BRAKER3: Fully automated genome annotation using RNA-seq and protein evidence with GeneMark-ETP, AUGUSTUS, and TSEBRA.

Gene prediction has remained an active area of bioinformatics research for a long time. Still, gene prediction in large eukaryotic genomes presents a challenge that must be addressed by new algorithms. The amount and significance of the evidence available from transcriptomes and proteomes vary across genomes, between genes, and even along a single gene. User-friendly and accurate annotation pipelines that can cope with such data heterogeneity are needed. The previously developed annotation pipelines BRAKER1 and BRAKER2 use RNA-seq or protein data, respectively, but not both. A further significant performance improvement integrating all three data types was made by the recently released GeneMark-ETP. We here present the BRAKER3 pipeline that builds on GeneMark-ETP and AUGUSTUS, and further improves accuracy using the TSEBRA combiner. BRAKER3 annotates protein-coding genes in eukaryotic genomes using both short-read RNA-seq and a large protein database, along with statistical models learned iteratively and specifically for the target genome. We benchmarked the new pipeline on genomes of 11 species under an assumed level of relatedness of the target species proteome to available proteomes. BRAKER3 outperforms BRAKER1 and BRAKER2. The average transcript-level F1-score is increased by about 20 percentage points on average, whereas the difference is most pronounced for species with large and complex genomes. BRAKER3 also outperforms other existing tools, MAKER2, Funannotate, and FINDER. The code of BRAKER3 is available on GitHub and as a ready-to-run Docker container for execution with Docker or Singularity. Overall, BRAKER3 is an accurate, easy-to-use tool for eukaryotic genome annotation.

Standards recommendations for the Earth BioGenome Project.

A global international initiative, such as the Earth BioGenome Project (EBP), requires both agreement and coordination on standards to ensure that the collective effort generates rapid progress toward its goals. To this end, the EBP initiated five technical standards committees comprising volunteer members from the global genomics scientific community: Sample Collection and Processing, Sequencing and Assembly, Annotation, Analysis, and IT and Informatics. The current versions of the resulting standards documents are available on the EBP website, with the recognition that opportunities, technologies, and challenges may improve or change in the future, requiring flexibility for the EBP to meet its goals. Here, we describe some highlights from the proposed standards, and areas where additional challenges will need to be met.

The genomic basis of evolutionary differentiation among honey bees.

In contrast to the western honey bee, Apis mellifera, other honey bee species have been largely neglected despite their importance and diversity. The genetic basis of the evolutionary diversification of honey bees remains largely unknown. Here, we provide a genome-wide comparison of three honey bee species, each representing one of the three subgenera of honey bees, namely the dwarf (Apis florea), giant (A. dorsata), and cavity-nesting (A. mellifera) honey bees with bumblebees as an outgroup. Our analyses resolve the phylogeny of honey bees with the dwarf honey bees diverging first. We find that evolution of increased eusocial complexity in Apis proceeds via increases in the complexity of gene regulation, which is in agreement with previous studies. However, this process seems to be related to pathways other than transcriptional control. Positive selection patterns across Apis reveal a trade-off between maintaining genome stability and generating genetic diversity, with a rapidly evolving piRNA pathway leading to genomes depleted of transposable elements, and a rapidly evolving DNA repair pathway associated with high recombination rates in all Apis species. Diversification within Apis is accompanied by positive selection in several genes whose putative functions present candidate mechanisms for lineage-specific adaptations, such as migration, immunity, and nesting behavior.

Reduced interleukin-18 secretion by human monocytic cells in response to infections with hyper-virulent Streptococcus pyogenes.

