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Next-Generation Ecological Immunology

Authors: Maxine, Zylberberg;

Next-Generation Ecological Immunology

Abstract

The application of next-generation sequencing (NGS) to the study of whole genomes and transcriptomes is becoming commonplace in molecular biology and molecular medicine. Over the past decade, these technologies have become more accessible to the broader biological community as the cost of NGS has decreased significantly and the availability of ready-to-use library preparation kits and user-friendly bioinformatic tools has increased. Indeed, these technologies are starting to be deployed in the study of ecological systems and immune function and have already yielded new discoveries and insights. However, despite the power of these techniques, they remain underutilized by the ecological immunology (ecoimmunology) community. This is unfortunate because there are several key challenges faced by ecological immunologists that these technologies are particularly well suited to address: (1) to measure immune function in biologically meaningful ways, (2) to describe the complex relationship between immunology and other aspects of physiology in an ecological context, and (3) to relate ecoimmunology to disease ecology. Each of these three challenges confronting the ecoimmunology community is critical to understanding ecoimmunology, and each has been stymied by a lack of sufficient data to effectively tackle the questions at hand. Deploying NGS methods to tackle these challenges promises to revolutionize the field of ecoimmunology by facilitating the unbiased, broad-scale, and efficient discovery of novel immune genes and mechanisms; the quantification of variation in immune systems; the characterization of relevant physiological pathways; and the description of microbial communities.

Related Organizations
Keywords

Ecology, Vertebrates, Immunologic Techniques, Animals, High-Throughput Nucleotide Sequencing, Invertebrates

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%
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