万物是如何相互联系的——适应性进化、疾病易感性和药物反应之间的群体特异性联系

Ji Tang, Hao Zhu
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引用次数: 0

摘要

基因组就像一个万花筒,研究人员通过它获得了各种各样的发现,包括有利的突变、疾病易感性位点和药物反应位点。这些发现是否有内在联系是一个值得研究的问题。有利的突变使人类能够适应不断变化的环境和生活方式;然而,这种适应可能会带来一些代价。这是因为一个有利的突变可以改变一个大的基因组区域中各种中性核苷酸的频率,而一个有利的突变可能随着环境和生活方式的进一步改变而变得不利。这些是最著名的联系类别,其原因和结果已经被理解。然而,许多有利的突变仍未被发现。利用深度学习网络(deepfavor)集成了统计测试,并在大型数据集上进行了训练,最近在17个人群中发现了有利的突变。对结果的分析与全基因组关联研究(GWAS)数据相结合,表明适应性进化、疾病易感性和药物反应性(称为权衡)之间的联系是广泛的,并且具有高度的人群特异性。这些分析以及其他新出现的证据表明,还有其他类型的联系。在这篇评论中,这些问题从回顾和展望的角度进行了讨论,包括当前的挑战和未来的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

How Everything Is Connected to Everything Else – Population-Specific Connections between Adaptive Evolution, Disease Susceptibility, and Drug Responsiveness

How Everything Is Connected to Everything Else – Population-Specific Connections between Adaptive Evolution, Disease Susceptibility, and Drug Responsiveness

The genome is like a kaleidoscope through which researchers have obtained varied findings, including favored mutations, disease susceptibility sites, and drug-responsive sites. Whether these findings have inherent connections is a question deserving investigation. Favored mutations enable humans to adapt to changing environments and lifestyles; however, the adaptation may come with some costs. This is because a favored mutation can change the frequency of varied neutral nucleotides across a large genomic region, and a favored mutation may become disfavored as environments and lifestyles change further. These are the best-known classes of connections whose causes and consequences have been understood. However, many favored mutations remain unidentified. Using a deep learning network (DeepFavored) that integrates statistical tests and is trained on large datasets, favored mutations are recently identified in 17 human populations. The analyses of the results, in conjunction with genome-wide association study (GWAS) data, suggest that the connection between adaptive evolution, disease susceptibility, and drug responsiveness (referred to as a trade-off) is extensive and highly population-specific. The analyses, along with other emerging evidence, suggest that there are other types of connections. In this commentary, these issues are discussed from both retrospective and prospective views, including current challenges and future directions.

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