In-depth exploration of the genomic diversity in tea varieties based on a newly constructed pangenome of Camellia sinensis.

Tea, one of the most widely consumed beverages globally, exhibits remarkable genomic diversity in its underlying flavour and health-related compounds. In this study, we present the construction and analysis of a tea pangenome comprising a total of 11 genomes, with a focus on three newly sequenced genomes comprising the purple-leaved assamica cultivar "Zijuan", the temperature-sensitive sinensis cultivar "Anjibaicha" and the wild accession "L618" whose assemblies exhibited excellent quality scores as they profited from latest sequencing technologies. Our analysis incorporates a detailed investigation of transposon complement across the tea pangenome, revealing shared patterns of transposon distribution among the studied genomes and improved transposon resolution with long read technologies, as shown by long terminal repeat (LTR) Assembly Index analysis. Furthermore, our study encompasses a gene-centric exploration of the pangenome, exploring the genomic landscape of the catechin pathway with our study, providing insights on copy number alterations and gene-centric variants, especially for Anthocyanidin synthases. We constructed a gene-centric pangenome by structurally and functionally annotating all available genomes using an identical pipeline, which both increased gene completeness and allowed for a high functional annotation rate. This improved and consistently annotated gene set will allow for a better comparison between tea genomes. We used this improved pangenome to capture the core and dispensable gene repertoire, elucidating the functional diversity present within the tea species. This pangenome resource might serve as a valuable resource for understanding the fundamental genetic basis of traits such as flavour, stress tolerance, and disease resistance, with implications for tea breeding programmes.

RdRp-scan: A bioinformatic resource to identify and annotate divergent RNA viruses in metagenomic sequence data.

Despite a rapid expansion in the number of documented viruses following the advent of metagenomic sequencing, the identification and annotation of highly divergent RNA viruses remain challenging, particularly from poorly characterized hosts and environmental samples. Protein structures are more conserved than primary sequence data, such that structure-based comparisons provide an opportunity to reveal the viral 'dusk matter': viral sequences with low, but detectable, levels of sequence identity to known viruses with available protein structures. Here, we present a new open computational resource-RdRp-scan-that contains a standardized bioinformatic toolkit to identify and annotate divergent RNA viruses in metagenomic sequence data based on the detection of RNA-dependent RNA polymerase (RdRp) sequences. By combining RdRp-specific hidden Markov models (HMMs) and structural comparisons, we show that RdRp-scan can efficiently detect RdRp sequences with identity levels as low as 10 per cent to those from known viruses and not identifiable using standard sequence-to-sequence comparisons. In addition, to facilitate the annotation and placement of newly detected and divergent virus-like sequences into the diversity of RNA viruses, RdRp-scan provides new custom and curated databases of viral RdRp sequences and core motifs, as well as pre-built RdRp multiple sequence alignments. In parallel, our analysis of the sequence diversity detected by the RdRp-scan revealed that while most of the taxonomically unassigned RdRps fell into pre-established clusters, some fell into potentially new orders of RNA viruses related to the Wolframvirales and Tolivirales. Finally, a survey of the conserved A, B, and C RdRp motifs within the RdRp-scan sequence database revealed additional variations of both sequence and position that might provide new insights into the structure, function, and evolution of viral polymerases.

Collecting and managing taxonomic data with NCBI-taxonomist.

SUMMARY: We present NCBI-taxonomist-a command-line tool written in Python that collects and manages taxonomic data from the National Center for Biotechnology Information (NCBI). NCBI-taxonomist does not depend on a pre-downloaded taxonomic database but can store data locally. NCBI-taxonomist has six commands to map, collect, extract, resolve, import and group taxonomic data that can be linked together to create powerful analytical pipelines. Because many lifescience databases use the same taxonomic information, the data managed by NCBI-taxonomist is not limited to NCBI and can be used to find data linked to taxonomic information present in other scientific databases. AVAILABILITY AND IMPLEMENTATION: NCBI-taxonomist is implemented in Python 3 (≥3.8) and available at https://gitlab.com/janpb/ncbi-taxonomist and via PyPi (https://pypi.org/project/ncbi-taxonomist/), as a Docker container (https://gitlab.com/janpb/ncbi-taxonomist/container_registry/) and Singularity (v3.5.3) image (https://cloud.sylabs.io/library/jpb/ncbi-taxonomist). NCBI-taxonomist is licensed under the GPLv3.

