USING POPULATION GENOMICS TO DETECT SELECTION IN NATURAL POPULATIONS: KEY CONCEPTS AND METHODOLOGICAL CONSIDERATIONS.
USING POPULATION GENOMICS TO DETECT SELECTION IN NATURAL POPULATIONS: KEY CONCEPTS AND METHODOLOGICAL CONSIDERATIONS.
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DOI：
10.1086/656306
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发表时间：
2010-11-01
影响因子：
2.3
通讯作者：
Cresko WA
中科院分区：
文献类型：
--
作者：
Hohenlohe PA;Phillips PC;Cresko WA
自然选择塑造了个体、种群和物种之间的遗传变异模式，而且这种模式在基因组中是不同的。种群基因组学领域提供了一个关于选择行为的全面的基因组尺度的观点，甚至超越了传统的模式生物。然而，即使拥有几乎完整的基因组序列信息，我们检测特定基因组区域选择特征的能力也取决于选择适合生物情况的实验和分析工具。例如，发生在不同时间尺度上的过程，如对现有遗传变异的排序、突变-选择平衡或固定的种间差异，对变异的基因组模式有不同的后果。不适当的实验或分析方法可能无法检测到甚至强烈的选择，或者错误地识别选择的特征。在这里，我们概述了种群基因组学的概念框架，将基因组变异模式与进化过程联系起来，并确定了在选择研究中要考虑的主要生物学因素。随着数据收集技术的不断进步，我们理解自然种群选择的能力将更多地受到概念和分析缺陷的限制，而不是分子数据量的限制。我们的目标是在种群基因组研究中突出关键的生物学考虑，并促进适合不同生物系统的分析工具的开发和应用。
Natural selection shapes patterns of genetic variation among individuals, populations, and species, and it does so differentially across genomes. The field of population genomics provides a comprehensive genome-scale view of the action of selection, even beyond traditional model organisms. However, even with nearly complete genomic sequence information, our ability to detect the signature of selection on specific genomic regions depends on choosing experimental and analytical tools appropriate to the biological situation. For example, processes that occur at different timescales, such as sorting of standing genetic variation, mutation-selection balance, or fixed interspecific divergence, have different consequences for genomic patterns of variation. Inappropriate experimental or analytical approaches may fail to detect even strong selection or falsely identify a signature of selection. Here we outline the conceptual framework of population genomics, relate genomic patterns of variation to evolutionary processes, and identify major biological factors to be considered in studies of selection. As data-gathering technology continues to advance, our ability to understand selection in natural populations will be limited more by conceptual and analytical weaknesses than by the amount of molecular data. Our aim is to bring critical biological considerations to the fore in population genomics research and to spur the development and application of analytical tools appropriate to diverse biological systems.
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影响因子：
4.5
作者：
Gutenkunst RN;Hernandez RD;Williamson SH;Bustamante CD
通讯作者：
Bustamante CD
影响因子：
10.7
作者：
Charlesworth, B
通讯作者：
Charlesworth, B
影响因子：
4.5
作者：
Brachi B;Faure N;Horton M;Flahauw E;Vazquez A;Nordborg M;Bergelson J;Cuguen J;Roux F
通讯作者：
Roux F
影响因子：
3.3
作者：
Foll, Matthieu;Gaggiotti, Oscar
通讯作者：
Gaggiotti, Oscar
影响因子：
1.5
作者：
Charlesworth, B;Nordborg, M;Charlesworth, D
通讯作者：
Charlesworth, D