A methodological framework for the reconstruction of contiguous regions of ancestral genomes and its application to mammalian genomes.
A methodological framework for the reconstruction of contiguous regions of ancestral genomes and its application to mammalian genomes.
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DOI：
10.1371/journal.pcbi.1000234
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发表时间：
2008-11
影响因子：
4.3
通讯作者：
Tannier E
中科院分区：
文献类型：
--
作者：
Chauve C;Tannier E
从现存物种之间的同源性重建祖先基因组结构和基因序列是一个长期存在的问题，细胞遗传学家和生物信息学家都认为这是一个长期存在的问题。最近在一系列论文中对这两种方法的比较进行了调查和讨论，有时对这两种方法的性能有不同的观点。我们描述了一个从现存基因组中保守的合线重建祖先基因组片段的一般方法框架。我们表明，从计算的角度来看，这个问题自然与染色体的物理映射有关，并从使用在此范围内开发的组合工具中受益。我们将这个框架发展成一种新的重建方法，考虑了具有相似基因含量的保守基因簇，模仿了大多数细胞遗传学研究中使用的原理，尽管是基于不同类型的数据。我们实现了它，并将其应用于哺乳动物基因组的数据集。我们与其他生物信息学方法进行了深入的理论和实验比较，以重建祖先基因组片段。结果表明，我们提出的方法是稳定可靠的：它给出了几种数据在不同分辨率水平下的收敛结果，并且所有预测的祖先区域都得到了很好的支持。这些结果最终与细胞遗传学研究非常接近。这表明，祖先基因组重建方法的比较应包括方法的算法方面以及数据获取的学科差异。数十万年后，没有DNA分子被保存下来，因此，只有通过计算估计，使用现存物种染色体之间的异同，才能推断出超过数百万年的古代生物的DNA序列组织。这就是古基因组学的范围，它可以帮助更好地理解基因组是如何进化到今天的。我们在这里提出了一个计算框架来估计祖先染色体的连续片段，该框架基于物理作图技术，当现有物种的基因组没有测序时，这些技术被用来推断它们的染色体图谱。这一框架不受可能的进化事件(如重排)的指导，只提出了祖先的基因组结构。我们开发了一种遵循这一框架的方法，并将其应用于哺乳动物基因组。我们推断，祖先的染色体区域在不同的分辨率水平上是稳定的和得到很好支持的。这些祖先的染色体区域与之前的细胞遗传学研究一致，很可能是生活在1.2亿年前的人类共同祖先猕猴、老鼠、狗和牛的基因组的一部分。我们通过与其他生物信息学方法的比较，说明了在比较从不同方法获得的祖先基因组架构建议时，正式方法学背景的重要性。
The reconstruction of ancestral genome architectures and gene orders from homologies between extant species is a long-standing problem, considered by both cytogeneticists and bioinformaticians. A comparison of the two approaches was recently investigated and discussed in a series of papers, sometimes with diverging points of view regarding the performance of these two approaches. We describe a general methodological framework for reconstructing ancestral genome segments from conserved syntenies in extant genomes. We show that this problem, from a computational point of view, is naturally related to physical mapping of chromosomes and benefits from using combinatorial tools developed in this scope. We develop this framework into a new reconstruction method considering conserved gene clusters with similar gene content, mimicking principles used in most cytogenetic studies, although on a different kind of data. We implement and apply it to datasets of mammalian genomes. We perform intensive theoretical and experimental comparisons with other bioinformatics methods for ancestral genome segments reconstruction. We show that the method that we propose is stable and reliable: it gives convergent results using several kinds of data at different levels of resolution, and all predicted ancestral regions are well supported. The results come eventually very close to cytogenetics studies. It suggests that the comparison of methods for ancestral genome reconstruction should include the algorithmic aspects of the methods as well as the disciplinary differences in data aquisition. No DNA molecule is preserved after a few hundred thousand years, so inferring the DNA sequence organization of ancient living organisms beyond several million years can only be achieved by computational estimations, using the similarities and differences between chromosomes of extant species. This is the scope of “paleogenomics”, and it can help to better understand how genomes have evolved until today. We propose here a computational framework to estimate contiguous segments of ancestral chromosomes, based on techniques of physical mapping that are used to infer chromosome maps of extant species when their genome is not sequenced. This framework is not guided by possible evolutionary events such as rearrangements but only proposes ancestral genome architectures. We developed a method following this framework and applied it to mammalian genomes. We inferred ancestral chromosomal regions that are stable and well supported at different levels of resolution. These ancestral chromosomal regions agree with previous cytogenetics studies and were very probably part of the genome of the common ancestor of humans, macaca, mice, dogs, and cows, living 120 million years ago. We illustrate, through comparison with other bioinformatics methods, the importance of a formal methodological background when comparing ancestral genome architecture proposals obtained from different methods.
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影响因子：
1.1
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