Avian Influenza Surveillance with FTA Cards: Field Methods, Biosafety, and Transportation Issues Solved

Avian Influenza Viruses (AIVs) infect many mammals, including humans1. These AIVs are diverse in their natural hosts, harboring almost all possible viral subtypes2. Human pandemics of flu originally stem from AIVs3. Many fatal human cases during the H5N1 outbreaks in recent years were reported. Lately, a new AIV related strain swept through the human population, causing the 'swine flu epidemic'4. Although human trading and transportation activity seems to be responsible for the spread of highly pathogenic strains5, dispersal can also partly be attributed to wild birds6, 7. However, the actual reservoir of all AIV strains is wild birds

Avian introgression in the genomic era

Introgression, the incorporation of genetic material from one (sub)species into the gene pool of another by means of hybridization and backcrossing, is a common phenomenon in birds and can provide important insights into the speciation process. In the last decade, the toolkit for studying introgression has expanded together with the development of molecular markers. In this review, we explore how genomic data, the most recent step in this methodological progress, impacts different aspects in the study of avian introgression. First, the detection of hybrids and backcrosses has improved dramatically. The most widely used software package is STRUCTURE. Phylogenetic discordance (i.e. different loci resulting in discordant gene trees) is another means for the detection of introgression, although it should be regarded as a starting point for further analyses, not as a definitive proof of introgression. Specifically, disentangling introgression from other biological processes, such as incomplete lineage sorting, remains a challenging endeavour, although new techniques, such as the D-statistic, are being developed. In addition, phylogenetics might require a shift from trees to networks. Second, the study of hybrid zones by means of geographical or genomic cline analysis has led to important insights into the complex interplay between hybridization and speciation. However, because each hybrid zone study is just a single snapshot of a complex and continuously changing interaction, hybrid zones should be studied across different temporal and/or spatial scales. A third powerful tool is the genome scan. The debate on which evolutionary processes underlie the genomic landscape is still ongoing, as is the question whether loci involved in reproductive isolation cluster together in 'islands of speciation' or whether they are scattered throughout the genome. Exploring genomic landscapes across the avian tree of life will be an exciting field for further research. Finally, the findings from these different methods should be incorporated into specific speciation scenarios, which can consequently be tested using a modelling approach. All in all, this genomic perspective on avian hybridization and speciation will further our understanding in evolution in general

A history of hybrids? Genomic patterns of introgression in the True Geese

Background: The impacts of hybridization on the process of speciation are manifold, leading to distinct patterns across the genome. Genetic differentiation accumulates in certain genomic regions, while divergence is hampered in other regions by homogenizing gene flow, resulting in a heterogeneous genomic landscape. A consequence of this heterogeneity is that genomes are mosaics of different gene histories that can be compared to unravel complex speciation and hybridization events. However, incomplete lineage sorting (often the outcome of rapid speciation) can result in similar patterns. New statistical techniques, such as the D-statistic and hybridization networks, can be applied to disentangle the contributions of hybridization and incomplete lineage sorting. We unravel patterns of hybridization and incomplete lineage sorting during and after the diversification of the True Geese (family Anatidae, tribe Anserini, genera Anser and Branta) using an exon-based hybridization network approach and taking advantage of discordant gene tree histories by re-sequencing all taxa of this clade. In addition, we determine the timing of introgression and reconstruct historical effective population sizes for all goose species to infer which demographic or biogeographic factors might explain the observed patterns of introgression. Results: We find indications for ancient interspecific gene flow during the diversification of the True Geese and were able to pinpoint several putative hybridization events. Specifically, in the genus Branta, both the ancestor of the White-cheeked Geese (Hawaiian Goose, Canada Goose, Cackling Goose and Barnacle Goose) and the ancestor of the Brent Goose hybridized with Red-breasted Goose. One hybridization network suggests a hybrid origin for the Red-breasted Goose, but this scenario seems unlikely and it not supported by the D-statistic analysis. The complex, highly reticulated evolutionary history of the genus Anser hampered the estimation of ancient hybridization events by means of hybridization networks. The reconstruction of historical effective population sizes shows that most species showed a steady increase during the Pliocene and Pleistocene. These large effective population sizes might have facilitated contact between diverging goose species, resulting in the establishment of hybrid zones and consequent gene flow. Conclusions: Our analyses suggest that the evolutionary history of the True Geese is influenced by introgressive hybridization. The approach that we have used, based on genome-wide phylogenetic incongruence and network analyses, will be a useful procedure to reconstruct the complex evolutionary histories of many naturally hybridizing species groups

