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作用于复杂性状的自然选择会降低古代样本中多基因评分的预测准确性。

Natural selection acting on complex traits hampers the predictive accuracy of polygenic scores in ancient samples.

作者信息

Añorve-Garibay Valeria, Huerta-Sanchez Emilia, Sohail Mashaal, Ortega-Del Vecchyo Diego

机构信息

Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA; Laboratorio Internacional de Investigación sobre el Genoma Humano (LIIGH), Universidad Nacional Autónoma de México (UNAM), Juriquilla, Querétaro, México.

Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA; Department of Ecology, Evolution and Organismal Biology, Brown University, Providence, RI, USA.

出版信息

Am J Hum Genet. 2025 Jun 6. doi: 10.1016/j.ajhg.2025.05.009.

Abstract

The prediction of phenotypes from ancient humans has gained interest due to its potential to investigate the evolution of complex traits. These predictions are commonly performed using polygenic scores computed with DNA information from ancient humans along with genome-wide association study (GWAS) data from present-day humans. However, numerous evolutionary processes could impact these phenotypic predictions. In this work, we investigate how natural selection shapes the temporal dynamics of variants with an effect on the trait and how these changes impact phenotypic predictions for ancient individuals using polygenic scores. We find that stabilizing selection accelerates the loss of large-effect alleles contributing to trait variation. Conversely, directional selection accelerates the loss of small- and large-effect alleles that drive individuals farther away from the optimal phenotypic value. These phenomena result in specific shared genetic variation patterns between ancient and modern populations that hamper the accuracy of polygenic scores to predict phenotypes. Our results assume perfectly estimated effect sizes at the causal loci of complex traits segregating in a GWAS performed in the present and, therefore, provide a putatively loose upper bound on the polygenic score portability to predict traits in the past. Furthermore, we show how natural selection could impact the predictive accuracy of ancient polygenic scores for two widely studied traits: height and body mass index. Our results emphasize the importance of considering decreases on the reliability of polygenic scores to perform phenotypic predictions in ancient individuals due to allele frequency changes driving the loss of alleles via natural selection.

摘要

由于其在研究复杂性状进化方面的潜力,从古代人类预测表型已引起关注。这些预测通常使用根据古代人类的DNA信息以及现代人类的全基因组关联研究(GWAS)数据计算出的多基因分数来进行。然而,众多进化过程可能会影响这些表型预测。在这项工作中,我们研究自然选择如何塑造对性状有影响的变异的时间动态,以及这些变化如何使用多基因分数影响古代个体的表型预测。我们发现稳定选择加速了导致性状变异的大效应等位基因的丢失。相反,定向选择加速了使个体远离最优表型值的小效应和大效应等位基因的丢失。这些现象导致古代和现代人群之间出现特定的共享遗传变异模式,从而妨碍了多基因分数预测表型的准确性。我们的结果假设在当前进行的GWAS中复杂性状的因果位点上效应大小得到了完美估计,因此为多基因分数预测过去性状的可转移性提供了一个可能宽松的上限。此外,我们展示了自然选择如何影响两个广泛研究的性状(身高和体重指数)的古代多基因分数的预测准确性。我们的结果强调了由于自然选择导致等位基因频率变化驱动等位基因丢失,从而在对古代个体进行表型预测时考虑多基因分数可靠性下降的重要性。

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