NCBI's Virus Discovery Codeathon: Building "FIVE" -The Federated Index of Viral Experiments API Index.

Viruses represent important test cases for data federation due to their genome size and the rapid increase in sequence data in publicly available databases. However, some consequences of previously decentralized (unfederated) data are lack of consensus or comparisons between feature annotations. Unifying or displaying alternative annotations should be a priority both for communities with robust entry representation and for nascent communities with burgeoning data sources. To this end, during this three-day continuation of the Virus Hunting Toolkit codeathon series (VHT-2), a new integrated and federated viral index was elaborated. This Federated Index of Viral Experiments (FIVE) integrates pre-existing and novel functional and taxonomy annotations and virus-host pairings. Variability in the context of viral genomic diversity is often overlooked in virus databases. As a proof-of-concept, FIVE was the first attempt to include viral genome variation for HIV, the most well-studied human pathogen, through viral genome diversity graphs. As per the publication of this manuscript, FIVE is the first implementation of a virus-specific federated index of such scope. FIVE is coded in BigQuery for optimal access of large quantities of data and is publicly accessible. Many projects of database or index federation fail to provide easier alternatives to access or query information. To this end, a Python API query system was developed to enhance the accessibility of FIVE.

CCMetagen: comprehensive and accurate identification of eukaryotes and prokaryotes in metagenomic data.

There is an increasing demand for accurate and fast metagenome classifiers that can not only identify bacteria, but all members of a microbial community. We used a recently developed concept in read mapping to develop a highly accurate metagenomic classification pipeline named CCMetagen. The pipeline substantially outperforms other commonly used software in identifying bacteria and fungi and can efficiently use the entire NCBI nucleotide collection as a reference to detect species with incomplete genome data from all biological kingdoms. CCMetagen is user-friendly, and the results can be easily integrated into microbial community analysis software for streamlined and automated microbiome studies.

Coding-Complete Genome Sequence of Yada Yada Virus, a Novel Alphavirus Detected in Australian Mosquitoes.

Here, we report the detection of a novel alphavirus in Australian mosquitoes, provisionally named Yada Yada virus (YYV). Phylogenetic analysis indicated that YYV belongs to the mosquito-specific alphavirus complex. The assembled genome is 11,612 nucleotides in length and encodes two open reading frames.

NCBI's Virus Discovery Hackathon: Engaging Research Communities to Identify Cloud Infrastructure Requirements.

A wealth of viral data sits untapped in publicly available metagenomic data sets when it might be extracted to create a usable index for the virological research community. We hypothesized that work of this complexity and scale could be done in a hackathon setting. Ten teams comprised of over 40 participants from six countries, assembled to create a crowd-sourced set of analysis and processing pipelines for a complex biological data set in a three-day event on the San Diego State University campus starting 9 January 2019. Prior to the hackathon, 141,676 metagenomic data sets from the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) were pre-assembled into contiguous assemblies (contigs) by NCBI staff. During the hackathon, a subset consisting of 2953 SRA data sets (approximately 55 million contigs) was selected, which were further filtered for a minimal length of 1 kb. This resulted in 4.2 million (Mio) contigs, which were aligned using BLAST against all known virus genomes, phylogenetically clustered and assigned metadata. Out of the 4.2 Mio contigs, 360,000 contigs were labeled with domains and an additional subset containing 4400 contigs was screened for virus or virus-like genes. The work yielded valuable insights into both SRA data and the cloud infrastructure required to support such efforts, revealing analysis bottlenecks and possible workarounds thereof. Mainly: (i) Conservative assemblies of SRA data improves initial analysis steps; (ii) existing bioinformatic software with weak multithreading/multicore support can be elevated by wrapper scripts to use all cores within a computing node; (iii) redesigning existing bioinformatic algorithms for a cloud infrastructure to facilitate its use for a wider audience; and (iv) a cloud infrastructure allows a diverse group of researchers to collaborate effectively. The scientific findings will be extended during a follow-up event. Here, we present the applied workflows, initial results, and lessons learned from the hackathon.