A tree of geese : A phylogenomic perspective on the evolutionary history of True Geese

Phylogenetic incongruence can be caused by analytical shortcomings or can be the result of biological processes, such as hybridization, incomplete lineage sorting and gene duplication. Differentiation between these causes of incongruence is essential to unravel complex speciation and diversification events. The phylogeny of the True Geese (tribe Anserini, Anatidae, Anseriformes) was, until now, contentious, i.e., the phylogenetic relationships and the timing of divergence between the different goose species could not be fully resolved. We sequenced nineteen goose genomes (representing seventeen species of which three subspecies of the Brent Goose, Branta bernicla) and used an exon-based phylogenomic approach (41,736 exons, representing 5887 genes) to unravel the evolutionary history of this bird group. We thereby provide general guidance on the combination of whole genome evolutionary analyses and analytical tools for such cases where previous attempts to resolve the phylogenetic history of several taxa could not be unravelled. Identical topologies were obtained using either a concatenation (based upon an alignment of 6,630,626 base pairs) or a coalescent-based consensus method. Two major lineages, corresponding to the genera Anser and Branta, were strongly supported. Within the Branta lineage, the White-cheeked Geese form a well-supported sub-lineage that is sister to the Red-breasted Goose (Branta ruficollis). In addition, two main clades of Anser species could be identified, the White Geese and the Grey Geese. The results from the consensus method suggest that the diversification of the genus Anser is heavily influenced by rapid speciation and by hybridization, which may explain the failure of previous studies to resolve the phylogenetic relationships within this genus. The majority of speciation events took place in the late Pliocene and early Pleistocene (between 4 and 2 million years ago), conceivably driven by a global cooling trend that led to the establishment of a circumpolar tundra belt and the emergence of temperate grasslands. Our approach will be a fruitful strategy for resolving many other complex evolutionary histories at the level of genera, species, and subspecies.</p

Health monitoring in birds using bio-loggers and whole blood transcriptomics

Monitoring and early detection of emerging infectious diseases in wild animals is of crucial global importance, yet reliable ways to measure immune status and responses are lacking for animals in the wild. Here we assess the usefulness of bio-loggers for detecting disease outbreaks in free-living birds and confirm detailed responses using leukocyte composition and large-scale transcriptomics. We simulated natural infections by viral and bacterial pathogens in captive mallards (Anas platyrhynchos), an important natural vector for avian influenza virus. We show that body temperature, heart rate and leukocyte composition change reliably during an acute phase immune response. Using genome-wide gene expression profiling of whole blood across time points we confirm that immunostimulants activate pathogen-specific gene regulatory networks. By reporting immune response related changes in physiological and behavioural traits that can be studied in free-ranging populations, we provide baseline information with importance to the global monitoring of zoonotic diseases

Contrasting context-dependence of familiarity and kinship in animal social networks

Highlights • We studied which traits affect foraging associations and mate choice in geese. • We collected data on boldness, dominance, familiarity and genetic relatedness. • During foraging geese associated with familiar and genetically related geese. • During mate choice geese selected unfamiliar individuals. • There was no effect of boldness or dominance during foraging or mate choice. The social structure of a population is a crucial element of an individual's environment, fundamentally influencing the transfer of genes, information and diseases. A central question in social network analysis is how different traits affect associations within populations. However, previous studies of animal social networks have typically focused on a single predictor or stage in the life cycle whereas social interactions within populations are known to be dynamic and not fixed through time and/or context. Relatively few animal network studies have explored how individual traits affect decisions across different ecologically relevant contexts. We collected detailed behavioural data (personality, dominance, familiarity) and high-resolution genetic data from a flock of 43 captive barnacle geese, Branta leucopsis, to understand how these traits affect association patterns in two different evolutionary and ecologically highly relevant contexts: foraging and mate choice. Using a novel analytical framework for node label permutations, we found that barnacle geese preferentially associated with close kin and other individuals familiar from earlier in life when foraging, but selected unfamiliar partners during mate choice. We found no effect of either personality or dominance on foraging associations or mate choice. Our study shows how using social network analysis can increase our understanding of the drivers behind population structure (in our case kin selection and inbreeding avoidance). Moreover, our study demonstrates that social networks can be largely determined by long-term processes, in particular early life familiarity.