BACKGROUND: Streptococcus pyogenes (group A streptococcus, GAS) causes a variety of diseases ranging from mild superficial infections of the throat and skin to severe invasive infections, such as necrotizing soft tissue infections (NSTIs). Tissue passage of GAS often results in mutations within the genes encoding for control of virulence (Cov)R/S two component system leading to a hyper-virulent phenotype. Dendritic cells (DCs) are innate immune sentinels specialized in antigen uptake and subsequent T cell priming. This study aimed to analyze cytokine release by DCs and other cells of monocytic origin in response to wild-type and natural covR/S mutant infections. METHODS: Human primary monocyte-derived (mo)DCs were used. DC maturation and release of pro-inflammatory cytokines in response to infections with wild-type and covR/S mutants were assessed via flow cytometry. Global proteome changes were assessed via mass spectrometry. As a proof-of-principle, cytokine release by human primary monocytes and macrophages was determined. RESULTS: In vitro infections of moDCs and other monocytic cells with natural GAS covR/S mutants resulted in reduced secretion of IL-8 and IL-18 as compared to wild-type infections. In contrast, moDC maturation remained unaffected. Inhibition of caspase-8 restored secretion of both molecules. Knock-out of streptolysin O in GAS strain with unaffected CovR/S even further elevated the IL-18 secretion by moDCs. Of 67 fully sequenced NSTI GAS isolates, 28 harbored mutations resulting in dysfunctional CovR/S. However, analyses of plasma IL-8 and IL-18 levels did not correlate with presence or absence of such mutations. CONCLUSIONS: Our data demonstrate that strains, which harbor covR/S mutations, interfere with IL-18 and IL-8 responses in monocytic cells by utilizing the caspase-8 axis. Future experiments aim to identify the underlying mechanism and consequences for NSTI patients.

A reference genome for ecological restoration of the sunflower sea star, Pycnopodia helianthoides.

Wildlife diseases, such as the sea star wasting (SSW) epizootic that outbroke in the mid-2010s, appear to be associated with acute and/or chronic abiotic environmental change; dissociating the effects of different drivers can be difficult. The sunflower sea star, Pycnopodia helianthoides, was the species most severely impacted during the SSW outbreak, which overlapped with periods of anomalous atmospheric and oceanographic conditions, and there is not yet a consensus on the cause(s). Genomic data may reveal underlying molecular signatures that implicate a subset of factors and, thus, clarify past events while also setting the scene for effective restoration efforts. To advance this goal, we used Pacific Biosciences HiFi long sequencing reads and Dovetail Omni-C proximity reads to generate a highly contiguous genome assembly that was then annotated using RNA-seq-informed gene prediction. The genome assembly is 484 Mb long, with contig N50 of 1.9 Mb, scaffold N50 of 21.8 Mb, BUSCO completeness score of 96.1%, and 22 major scaffolds consistent with prior evidence that sea star genomes comprise 22 autosomes. These statistics generally fall between those of other recently assembled chromosome-scale assemblies for two species in the distantly related asteroid genus Pisaster. These novel genomic resources for P. helianthoides will underwrite population genomic, comparative genomic, and phylogenomic analyses-as well as their integration across scales-of SSW and environmental stressors.

Galba: genome annotation with miniprot and AUGUSTUS.

BACKGROUND: The Earth Biogenome Project has rapidly increased the number of available eukaryotic genomes, but most released genomes continue to lack annotation of protein-coding genes. In addition, no transcriptome data is available for some genomes. RESULTS: Various gene annotation tools have been developed but each has its limitations. Here, we introduce GALBA, a fully automated pipeline that utilizes miniprot, a rapid protein-to-genome aligner, in combination with AUGUSTUS to predict genes with high accuracy. Accuracy results indicate that GALBA is particularly strong in the annotation of large vertebrate genomes. We also present use cases in insects, vertebrates, and a land plant. GALBA is fully open source and available as a docker image for easy execution with Singularity in high-performance computing environments. CONCLUSIONS: Our pipeline addresses the critical need for accurate gene annotation in newly sequenced genomes, and we believe that GALBA will greatly facilitate genome annotation for diverse organisms.

Neutrophil-derived reactive agents induce a transient SpeB negative phenotype in Streptococcus pyogenes.

BACKGROUND: Streptococcus pyogenes (group A streptococci; GAS) is the main causative pathogen of monomicrobial necrotizing soft tissue infections (NSTIs). To resist immuno-clearance, GAS adapt their genetic information and/or phenotype to the surrounding environment. Hyper-virulent streptococcal pyrogenic exotoxin B (SpeB) negative variants caused by covRS mutations are enriched during infection. A key driving force for this process is the bacterial Sda1 DNase. METHODS: Bacterial infiltration, immune cell influx, tissue necrosis and inflammation in patient´s biopsies were determined using immunohistochemistry. SpeB secretion and activity by GAS post infections or challenges with reactive agents were determined via Western blot or casein agar and proteolytic activity assays, respectively. Proteome of GAS single colonies and neutrophil secretome were profiled, using mass spectrometry. RESULTS: Here, we identify another strategy resulting in SpeB-negative variants, namely reversible abrogation of SpeB secretion triggered by neutrophil effector molecules. Analysis of NSTI patient tissue biopsies revealed that tissue inflammation, neutrophil influx, and degranulation positively correlate with increasing frequency of SpeB-negative GAS clones. Using single colony proteomics, we show that GAS isolated directly from tissue express but do not secrete SpeB. Once the tissue pressure is lifted, GAS regain SpeB secreting function. Neutrophils were identified as the main immune cells responsible for the observed phenotype. Subsequent analyses identified hydrogen peroxide and hypochlorous acid as reactive agents driving this phenotypic GAS adaptation to the tissue environment. SpeB-negative GAS show improved survival within neutrophils and induce increased degranulation. CONCLUSIONS: Our findings provide new information about GAS fitness and heterogeneity in the soft tissue milieu and provide new potential targets for therapeutic intervention in NSTIs.

