The duck (Anas platyrhynchos) is one of the principal natural hosts of influenza A viruses. We present the duck genome sequence and perform deep transcriptome analyses to investigate immune-related genes. Our data indicate that the duck possesses a contractive immune gene repertoire, as in chicken and zebra finch, and this repertoire has been shaped through lineage-specific duplications. We identify genes that are responsive to influenza A viruses using the lung transcriptomes of control ducks and ones that were infected with either a highly pathogenic (A/duck/Hubei/49/05) or a weakly pathogenic (A/goose/Hubei/65/05) H5N1 virus. Further, we show how the duck’s defense mechanisms against influenza infection have been optimized through the diversification of its β-defensin and butyrophilin-like repertoires. These analyses, in combination with the genomic and transcriptomic data, provide a resource for characterizing the interaction between host and influenza viruses.
Noninvasive genetics based on microsatellite markers has become an indispensable tool for wildlife monitoring and conservation research over the past decades. However, microsatellites have several drawbacks, such as the lack of standardisation between laboratories and high error rates. Here, we propose an alternative single-nucleotide polymorphism (SNP)-based marker system for noninvasively collected samples, which promises to solve these problems. Using nanofluidic SNP genotyping technology (Fluidigm), we genotyped 158 wolf samples (tissue, scats, hairs, urine) for 192 SNP loci selected from the Affymetrix v2 Canine SNP Array. We carefully selected an optimised final set of 96 SNPs (and discarded the worse half), based on assay performance and reliability. We found rates of missing data in this SNP set of <10% and genotyping error of~1%, which improves genotyping accuracy by nearly an order of magnitude when compared to published data for other marker types. Our approach provides a tool for rapid and cost-effective genotyping of noninvasively collected wildlife samples. The ability to standardise genotype scoring combined with low error rates promises to constitute a major technological advancement and could establish SNPs as a standard marker for future wildlife monitoring.
The European wildcat, Felis silvestris silvestris, serves as a prominent target species for the reconnection of central European forest habitats. Monitoring of this species, however, appears difficult due to its elusive behaviour and the ease of confusion with domestic cats. Recently, evidence for multiple wildcat occurrences outside its known distribution has accumulated in several areas across Central Europe, questioning the validity of available distribution data for this species. Our aim was to assess the fine-scale distribution and genetic status of the wildcat in its central European distribution range. We compiled and analysed genetic samples from roadkills and hundreds of recent hair-trapping surveys and applied phylogenetic and genetic clustering methods to discriminate wild and domestic cats and identify population subdivision. 2220 individuals were confirmed as either wildcat (n = 1792) or domestic cat (n = 342), and the remaining 86 (3.9 %) were identified as hybrids between the two. Remarkably, genetic distinction of domestic cats, wildcats and their hybrids was only possible when taking into account the presence of two highly distinct genetic lineages of wildcats, with a suture zone in central Germany. 44 % of the individual wildcats where sampled outside the previously published distribution. Our analyses confirm a relatively continuous spatial presence of wildcats across large parts of the study area in contrast to previous analyses indicating a highly fragmented distribution. Our results suggest that wildcat conservation and management should take advantage of the higher than previously assumed dispersal potential of wildcats, which may use wildlife corridors very efficiently.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.