多倍体植物系谱的概率重建
Probabilistic reconstruction of genealogies for polyploid plant species
摘要：
通过考虑作为给定基因型中等位基因存在的概率分析的遗传数据，研究了多倍体群体（从2x到4x）中系谱的概率重建。基于所有可能的杂交模式的可能性，我们的模型使我们能够推断和量化人口中的整个潜在系谱。我们特别解释如何处理不确定的等位基因多样性，可能会发生与多倍体。然后，我们建立一个\textit{ad hoc}惩罚似然比较家谱，并决定是否一个特定的个人带来了足够的信息，包括在所采取的家谱。这个决策标准使我们能够在下一部分中提出一个贪婪算法，以探索缺失的链接，并在家谱中重建一些联系。作为一个副产品，我们还提供了一种方法来推断这些年来可能受到育种者青睐的个体。在最后一部分中，我们突出了我们的模型和算法给出的结果，首先在模拟人口，然后在一个真正的人口玫瑰丛。大多数方法依赖于最大似然原理和图论。
英文摘要：
A probabilistic reconstruction of genealogies in a polyploid population (from 2x to 4x) is investigated, by considering genetic data analyzed as the probability of allele presence in a given genotype. Based on the likelihood of all possible crossbreeding patterns, our model enables us to infer and to quantify the whole potential genealogies in the population. We explain in particular how to deal with the uncertain allelic multiplicity that may occur with polyploids. Then we build an \textit{ad hoc} penalized likelihood to compare genealogies and to decide whether a particular individual brings sufficient information to be included in the taken genealogy. This decision criterion enables us in a next part to suggest a greedy algorithm in order to explore missing links and to rebuild some connections in the genealogies, retrospectively. As a by-product, we also give a way to infer the individuals that may have been favored by breeders over the years. In the last part we highlight the results given by our model and our algorithm, firstly on a simulated population and then on a real population of rose bushes. Most of the methodology relies on the maximum likelihood principle and on graph theory.
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