The draft chromosome-level genome assembly of tetraploid ground cherry (Prunus fruticosa Pall.) from long reads.

Cherries are stone fruits and belong to the economically important plant family of Rosaceae with worldwide cultivation of different species. The ground cherry, Prunus fruticosa Pall., is an ancestor of cultivated sour cherry, an important tetraploid cherry species. Here, we present a long read chromosome-level draft genome assembly and related plastid sequences using the Oxford Nanopore Technology PromethION platform and R10.3 pore type. We generated a final consensus genome sequence of 366 Mb comprising eight chromosomes. The N50 scaffold was ~44 Mb with the longest chromosome being 66.5 Mb. The chloroplast and mitochondrial genomes were 158,217 bp and 383,281 bp long, which is in accordance with previously published plastid sequences. This is the first report of the genome of ground cherry (P. fruticosa) sequenced by long read technology only. The datasets obtained from this study provide a foundation for future breeding, molecular and evolutionary analysis in Prunus studies.

TSEBRA: transcript selector for BRAKER.

BACKGROUND: BRAKER is a suite of automatic pipelines, BRAKER1 and BRAKER2, for the accurate annotation of protein-coding genes in eukaryotic genomes. Each pipeline trains statistical models of protein-coding genes based on provided evidence and, then predicts protein-coding genes in genomic sequences using both the extrinsic evidence and statistical models. For training and prediction, BRAKER1 and BRAKER2 incorporate complementary extrinsic evidence: BRAKER1 uses only RNA-seq data while BRAKER2 uses only a database of cross-species proteins. The BRAKER suite has so far not been able to reliably exceed the accuracy of BRAKER1 and BRAKER2 when incorporating both types of evidence simultaneously. Currently, for a novel genome project where both RNA-seq and protein data are available, the best option is to run both pipelines independently, and to pick one, likely better output. Therefore, one or another type of the extrinsic evidence would remain unexploited. RESULTS: We present TSEBRA, a software that selects gene predictions (transcripts) from the sets generated by BRAKER1 and BRAKER2. TSEBRA uses a set of rules to compare scores of overlapping transcripts based on their support by RNA-seq and homologous protein evidence. We show in computational experiments on genomes of 11 species that TSEBRA achieves higher accuracy than either BRAKER1 or BRAKER2 running alone and that TSEBRA compares favorably with the combiner tool EVidenceModeler. CONCLUSION: TSEBRA is an easy-to-use and fast software tool. It can be used in concert with the BRAKER pipeline to generate a gene prediction set supported by both RNA-seq and homologous protein evidence.

Transposable elements and introgression introduce genetic variation in the invasive ant Cardiocondyla obscurior.

Introduced populations of invasive organisms have to cope with novel environmental challenges, while having reduced genetic variation caused by founder effects. The mechanisms associated with this "genetic paradox of invasive species" has received considerable attention, yet few studies have examined the genomic architecture of invasive species. Populations of the heart node ant Cardiocondyla obscurior belong to two distinct lineages, a New World lineage so far only found in Latin America and a more globally distributed Old World lineage. In the present study, we use population genomic approaches to compare populations of the two lineages with apparent divergent invasive potential. We find that the strong genetic differentiation of the two lineages began at least 40,000 generations ago and that activity of transposable elements (TEs) has contributed significantly to the divergence of both lineages, possibly linked to the very unusual genomic distribution of TEs in this species. Furthermore, we show that introgression from the Old World lineage is a dominant source of genetic diversity in the New World lineage, despite the lineages' strong genetic differentiation. Our study uncovers mechanisms underlying novel genetic variation in introduced populations of C. obscurior that could contribute to the species' adaptive potential.

