Effect and interaction of mutation and recombination in the dynamics of genetic variation in modern chickens

解决在定向选择下封闭群体中遗传变异是如何保持的是数量遗传学中的一个基本问题，但仍然是一个悬而未决的问题。解决这一问题也对作为全球主食生产系统基础的遗传改良方案的可持续性产生重大影响。相当多的研究工作集中在研究选择如何减少遗传变异以及如何在基因组中识别其足迹。很少有人研究遗传变异是如何重新产生并在几代人之间洗牌的。原因是，由于技术和经济的限制，到目前为止，在分析所需的大规模上跟踪突变是不可行的，突变是创造新的遗传变异的进化力量。遗传学家唯一可用的选择是依赖于突变率的低精度估计，因为它们大多来自实验群体的小规模研究。然后，这些参数将用于旨在描述遗传变异动态的模型中，由于缺乏观察到的突变率数据，这些模型基于许多理论假设。所用参数的不确定性，加上我们对遗传变异力的相互作用的有限理解，降低了我们目前模型捕捉潜在过程的能力，因此，解释了为什么“仍然没有明确的解决方案，进化力量负责维持变异”，作为定量遗传学的黄金标准教科书之一。（Lynch和沃尔什，2018）强调指出。该提议的主要假设是，在有限封闭群体中，例如精英育种群体，遗传变异的产生和改组速率可以抵消选择、遗传漂变和近交的影响。我们的目标是采取数据驱动的方法，以前所未有的准确性量化突变和重组过程，这可以解释遗传变异如何在处于强烈定向选择下的封闭种群中保持。为了实现这一目标，我们将使用一个独特的基因组库，该库由数十万只鸟类组成（无论是高深度测序还是用SNP阵列进行基因分型），这些鸟类延续了25代，具有完整的谱系和表型信息，以研究遗传变异如何随着时间的推移而保持。该数据集为我们提供了精确估计重要参数所需的能力，例如每一代发生多少突变事件，它们往往发生在基因组的何处，以及由于突变而产生的新遗传变异如何平衡其去除。随着我们的数据跨越多代，我们将有能力通过系谱追踪突变和染色体片段，以消除可能夸大估计的假阳性观察结果。我们的研究还将集中在量化重组，作为力量洗牌遗传变异，我们将探索其与突变的相互作用。最后，我们将应用我们更精确的估计来更新选择限制可能存在的理论预期，因此我们的目标是协调理论预测和观察结果。除了解决遗传变异如何维持这一关键问题的潜力外，我们的研究结果还可以直接应用于动植物育种组织，以提高其遗传改良计划的适应性和可持续性。

Resolving how genetic variation is maintained in closed populations under directional selection is one of the fundamental, yet still open questions in quantitative genetics. Addressing this question has also vital implications for the sustainability of genetic improvement programmes that underpin global staple food production systems. Considerable research effort has focused on studying how selection reduces genetic variation and how its footprint can be identified in the genome. Little effort has been placed to study how genetic variation is de-novo created and shuffled across generations. The reason is that until now, it was not feasible to track mutation, the evolutionary force creating new genetic variation, on the large-scale that analysis required, due to technological and economic constraints. The only option available to geneticists was to rely on low precision estimates for the mutation rate, since they mostly arose from small scale studies in experimental populations. These parameters then would be used in models aiming to describe the dynamics of genetic variation, which were based on many theoretical assumptions due to lack of data on the observed rate of mutation. The uncertainty of the parameters used, combined with our limited understanding of the interplay of forces on genetic variation, reduce the power of our current models to capture the underlying processes and therefore, explain why "there is still no clear resolution on the evolutionary forces responsible for the maintenance of variation", as one of the gold standard textbooks in Quantitative Genetics (Lynch and Walsh, 2018) emphatically states. The main hypothesis of this proposal is that the rate of creation and shuffling of genetic variation can counterbalance the effects of selection, genetic drift and inbreeding in finite closed populations, such as the elite breeding populations. Our goal is to take a data-driven approach to quantify with unprecedented accuracy the mutation and recombination processes that could explain how genetic variation appears to be maintained in closed populations that are under intense directional selection. To achieve this aim, we will use a unique genomic repository consisting of hundreds of thousands of birds (either sequenced in high-depth or genotyped with SNP arrays) extending over 25 generations with full pedigree and phenotypic information to study how genetic variation is maintained over time. This dataset gives us the required power to precisely estimate important parameters, such as how many mutational events occur per generation, where they tend to occur across the genome, and how the new genetic variation due to mutation balances its removal. As our data extend over many generations, we will have the power to track both mutations and chromosomal segments through the pedigree in order to remove false positive observations that can inflate estimates. Our study will also focus on quantifying recombination, as the force shuffling genetic variation, and we will explore its interplay with mutation. Finally, we will apply our more precise estimates to update theoretical expectations on where selection limits may lay and thus we will aim to reconcile theoretical predictions and observations. Beyond the potential to address the key question of how genetic variation is maintained, our findings could be directly applicable across animal and plant breeding organisations to improve the resilience and sustainability of their genetic improvement programmes.