Entrezpy: a Python library to dynamically interact with the NCBI Entrez databases.

SUMMARY: Entrezpy is a Python library that automates the querying and downloading of data from the Entrez databases at National Center for Biotechnology Information by interacting with E-Utilities. Entrezpy implements complex queries by automatically creating E-Utility parameters from the results obtained that can then be used directly in subsequent queries. Entrezpy also allows the user to cache and retrieve results locally, implements interactions with all Entrez databases as part of an analysis pipeline and adjusts parameters within an ongoing query or using prior results. Entrezpy's modular design enables it to easily extend and adjust existing E-Utility functions. AVAILABILITY AND IMPLEMENTATION: Entrezpy is implemented in Python 3 (≥3.6) and depends only on the Python Standard Library. It is available via PyPi (https://pypi.org/project/entrezpy/) and at https://gitlab.com/ncbipy/entrezpy.git. Entrezpy is licensed under the LGPLv3 and also at http://entrezpy.readthedocs.io/.

A Simple Method to Detect Candidate Overlapping Genes in Viruses Using Single Genome Sequences.

Overlapping genes in viruses maximize the coding capacity of their genomes and allow the generation of new genes without major increases in genome size. Despite their importance, the evolution and function of overlapping genes are often not well understood, in part due to difficulties in their detection. In addition, most bioinformatic approaches for the detection of overlapping genes require the comparison of multiple genome sequences that may not be available in metagenomic surveys of virus biodiversity. We introduce a simple new method for identifying candidate functional overlapping genes using single virus genome sequences. Our method uses randomization tests to estimate the expected length of open reading frames and then identifies overlapping open reading frames that significantly exceed this length and are thus predicted to be functional. We applied this method to 2548 reference RNA virus genomes and find that it has both high sensitivity and low false discovery for genes that overlap by at least 50 nucleotides. Notably, this analysis provided evidence for 29 previously undiscovered functional overlapping genes, some of which are coded in the antisense direction suggesting there are limitations in our current understanding of RNA virus replication.

The Biological Object Notation (BON): a structured file format for biological data.

The large size and high complexity of biological data can represent a major methodological challenge for the analysis and exchange of data sets between computers and applications. There has also been a substantial increase in the amount of metadata associated with biological data sets, which is being increasingly incorporated into existing data formats. Despite the existence of structured formats based on XML, biological data sets are mainly formatted using unstructured file formats, and the incorporation of metadata results in increasingly complex parsing routines such that they become more error prone. To overcome these problems, we present the "biological object notation" (BON) format, a new way to exchange and parse nearly all biological data sets more efficiently and with less error than other currently available formats. Based on JavaScript Object Notation (JSON), BON simplifies parsing by clearly separating the biological data from its metadata and reduces complexity compared to XML based formats. The ability to selectively compress data up to 87% compared to other file formats and the reduced complexity results in improved transfer times and less error prone applications.

Virological Sampling of Inaccessible Wildlife with Drones.

