SPECTRE: a suite of phylogenetic tools for reticulate evolution.

Summary: Split-networks are a generalization of phylogenetic trees that have proven to be a powerful tool in phylogenetics. Various ways have been developed for computing such networks, including split-decomposition, NeighborNet, QNet and FlatNJ. Some of these approaches are implemented in the user-friendly SplitsTree software package. However, to give the user the option to adjust and extend these approaches and to facilitate their integration into analysis pipelines, there is a need for robust, open-source implementations of associated data structures and algorithms. Here, we present SPECTRE, a readily available, open-source library of data structures written in Java, that comes complete with new implementations of several pre-published algorithms and a basic interactive graphical interface for visualizing planar split networks. SPECTRE also supports the use of longer running algorithms by providing command line interfaces, which can be executed on servers or in High Performance Computing environments. Availability and implementation: Full source code is available under the GPLv3 license at: https://github.com/maplesond/SPECTRE. SPECTRE's core library is available from Maven Central at: https://mvnrepository.com/artifact/uk.ac.uea.cmp.spectre/core. Documentation is available at: http://spectre-suite-of-phylogenetic-tools-for-reticulate-evolution.readthedocs.io/en/latest/. Contact: sarah.bastkowski@earlham.ac.uk. Supplementary information: Supplementary data are available at Bioinformatics online.

Expression of KIR2DS1 does not significantly contribute to NK cell cytotoxicity in HLA-C1/C2 heterozygous haplotype B donors.

NK cells are functionally controlled by the killer immunoglobulin-like receptor (KIR) family that comprises inhibitory (iKIR) and activating (aKIR) members. Genetic association studies suggest that donors expressing aKIRs next to iKIRs will be superior donors in the setting of hematopoietic stem cell transplantation of patients with leukemia. However, contrary evidence states that aKIR expression may be irrelevant or even detrimental. Using a complex methodology incorporating KIR-Q-PCR, double fluorescence and viSNE analysis, we characterized subset distribution patterns and functionality in haplotype A donors which lack aKIRs and haplotype B donors that express a variety of B-specific genes. Here, we show that the alloreactive KIR2DS1+ NK cell subset in HLA-C1/C2 donors is highly responsive towards C2-expressing targets but quantitatively small and as such does not significantly contribute to cytotoxicity. Thus, we fail to find a direct link between haplotype allocation status and NK cell cytotoxicity at least in HLA-C1/C2 heterozygous donors.

Critical Assessment of Metagenome Interpretation-a benchmark of metagenomics software.

Methods for assembly, taxonomic profiling and binning are key to interpreting metagenome data, but a lack of consensus about benchmarking complicates performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on highly complex and realistic data sets, generated from ∼700 newly sequenced microorganisms and ∼600 novel viruses and plasmids and representing common experimental setups. Assembly and genome binning programs performed well for species represented by individual genomes but were substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below family level. Parameter settings markedly affected performance, underscoring their importance for program reproducibility. The CAMI results highlight current challenges but also provide a roadmap for software selection to answer specific research questions.

SILVA, RDP, Greengenes, NCBI and OTT - how do these taxonomies compare?

BACKGROUND: A key step in microbiome sequencing analysis is read assignment to taxonomic units. This is often performed using one of four taxonomic classifications, namely SILVA, RDP, Greengenes or NCBI. It is unclear how similar these are and how to compare analysis results that are based on different taxonomies. RESULTS: We provide a method and software for mapping taxonomic entities from one taxonomy onto another. We use it to compare the four taxonomies and the Open Tree of life Taxonomy (OTT). CONCLUSIONS: While we find that SILVA, RDP and Greengenes map well into NCBI, and all four map well into the OTT, mapping the two larger taxonomies on to the smaller ones is problematic.

Comprehensive analysis of DNA polymerase III α subunits and their homologs in bacterial genomes.

The analysis of ∼ 2000 bacterial genomes revealed that they all, without a single exception, encode one or more DNA polymerase III α-subunit (PolIIIα) homologs. Classified into C-family of DNA polymerases they come in two major forms, PolC and DnaE, related by ancient duplication. While PolC represents an evolutionary compact group, DnaE can be further subdivided into at least three groups (DnaE1-3). We performed an extensive analysis of various sequence, structure and surface properties of all four polymerase groups. Our analysis suggests a specific evolutionary pathway leading to PolC and DnaE from the last common ancestor and reveals important differences between extant polymerase groups. Among them, DnaE1 and PolC show the highest conservation of the analyzed properties. DnaE3 polymerases apparently represent an 'impaired' version of DnaE1. Nonessential DnaE2 polymerases, typical for oxygen-using bacteria with large GC-rich genomes, have a number of features in common with DnaE3 polymerases. The analysis of polymerase distribution in genomes revealed three major combinations: DnaE1 either alone or accompanied by one or more DnaE2s, PolC + DnaE3 and PolC + DnaE1. The first two combinations are present in Escherichia coli and Bacillus subtilis, respectively. The third one (PolC + DnaE1), found in Clostridia, represents a novel, so far experimentally uncharacterized, set.