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An integrated approach to genome evolution using the Drosophila model

使用果蝇模型进行基因组进化的综合方法

基本信息

批准号：
BB/T007516/1
负责人：
Darren Obbard
金额：
$ 79.78万
依托单位：
University of Edinburgh
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2020
资助国家：
英国
起止时间：
2020 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=BB%2FT007516%2F1
关键词：
integrated approach genome evolution using

项目摘要

Developed over the past hundred years, 'population genetics' (the study of how genes and genetic material are inherited in populations) has provided a rigorous mathematical basis for evolutionary theory. More recently, as genome-scale DNA sequencing has moved from being merely possible to routine, 'population genetics' has become 'population genomics', and our power to link theory with data has grown beyond the wildest dreams of early evolutionary biologists. We now, almost routinely, have access to hundreds or even thousands of genomes -- at least from a few key species such as humans, mice, and the classical laboratory fruit fly, Drosophila melanogaster. These data allow us deep insight into the mechanisms of genome evolution in these species, and start to allow us a general picture of the way genomes evolve.From a genetic perspective, theory says that -- when single populations are considered -- four processes matter. These are mutation, which creates new variants in the population, recombination, which creates new combinations of variants, natural selection, which determines whether variants become more common or are lost from the population, and genetic drift, which describes how variants change in frequency when selection is weak or absent. By estimating the rates at which each of these processes occur, how they vary within genomes and among species, and how they correlate with each other, we can ultimately hope to provide a complete genetic view of genome evolution.However, while there are good estimates for some rates (such as recombination rate) from many species, and good estimates of all rates from a very few species, there is no group of related plant or animal species for which all rates have been estimated. In particular, there are very few direct experimental estimates of mutation rate from plants or animals, so we have little idea of how this varies among species or how it correlates with the other processes. Our research aims to fill this gap in our knowledge by quantifying all four processes in a single set of 23 related Drosophila species. The most recent ancestor of these flies lived more than 30 million year ago, the species come from all over the world, and they vary in their size, what they eat, how long they live, their optimum temperature, and even how susceptible they are to disease. What they have in common is that we can breed them in the lab, and that we already know enough about their biology to benefit from studying it further. In this project we will directly estimate mutation and recombination rates and how they vary within and among species, and we will use population-genetic theory to indirectly estimate the strength of selection and the long-term rate of genetic drift. We will do this by sequencing 7 genomes (two parents and 5 offspring) from 5 families from each of the 23 species of Drosophila. We will directly identify new mutations and new recombination events that are present in the offspring but absent from their parents to estimate the rate that these processes occur. Then, using the parental genomes (and incorporating information from the offspring), we will use indirect (population-genetic) methods to infer the historic strength of selection and rates of genetic drift. These data will allow us to describe genome evolution in this group of important and well-studied species more completely that ever before. And, by doing this, we will not only gain a better understanding of the evolutionary process, but also provide data to further test theory and drive its ongoing development. Our data will also be available to many other researchers for future work on other topics, beyond this proposal.

经过过去百年的发展，“群体遗传学”（研究基因和遗传物质如何在群体中遗传）为进化论提供了严格的数学基础。最近，随着基因组规模的 DNA 测序已从仅仅可能变为常规，“群体遗传学”已成为“群体基因组学”，我们将理论与数据联系起来的能力已经超出了早期进化生物学家最疯狂的梦想。现在，我们几乎可以例行公事地获得数百甚至数千个基因组——至少来自人类、小鼠和经典实验室果蝇、黑腹果蝇等几个关键物种的基因组。这些数据使我们能够深入了解这些物种的基因组进化机制，并开始让我们对基因组进化方式有一个总体了解。从遗传学的角度来看，理论表明，当考虑单个种群时，有四个过程很重要。它们是突变（在群体中产生新的变异）、重组（产生新的变异组合）、自然选择（决定变异是否变得更常见还是从群体中消失）以及遗传漂变（描述当选择较弱或不存在时变异频率如何变化）。通过估计每个过程发生的速率、它们在基因组内和物种之间如何变化以及它们如何相互关联，我们最终希望提供基因组进化的完整遗传视图。然而，虽然对许多物种的某些速率（例如重组率）有很好的估计，并且对极少数物种的所有速率都有很好的估计，但没有一组相关的植物或动物物种的所有速率都已估计。特别是，很少有对植物或动物突变率的直接实验估计，因此我们几乎不知道突变率在物种之间如何变化，或者它与其他过程如何相关。我们的研究旨在通过量化一组 23 个相关果蝇物种的所有四个过程来填补我们的知识空白。这些苍蝇的最近祖先生活在超过3000万年前，其物种来自世界各地，它们的大小、吃什么、寿命、最适温度，甚至对疾病的易感性都各不相同。它们的共同点是我们可以在实验室中培育它们，并且我们已经对它们的生物学了解足够多，可以从进一步研究中受益。在这个项目中，我们将直接估计突变和重组率以及它们在物种内部和物种之间的变化，并且我们将使用群体遗传理论来间接估计选择的强度和遗传漂变的长期速率。我们将通过对 23 个果蝇物种的 5 个科的 7 个基因组（两个亲本和 5 个后代）进行测序来实现这一目标。我们将直接识别后代中存在但其父母中不存在的新突变和新重组事件，以估计这些过程发生的速率。然后，利用亲代基因组（并结合后代的信息），我们将使用间接（群体遗传）方法来推断选择的历史强度和遗传漂变率。这些数据将使我们能够比以往更完整地描述这组重要且经过充分研究的物种的基因组进化。而且，通过这样做，我们不仅可以更好地理解进化过程，还可以提供数据来进一步检验理论并推动其持续发展。除了本提案之外，我们的数据也将提供给许多其他研究人员用于未来其他主题的工作。