An initial comparative genomic autopsy of wasting disease in sea stars.

Beginning in 2013, sea stars throughout the Eastern North Pacific were decimated by wasting disease, also known as "asteroid idiopathic wasting syndrome" (AIWS) due to its elusive aetiology. The geographic extent and taxonomic scale of AIWS meant events leading up to the outbreak were heterogeneous, multifaceted, and oftentimes unobserved; progression from morbidity to death was rapid, leaving few tell-tale symptoms. Here, we take a forensic genomic approach to discover candidate genes that may help explain sea star wasting syndrome. We report the first genome and annotation for Pisaster ochraceus, along with differential gene expression (DGE) analyses in four size classes, three tissue types, and in symptomatic and asymptomatic individuals. We integrate nucleotide polymorphisms associated with survivors of the wasting disease outbreak, DGE associated with temperature treatments in P. ochraceus, and DGE associated with wasting in another asteroid Pycnopodia helianthoides. In P. ochraceus, we found DGE across all tissues, among size classes, and between asymptomatic and symptomatic individuals; the strongest wasting-associated DGE signal was in pyloric caecum. We also found previously identified outlier loci co-occur with differentially expressed genes. In cross-species comparisons of symptomatic and asymptomatic individuals, consistent responses distinguish genes associated with invertebrate innate immunity and chemical defence, consistent with context-dependent stress responses, defensive apoptosis, and tissue degradation. Our analyses thus highlight genomic constituents that may link suspected environmental drivers (elevated temperature) with intrinsic differences among individuals (age/size, alleles associated with susceptibility) that elicit organismal responses (e.g., coelomocyte proliferation) and manifest as sea star wasting mass mortality.

VARUS: sampling complementary RNA reads from the sequence read archive.

BACKGROUND: Vast amounts of next generation sequencing RNA data has been deposited in archives, accompanying very diverse original studies. The data is readily available also for other purposes such as genome annotation or transcriptome assembly. However, selecting a subset of available experiments, sequencing runs and reads for this purpose is a nontrivial task and complicated by the inhomogeneity of the data. RESULTS: This article presents the software VARUS that selects, downloads and aligns reads from NCBI's Sequence Read Archive, given only the species' binomial name and genome. VARUS automatically chooses runs from among all archived runs to randomly select subsets of reads. The objective of its online algorithm is to cover a large number of transcripts adequately when network bandwidth and computing resources are limited. For most tested species VARUS achieved both a higher sensitivity and specificity with a lower number of downloaded reads than when runs were manually selected. At the example of twelve eukaryotic genomes, we show that RNA-Seq that was sampled with VARUS is well-suited for fully-automatic genome annotation with BRAKER. CONCLUSIONS: With VARUS, genome annotation can be automatized to the extent that not even the selection and quality control of RNA-Seq has to be done manually. This introduces the possibility to have fully automatized genome annotation loops over potentially many species without incurring a loss of accuracy over a manually supervised annotation process.

BRAKER1: Unsupervised RNA-Seq-Based Genome Annotation with GeneMark-ET and AUGUSTUS.

MOTIVATION: Gene finding in eukaryotic genomes is notoriously difficult to automate. The task is to design a work flow with a minimal set of tools that would reach state-of-the-art performance across a wide range of species. GeneMark-ET is a gene prediction tool that incorporates RNA-Seq data into unsupervised training and subsequently generates ab initio gene predictions. AUGUSTUS is a gene finder that usually requires supervised training and uses information from RNA-Seq reads in the prediction step. Complementary strengths of GeneMark-ET and AUGUSTUS provided motivation for designing a new combined tool for automatic gene prediction. RESULTS: We present BRAKER1, a pipeline for unsupervised RNA-Seq-based genome annotation that combines the advantages of GeneMark-ET and AUGUSTUS. As input, BRAKER1 requires a genome assembly file and a file in bam-format with spliced alignments of RNA-Seq reads to the genome. First, GeneMark-ET performs iterative training and generates initial gene structures. Second, AUGUSTUS uses predicted genes for training and then integrates RNA-Seq read information into final gene predictions. In our experiments, we observed that BRAKER1 was more accurate than MAKER2 when it is using RNA-Seq as sole source for training and prediction. BRAKER1 does not require pre-trained parameters or a separate expert-prepared training step. AVAILABILITY AND IMPLEMENTATION: BRAKER1 is available for download at http://bioinf.uni-greifswald.de/bioinf/braker/ and http://exon.gatech.edu/GeneMark/ CONTACT: katharina.hoff@uni-greifswald.de or borodovsky@gatech.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The nervous system of Xenacoelomorpha: a genomic perspective.

