An integrated approach to genome evolution using the Drosophila model

在过去的一百年里，“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测序从仅仅是可能的变成了常规，“群体遗传学”已经成为“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。我们现在几乎可以常规地获得数百甚至数千个基因组--至少是来自一些关键物种，如人类、小鼠和经典的实验室果蝇。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的方式有一个大致的了解。从遗传学的角度来看，理论认为，当考虑单个种群时，四个过程很重要。它们是突变，在种群中产生新的变异;重组，产生新的变异组合;自然选择，决定变异是变得更常见还是从种群中消失;遗传漂变，描述当选择弱或不存在时变异的频率如何变化。通过估计这些过程中每一个发生的速率，它们在基因组内和物种间如何变化，以及它们如何相互关联，我们最终有望提供基因组进化的完整遗传学观点。（如重组率）从许多物种，和良好的估计所有率从极少数物种，没有一组相关的植物或动物物种的所有发病率都已估计。特别是，很少有直接的实验估计的突变率从植物或动物，所以我们不知道这是如何在物种之间的变化或它如何与其他过程的相关性。我们的研究旨在通过量化23个相关果蝇物种的所有四个过程来填补我们知识中的这一空白。这些苍蝇的最新祖先生活在3000多万年前，这些物种来自世界各地，它们的大小，它们吃什么，它们的寿命，它们的最适温度，甚至它们对疾病的易感性都不同。它们的共同点是，我们可以在实验室里培育它们，而且我们已经对它们的生物学有了足够的了解，可以从进一步的研究中受益。在这个项目中，我们将直接估计突变和重组率，以及它们在物种内和物种间的变化，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。我们将通过对来自23种果蝇中的每一种的5个家族的7个基因组（两个亲本和5个后代）进行测序来做到这一点。我们将直接识别存在于后代中但不存在于其亲本中的新突变和新重组事件，以估计这些过程发生的速率。然后，使用亲本基因组（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任何时候都更完整地描述这组重要且研究充分的物种的基因组进化。通过这样做，我们不仅可以更好地了解进化过程，还可以提供数据来进一步测试理论并推动其持续发展。我们的数据也将提供给许多其他研究人员，供他们在本提案之外的其他主题上开展未来的工作。

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.