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环状基因组上的重排事件。

Rearrangement Events on Circular Genomes.

机构信息

University of Tasmania, Hobart, Australia.

University of South Australia, Adelaide, Australia.

出版信息

Bull Math Biol. 2023 Sep 25;85(11):107. doi: 10.1007/s11538-023-01209-5.

Abstract

Early literature on genome rearrangement modelling views the problem of computing evolutionary distances as an inherently combinatorial one. In particular, attention is given to estimating distances using the minimum number of events required to transform one genome into another. In hindsight, this approach is analogous to early methods for inferring phylogenetic trees from DNA sequences such as maximum parsimony-both are motivated by the principle that the true distance minimises evolutionary change, and both are effective if this principle is a true reflection of reality. Recent literature considers genome rearrangement under statistical models, continuing this parallel with DNA-based methods, with the goal of using model-based methods (for example maximum likelihood techniques) to compute distance estimates that incorporate the large number of rearrangement paths that can transform one genome into another. Crucially, this approach requires one to decide upon a set of feasible rearrangement events and, in this paper, we focus on characterising well-motivated models for signed, uni-chromosomal circular genomes, where the number of regions remains fixed. Since rearrangements are often mathematically described using permutations, we isolate the sets of permutations representing rearrangements that are biologically reasonable in this context, for example inversions and transpositions. We provide precise mathematical expressions for these rearrangements, and then describe them in terms of the set of cuts made in the genome when they are applied. We directly compare cuts to breakpoints, and use this concept to count the distinct rearrangement actions which apply a given number of cuts. Finally, we provide some examples of rearrangement models, and include a discussion of some questions that arise when defining plausible models.

摘要

早期的基因组重排模型文献将计算进化距离的问题视为组合问题。具体来说,关注的是使用将一个基因组转换为另一个基因组所需的最少事件数来估计距离。事后看来,这种方法类似于从 DNA 序列推断系统发育树的早期方法,如最大简约法——两者都是基于真实距离最小化进化变化的原理,并且如果这一原理真实反映了现实,两者都是有效的。最近的文献考虑了在统计模型下的基因组重排,与基于 DNA 的方法保持这种平行关系,目的是使用基于模型的方法(例如最大似然技术)来计算距离估计,其中包括可以将一个基因组转换为另一个基因组的大量重排路径。至关重要的是,这种方法需要决定一组可行的重排事件,在本文中,我们专注于描述有充分理由的有符号、单染色体圆形基因组的模型,其中区域的数量保持不变。由于重排通常使用排列来数学描述,我们将表示在这种情况下具有生物学合理性的排列集分离出来,例如反转和转座。我们为这些重排提供了精确的数学表达式,然后根据在应用它们时在基因组中进行的切割集来描述它们。我们直接将切割与断点进行比较,并使用此概念来计算应用给定数量的切割的不同重排操作。最后,我们提供了一些重排模型的示例,并讨论了在定义合理模型时出现的一些问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd17/10520144/cbb01b1f442e/11538_2023_1209_Fig2_HTML.jpg

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