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Interplay of Interlocus Gene Conversion and Crossover in Segmental Duplications Under a Neutral Scenario

机译:中性情景下节间基因转换和节间基因转换之间的相互作用。

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摘要

Interlocus gene conversion is a major evolutionary force that drives the concerted evolution of duplicated genomic regions. Theoretical models successfully have addressed the effects of interlocus gene conversion and the importance of crossover in the evolutionary fate of gene families and duplications but have not considered complex recombination scenarios, such as the presence of hotspots. To study the interplay between interlocus gene conversion and crossover, we have developed a forward-time simulator that allows the exploration of a wide range of interlocus gene conversion rates under different crossover models. Using it, we have analyzed patterns of nucleotide variation and linkage disequilibrium within and between duplicate regions, focusing on a neutral scenario with constant population size and validating our results with the existing theoretical models. We show that the interaction of gene conversion and crossover is nontrivial and that the location of crossover junctions is a fundamental determinant of levels of variation and linkage disequilibrium in duplicated regions. We also show that if crossover activity between duplications is strong enough, recurrent interlocus gene conversion events can break linkage disequilibrium within duplicates. Given the complex nature of interlocus gene conversion and crossover, we provide a framework to explore their interplay to help increase knowledge on molecular evolution within segmental duplications under more complex scenarios, such as demographic changes or natural selection.
机译:Interlocus基因转换是一种主要的进化力,它驱动重复的基因组区域的协调进化。理论模型成功地解决了基因间基因转换的影响以及交叉在基因家族和复制的进化命运中的重要性,但是并未考虑复杂的重组情况,例如热点的存在。为了研究中间基因转换与交叉之间的相互作用,我们开发了一种前向时间模拟器,该模拟器可以探讨不同交叉模型下广泛的中间基因转换率。使用它,我们分析了重复区域内和之间的核苷酸变异和连锁不平衡的模式,重点研究了种群数量恒定的中性场景,并用现有的理论模型验证了我们的结果。我们表明基因转换和交叉的相互作用是不平凡的,并且交叉连接的位置是重复区域中变异和连锁不平衡水平的基本决定因素。我们还显示,如果重复之间的交叉活性足够强,重复的基因座间基因转换事件可能会破坏重复内部的连锁不平衡。考虑到中间基因转换和交叉的复杂性,我们提供了一个框架来探索它们之间的相互作用,以帮助增加在更复杂的情况下(如人口变化或自然选择)在区段重复中分子进化的知识。

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