Evolutionary processes, including selection, can be indirectly inferred based on patterns of genomic variation among contemporary populations or species. However, this often requires unrealistic assumptions of ancestral demography and selective regimes. Sequencing ancient DNA from temporally spaced samples can inform about past selection processes, as time series data allow direct quantification of population parameters collected before, during, and after genetic changes driven by selection. In this Comment and Opinion, we advocate for the inclusion of temporal sampling and the generation of paleogenomic datasets in evolutionary biology, and highlight some of the recent advances that have yet to be broadly applied by evolutionary biologists. In doing so, we consider the expected signatures of balancing, purifying, and positive selection in time series data, and detail how this can advance our understanding of the chronology and tempo of genomic change driven by selection. However, we also recognize the limitations of such data, which can suffer from postmortem damage, fragmentation, low coverage, and typically low sample size. We therefore highlight the many assumptions and considerations associated with analyzing paleogenomic data and the assumptions associated with analytical methods.

中文翻译：

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从古代DNA推断自然选择

可以基于当代种群或物种之间的基因组变异模式，间接推断包括选择在内的进化过程。然而，这通常需要对祖先人口学和选择制度的不切实际的假设。从时间间隔的样本中测序古代DNA可以告知过去的选择过程，因为时间序列数据可以直接量化由选择驱动的遗传变化之前，之中和之后收集的种群参数。在本评论中，我们主张在进化生物学中包括时间采样和古基因组数据集的生成，并强调进化生物学家尚未广泛应用的一些最新进展。在此过程中，我们考虑了平衡，净化，以及时序数据中的正选择，并详细说明如何提高我们对选择驱动的基因组变化的时间顺序和速度的理解。但是，我们也认识到此类数据的局限性，这些局限性可能会导致事后调查损坏，碎片化，覆盖率低，并且样本量通常较小。因此，我们重点介绍了与分析古基因组数据有关的许多假设和考虑因素以及与分析方法有关的假设。