A 20-kb lineage-specific genomic region tames virulence in pathogenic amphidiploid Verticillium longisporum.

Amphidiploid fungal Verticillium longisporum strains Vl43 and Vl32 colonize the plant host Brassica napus but differ in their ability to cause disease symptoms. These strains represent two V. longisporum lineages derived from different hybridization events of haploid parental Verticillium strains. Vl32 and Vl43 carry same-sex mating-type genes derived from both parental lineages. Vl32 and Vl43 similarly colonize and penetrate plant roots, but asymptomatic Vl32 proliferation in planta is lower than virulent Vl43. The highly conserved Vl43 and Vl32 genomes include less than 1% unique genes, and the karyotypes of 15 or 16 chromosomes display changed genetic synteny due to substantial genomic reshuffling. A 20 kb Vl43 lineage-specific (LS) region apparently originating from the Verticillium dahliae-related ancestor is specific for symptomatic Vl43 and encodes seven genes, including two putative transcription factors. Either partial or complete deletion of this LS region in Vl43 did not reduce virulence but led to induction of even more severe disease symptoms in rapeseed. This suggests that the LS insertion in the genome of symptomatic V. longisporum Vl43 mediates virulence-reducing functions, limits damage on the host plant, and therefore tames Vl43 from being even more virulent.

Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data.

MOTIVATION: The characterization of phylogenetic and functional diversity is a key element in the analysis of microbial communities. Amplicon-based sequencing of marker genes, such as 16S rRNA, is a powerful tool for assessing and comparing the structure of microbial communities at a high phylogenetic resolution. Because 16S rRNA sequencing is more cost-effective than whole metagenome shotgun sequencing, marker gene analysis is frequently used for broad studies that involve a large number of different samples. However, in comparison to shotgun sequencing approaches, insights into the functional capabilities of the community get lost when restricting the analysis to taxonomic assignment of 16S rRNA data. RESULTS: Tax4Fun is a software package that predicts the functional capabilities of microbial communities based on 16S rRNA datasets. We evaluated Tax4Fun on a range of paired metagenome/16S rRNA datasets to assess its performance. Our results indicate that Tax4Fun provides a good approximation to functional profiles obtained from metagenomic shotgun sequencing approaches. AVAILABILITY AND IMPLEMENTATION: Tax4Fun is an open-source R package and applicable to output as obtained from the SILVAngs web server or the application of QIIME with a SILVA database extension. Tax4Fun is freely available for download at http://tax4fun.gobics.de/. CONTACT: kasshau@gwdg.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Exploring neighborhoods in the metagenome universe.

The variety of metagenomes in current databases provides a rapidly growing source of information for comparative studies. However, the quantity and quality of supplementary metadata is still lagging behind. It is therefore important to be able to identify related metagenomes by means of the available sequence data alone. We have studied efficient sequence-based methods for large-scale identification of similar metagenomes within a database retrieval context. In a broad comparison of different profiling methods we found that vector-based distance measures are well-suitable for the detection of metagenomic neighbors. Our evaluation on more than 1700 publicly available metagenomes indicates that for a query metagenome from a particular habitat on average nine out of ten nearest neighbors represent the same habitat category independent of the utilized profiling method or distance measure. While for well-defined labels a neighborhood accuracy of 100% can be achieved, in general the neighbor detection is severely affected by a natural overlap of manually annotated categories. In addition, we present results of a novel visualization method that is able to reflect the similarity of metagenomes in a 2D scatter plot. The visualization method shows a similarly high accuracy in the reduced space as compared with the high-dimensional profile space. Our study suggests that for inspection of metagenome neighborhoods the profiling methods and distance measures can be chosen to provide a convenient interpretation of results in terms of the underlying features. Furthermore, supplementary metadata of metagenome samples in the future needs to comply with readily available ontologies for fine-grained and standardized annotation. To make profile-based k-nearest-neighbor search and the 2D-visualization of the metagenome universe available to the research community, we included the proposed methods in our CoMet-Universe server for comparative metagenome analysis.