利用优势分离标记构建连锁-连锁不平衡图谱

Xuli Zhu, Leiming Dong, Libo Jiang, Huan Li, Lidan Sun, Hui Zhang, Weiwu Yu, Haokai Liu, Wensheng Dai, Yanru Zeng, R. Wu
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引用次数: 15

摘要

链接不平衡(LD)与重组分数之间的关系可以用来推断人类和其他系统的遗传变异模式和进化过程。我们描述了一个计算框架,从常用的双等位基因,单核苷酸多态性(SNP)标记构建一个连锁- LD图谱,通过该图谱,LD的下降随着遗传距离的增加而可视化。该框架来源于一个开放授粉(OP)设计,该设计由从自然群体中随机取样的植物和每个取样植物的种子组成,可以同时估计自然群体中的LD和由于减数分裂期间等位基因共分离而导致的重组分数。我们修改了这个框架,利用那些以主导方式分离的标记类型来推断自然种群的进化历史,考虑到它们在创造和维持种群遗传多样性方面的作用。采用一种复杂的两级EM算法来估计和检索以单甲基化多态性等显性分离标记为特征的分离缺失信息。应用该模型研究了中国东南部自然分布的裸子植物大香榧(Torreya grandis)非模式异交种的连锁与遗传变异的关系。利用各种类型的分子标记构建的连锁- ld图谱为研究植物进化史打开了一个强有力的门户。
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Constructing a linkage–linkage disequilibrium map using dominant-segregating markers
The relationship between linkage disequilibrium (LD) and recombination fraction can be used to infer the pattern of genetic variation and evolutionary process in humans and other systems. We described a computational framework to construct a linkage–LD map from commonly used biallelic, single-nucleotide polymorphism (SNP) markers for outcrossing plants by which the decline of LD is visualized with genetic distance. The framework was derived from an open-pollinated (OP) design composed of plants randomly sampled from a natural population and seeds from each sampled plant, enabling simultaneous estimation of the LD in the natural population and recombination fraction due to allelic co-segregation during meiosis. We modified the framework to infer evolutionary pasts of natural populations using those marker types that are segregating in a dominant manner, given their role in creating and maintaining population genetic diversity. A sophisticated two-level EM algorithm was implemented to estimate and retrieve the missing information of segregation characterized by dominant-segregating markers such as single methylation polymorphisms. The model was applied to study the relationship between linkage and LD for a non-model outcrossing species, a gymnosperm species, Torreya grandis, naturally distributed in mountains of the southeastern China. The linkage–LD map constructed from various types of molecular markers opens a powerful gateway for studying the history of plant evolution.
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