Detecting signatures of natural selection in the human genome with geographically explicit models

利用地理明确的模型检测人类基因组中自然选择的特征

• 批准号: BB/H008691/1
• 负责人: Paul Flicek
• 金额: $ 18.72万
• 依托单位: European Bioinformatics Institute
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2010
• 资助国家: 英国
• 起止时间: 2010 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FH008691%2F1
• 关键词: Detecting; signatures; natural; selection; human

Modern sequencing techniques have provided us with very large genetic datasets, on a scale that was hard to imagine only a couple of years ago. As these datasets comprise human populations from the entire globe, it is tempting to look at the geographic distribution of genetic variants and try to find explanations for why some variants are more common in some places rather than others. After all, we have known for a long time that sickle cell anaemia is found in regions where malaria was prevalent, as it can confer resistance to the deadly disease. So, could we find other important genetic variants that have been affected by natural selection by examining their geographic distribution? While this approach sounds promising, it raises the issue of being able to distinguish between those patterns that truly reflect past and present selection, and patterns that might have simply arisen by chance. In this project, we propose to develop a population genetics framework that will allow us to reconstruct the spread of anatomically modern humans around the globe, taking into account past changes in climate and the shape of continents. By knowing how and when people got to different parts of the world, we will then be able to distinguish which genetic variants have geographic distributions too extreme to be the result of mere chance, and thus have been the target of natural selection. Besides looking for regions under selection in the nuclear genome, we will also consider the small amount of genetic material contained in the mitochondria, small organelles that act as the biochemical powerhouses in our cells. Mitochondrial DNA is arguably the most widely used source of information for reconstructing human past history, but such reconstructions rely on the assumption that mitochondrial DNA has not been affected by natural selection. Our new framework, together with a better geographic coverage of mitochondrial genetic variability that will be achieved in this project, will allow us to test the assumption of neutrality and to find any deviation that should be taken into account in future work on human settlement history.

现代测序技术为我们提供了非常大的遗传数据集，其规模在几年​​前还是难以想象的。由于这些数据集包含来自全球的人口，因此很容易观察遗传变异的地理分布，并尝试找到解释为什么某些变异在某些地方而不是其他地方更常见。毕竟，我们很早就知道镰状细胞贫血症存在于疟疾流行的地区，因为它可以赋予人们对这种致命疾病的抵抗力。那么，我们能否通过检查其地理分布来找到其他受自然选择影响的重要遗传变异？虽然这种方法听起来很有希望，但它提出了一个问题，即能够区分那些真正反映过去和现在选择的模式，以及可能只是偶然出现的模式。在这个项目中，我们建议开发一个群体遗传学框架，使我们能够重建解剖学上现代人类在全球的传播，同时考虑到过去的气候变化和大陆形状。通过了解人们如何以及何时到达世界不同地区，我们将能够区分哪些基因变异的地理分布过于极端而不仅仅是偶然的结果，因此成为自然选择的目标。除了寻找核基因组中被选择的区域外，我们还将考虑线粒体中含有的少量遗传物质，线粒体是细胞中充当生化动力的小细胞器。线粒体 DNA 可以说是重建人类过去历史最广泛使用的信息来源，但这种重建依赖于线粒体 DNA 没有受到自然选择影响的假设。我们的新框架，加上该项目将实现的线粒体遗传变异性的更好地理覆盖，将使我们能够测试中立性假设，并找到在未来人类住区历史工作中应考虑的任何偏差。