Adaption to extreme environments: a perspective from fish genomics
Fishes exhibit greater species diversity than any other group of vertebrates. They are found in most bodies of water, including those that pose extreme challenges, such as sulfide springs, rivers contaminated with heavy metals and organic pollutants, and caves without light. Adaptation to these extreme environments usually occurs rapidly, which has stimulated much interest in uncovering the genetic basis of such rapid adaptation. Since the sequencing of the zebrafish genome in 2001, rapid development of high-throughput sequencing technology has facilitated the additional sequencing of ~ 210 ray-finned fish genomes to date. As a result of this wealth of resources, much attention has been focused on the genetic basis of adaptation in fishes, particularly in extreme environments. The goal of this review is to summarize recent advances in fish genomics, with a specific focus on the use of genomic data to understand the genetic basis of adaptation to extreme environments in fishes. The results highlight that fishes often adapt to extreme environments through phenotypic and physiological changes that have a confirmed or inferred genetic basis. Moreover, such changes are usually rapid and repeated when parallel adaptation to similar extreme environments occurs. Specifically, parallel genetic changes are usually observed at both the intra- and interspecific level. The advances in fish genomics provide the opportunity to understand how evolutionary changes feed back into ecosystems that are facing extreme environmental changes, as well as to advance our understanding of the repeatability and predictability of evolutionary response (of fishes) to extreme environmental changes.
KeywordsAdaptation Comparative genomics Extreme environment Parallelism Population genomics
This work was supported by CAS Pioneer Hundred Talents Program, the Second Tibetan Plateau Scientific Expedition and Research (STEP) program (Grant No. 2019QZKK0501), and the National Natural Science Foundation of China (Grant No. 31672273) to B.G.
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