Bayesian estimation of genomic clines
Bayesian estimation of genomic clines
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DOI：
10.1111/j.1365-294x.2011.05074.x
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发表时间：
2011-05-01
影响因子：
4.9
通讯作者：
Buerkle, C. Alex
中科院分区：
文献类型：
--
作者：
Gompert, Zachariah;Buerkle, C. Alex
我们建立了一个贝叶斯基因组无性系模型来研究杂交谱系之间的适应性分化和生殖隔离的遗传结构。该模型用两个渐变系参数来量化基因座特异性的渐渗模式，所述渐变系参数描述基因座特异性祖先的概率作为全基因组混合物的函数。可以鉴定相对于大多数基因组具有极端渐渗模式的“离群”基因座。这些位点可能与适应性分化或生殖隔离有关。我们模拟了混合种群的遗传数据，包括中性渐渗，以及基因座的定向，上位性或欠显性选择，并分析这些数据使用贝叶斯基因组渐变模型。在许多人口条件下，显性不足或定向选择有可检测和可预测的影响，对渐变系参数，和“离群”基因座的选择影响的遗传区域大大丰富。我们还分析了先前发表的遗传数据，从两个横断面通过一个混合区之间的小家鼠和M。肌肉我们发现在基因组的渐渗率相当大的变化，特别是两个X连锁标记的渐渗率低。两个样带之间的渐渗模式有相似性和差异，这可能反映了随机变异的组合，因为遗传漂变和地理变异的遗传结构的生殖隔离。通过提供一个强大的框架来量化和比较基因区域和种群之间的渐渗模式，贝叶斯基因组渐变群模型将促进我们对生殖隔离和物种形成过程的遗传学的理解。
We developed a Bayesian genomic cline model to study the genetic architecture of adaptive divergence and reproductive isolation between hybridizing lineages. This model quantifies locus-specific patterns of introgression with two cline parameters that describe the probability of locus-specific ancestry as a function of genome-wide admixture. 'Outlier' loci with extreme patterns of introgression relative to most of the genome can be identified. These loci are potentially associated with adaptive divergence or reproductive isolation. We simulated genetic data for admixed populations that included neutral introgression, as well as loci that were subject to directional, epistatic or underdominant selection, and analysed these data using the Bayesian genomic cline model. Under many demographic conditions, underdominance or directional selection had detectable and predictable effects on cline parameters, and 'outlier' loci were greatly enriched for genetic regions affected by selection. We also analysed previously published genetic data from two transects through a hybrid zone between Mus domesticus and M. musculus. We found considerable variation in rates of introgression across the genome and particularly low rates of introgression for two X-linked markers. There were similarities and differences in patterns of introgression between the two transects, which likely reflects a combination of stochastic variability because of genetic drift and geographic variation in the genetic architecture of reproductive isolation. By providing a robust framework to quantify and compare patterns of introgression among genetic regions and populations, the Bayesian genomic cline model will advance our understanding of the genetics of reproductive isolation and the speciation process.