There is growing interest in characterizing the viromes of diverse mammalian species, particularly in the context of disease emergence. However, little is known about virome diversity in aquatic mammals, in part due to difficulties in sampling. We characterized the virome of the exhaled breath (or blow) of the Eastern Australian humpback whale (Megaptera novaeangliae). To achieve an unbiased survey of virome diversity, a meta-transcriptomic analysis was performed on 19 pooled whale blow samples collected via a purpose-built Unmanned Aerial Vehicle (UAV, or drone) approximately 3 km off the coast of Sydney, Australia during the 2017 winter annual northward migration from Antarctica to northern Australia. To our knowledge, this is the first time that UAVs have been used to sample viruses. Despite the relatively small number of animals surveyed in this initial study, we identified six novel virus species from five viral families. This work demonstrates the potential of UAVs in studies of virus disease, diversity, and evolution.

17th Century Variola Virus Reveals the Recent History of Smallpox.

Smallpox holds a unique position in the history of medicine. It was the first disease for which a vaccine was developed and remains the only human disease eradicated by vaccination. Although there have been claims of smallpox in Egypt, India, and China dating back millennia [1-4], the timescale of emergence of the causative agent, variola virus (VARV), and how it evolved in the context of increasingly widespread immunization, have proven controversial [4-9]. In particular, some molecular-clock-based studies have suggested that key events in VARV evolution only occurred during the last two centuries [4-6] and hence in apparent conflict with anecdotal historical reports, although it is difficult to distinguish smallpox from other pustular rashes by description alone. To address these issues, we captured, sequenced, and reconstructed a draft genome of an ancient strain of VARV, sampled from a Lithuanian child mummy dating between 1643 and 1665 and close to the time of several documented European epidemics [1, 2, 10]. When compared to vaccinia virus, this archival strain contained the same pattern of gene degradation as 20th century VARVs, indicating that such loss of gene function had occurred before ca. 1650. Strikingly, the mummy sequence fell basal to all currently sequenced strains of VARV on phylogenetic trees. Molecular-clock analyses revealed a strong clock-like structure and that the timescale of smallpox evolution is more recent than often supposed, with the diversification of major viral lineages only occurring within the 18th and 19th centuries, concomitant with the development of modern vaccination.

Fire blight disease reactome: RNA-seq transcriptional profile of apple host plant defense responses to Erwinia amylovora pathogen infection.

The molecular basis of resistance and susceptibility of host plants to fire blight, a major disease threat to pome fruit production globally, is largely unknown. RNA-sequencing data from challenged and mock-inoculated flowers were analyzed to assess the susceptible response of apple to the fire blight pathogen Erwinia amylovora. In presence of the pathogen 1,080 transcripts were differentially expressed at 48 h post inoculation. These included putative disease resistance, stress, pathogen related, general metabolic, and phytohormone related genes. Reads, mapped to regions on the apple genome where no genes were assigned, were used to identify potential novel genes and open reading frames. To identify transcripts specifically expressed in response to E. amylovora, RT-PCRs were conducted and compared to the expression patterns of the fire blight biocontrol agent Pantoea vagans strain C9-1, another apple pathogen Pseudomonas syringae pv. papulans, and mock inoculated apple flowers. This led to the identification of a peroxidase superfamily gene that was lower expressed in response to E. amylovora suggesting a potential role in the susceptibility response. Overall, this study provides the first transcriptional profile by RNA-seq of the host plant during fire blight disease and insights into the response of susceptible apple plants to E. amylovora.

Cell Walls and the Convergent Evolution of the Viral Envelope.

Why some viruses are enveloped while others lack an outer lipid bilayer is a major question in viral evolution but one that has received relatively little attention. The viral envelope serves several functions, including protecting the RNA or DNA molecule(s), evading recognition by the immune system, and facilitating virus entry. Despite these commonalities, viral envelopes come in a wide variety of shapes and configurations. The evolution of the viral envelope is made more puzzling by the fact that nonenveloped viruses are able to infect a diverse range of hosts across the tree of life. We reviewed the entry, transmission, and exit pathways of all (101) viral families on the 2013 International Committee on Taxonomy of Viruses (ICTV) list. By doing this, we revealed a strong association between the lack of a viral envelope and the presence of a cell wall in the hosts these viruses infect. We were able to propose a new hypothesis for the existence of enveloped and nonenveloped viruses, in which the latter represent an adaptation to cells surrounded by a cell wall, while the former are an adaptation to animal cells where cell walls are absent. In particular, cell walls inhibit viral entry and exit, as well as viral transport within an organism, all of which are critical waypoints for successful infection and spread. Finally, we discuss how this new model for the origin of the viral envelope impacts our overall understanding of virus evolution.

