Novel and extendable genotyping system for Human Respiratory Syncytial Virus based on whole-genome sequence analysis

Background: Human respiratory syncytial virus (RSV) is one of the leading causes of respiratory infections, especially in infants and young children. Previous RSV sequencing studies have primarily focused on partial sequencing of G gene (200-300 nucleotides) for genotype characterization or diagnostics. However, the genotype assignment with G gene has not recapitulated the phylogenetic signal of other genes and there is no consensus on RSV genotype definition. Methods: We conducted Maximum Likelihood phylogenetic analysis with 10 RSV individual genes and whole-genome sequence (WGS) that are published in GenBank. RSV genotypes were assigned by the statistical support monophyletic clusters with at least 10-year detection time from the WGS phylogeny. Results: In this study, we first statistically examined the phylogenetic incongruence, rate variation for each RSV gene sequence and WGS. We then proposed a new RSV genotyping system based on a comparative analysis of WGS and the spatial and temporal distribution of each lineage. We also provided an RSV classification tool to perform RSV genotype assignment. Conclusions: This revised RSV genotyping system will provide important information for disease surveillance, epidemiology, and vaccine development.

Genotypic diversity and dynamic nomenclature of Parechovirus A

Human parechoviruses (PeV-A) can cause severe sepsis and neurological syndromes in neonates and children and are currently classified into 19 genotypes based on genetic divergence in the VP1 gene. However, the genotyping system has notable limitations including an arbitrary distance threshold and reliance on insufficiently robust phylogenetic reconstruction approaches leading to inconsistent genotype definitions. In order to improve the genotyping system, we investigated the molecular epidemiology of human parechoviruses, including the evolutionary history of the different PeV-A lineages as far as is possible. We found that PeV-A lineages suffer from severe substitution saturation in the VP1 gene which limit the inference of deep evolutionary timescales among the extant PeV-A and suggest that the degree of evolutionary divergence among current PeV-A lineages has been substantially underestimated, further confounding the current genotyping system. We propose an alternative nomenclature system based on robust, amino-acid level phylogenetic reconstruction and clustering with the PhyCLIP algorithm which delineates highly divergent currently designated genotypes more informatively. We also describe a dynamic nomenclature framework that combines PhyCLIP’s progressive clustering with phylogenetic placement for genotype assignment.

Mycorrhiza: genotype assignment using phylogenetic networks

Motivation The genotype assignment problem consists of predicting, from the genotype of an individual, which of a known set of populations it originated from. The problem arises in a variety of contexts, including wildlife forensics, invasive species detection and biodiversity monitoring. Existing approaches perform well under ideal conditions but are sensitive to a variety of common violations of the assumptions they rely on. Results In this article, we introduce Mycorrhiza, a machine learning approach for the genotype assignment problem. Our algorithm makes use of phylogenetic networks to engineer features that encode the evolutionary relationships among samples. Those features are then used as input to a Random Forests classifier. The classification accuracy was assessed on multiple published empirical SNP, microsatellite or consensus sequence datasets with wide ranges of size, geographical distribution and population structure and on simulated datasets. It compared favorably against widely used assessment tests or mixture analysis methods such as STRUCTURE and Admixture, and against another machine-learning based approach using principal component analysis for dimensionality reduction. Mycorrhiza yields particularly significant gains on datasets with a large average fixation index (FST) or deviation from the Hardy-Weinberg equilibrium. Moreover, the phylogenetic network approach estimates mixture proportions with good accuracy. Availability and implementation Mycorrhiza is released as an easy to use open-source python package at github.com/jgeofil/mycorrhiza. Supplementary information Supplementary data are available at Bioinformatics online.

