pyPaSWAS: Python-based multi-core CPU and GPU sequence alignment

Classification of the plant-associated lifestyle of Pseudomonas strains using genome properties and machine learning

The rhizosphere, the region of soil surrounding roots of plants, is colonized by a unique population of Plant Growth Promoting Rhizobacteria (PGPR). Many important PGPR as well as plant pathogens belong to the genus Pseudomonas. There is, however, uncertainty on the divide between beneficial and pathogenic strains as previously thought to be signifying genomic features have limited power to separate these strains. Here we used the Genome properties (GP) common biological pathways annotation system and Machine Learning (ML) to establish the relationship between the genome wide GP composition and the plant-associated lifestyle of 91 Pseudomonas strains isolated from the rhizosphere and the phyllosphere representing both plant-associated phenotypes. GP enrichment analysis, Random Forest model fitting and feature selection revealed 28 discriminating features. A test set of 75 new strains confirmed the importance of the selected features for classification. The results suggest that GP annotations provide a promising computational tool to better classify the plant-associated lifestyle.

Draft Genome Sequences of Three Isolates of Golubevia sp. Basidiomycete Fungi Isolated from Powdery Mildew Pustules

The genomes of three Golubevia isolates (BC0812, BC0850, and BC0902) that have been shown to reduce conidiation of Blumeria graminis f. sp. tritici were sequenced using a dual-platform approach. The assembled genomes will help to elucidate the molecular mechanisms underlying the biocontrol effect of this understudied group.

The genomes of three Golubevia isolates (BC0812, BC0850, and BC0902) that have been shown to reduce conidiation of Blumeria graminis f. sp. tritici were sequenced using a dual-platform approach. The assembled genomes will help to elucidate the molecular mechanisms underlying the biocontrol effect of this understudied group.

Correcting palindromes in long reads after whole-genome amplification

BACKGROUND

Next-generation sequencing requires sufficient DNA to be available. If limited, whole-genome amplification is applied to generate additional amounts of DNA. Such amplification often results in many chimeric DNA fragments, in particular artificial palindromic sequences, which limit the usefulness of long sequencing reads.

RESULTS

Here, we present Pacasus, a tool for correcting such errors. Two datasets show that it markedly improves read mapping and de novo assembly, yielding results similar to these that would be obtained with non-amplified DNA.

CONCLUSIONS

With Pacasus long-read technologies become available for sequencing targets with very small amounts of DNA, such as single cells or even single chromosomes.