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April 21, 2020

Comparative genomics and pathogenicity potential of members of the Pseudomonas syringae species complex on Prunus spp.

Diseases on Prunus spp. have been associated with a large number of phylogenetically different pathovars and species within the P. syringae species complex. Despite their economic significance, there is a severe lack of genomic information of these pathogens. The high phylogenetic diversity observed within strains causing disease on Prunus spp. in nature, raised the question whether other strains or species within the P. syringae species complex were potentially pathogenic on Prunus spp.To gain insight into the genomic potential of adaptation and virulence in Prunus spp., a total of twelve de novo whole genome sequences of P. syringae pathovars and species found in association with diseases on cherry (sweet, sour and ornamental-cherry) and peach were sequenced. Strains sequenced in this study covered three phylogroups and four clades. These strains were screened in vitro for pathogenicity on Prunus spp. together with additional genome sequenced strains thus covering nine out of thirteen of the currently defined P. syringae phylogroups. Pathogenicity tests revealed that most of the strains caused symptoms in vitro and no obvious link was found between presence of known virulence factors and the observed pathogenicity pattern based on comparative genomics. Non-pathogenic strains were displaying a two to three times higher generation time when grown in rich medium.In this study, the first set of complete genomes of cherry associated P. syringae strains as well as the draft genome of the quarantine peach pathogen P. syringae pv. persicae were generated. The obtained genomic data were matched with phenotypic data in order to determine factors related to pathogenicity to Prunus spp. Results of this study suggest that the inability to cause disease on Prunus spp. in vitro is not the result of host specialization but rather linked to metabolic impairments of individual strains.

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April 21, 2020

Assignment of virus and antimicrobial resistance genes to microbial hosts in a complex microbial community by combined long-read assembly and proximity ligation.

We describe a method that adds long-read sequencing to a mix of technologies used to assemble a highly complex cattle rumen microbial community, and provide a comparison to short read-based methods. Long-read alignments and Hi-C linkage between contigs support the identification of 188 novel virus-host associations and the determination of phage life cycle states in the rumen microbial community. The long-read assembly also identifies 94 antimicrobial resistance genes, compared to only seven alleles in the short-read assembly. We demonstrate novel techniques that work synergistically to improve characterization of biological features in a highly complex rumen microbial community.

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April 21, 2020

Haplotype-aware diplotyping from noisy long reads.

Current genotyping approaches for single-nucleotide variations rely on short, accurate reads from second-generation sequencing devices. Presently, third-generation sequencing platforms are rapidly becoming more widespread, yet approaches for leveraging their long but error-prone reads for genotyping are lacking. Here, we introduce a novel statistical framework for the joint inference of haplotypes and genotypes from noisy long reads, which we term diplotyping. Our technique takes full advantage of linkage information provided by long reads. We validate hundreds of thousands of candidate variants that have not yet been included in the high-confidence reference set of the Genome-in-a-Bottle effort.

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April 21, 2020

Comparative Phylogenomics, a Stepping Stone for Bird Biodiversity Studies

Birds are a group with immense availability of genomic resources, and hundreds of forthcoming genomes at the doorstep. We review recent developments in whole genome sequencing, phylogenomics, and comparative genomics of birds. Short read based genome assemblies are common, largely due to efforts of the Bird 10K genome project (B10K). Chromosome-level assemblies are expected to increase due to improved long-read sequencing. The available genomic data has enabled the reconstruction of the bird tree of life with increasing confidence and resolution, but challenges remain in the early splits of Neoaves due to their explosive diversification after the Cretaceous-Paleogene (K-Pg) event. Continued genomic sampling of the bird tree of life will not just better reflect their evolutionary history but also shine new light onto the organization of phylogenetic signal and conflict across the genome. The comparatively simple architecture of avian genomes makes them a powerful system to study the molecular foundation of bird specific traits. Birds are on the verge of becoming an extremely resourceful system to study biodiversity from the nucleotide up.

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April 21, 2020

CAMISIM: simulating metagenomes and microbial communities.

Shotgun metagenome data sets of microbial communities are highly diverse, not only due to the natural variation of the underlying biological systems, but also due to differences in laboratory protocols, replicate numbers, and sequencing technologies. Accordingly, to effectively assess the performance of metagenomic analysis software, a wide range of benchmark data sets are required.We describe the CAMISIM microbial community and metagenome simulator. The software can model different microbial abundance profiles, multi-sample time series, and differential abundance studies, includes real and simulated strain-level diversity, and generates second- and third-generation sequencing data from taxonomic profiles or de novo. Gold standards are created for sequence assembly, genome binning, taxonomic binning, and taxonomic profiling. CAMSIM generated the benchmark data sets of the first CAMI challenge. For two simulated multi-sample data sets of the human and mouse gut microbiomes, we observed high functional congruence to the real data. As further applications, we investigated the effect of varying evolutionary genome divergence, sequencing depth, and read error profiles on two popular metagenome assemblers, MEGAHIT, and metaSPAdes, on several thousand small data sets generated with CAMISIM.CAMISIM can simulate a wide variety of microbial communities and metagenome data sets together with standards of truth for method evaluation. All data sets and the software are freely available at https://github.com/CAMI-challenge/CAMISIM.

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