Computational Exploration of Virus Diversity on Transcriptomic Datasets

Most of the ongoing virus research is focused on mammalian and bird viruses, which are well known to be directly or indirectly associated with human diseases. While many viruses are transmitted by blood-feeding arthropods (Arboviruses), virus research on non-bloodfeeding arthropods has long been neglected. Within arthropods, insects are the most diverse animal group on earth and can be found in virtually every habitat. They play a key role in ecosystem health and thus set the basis for many environmental impact assessment studies. The under-estimation of viral diversity was recently made evident by broad sampling of arthropods and other invertebrates. Knowledge about viruses in insects can therefore give insight on the emergence and evolution of viruses. Discovery of yet unknown viruses and consequently, preparedness for emerging diseases are vital to prevent epidemics, especially in the context of globalization. Advancements in metagenomics with rapid growth of available gene databases in recent years have facilitated the exploration of virus diversity. Transcriptomes from the ’1000 Insect Transcriptome Evolution Project’ (1KITE; http: //1kite.org) have been screened for several groups of RNA viruses. In contrast to a genome, where DNA is sequenced, RNA of a sample is sequenced for a transcriptome. Therefore, only expressed genes of an organism is present in a transcriptome. However, it may contain RNA of viral origin as well. This dataset contains transcriptomes of over 1000 different arthropod species covering all extant orders of hexapods. The primary goal of 1KITE is to solve questions about the evolution of insects but in this study the focus is on the broad range of novel viruses that is expected to be within this large dataset. Since viruses have very high mutation rates and databases have a bias towards viruses that have an impact on humans, livestock, and agriculture, it is required to combine expert knowledge with sensitive search algorithms and appropriate support tools. A new kind of bioinformatic consistency-based virus detection pipeline called TRAVIS (TRAnscriptome VIrus Scanner) is proposed in this study. It is designed for the sensitive mass screening of transcriptomic data directed towards a specific virus group in order to find new, distantly related viruses in addition to closely related. It uses different search algorithms including BLAST, profile Hidden Markov Models (HMMER3) and a new k-mer approach implemented in MMSeqs2. The computational work-flow is mostly automated and delivers statistical and visual output for improved result evaluation. Specific databases containing different groups of RNA-viruses were used to systematically scan the 1KITE transcriptomes. Hundreds of potential new viruses were identified and partially characterized. While some of those viruses could have been assigned to existing taxonomical groups, the phylogenetic distance of many findings indicate novel virus genera and families

Statistical mechanics of two-dimensional shuffled foams: Geometry-topology correlation in small or large disorder limits

Bubble monolayers are model systems for experiments and simulations of two-dimensional packing problems of deformable objects. We explore the relation between the distributions of the number of bubble sides (topology) and the bubble areas (geometry) in the low liquid fraction limit. We use a statistical model [M. Durand, Europhys. Lett. 90, 60002 (2010)] which takes into account Plateau laws. We predict the correlation between geometrical disorder (bubble size dispersity) and topological disorder (width of bubble side number distribution) over an extended range of bubble size dispersities. Extensive data sets arising from shuffled foam experiments, surface evolver simulations, and cellular Potts model simulations all collapse surprisingly well and coincide with the model predictions, even at extremely high size dispersity. At moderate size dispersity, we recover our earlier approximate predictions [M. Durand, J. Kafer, C. Quilliet, S. Cox, S. A. Talebi, and F. Graner, Phys. Rev. Lett. 107, 168304 (2011)]. At extremely low dispersity, when approaching the perfectly regular honeycomb pattern, we study how both geometrical and topological disorders vanish. We identify a crystallization mechanism and explore it quantitatively in the case of bidisperse foams. Due to the deformability of the bubbles, foams can crystallize over a larger range of size dispersities than hard disks. The model predicts that the crystallization transition occurs when the ratio of largest to smallest bubble radii is 1.4

Re-assessing the diversity of negative strand RNA viruses in insects.

