An algorithmic framework for gene family evolution

基因家族进化的算法框架

• 批准号: RGPIN-2018-05049
• 负责人: ElMabrouk, Nadia
• 金额: $ 3.5万
• 依托单位: Université de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=689635
• 关键词: algorithmic; framework; gene; family; evolution

This is a computational biology project aiming at developing the appropriate algorithmic tools for inferring the evolution of genes.******Genes are the basic molecular units of heredity, key for understanding biological mechanisms. A first step of most genetic studies is to group genes into families according to sequence similarity, the underlying idea being that similar sequences reflect divergence from a common ancestor. Within a gene family, «orthlogs» genes originating from a speciation event are more likely to preserve the ancestral function than «paralogs» or «xenologs» originating from duplications or Horizontal Gene Transfer (HGT). This is a major motivation for inferring gene evolution, as it is a prerequisite for functional prediction purposes.******Tree-based methods for gene relation prediction consist in reconstructing a phylogenetic tree for the gene family, and then inferring the nature of internal nodes (speciation, duplication or HGT) from a «reconciliation», i.e. an embedding of the gene tree into the species tree. The accuracy of these methods strongly depend on the accuracy of the considered gene tree. However, for various reasons, classical phylogenetic methods are error prone. This motivates the gene tree correction part of this project.******Reconciliation is based on the assumption that each gene family evolves independently through single gain and loss events. Although this hypothesis holds for genes that are far apart in the genome, it is not appropriate for genes appearing grouped into blocs of co-linear genes, which are more plausibly the result of a concerted evolution. Methods for inferring segmental duplication, loss and HGT, combining both tree and order information, are required in this case.******Tree-free methods also exist for gene relation prediction. They are mainly based on hierarchical clustering according to sequence similarity. Results of these methods are pairwise gene relations that can be represented by means of a coloured graph (a colour for each type of relation). While a gene tree induces a set of relations between genes, the converse is not always true, as a set of relations may not represent a valid history for a gene family. Determining and correcting a set of relation for «satisfiability» and «consistency» with a species tree are two important problematics that we handle in this project.******In summary, our goal is to produce gold standard gene trees, infer accurate gene relations and predict the actual evolutionary events that have led to the observed gene diversity, as well as ancestral gene contents and orders. We will explore optimization problems on strings, trees and graphs, study their theoretical complexity, develop exact, approximation and heuristic algorithms, test them on simulated datasets and apply them to the biological datasets if interest. Developed algorithms will be implemented into freely available user-friendly and well documented software.**

这是一个计算生物学项目，旨在开发适当的算法工具来推断基因的演变。****基因是遗传的基本分子单位，是理解生物学机制的关键。大多数遗传研究的第一步是根据序列相似性将基因分为家族，而基本的想法是相似的序列反映了与共同祖先的差异。在基因家族中，源自规格事件的“正牙基因”基因更有可能保留祖先功能，而不是源自重复或水平基因转移（HGT）的«paralogs'或«Xenologs'。这是推断基因进化的主要动机，因为它是功能性预测目的的先决条件。****基于基因关系预测的基于树的方法包括重建基因家族的系统发育树，然后推断出内部节点的性质（从«conemed on onemed of nosece.ement of nosece.ement of note note of note of nocted on nosen on on egnemed on egnemed on nosecte nosecte of note of nocte of neg of neg of nege on egnem a note nosece。这些方法的准确性在很大程度上取决于所考虑的基因树的准确性。但是，由于各种原因，经典的系统发育方法是容易发生的。这激发了该项目的基因树校正部分。******和解基于以下假设：每个基因家族都通过单个增益和损失事件独立演变。尽管该假设适用于基因组中相距遥远的基因，但它并不适用于出现在共同基因集合中的基因，这些基因更合理地是由一致进化的结果。在这种情况下，需要推断分段重复，丢失和HGT（将树和订单信息结合在一起）的方法。******的无树方法也存在用于基因关系预测。它们主要根据序列相似性基于分层聚类。这些方法的结果是成对基因关系，可以通过彩色图表示（每种类型的关系的颜色）。尽管基因树诱导基因之间的一系列关系，但相反并不总是正确的，因为一组关系可能并不代表基因家族的有效历史。确定和纠正与物种树的“满意度”和“一致性”的一组关系是我们在该项目中处理的两个重要问题。******总而言之，我们的目标是生产金标准基因树，推断准确的基因关系并预测导致观察到的基因多样性的实际进化事件，以及祖先基因的内容以及祖先的基因和订单。我们将探索在字符串，树木和图形上的优化问题，研究其理论复杂性，确切，近似和启发式算法，在模拟数据集上测试它们，并在兴趣时将其应用于生物学数据集。开发的算法将被实施到可自由使用的用户友好且文档良好的软件中。**