Outbreaks of avian influenza virus (AIV) from wild waterfowl into the poultry industry is of upmost significance and is an ongoing and constant threat to the industry. Accurate surveillance of AIV in wild waterfowl is critical in understanding viral diversity in the natural reservoir. Current surveillance methods for AIV involve collection of samples and transportation to a laboratory for molecular diagnostics. Processing of samples using this approach takes more than three days and may limit testing locations to those with practical access to laboratories. In potential outbreak situations, response times are critical, and delays have implications in terms of the spread of the virus that leads to increased economic cost. This study used nanopore sequencing technology for in-field sequencing and subtype characterisation of AIV strains collected from wild bird faeces and poultry. A custom in-field virus screening and sequencing protocol, including a targeted offline bioinformatic pipeline, was developed to accurately subtype AIV. Due to the lack of optimal diagnostic MinION packages for Australian AIV strains the bioinformatic pipeline was specifically targeted to confidently subtype local strains. The method presented eliminates the transportation of samples, dependence on internet access and delivers critical diagnostic information in a timely manner.

Evidence for ancestral gene transfer between Epichloë fungal endophyte ancestors and their host grass species is described. From genomes of cool-season grasses (the Poeae tribe), two Epichloë-originated genes were identified through DNA sequence similarity analysis. The two genes showed 96% and 85% DNA sequence identities between the corresponding Epichloë genes. One of the genes was specific to the Loliinae sub-tribe. The other gene was more widely conserved in the Poeae and Triticeae tribes, including wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.). The genes were independently transferred during the last 39 million years. The transferred genes were expressed in plant tissues, presumably retaining molecular functions. Multiple gene transfer events between the specific plant and fungal lineages are unique. A range of cereal crops is included in the Poeae and Triticeae tribes, and the Loliinae sub-tribe is consisted of economically important pasture and forage crops. Identification and characterisation of the 'natural' adaptation transgenes in the genomes of cereals, and pasture and forage grasses, that worldwide underpin the production of major foods, such as bread, meat, and milk, may change the ‘unnatural’ perception status of transgenic and gene-edited plants.

Background Ross River virus (RRV) is Australia’s most common and widespread mosquito-transmitted arbovirus and is of significant public health concern. With increasing anthropogenic impacts on wildlife and mosquito populations, it is important that we understand how RRV circulates in its endemic hotspots to determine where public health efforts should be directed. Current surveillance methods are effective in locating the virus but do not provide data on the circulation of the virus and its strains within the environment. This study examined the ability to identify single nucleotide polymorphisms (SNPs) within the variable E2/E3 region by generating full-length haplotypes from a range of mosquito trap-derived samples. Methods A novel tiled primer amplification workflow for amplifying RRV was developed with analysis using Oxford Nanopore Technology’s MinION and a custom ARTIC/InterARTIC bioinformatic protocol. By creating a range of amplicons across the whole genome, fine-scale SNP analysis was enabled by specifically targeting the variable region that was amplified as a single fragment and established haplotypes that informed spatial-temporal variation of RRV in the study site in Victoria. Results A bioinformatic and laboratory pipeline was successfully designed and implemented on mosquito whole trap homogenates. Resulting data showed that genotyping could be conducted in real time and that whole trap consensus of the viruses (with major SNPs) could be determined in a timely manner. Minor variants were successfully detected from the variable E2/E3 region of RRV, which allowed haplotype determination within complex mosquito homogenate samples. Conclusions The novel bioinformatic and wet laboratory methods developed here will enable fast detection and characterisation of RRV isolates. The concepts presented in this body of work are transferable to other viruses that exist as quasispecies in samples. The ability to detect minor SNPs, and thus haplotype strains, is critically important for understanding the epidemiology of viruses their natural environment. Graphical Abstract