Xenacoelomorpha is, most probably, a monophyletic group that includes three clades: Acoela, Nemertodermatida and Xenoturbellida. The group still has contentious phylogenetic affinities; though most authors place it as the sister group of the remaining bilaterians, some would include it as a fourth phylum within the Deuterostomia. Over the past few years, our group, along with others, has undertaken a systematic study of the microscopic anatomy of these worms; our main aim is to understand the structure and development of the nervous system. This research plan has been aided by the use of molecular/developmental tools, the most important of which has been the sequencing of the complete genomes and transcriptomes of different members of the three clades. The data obtained has been used to analyse the evolutionary history of gene families and to study their expression patterns during development, in both space and time. A major focus of our research is the origin of 'cephalized' (centralized) nervous systems. How complex brains are assembled from simpler neuronal arrays has been a matter of intense debate for at least 100 years. We are now tackling this issue using Xenacoelomorpha models. These represent an ideal system for this work because the members of the three clades have nervous systems with different degrees of cephalization; from the relatively simple sub-epithelial net of Xenoturbella to the compact brain of acoels. How this process of 'progressive' cephalization is reflected in the genomes or transcriptomes of these three groups of animals is the subject of this paper.

WebAUGUSTUS--a web service for training AUGUSTUS and predicting genes in eukaryotes.

The prediction of protein coding genes is an important step in the annotation of newly sequenced and assembled genomes. AUGUSTUS is one of the most accurate tools for eukaryotic gene prediction. Here, we present WebAUGUSTUS, a web interface for training AUGUSTUS and predicting genes with AUGUSTUS. Depending on the needs of the user, WebAUGUSTUS generates training gene structures automatically. Besides a genome file, either a file with expressed sequence tags or a file with protein sequences is required for this step. Alternatively, it is possible to submit an externally generated training gene structure file and a genome file. The web service optimizes AUGUSTUS parameters and predicts genes with those parameters. WebAUGUSTUS is available at http://bioinf.uni-greifswald.de/webaugustus.

BRAKER3: Fully automated genome annotation using RNA-seq and protein evidence with GeneMark-ETP, AUGUSTUS and TSEBRA.

Gene prediction has remained an active area of bioinformatics research for a long time. Still, gene prediction in large eukaryotic genomes presents a challenge that must be addressed by new algorithms. The amount and significance of the evidence available from transcriptomes and proteomes vary across genomes, between genes and even along a single gene. User-friendly and accurate annotation pipelines that can cope with such data heterogeneity are needed. The previously developed annotation pipelines BRAKER1 and BRAKER2 use RNA-seq or protein data, respectively, but not both. A further significant performance improvement was made by the recently released GeneMark-ETP integrating all three data types. We here present the BRAKER3 pipeline that builds on GeneMark-ETP and AUGUSTUS and further improves accuracy using the TSEBRA combiner. BRAKER3 annotates protein-coding genes in eukaryotic genomes using both short-read RNA-seq and a large protein database, along with statistical models learned iteratively and specifically for the target genome. We benchmarked the new pipeline on genomes of 11 species under assumed level of relatedness of the target species proteome to available proteomes. BRAKER3 outperformed BRAKER1 and BRAKER2. The average transcript-level F1-score was increased by ~20 percentage points on average, while the difference was most pronounced for species with large and complex genomes. BRAKER3 also outperformed other existing tools, MAKER2, Funannotate and FINDER. The code of BRAKER3 is available on GitHub and as a ready-to-run Docker container for execution with Docker or Singularity. Overall, BRAKER3 is an accurate, easy-to-use tool for eukaryotic genome annotation.

Marine particle microbiomes during a spring diatom bloom contain active sulfate-reducing bacteria.

