Spatio-temporal spread of Lassa virus and a new rodent host in the Mano River Union area, West Africa.

The spread of Lassa virus (LASV) in Guinea, Liberia and Sierra Leone, which together are named the Mano River Union (MRU) area, was examined phylogeographically. To provide a reliable evolutionary scenario, new rodent-derived, whole LASV sequences were included. These were generated by metatranscriptomic next-generation sequencing from rodents sampled between 2003 and 2020 in 21 localities of Guinea and Sierra Leone. An analysis was performed using BEAST to perform continuous phylogeographic inference and EvoLaps v36 to visualize spatio-temporal spread. LASV was identified as expected in its primary host reservoir, the Natal multimammate mouse (Mastomys natalensis), and also in two Guinean multimammate mice (Mastomys erythroleucus) in northern Sierra Leone and two rusty-bellied brush-furred mice (Lophuromys sikapusi) in southern Sierra Leone. This finding is consistent with the latter two species being secondary host reservoirs. The strains in these three species were very closely related in LASV lineage IV. Phylogenetic analysis indicated that the most recent common ancestor of lineage IV existed 316-374 years ago and revealed distinct, well-supported clades from Sierra Leone (Bo, Kabala and Kenema), Guinea (Faranah, Kissidougou-Guekedou and Macenta) and Liberia (Phebe-Ganta). The phylogeographic scenario suggests southern Guinea as the point of origin of LASV in the MRU area, with subsequent spread to towards Mali, Liberia and Sierra Leone at a mean speed of 1.6 to 1.1 km/year.

Genome sequence of white sturgeon herpesvirus 1 isolated from farmed white sturgeon (Acipenser transmontanus).

The genome sequence of white sturgeon herpesvirus 1, which was isolated from farmed white sturgeon (Acipenser transmontanus), was determined. Comparative analyses suggest the classification of this virus as a new species in a new genus in the family Alloherpesviridae.

Isolation and genome sequencing of cytomegaloviruses from Natal multimammate mice (Mastomys natalensis).

Distinct cytomegaloviruses (CMVs) are widely distributed across their mammalian hosts in a highly host species-restricted pattern. To date, evidence demonstrating this has been limited largely to PCR-based approaches targeting small, conserved genomic regions, and only a few complete genomes of isolated viruses representing distinct CMV species have been sequenced. We have now combined direct isolation of infectious viruses from tissues with complete genome sequencing to provide a view of CMV diversity in a wild animal population. We targeted Natal multimammate mice (Mastomys natalensis), which are common in sub-Saharan Africa, are known to carry a variety of zoonotic pathogens, and are regarded as the primary source of Lassa virus (LASV) spillover into humans. Using transformed epithelial cells prepared from M. natalensis kidneys, we isolated CMVs from the salivary gland tissue of 14 of 37 (36 %) animals from a field study site in Mali. Genome sequencing showed that these primary isolates represent three different M. natalensis CMVs (MnatCMVs: MnatCMV1, MnatCMV2 and MnatCMV3), with some animals carrying multiple MnatCMVs or multiple strains of a single MnatCMV presumably as a result of coinfection or superinfection. Including primary isolates and plaque-purified isolates, we sequenced and annotated the genomes of two MnatCMV1 strains (derived from sequencing 14 viruses), six MnatCMV2 strains (25 viruses) and ten MnatCMV3 strains (21 viruses), totalling 18 MnatCMV strains isolated as 60 infectious viruses. Phylogenetic analysis showed that these MnatCMVs group with other murid viruses in the genus Muromegalovirus (subfamily Betaherpesvirinae, family Orthoherpesviridae), and that MnatCMV1 and MnatCMV2 are more closely related to each other than to MnatCMV3. The availability of MnatCMV isolates and the characterization of their genomes will serve as the prelude to the generation of a MnatCMV-based vaccine to target LASV in the M. natalensis reservoir.

Identifying the genetic basis of viral spillover using Lassa virus as a test case.

