synthetic compounds. Systematic enumeration is especially desirable in the study of zeolites and related materials, of which there are now 121 recognized structural types, with several new types being identified every year. But as the number of possible 4-connected three-dimensional networks is infinite, and as there exists no systematic procedure for their derivation, the prediction of new structural types has hitherto relied on empirical methods (see, for example, refs 2–4). Here we report a partial solution to this problem, basedon recent advances in mathematical tiling theory. We establish that there are exactly 9, 117 and 926 topological types of, respectively, 4-connected uninodal, binodal and trinodal networks, derived from simple tilings based on tetrahedra. (Here nodality refers to the number of topologically distinct vertices from which the network is composed.) We also show that there are at least 145 more distinct uninodal networks based on a more complex tiling unit. Of the total number of networks that we have derived, only two contain neither three- nor four-membered rings, and most of the binodal and trinodal networks are new.

MEGAN Community Edition - Interactive Exploration and Analysis of Large-Scale Microbiome Sequencing Data

There is increasing interest in employing shotgun sequencing, rather than amplicon sequencing, to analyze microbiome samples. Typical projects may involve hundreds of samples and billions of sequencing reads. The comparison of such samples against a protein reference database generates billions of alignments and the analysis of such data is computationally challenging. To address this, we have substantially rewritten and extended our widely-used microbiome analysis tool MEGAN so as to facilitate the interactive analysis of the taxonomic and functional content of very large microbiome datasets. Other new features include a functional classifier called InterPro2GO, gene-centric read assembly, principal coordinate analysis of taxonomy and function, and support for metadata. The new program is called MEGAN Community Edition (CE) and is open source. By integrating MEGAN CE with our high-throughput DNA-to-protein alignment tool DIAMOND and by providing a new program MeganServer that allows access to metagenome analysis files hosted on a server, we provide a straightforward, yet powerful and complete pipeline for the analysis of metagenome shotgun sequences. We illustrate how to perform a full-scale computational analysis of a metagenomic sequencing project, involving 12 samples and 800 million reads, in less than three days on a single server. All source code is available here: https://github.com/danielhuson/megan-ce