Evolution of Genome Organization

这是一个计算生物学程序，旨在提高我们对基因组进化的理解。公共资料库中丰富的已测序和注释基因组揭示了在序列、基因组织和核型方面巨大的结构多样性，这是进化过程中发生的各种机制的足迹：单核苷酸替换是序列多样性的起源，重复和其他内容修改操作是基因家族多样性的起源，重排是基因顺序多样性的起源。每一种类型的足迹都被单独用来解决不同的问题。序列相似性是将基因聚类成家族和构建系统发育树的主要标准。内容修改操作被用来推断基因拷贝之间的同源/同源关系，这对基因的注释和功能特异性具有重要的意义。至于基因序列的多样性，在比较基因组学中被用来推断祖先的特征，并研究进化过程中发生的重排(倒位、转位、易位、融合、裂变)。在这个项目中，我们试图将这三种类型的足迹整合到一个统一的方法中，用于推断祖先基因组。这是比较基因组学的主要目标之一，不仅从进化论的角度来看是至关重要的，而且对于进化过程中发生的机制对物种的遗传和生理特性的重要影响也是重要的，对药物发现和个人医学具有深远的应用。现有的大多数推断祖先基因组的方法完全依赖于基因序列信息，忽略了所有关于基因家族的系统发育信息，这严重限制了它们对具有多个基因拷贝的基因组的适用性。考虑基因树的综合方法最直接的好处是避免了对数据集的大幅过滤，从而提高了预测祖先特征的精度。

This is a computational biology program aiming to improve our understanding of genome evolution. The abundance of sequenced and annotated genomes present in public repositories has revealed a tremendous diversity of structures in terms of sequence, gene organization and karyotype, which is the footprint of the various mechanisms taking place during evolution: single nucleotide substitutions are at the origin of sequence diversity, duplications and other content-modifying operations are at the origin of gene family diversity and rearrangements are at the origin of gene order diversity. Each of these types of footprints has been used separately to address different questions. Sequence similarity is the main criterion used to cluster genes into families and to construct phylogenetic trees. Content-modifying operations are used to infer the orthology/paralogy relation between gene copies, which has important implications towards the annotation and functional specificity of genes. As for the diversity of gene order, it is used in comparative genomics to infer ancestral features and study the rearrangements (inversions, transpositions, translocations, fusions, fissions) taking place during evolution. In this program we seek to integrate the three types of footprints in a unified methodology for the Inference of Ancestral Genomes. This is one of the main goals of comparative genomics essential not only from an evolutionary perspective, but also for important implications of the mechanisms taking place during evolution on the genetic and physiological specificities of species, with far-reaching applications to drug discovery and personal medicine. Most existing methods for inferring ancestral genomes stand exclusively on gene order information, ignoring all available phylogenetic information on gene families, which is a serious limitation towards their applicability to genomes with multiple gene copies. The most direct benefit of an integrative method accounting for gene trees will be to avoid a drastic filtering of datasets, allowing an increase of precision of the predicted ancestral features.