The spectrum of viruses in insects is important for subjects as diverse as public health, veterinary medicine, food production, and biodiversity conservation. The traditional interest in vector-borne diseases of humans and livestock has drawn the attention of virus studies to hematophagous insect species. However, these represent only a tiny fraction of the broad diversity of Hexapoda, the most speciose group of animals. Here, we systematically probed the diversity of negative strand RNA viruses in the largest and most representative collection of insect transcriptomes from samples representing all 34 extant orders of Hexapoda and 3 orders of Entognatha, as well as outgroups, altogether representing 1243 species. Based on profile hidden Markov models we detected 488 viral RNA-directed RNA polymerase (RdRp) sequences with similarity to negative strand RNA viruses. These were identified in members of 324 arthropod species. Selection for length, quality, and uniqueness left 234 sequences for analyses, showing similarity to genomes of viruses classified in Bunyavirales (n = 86), Articulavirales (n = 54), and several orders within Haploviricotina (n = 94). Coding-complete genomes or nearly-complete subgenomic assemblies were obtained in 61 cases. Based on phylogenetic topology and the availability of coding-complete genomes we estimate that at least 20 novel viral genera in seven families need to be defined, only two of them monospecific. Seven additional viral clades emerge when adding sequences from the present study to formerly monospecific lineages, potentially requiring up to seven additional genera. One long sequence may indicate a novel family. For segmented viruses, cophylogenies between genome segments were generally improved by the inclusion of viruses from the present study, suggesting that in silico misassembly of segmented genomes is rare or absent. Contrary to previous assessments, significant virus-host codivergence was identified in major phylogenetic lineages based on two different approaches of codivergence analysis in a hypotheses testing framework. In spite of these additions to the known spectrum of viruses in insects, we caution that basing taxonomic decisions on genome information alone is challenging due to technical uncertainties, such as the inability to prove integrity of complete genome assemblies of segmented viruses

Multiple Nuclear Gene Phylogenetic Analysis of the Evolution of Dioecy and Sex Chromosomes in the Genus Silene

In the plant genus Silene, separate sexes and sex chromosomes are believed to have evolved twice. Silene species that are wholly or largely hermaphroditic are assumed to represent the ancestral state from which dioecy evolved. This assumption is important for choice of outgroup species for inferring the genetic and chromosomal changes involved in the evolution of dioecy, but is mainly based on data from a single locus (ITS). To establish the order of events more clearly, and inform outgroup choice, we therefore carried out (i) multi-nuclear-gene phylogenetic analyses of 14 Silene species (including 7 hermaphrodite or gynodioecious species), representing species from both Silene clades with dioecious members, plus a more distantly related outgroup, and (ii) a BayesTraits character analysis of the evolution of dioecy. We confirm two origins of dioecy within this genus in agreement with recent work on comparing sex chromosomes from both clades with dioecious species. We conclude that sex chromosomes evolved after the origin of Silene and within a clade that includes only S. latifolia and its closest relatives. We estimate that sex chromosomes emerged soon after the split with the ancestor of S. viscosa, the probable closest non-dioecious S. latifolia relative among the species included in our study

TRAVIS Singularity Image

Singularity image mentioned here : https://github.com/kaefers/travis</p

Back to the trees: Identifying plants with Human Intelligence

International audienceWe investigate a way to build a convivial plant identification tool halfway between the complex determination keys of botanists and the more recent but poorly explainable approaches based on AI image recognition. Our approach consists of a formal language to organize morphological traits and a Bayesian technique to describe plants with possible polymorphisms at all taxonomic levels, and to handle errors and uncertainties. From these structured data, automatic approaches can be designed to generate versatile determination keys, i.e. decision trees, which are otherwise tedious to design by hand

Untangling an insect’s virome from its endogenous viral elements

Abstract Background Insects are an important reservoir of viral biodiversity, but the vast majority of viruses associated with insects have not been discovered. Recent studies have employed high-throughput RNA sequencing, which has led to rapid advances in our understanding of insect viral diversity. However, insect genomes frequently contain transcribed endogenous viral elements (EVEs) with significant homology to exogenous viruses, complicating the use of RNAseq for viral discovery. Methods In this study, we used a multi-pronged sequencing approach to study the virome of an important agricultural pest and prolific vector of plant pathogens, the potato aphid Macrosiphum euphorbiae. We first used rRNA-depleted RNAseq to characterize the microbes found in individual insects. We then used PCR screening to measure the frequency of two heritable viruses in a local aphid population. Lastly, we generated a quality draft genome assembly for M. euphorbiae using Illumina-corrected Nanopore sequencing to identify transcriptionally active EVEs in the host genome. Results We found reads from two insect-specific viruses (a Flavivirus and an Ambidensovirus) in our RNAseq data, as well as a parasitoid virus (Bracovirus), a plant pathogenic virus (Tombusvirus), and two phages (Acinetobacter and APSE). However, our genome assembly showed that part of the ‘virome’ of this insect can be attributed to EVEs in the host genome. Conclusion Our work shows that EVEs have led to the misidentification of aphid viruses from RNAseq data, and we argue that this is a widespread challenge for the study of viral diversity in insects