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The utility of transcriptomics in fish conservation
Author(s) -
Richard E. Con,
Ken M. Jeffries,
Lisa M. Komoroske,
Anne E. Todgham,
Nann A. Fangue
Publication year - 2018
Publication title -
journal of experimental biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.367
H-Index - 185
eISSN - 1477-9145
pISSN - 0022-0949
DOI - 10.1242/jeb.148833
Subject(s) - biology , transcriptome , psychological resilience , identification (biology) , resource (disambiguation) , conservation biology , ecology , data science , computational biology , computer science , psychology , genetics , gene , computer network , gene expression , psychotherapist
There is growing recognition of the need to understand the mechanisms underlying organismal resilience (i.e. tolerance, acclimatization) to environmental change to support the conservation management of sensitive and economically important species. Here, we discuss how functional genomics can be used in conservation biology to provide a cellular-level understanding of organismal responses to environmental conditions. In particular, the integration of transcriptomics with physiological and ecological research is increasingly playing an important role in identifying functional physiological thresholds predictive of compensatory responses and detrimental outcomes, transforming the way we can study issues in conservation biology. Notably, with technological advances in RNA sequencing, transcriptome-wide approaches can now be applied to species where no prior genomic sequence information is available to develop species-specific tools and investigate sublethal impacts that can contribute to population declines over generations and undermine prospects for long-term conservation success. Here, we examine the use of transcriptomics as a means of determining organismal responses to environmental stressors and use key study examples of conservation concern in fishes to highlight the added value of transcriptome-wide data to the identification of functional response pathways. Finally, we discuss the gaps between the core science and policy frameworks and how thresholds identified through transcriptomic evaluations provide evidence that can be more readily used by resource managers.

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