The practice and promise of temporal genomics for measuring evolutionary responses to global change
The practice and promise of temporal genomics for measuring evolutionary responses to global change
复制标题
DOI：
10.1111/1755-0998.13789
复制
发表时间：
2023-04-02
影响因子：
7.7
通讯作者：
Pinsky，Malin L.
中科院分区：
文献类型：
--
作者：
Clark，Rene D.;Catalano，Katrina A.;Pinsky，Malin L.
了解人为变化的进化后果对于估计长期物种恢复力至关重要。虽然当代基因组数据可以为我们提供对最近人口统计历史的重要见解，但仅使用当前基因组数据调查过去的变化具有局限性。相比之下，时间基因组学研究，本文定义为那些纳入时间序列基因组数据，利用博物馆收藏和重复的实地采样，直接检查进化的变化。随着时间基因组学应用于更多的系统、物种和问题，最佳实践可以成为最有效利用有限资源的有益指南。在这里，我们进行了系统的文献综述，以综合时间基因组学方法对我们检测进化变化的能力的影响。我们专注于研究调查最近的变化在过去200年，突出了在过去两个世纪的加速人为压力发生的进化过程。我们首先确定了最常研究的分类群，系统，问题和驱动程序，然后强调被忽视的领域，进一步的时间基因组研究可能特别有启发性。然后，我们为未来的研究和样本设计提供指导方针，同时确定可能影响统计和分析能力的关键因素。我们的目标是为有兴趣在工作中使用时间基因组学的广泛研究人员提供建议。
Understanding the evolutionary consequences of anthropogenic change is imperative for estimating long‐term species resilience. While contemporary genomic data can provide us with important insights into recent demographic histories, investigating past change using present genomic data alone has limitations. In comparison, temporal genomics studies, defined herein as those that incorporate time series genomic data, utilize museum collections and repeated field sampling to directly examine evolutionary change. As temporal genomics is applied to more systems, species and questions, best practices can be helpful guides to make the most efficient use of limited resources. Here, we conduct a systematic literature review to synthesize the effects of temporal genomics methodology on our ability to detect evolutionary changes. We focus on studies investigating recent change within the past 200 years, highlighting evolutionary processes that have occurred during the past two centuries of accelerated anthropogenic pressure. We first identify the most frequently studied taxa, systems, questions and drivers, before highlighting overlooked areas where further temporal genomic studies may be particularly enlightening. Then, we provide guidelines for future study and sample designs while identifying key considerations that may influence statistical and analytical power. Our aim is to provide recommendations to a broad array of researchers interested in using temporal genomics in their work.