Phytoplankton blooms fuel marine food webs with labile dissolved carbon and also lead to the formation of particulate organic matter composed of living and dead algal cells. These particles contribute to carbon sequestration and are sites of intense algal-bacterial interactions, providing diverse niches for microbes to thrive. We analyzed 16S and 18S ribosomal RNA gene amplicon sequences obtained from 51 time points and metaproteomes from 3 time points during a spring phytoplankton bloom in a shallow location (6-10 m depth) in the North Sea. Particulate fractions larger than 10 µm diameter were collected at near daily intervals between early March and late May in 2018. Network analysis identified two major modules representing bacteria co-occurring with diatoms and with dinoflagellates, respectively. The diatom network module included known sulfate-reducing Desulfobacterota as well as potentially sulfur-oxidizing Ectothiorhodospiraceae. Metaproteome analyses confirmed presence of key enzymes involved in dissimilatory sulfate reduction, a process known to occur in sinking particles at greater depths and in sediments. Our results indicate the presence of sufficiently anoxic niches in the particle fraction of an active phytoplankton bloom to sustain sulfate reduction, and an important role of benthic-pelagic coupling for microbiomes in shallow environments. Our findings may have implications for the understanding of algal-bacterial interactions and carbon export during blooms in shallow-water coastal areas.

GALBA: Genome Annotation with Miniprot and AUGUSTUS.

The Earth Biogenome Project has rapidly increased the number of available eukaryotic genomes, but most released genomes continue to lack annotation of protein-coding genes. In addition, no transcriptome data is available for some genomes. Various gene annotation tools have been developed but each has its limitations. Here, we introduce GALBA, a fully automated pipeline that utilizes miniprot, a rapid protein- to-genome aligner, in combination with AUGUSTUS to predict genes with high accuracy. Accuracy results indicate that GALBA is particularly strong in the annotation of large vertebrate genomes. We also present use cases in insects, vertebrates, and a previously unannotated land plant. GALBA is fully open source and available as a docker image for easy execution with Singularity in high-performance computing environments. Our pipeline addresses the critical need for accurate gene annotation in newly sequenced genomes, and we believe that GALBA will greatly facilitate genome annotation for diverse organisms.

The structure of the tetraploid sour cherry 'Schattenmorelle' (Prunus cerasus L.) genome reveals insights into its segmental allopolyploid nature.

Sour cherry (Prunus cerasus L.) is an important allotetraploid cherry species that evolved in the Caspian Sea and Black Sea regions from a hybridization of the tetraploid ground cherry (Prunus fruticosa Pall.) and an unreduced pollen of the diploid sweet cherry (P. avium L.) ancestor. Details of when and where the evolution of this species occurred are unclear, as well as the effect of hybridization on the genome structure. To gain insight, the genome of the sour cherry cultivar 'Schattenmorelle' was sequenced using Illumina NovaSeqTM and Oxford Nanopore long-read technologies, resulting in a ~629-Mbp pseudomolecule reference genome. The genome could be separated into two subgenomes, with subgenome PceS_a originating from P. avium and subgenome PceS_f originating from P. fruticosa. The genome also showed size reduction compared to ancestral species and traces of homoeologous sequence exchanges throughout. Comparative analysis confirmed that the genome of sour cherry is segmental allotetraploid and evolved very recently in the past.

Genomic analysis of the international high-risk clonal lineage Klebsiella pneumoniae sequence type 395.

BACKGROUND: Klebsiella pneumoniae, which is frequently associated with hospital- and community-acquired infections, contains multidrug-resistant (MDR), hypervirulent (hv), non-MDR/non-hv as well as convergent representatives. It is known that mostly international high-risk clonal lineages including sequence types (ST) 11, 147, 258, and 307 drive their global spread. ST395, which was first reported in the context of a carbapenemase-associated outbreak in France in 2010, is a less well-characterized, yet emerging clonal lineage. METHODS: We computationally analyzed a large collection of K. pneumoniae ST395 genomes (n = 297) both sequenced in this study and reported previously. By applying multiple bioinformatics tools, we investigated the core-genome phylogeny and evolution of ST395 as well as distribution of accessory genome elements associated with antibiotic resistance and virulence features. RESULTS: Clustering of the core-SNP alignment revealed four major clades with eight smaller subclades. The subclades likely evolved through large chromosomal recombination, which involved different K. pneumoniae donors and affected, inter alia, capsule and lipopolysaccharide antigen biosynthesis regions. Most genomes contained acquired resistance genes to extended-spectrum cephalosporins, carbapenems, and other antibiotic classes carried by multiple plasmid types, and many were positive for hypervirulence markers, including the siderophore aerobactin. The detection of "hybrid" resistance and virulence plasmids suggests the occurrence of the convergent ST395 pathotype. CONCLUSIONS: To the best of our knowledge, this is the first study that investigated a large international collection of K. pneumoniae ST395 genomes and elucidated phylogenetics and detailed genomic characteristics of this emerging high-risk clonal lineage.