The rate at which zoonotic viruses spill over into the human population varies significantly over space and time. Remarkably, we do not yet know how much of this variation is attributable to genetic variation within viral populations. This gap in understanding arises because we lack methods of genetic analysis that can be easily applied to zoonotic viruses, where the number of available viral sequences is often limited, and opportunistic sampling introduces significant population stratification. Here, we explore the feasibility of using patterns of shared ancestry to correct for population stratification, enabling genome-wide association methods to identify genetic substitutions associated with spillover into the human population. Using a combination of phylogenetically structured simulations and Lassa virus sequences collected from humans and rodents in Sierra Leone, we demonstrate that existing methods do not fully correct for stratification, leading to elevated error rates. We also demonstrate, however, that the Type I error rate can be substantially reduced by confining the analysis to a less-stratified region of the phylogeny, even in an already-small dataset. Using this method, we detect two candidate single-nucleotide polymorphisms associated with spillover in the Lassa virus polymerase gene and provide generalized recommendations for the collection and analysis of zoonotic viruses.

Genome Sequences of Five Arenaviruses from Pygmy Mice (Mus minutoides) in Sierra Leone.

The genome sequences of five strains of a mammarenavirus were assembled from metagenomic data from pygmy mice (Mus minutoides) captured in Sierra Leone. The nearest fully sequenced relatives of this virus, which was named Seli virus, are lymphocytic choriomeningitis virus, Lunk virus, and Ryukyu virus.

Leaf shape in Populus tremula is a complex, omnigenic trait.

Leaf shape is a defining feature of how we recognize and classify plant species. Although there is extensive variation in leaf shape within many species, few studies have disentangled the underlying genetic architecture. We characterized the genetic architecture of leaf shape variation in Eurasian aspen (Populus tremula L.) by performing genome-wide association study (GWAS) for physiognomy traits. To ascertain the roles of identified GWAS candidate genes within the leaf development transcriptional program, we generated RNA-Seq data that we used to perform gene co-expression network analyses from a developmental series, which is publicly available within the PlantGenIE resource. We additionally used existing gene expression measurements across the population to analyze GWAS candidate genes in the context of a population-wide co-expression network and to identify genes that were differentially expressed between groups of individuals with contrasting leaf shapes. These data were integrated with expression GWAS (eQTL) results to define a set of candidate genes associated with leaf shape variation. Our results identified no clear adaptive link to leaf shape variation and indicate that leaf shape traits are genetically complex, likely determined by numerous small-effect variations in gene expression. Genes associated with shape variation were peripheral within the population-wide co-expression network, were not highly connected within the leaf development co-expression network, and exhibited signatures of relaxed selection. As such, our results are consistent with the omnigenic model.

DisCVR: Rapid viral diagnosis from high-throughput sequencing data.

High-throughput sequencing (HTS) enables most pathogens in a clinical sample to be detected from a single analysis, thereby providing novel opportunities for diagnosis, surveillance, and epidemiology. However, this powerful technology is difficult to apply in diagnostic laboratories because of its computational and bioinformatic demands. We have developed DisCVR, which detects known human viruses in clinical samples by matching sample k-mers (twenty-two nucleotide sequences) to k-mers from taxonomically labeled viral genomes. DisCVR was validated using published HTS data for eighty-nine clinical samples from adults with upper respiratory tract infections. These samples had been tested for viruses metagenomically and also by real-time polymerase chain reaction assay, which is the standard diagnostic method. DisCVR detected human viruses with high sensitivity (79%) and specificity (100%), and was able to detect mixed infections. Moreover, it produced results comparable to those in a published metagenomic analysis of 177 blood samples from patients in Nigeria. DisCVR has been designed as a user-friendly tool for detecting human viruses from HTS data using computers with limited RAM and processing power, and includes a graphical user interface to help users interpret and validate the output. It is written in Java and is publicly available from http://bioinformatics.cvr.ac.uk/discvr.php.