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首页> 外文期刊>Genetics and molecular biology: publication of the Sociedade Brasileira de Genetica >Null expectation of spatial correlograms under a stochastic process of genetic divergence with small sample sizes
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Null expectation of spatial correlograms under a stochastic process of genetic divergence with small sample sizes

机译：小样本量的遗传差异随机过程下空间相关图的零期望

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An Ornstein-Uhlenbeck process was used to simulate the exponential relationship between genetic divergence and geographic distances, as predicted by stochastic processes of population differentiation, such as isolation-by-distance, stepping-stone or coalescence models. These simulations were based only on the spatial coordinates of the local populations that defined a spatial unweighted pair-group method using arithmetic averages (UPGMA) link among them. The simulated gene frequency surfaces were then analyzed using spatial autocorrelation procedures and Nei's genetic distances, constructed with different numbers of variables (gene frequencies). Stochastic divergence in space produced strong spatial patterns at univariate and mutivariate levels. Using a relatively small number of local populations, the correlogram profiles varied considerably, with Manhattan distances greater than those defined by other simulation studies. This method allows one to establish a range of correlogram profiles under the same stochastic process of spatial divergence, thereby avoiding the use of unnecessary explanations of genetic divergence based on other microevolutionary processes.
机译：如人口隔离的随机过程（如按距离隔离，踏脚石或合并模型）所预测的那样，使用了Ornstein-Uhlenbeck过程来模拟遗传差异与地理距离之间的指数关系。这些模拟仅基于局部种群的空间坐标，该局部种群使用算术平均值（UPGMA）链接定义了空间非加权成对分组方法。然后使用空间自相关程序和由不同数量的变量（基因频率）构建的Nei遗传距离分析模拟的基因频率表面。空间的随机发散在单变量和多变量水平上产生了强大的空间格局。使用相对较少的本地人口，相关图谱的变化很大，曼哈顿距离大于其他模拟研究所定义的距离。这种方法允许在相同的空间发散随机过程下建立一系列相关图谱，从而避免使用基于其他微进化过程的不必要的遗传发散解释。

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