Distinct lineages of Ebola virus in Guinea during the 2014 West African epidemic.

An epidemic of Ebola virus disease of unprecedented scale has been ongoing for more than a year in West Africa. As of 29 April 2015, there have been 26,277 reported total cases (of which 14,895 have been laboratory confirmed) resulting in 10,899 deaths. The source of the outbreak was traced to the prefecture of Guéckédou in the forested region of southeastern Guinea. The virus later spread to the capital, Conakry, and to the neighbouring countries of Sierra Leone, Liberia, Nigeria, Senegal and Mali. In March 2014, when the first cases were detected in Conakry, the Institut Pasteur of Dakar, Senegal, deployed a mobile laboratory in Donka hospital to provide diagnostic services to the greater Conakry urban area and other regions of Guinea. Through this process we sampled 85 Ebola viruses (EBOV) from patients infected from July to November 2014, and report their full genome sequences here. Phylogenetic analysis reveals the sustained transmission of three distinct viral lineages co-circulating in Guinea, including the urban setting of Conakry and its surroundings. One lineage is unique to Guinea and closely related to the earliest sampled viruses of the epidemic. A second lineage contains viruses probably reintroduced from neighbouring Sierra Leone on multiple occasions, while a third lineage later spread from Guinea to Mali. Each lineage is defined by multiple mutations, including non-synonymous changes in the virion protein 35 (VP35), glycoprotein (GP) and RNA-dependent RNA polymerase (L) proteins. The viral GP is characterized by a glycosylation site modification and mutations in the mucin-like domain that could modify the outer shape of the virion. These data illustrate the ongoing ability of EBOV to develop lineage-specific and potentially phenotypically important variation.

Analysis of CACTA transposases reveals intron loss as major factor influencing their exon/intron structure in monocotyledonous and eudicotyledonous hosts.

BACKGROUND: CACTA elements are DNA transposons and are found in numerous organisms. Despite their low activity, several thousand copies can be identified in many genomes. CACTA elements transpose using a 'cut-and-paste' mechanism, which is facilitated by a DDE transposase. DDE transposases from CACTA elements contain, despite their conserved function, different exon numbers among various CACTA families. While earlier studies analyzed the ancestral history of the DDE transposases, no studies have examined exon loss and gain with a view of mechanisms that could drive the changes. RESULTS: We analyzed 64 transposases from different CACTA families among monocotyledonous and eudicotyledonous host species. The annotation of the exon/intron boundaries showed a range from one to six exons. A robust multiple sequence alignment of the 64 transposases based on their protein sequences was created and used for phylogenetic analysis, which revealed eight different clades. We observed that the exon numbers in CACTA transposases are not specific for a host genome. We found that ancient CACTA lineages diverged before the divergence of monocotyledons and eudicotyledons. Most exon/intron boundaries were found in three distinct regions among all the transposases, grouping 63 conserved intron/exon boundaries. CONCLUSIONS: We propose a model for the ancestral CACTA transposase gene, which consists of four exons, that predates the divergence of the monocotyledons and eudicotyledons. Based on this model, we propose pathways of intron loss or gain to explain the observed variation in exon numbers. While intron loss appears to have prevailed, a putative case of intron gain was nevertheless observed.

The Tvv1 retrotransposon family is conserved between plant genomes separated by over 100 million years.

