Using genomics to characterize evolutionary potential for conservation of wild populations.

Using genomics to characterize evolutionary potential for conservation of wild populations.
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DOI:
10.1111/eva.12149
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发表时间:
2014-11
影响因子:
4.1
通讯作者:
Sunnucks P
Sunnucks P
中科院分区:
生物学2区
文献类型:
--
作者:
Harrisson KA;Pavlova A;Telonis-Scott M;Sunnucks P

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尽管存在相关的挑战,但基因组学有望在实现最大化进化潜力这一重要保护目标方面取得令人兴奋的进展。在这里,我们探讨了适应遗传学的一些复杂性,并讨论了基因组学作为表征保护管理背景下进化潜力的工具的优势和局限性。许多性状是多基因的,可以受到调控网络的微小差异和DNA序列中不可见的表观遗传变异的强烈影响。使用通常用于识别适应性变异的方法很难检测到这种关键的复杂性,在规划基因组筛选和基于基因组数据的管理决策时,需要适当考虑这一点。当适应的基因组基础和未来的威胁得到充分了解时,将管理重点放在特定的适应性状上可能是适当的。对于更典型的保守情况,我们认为筛选全基因组变异应该是一种明智的方法,它可以提供一种通用的进化潜力测量方法,该方法可以解释小效应位点和隐性变异的贡献,并且对未来变化的不确定性和所需的适应性反应具有鲁棒性。当在适应性管理框架内使用进化潜力的基因组估计时,应该实现最佳的保护结果。
Genomics promises exciting advances towards the important conservation goal of maximizing evolutionary potential, notwithstanding associated challenges. Here, we explore some of the complexity of adaptation genetics and discuss the strengths and limitations of genomics as a tool for characterizing evolutionary potential in the context of conservation management. Many traits are polygenic and can be strongly influenced by minor differences in regulatory networks and by epigenetic variation not visible in DNA sequence. Much of this critical complexity is difficult to detect using methods commonly used to identify adaptive variation, and this needs appropriate consideration when planning genomic screens, and when basing management decisions on genomic data. When the genomic basis of adaptation and future threats are well understood, it may be appropriate to focus management on particular adaptive traits. For more typical conservations scenarios, we argue that screening genome-wide variation should be a sensible approach that may provide a generalized measure of evolutionary potential that accounts for the contributions of small-effect loci and cryptic variation and is robust to uncertainty about future change and required adaptive response(s). The best conservation outcomes should be achieved when genomic estimates of evolutionary potential are used within an adaptive management framework.
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