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The population genomics of plant adaptation

机译:植物适应的种群基因组学

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There has been an enormous increase in the amount of data on DNA sequence polymorphism available for many organisms in the last decade. New sequencing technologies provide great potential for investigating natural selection in plants using population genomic approaches. However, plant populations frequently show significant departures from the assumptions of standard models used to detect selection and many forms of directional selection do not fit with classical population genetics theory. Here, we explore the extent to which plant populations show departures from standard model assumptions, and the implications this has for detecting selection on molecular variation. A growing number of multilocus studies of nucleotide variation suggest that changes in population size, particularly bottlenecks, and strong subdivision may be common in plants. This demographic variation presents important challenges for models used to infer selection. In addition, selection from standing genetic variation and multiple independent adaptive substitutions can further complicate efforts to understand the nature of selection. We discuss emerging patterns from plant studies and propose that, rather than treating population history as a nuisance variable when testing for selection, the interaction between demography and selection is of fundamental importance for evolutionary studies of plant populations using molecular data.
机译:在过去的十年中,可用于许多生物体的DNA序列多态性数据量大大增加。新的测序技术为利用种群基因组方法研究植物的自然选择提供了巨大的潜力。然而,植物种群经常显示出与用于检测选择的标准模型的假设有很大的出入,许多形式的定向选择都不符合经典的种群遗传学理论。在这里,我们探讨了植物种群显示出偏离标准模型假设的程度,以及其对检测分子变异选择的影响。越来越多的核苷酸变异多位点研究表明,种群大小的变化(尤其是瓶颈)和强烈的细分可能在植物中很常见。这种人口统计学差异对用于推断选择的模型提出了重要挑战。此外,从常规遗传变异和多个独立的适应性替代中进行选择,会使了解选择性质的努力进一步复杂化。我们讨论了植物研究中的新兴模式,并提出,人口统计学和选择之间的相互作用对于使用分子数据进行植物种群进化研究至关重要,而不是将种群历史作为选择选择时的滋扰变量。

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