基因组比对中的隐藏断点
Hidden breakpoints in genome alignments
摘要：
在进化过程中，生物体的基因组可以经历影响基因组大规模结构的变化。这些变化包括基因获得、丢失、复制、染色体融合、分裂和重排。当基因获得和丢失除了发生其他类型的重排，重排的断点可以存在，只能通过比较三个或更多个基因组检测。任意数量的这些“隐藏”断点可以存在于在成对比较中没有表现出重排的基因组中。我们提出了一个扩展的多染色体断点中位数问题的基因组，经历了基因的获得和损失。然后，我们证明了三个基因组之间的中位数距离可以用来计算存在的隐藏断点的数量的下限。我们提供了这种计算的实现，包括中值距离，以及底层算法的时间复杂度的一些实际改进。我们应用我们的方法来衡量丰富的隐藏断点在模拟数据集下的广泛的进化场景。我们表明，在模拟中的隐藏断点计数强烈依赖于相对速率的反转和基因的增益/损失。最后，我们将当前的多个基因组比对的模拟基因组，并表明，所有的比对引入了高度的错误隐藏断点计数，这种错误的增长与进化的距离在模拟。我们的研究结果表明，隐藏的断点错误可能是普遍的基因组比对。
英文摘要：
During the course of evolution, an organism's genome can undergo changes that affect the large-scale structure of the genome. These changes include gene gain, loss, duplication, chromosome fusion, fission, and rearrangement. When gene gain and loss occurs in addition to other types of rearrangement, breakpoints of rearrangement can exist that are only detectable by comparison of three or more genomes. An arbitrarily large number of these "hidden" breakpoints can exist among genomes that exhibit no rearrangements in pairwise comparisons. We present an extension of the multichromosomal breakpoint median problem to genomes that have undergone gene gain and loss. We then demonstrate that the median distance among three genomes can be used to calculate a lower bound on the number of hidden breakpoints present. We provide an implementation of this calculation including the median distance, along with some practical improvements on the time complexity of the underlying algorithm. We apply our approach to measure the abundance of hidden breakpoints in simulated data sets under a wide range of evolutionary scenarios. We demonstrate that in simulations the hidden breakpoint counts depend strongly on relative rates of inversion and gene gain/loss. Finally we apply current multiple genome aligners to the simulated genomes, and show that all aligners introduce a high degree of error in hidden breakpoint counts, and that this error grows with evolutionary distance in the simulation. Our results suggest that hidden breakpoint error may be pervasive in genome alignments.
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