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- Aguilar, J. Rivero De, et al.
(author)
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MHC-I provides both quantitative resistance and susceptibility to blood parasites in blue tits in the wild
- 2016
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In: Journal of Avian Biology. - : Wiley. - 0908-8857. ; 47:5, s. 669-677
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Journal article (peer-reviewed)abstract
- Major histocompatibility complex (MHC) genes are central for the adaptive immune response against parasites. Here, we investigated potential associations among MHC-I alleles and blood parasite infections in a natural breeding population of a passerine bird, the blue tit Cyanistes caeruleus, in central Spain. We screened both infection status (presence/absence of infection) and infection intensity to the pathogenic blood parasites Haemoproteus and Leucocytozoon. Three MHC-I alleles (UA104, UA108 and UA117) were associated with higher or lower infection intensities by Leucocytozoon. Interestingly, these associations were dependent on age and were found both among young and adult birds. No MHC alleles were associated with infection intensity by Haemoproteus parasites. In addition, no significant relationships were detected between infection status by Haemoproteus and Leucocytozoon infections and MHC alleles. The very high prevalence of these two parasites in our study population (79-100%) poses challenges to identify associations with infection status and also suggests that clearance of infections may be rare. In conclusion, associations between specific MHC-I alleles and Leucocytozoon parasites were related to either high or low infection intensities, and hence increased susceptibility or resistance to infection.
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2. |
- Näpflin, Kathrin, et al.
(author)
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Genomics of host-pathogen interactions: challenges and opportunities across ecological and spatiotemporal scales
- 2019
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In: PeerJ. - : PeerJ. - 2167-8359. ; 7
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Journal article (peer-reviewed)abstract
- Evolutionary genomics has recently entered a new era in the study of host-pathogen interactions. A variety of novel genomic techniques has transformed the identification, detection and classification of both hosts and pathogens, allowing a greater resolution that helps decipher their underlying dynamics and provides novel insights into their environmental context. Nevertheless, many challenges to a general understanding of host-pathogen interactions remain, in particular in the synthesis and integration of concepts and findings across a variety of systems and different spatiotemporal and ecological scales. In this perspective we aim to highlight some of the commonalities and complexities across diverse studies of host-pathogen interactions, with a focus on ecological, spatiotemporal variation, and the choice of genomic methods used. We performed a quantitative review of recent literature to investigate links, patterns and potential tradeoffs between the complexity of genomic, ecological and spatiotemporal scales undertaken in individual host-pathogen studies. We found that the majority of studies used whole genome resolution to address their research objectives across a broad range of ecological scales, especially when focusing on the pathogen side of the interaction. Nevertheless, genomic studies conducted in a complex spatiotemporal context are currently rare in the literature. Because processes of host-pathogen interactions can be understood at multiple scales, from molecular-, cellular-, and physiological-scales to the levels of populations and ecosystems, we conclude that a major obstacle for synthesis across diverse host-pathogen systems is that data are collected on widely diverging scales with different degrees of resolution. This disparity not only hampers effective infrastructural organization of the data but also data granularity and accessibility. Comprehensive metadata deposited in association with genomic data in easily accessible databases will allow greater inference across systems in the future, especially when combined with open data standards and practices. The standardization and comparability of such data will facilitate early detection of emerging infectious diseases as well as studies of the impact of anthropogenic stressors, such as climate change, on disease dynamics in humans and wildlife.
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7. |
- Naepflin, Kathrin, et al.
(author)
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Genomics of host-pathogen interactions: challenges and opportunities across ecological and spatiotemporal scales
- 2019
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In: PeerJ. - 2167-8359. ; 7
-
Journal article (peer-reviewed)abstract
- Evolutionary genomics has recently entered a new era in the study of host-pathogen interactions. A variety of novel genomic techniques has transformed the identification, detection and classification of both hosts and pathogens, allowing a greater resolution that helps decipher their underlying dynamics and provides novel insights into their environmental context. Nevertheless, many challenges to a general understanding of host-pathogen interactions remain, in particular in the synthesis and integration of concepts and findings across a variety of systems and different spatiotemporal and ecological scales. In this perspective we aim to highlight some of the commonalities and complexities across diverse studies of host-pathogen interactions, with a focus on ecological, spatiotemporal variation, and the choice of genomic methods used. We performed a quantitative review of recent literature to investigate links, patterns and potential tradeoffs between the complexity of genomic, ecological and spatiotemporal scales undertaken in individual host-pathogen studies. We found that the majority of studies used whole genome resolution to address their research objectives across a broad range of ecological scales, especially when focusing on the pathogen side of the interaction. Nevertheless, genomic studies conducted in a complex spatiotemporal context are currently rare in the literature. Because processes of host-pathogen interactions can be understood at multiple scales, from molecular-, cellular-, and physiological-scales to the levels of populations and ecosystems, we conclude that a major obstacle for synthesis across diverse host-pathogen systems is that data are collected on widely diverging scales with different degrees of resolution. This disparity not only hampers effective infrastructural organization of the data but also data granularity and accessibility. Comprehensive metadata deposited in association with genomic data in easily accessible databases will allow greater inference across systems in the future, especially when combined with open data standards and practices. The standardization and comparability of such data will facilitate early detection of emerging infectious diseases as well as studies of the impact of anthropogenic stressors, such as climate change, on disease dynamics in humans and wildlife.
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