KEY MESSAGE: Combining several different approaches, we have examined the structure, variability, and distribution of Tvv1 retrotransposons. Tvv1 is an unusual example of a low-copy retrotransposon metapopulation dispersed unevenly among very distant species and is promising for the development of molecular markers. Retrotransposons are ubiquitous throughout the genomes of the vascular plants, but individual retrotransposon families tend to be confined to the level of plant genus or at most family. This restricts the general applicability of a family as molecular markers. Here, we characterize a new plant retrotransposon named Tvv1_Sdem, a member of the Copia superfamily of LTR retrotransposons, from the genome of the wild potato Solanum demissum. Comparative analyses based on structure and sequence showed a high level of similarity of Tvv1_Sdem with Tvv1-VB, a retrotransposon previously described in the grapevine genome Vitis vinifera. Extending the analysis to other species by in silico and in vitro approaches revealed the presence of Tvv1 family members in potato, tomato, and poplar genomes, and led to the identification of full-length copies of Tvv1 in these species. We were also able to identify polymorphism in UTL sequences between Tvv1_Sdem copies from wild and cultivated potatoes that are useful as molecular markers. Combining different approaches, our results suggest that the Tvv1 family of retrotransposons has a monophyletic origin and has been maintained in both the rosids and the asterids, the major clades of dicotyledonous plants, since their divergence about 100 MYA. To our knowledge, Tvv1 represents an unusual plant retrotransposon metapopulation comprising highly similar members disjointedly dispersed among very distant species. The twin features of Tvv1 presence in evolutionarily distant genomes and the diversity of its UTL region in each species make it useful as a source of robust molecular markers for diversity studies and breeding.

The wheat powdery mildew genome shows the unique evolution of an obligate biotroph.

Wheat powdery mildew, Blumeria graminis forma specialis tritici, is a devastating fungal pathogen with a poorly understood evolutionary history. Here we report the draft genome sequence of wheat powdery mildew, the resequencing of three additional isolates from different geographic regions and comparative analyses with the barley powdery mildew genome. Our comparative genomic analyses identified 602 candidate effector genes, with many showing evidence of positive selection. We characterize patterns of genetic diversity and suggest that mildew genomes are mosaics of ancient haplogroups that existed before wheat domestication. The patterns of diversity in modern isolates suggest that there was no pronounced loss of genetic diversity upon formation of the new host bread wheat 10,000 years ago. We conclude that the ready adaptation of B. graminis f.sp. tritici to the new host species was based on a diverse haplotype pool that provided great genetic potential for pathogen variation.

Genotype-specific SNP map based on whole chromosome 3B sequence information from wheat cultivars Arina and Forno.

Agronomically important traits are frequently controlled by rare, genotype-specific alleles. Such genes can only be mapped in a population derived from the donor genotype. This requires the development of a specific genetic map, which is difficult in wheat because of the low level of polymorphism among elite cultivars. The absence of sufficient polymorphism, the complexity of the hexaploid wheat genome as well as the lack of complete sequence information make the construction of genetic maps with a high density of reproducible and polymorphic markers challenging. We developed a genotype-specific genetic map of chromosome 3B from winter wheat cultivars Arina and Forno. Chromosome 3B was isolated from the two cultivars and then sequenced to 10-fold coverage. This resulted in a single-nucleotide polymorphisms (SNP) database of the complete chromosome. Based on proposed synteny with the Brachypodium model genome and gene annotation, sequences close to coding regions were used for the development of 70 SNP-based markers. They were mapped on a Arina × Forno Recombinant Inbred Lines population and found to be spread over the complete chromosome 3B. While overall synteny was well maintained, numerous exceptions and inversions of syntenic gene order were identified. Additionally, we found that the majority of recombination events occurred in distal parts of chromosome 3B, particularly in hot-spot regions. Compared with the earlier map based on SSR and RFLP markers, the number of markers increased fourfold. The approach presented here allows fast development of genotype-specific polymorphic markers that can be used for mapping and marker-assisted selection.