An integrated approach to understanding spontaneous mutation and natural selection in the Chlamydomonas genome

自然选择的进化是由个体之间的基因变异推动的，这些变异最终源于新的突变。因此，新的自发突变的出现速度，无论它们是有益的还是有害的，及其影响的程度都对进化的模式和速度产生深远的影响。例如，如果新的有益突变的出现率非常低，适应往往会受到这些突变供应的限制，而如果有益突变的比率很高，适应将受到其他过程的限制，例如自然选择改变基因频率的速度。不幸的是，事实证明，估计突变参数很困难，尽管新突变对进化很重要，但几乎没有可靠的估计。我们将结合两种方法，旨在提供我们的模型系统--单细胞藻类莱茵衣藻--突变过程的更全面的图景。研究突变供应的部分困难在于，自然选择在自然种群中运作，移除有害突变并增加有益突变的频率。因此，我们在种群内和物种之间观察到的遗传差异是最初出现的那些突变的过滤和有偏见的子集。我们的第一个方法将是在自然选择的影响最小化的条件下，将莱茵哈迪伊线虫的复制系保持数百代。这将使我们能够检查新突变的全部谱系的影响，而不仅仅是那些通过选择过滤器的突变。然后，我们将使用最先进的基因组测序技术来检查这些品系的子集的完整基因组序列，这将使我们能够直接在DNA水平上测量突变的数量和种类。综上所述，这些信息将为我们提供自然选择可用的燃料的详细图景。我们的第二种方法也将利用全基因组测序的力量来获得从自然种群中采样的莱茵哈迪伊线虫基因组变异的详细图片。通过比较基因组不同部分的变异数量和分布，我们将能够量化自然条件下的选择如何作用于最初产生我们观察到的变异的突变。通过比较基因组不同区域之间的遗传差异，我们还将能够剖析基因组的功能组织，并确定哪些区域受到限制，因此保持相对不变，哪些区域有更大的变化自由。我们还计划获得与莱恩哈迪伊线虫最接近的近亲Incerta的基因组序列。通过比较莱茵隐翅虫和不确定隐翅虫的基因组序列，我们将能够推断这两个物种之间基因组的主要适应性变化。这些问题的答案将在进化生物学的许多领域提供重要的见解，从帮助我们理解为什么大多数真核物种有性繁殖，到使我们能够预测未来种群对环境变化的反应可能是基于现有的或新的基因变异。

Evolution by natural selection is fueled by genetic variation among individuals that ultimately originates from new mutations. Thus, the rate of appearance of new spontaneous mutations, whether they are beneficial or harmful and the magnitudes of their effects have profound consequences for the mode and speed of evolution. For example, if the rate of appearance of new beneficial mutations is very low, adaptation will frequently be limited by the supply of these mutations, whereas if the rate of beneficial mutations is high, adaptation will be limited by other processes, such as the speed with which natural selection can alter gene frequencies. Unfortunately, estimating mutational parameters has proved difficult, and, in spite of the importance of new mutations for evolution, there are few reliable estimates. We shall combine two approaches that aim to provide a fuller picture of the mutational process in our model system, the single-celled alga Chlamydomonas reinhardtii. Part of the difficulty in examining the supply of mutations is that natural selection operates in natural populations and removes deleterious mutations and increases the frequency of beneficial ones. Thus, the genetic differences that we observe within populations and between species are filtered and biased subsets of those mutations that arose in the first place. Our first approach will be to maintain replicate lines of C. reinhardtii for several hundred generations in conditions in which the effects of natural selection are minimised. This will allow us to examine the effects of the full spectrum of new mutations, not just those that pass through the filter of selection. We will then use state-of-the-art genome sequencing technologies to examine the complete genome sequences of a subset of these lines, which will allow us to measure directly the number and kinds of mutational changes at the DNA level. Taken together this information will provide us with a detailed picture of the fuel available to natural selection. Our second approach will also harness the power of whole genome sequencing to obtain a detailed picture of variation in the genome of C. reinhardtii sampled from a natural population. By comparing the amount and distribution of variation in different parts of the genome, we will be able to quantify how selection in natural conditions has acted on the mutations that originally generated the variation we observe. By comparing the genetic differences between different regions of the genome we will also be able to dissect the functional organisation of the genome, and determine which regions are constrained and so have remained relatively unchanged and which areas have more freedom to vary. We also plan to obtain the genome sequence of the closest relative of C. reinhardtii, C. incerta. By comparing the sequences of the C. reinhardtii and C. incerta genomes we shall be able to infer the principal adaptive changes in the genome between the two species. Answers to these questions will provide important insights in many areas of evolutionary biology, from helping us to understand why most eukaryotic species reproduce sexually to allowing us to predict whether the future responses of populations to environmental change is likely to be based on existing or new genetic variation.