Genotype Diversity of Newcastle Disease Virus in Nigeria: Disease Control Challenges and Future Outlook

Newcastle disease (ND) is one of the most important avian diseases with considerable threat to the productivity of poultry all over the world. The disease is associated with severe respiratory, gastrointestinal, and neurological lesions in chicken leading to high mortality and several other production related losses. The aetiology of the disease is an avian paramyxovirus type-1 or Newcastle disease virus (NDV), whose isolates are serologically grouped into a single serotype but genetically classified into a total of 19 genotypes, owing to the continuous emergence and evolution of the virus. In Nigeria, molecular characterization of NDV is generally very scanty and majorly focuses on the amplification of the partial F gene for genotype assignment. However, with the introduction of the most objective NDV genotyping criteria which utilize complete fusion protein coding sequences in phylogenetic taxonomy, the enormous genetic diversity of the virus in Nigeria became very conspicuous. In this review, we examine the current ecological distribution of various NDV genotypes in Nigeria based on the available complete fusion protein nucleotide sequences (1662 bp) in the NCBI database. We then discuss the challenges of ND control as a result of the wide genetic distance between the currently circulating NDV isolates and the commonest vaccines used to combat the disease in the country. Finally, we suggest future directions in the war against the economically devastating ND in Nigeria.

Genetic tracing of farmed shrimp (Decapoda, Penaeidae) in wild populations from a main aquaculture region in Mexico

Release or escapes of aquaculture organisms may impact the genetic composition and variability of wild populations, leading to diverse issues that may compromise long-term wild stock fitness. Therefore, it is relevant to determine if farmed stocks are currently interacting with wild populations. Shrimp farming is an aquaculture activity taking place along the tropical Pacific coast of the Americas, and represents the most important culture bussiness of Northwestern Mexico. In this study, wild and farmed whiteleg shrimp Litopenaeus vannamei from the State of Sinaloa were genetically evaluated to determine admixture levels. A newly developed set of 14 microsatellite markers (mean number of alleles per locus 11.8, and 0.836 expected heterozygosity) was obtained by Next Generation Sequencing to characterize samples. Sampling consisted of 32 wild shrimps collected during three years (2002, 2012, and 2013) and three different sites, and two hatchery stocks from 2007. No significant differences were observed among years in the wild samples, but cluster analyses showed that hatchery-produced individuals were different from wild specimens. Deviations from Hardy-Weinberg Equilibrium and genotype assignment tests indicated that a fraction from each sample could contain individuals from hatchery origin. Even though the estimated fraction of escaped farmed individuals in the most recent samples (2012-2013; mean = 7.1 %) is considered of low genetic risk, management recommendations for hatcheries and farms were provided. Besides, the reasons that explain the intended and unintended farmed shrimp release into the wild were discussed.

Genetic diversity of circulating Saffold viruses in Pakistan and Afghanistan

Human cardioviruses or Saffold viruses (SAFVs) of the family Picornaviridae are newly emerging viruses whose genetic and phenotypic diversity are poorly understood. We report here the full genome sequence of 11 SAFV genotypes from Pakistan and Afghanistan, along with a re-evaluation of their genetic diversity and recombination. We detected 88 SAFV from stool samples of 943 acute flaccid paralysis cases using reverse transcriptase-PCR targeting the 5′ untranslated region (UTR). Further characterization based on complete VP1 analysis revealed 71 SAFVs belonging to 11 genotypes, including three previously unidentified genotypes. SAFV showed high genetic diversity and recombination based on phylogenetic, pairwise distance distributions and recombination mapping analyses performed herein. Phylogenies based on non-structural and UTRs were highly incongruent indicating frequent recombination events among SAFVs. We improved the SAFV genotyping classification criteria by determining new VP1 thresholds based on the principles used for the classification of enteroviruses. For genotype assignment, we propose a threshold of 23 and 10 % divergence for VP1 nucleotide and amino acid sequences, respectively. Other members of the species Theilovirus, such as Thera virus and Theiler’s murine encephalomyelitis virus, are difficult to classify in the same species as SAFV, because they are genetically distinct from SAFV, with 41–56 % aa pairwise distances. The new genetic information obtained in this study will improve our understanding of the evolution and classification of SAFV.