A Bioinformatics Framework to Understand the Fate of Duplicated Genes in Evolution

在进化过程中，物种经历基因组突变，使它们获得独特的性状和生物功能。 基因复制就是这样一个事件，它是今天生物多样性的主要原因。 当一个基因被复制时，它会产生一个多余的拷贝，可以自由进化和开发新的功能。 然而，并不是所有的基因都会经历这种命运，因为一些拷贝可能与它们的原始基因具有相同的功能，或者变得无功能。 因此，了解复制基因的机制和命运对于了解生物功能是如何获得和丧失的至关重要。 这项国际合作的主要目标是开发一个计算框架，从基因组数据中推断重复基因的命运。 我们将为这项任务设计新的模型和算法，我们将评估我们的框架上的生物进化的现实模拟器，其次是应用程序上的真实的数据。 这项合作结合了Guillaume Beslon博士（ENS-Lyon）模拟现实进化的专业知识和Manuel Lafond博士（U。de Sherbrooke）创建高效的推理和分析算法。 这一提议将提高我们对进化的基本理解，这在生物学上有几个实际应用。 例如，这可以帮助寻找人类和动物共有的基因进行药物测试，或预测病毒和肿瘤的进化。 我们的研究还将通过改进当前的进化模型和为软件开发人员提供更逼真的模拟来影响生物信息学的计算机科学方面。 最后，这项建议将加强加拿大在比较基因组学方面的领导地位。

During the course of evolution, species undergo genomic mutations that allow them to gain distinct traits and biological functions. Gene duplication is one such event and is largely responsible for today's biodiversity. When a gene is duplicated, it creates a redundant copy that is free to evolve and develop new functions. However, not all genes go through this fate, as some copies may share the same function as their originator or become non-functional. Understanding the mechanisms and fates of duplicated genes is therefore crucial to gain knowledge on how biological functions are gained and lost. The main objective of this international collaboration is to develop a computational framework to infer the fate of duplicated genes from genomic data. We will devise novel models and algorithms for this task and we will evaluate our framework on a realistic simulator of biological evolution, followed by applications on real data. This collaboration combines the expertise of Dr. Guillaume Beslon (ENS-Lyon) for the simulation of realistic evolution, and Dr. Manuel Lafond (U. de Sherbrooke) for the creation of efficient inference and analysis algorithms. This proposal will improve our fundamental understanding of evolution, which can have several practical applications in biology. For instance, this can help finding genes shared by human and animals for drug-testing, or predicting the evolution of viruses and tumors. Our research will also impact the computer science side of bioinformatics by improving current evolutionary models and providing more realistic simulations to software developers. Finally, this proposal will reinforce Canada's leadership position in comparative genomics.