A temporal hidden Markov model approach to investigating the evolutionary fate of duplicated genes

进化论将来自不同有机体的实验观察联系在一起，为理解自然世界和生命是如何形成的提供了一个框架。分子生物学和遗传学的基础研究，再加上进化理论，直接促成了许多重要的经济和医学发现，从预测导致流感流行的病毒株，到工业过程中涉及的生物体和蛋白质的工程。这一建议使用进化论来研究新基因的起源，新基因是生物适应背后的主要驱动力之一。基因复制过程是新基因的主要来源，并被认为是基因组中功能创新和多样性的重要组成部分。复制在表型多样性、物种形成和发育中起着至关重要的作用。这项拟议的研究将调查1亿年前发生在酵母c1中的全基因组复制，这为更多地了解影响基因复制的进化机制提供了一个极好的机会。基因复制的通常结果是基因的两个副本中的一个丢失，因为它们最初都具有相同的功能。这一建议审查了复制后不会丢失的复制部分，因为它们发展了不同的功能和/或表达模式。有时，其中一个复制体获得了新的功能，导致有机体能够更好地利用其环境。或者，现有的功能和/或模式分布在这对复制品之间，这意味着为了有机体的生存，两者都需要保留。导致这两种结果的自然选择的力量仍然有待充分阐明，理解这些力量是解决关于基因功能起源的问题的基础。这项拟议的研究建立在PI创建的新计算方法的基础上，通过创建工具来解决关于这些关键进化事件的新问题。这些方法使用复杂的统计学方法来识别在基因进化史上作用于基因的选择性力量的变化，以及基因中选择性力量的变化。开发计算工具而不是实验室实验意味着可以检查酵母的整个基因组，并可以确定在整个基因组复制后负责保持特定复制的特定选择性作用力。大量关于酵母菌种类的实验室研究结果保存在世界各地的计算机数据库中。这项提议将把这些功能研究和从新方法中推断出的进化事件联系起来。这将揭示是什么生物因素影响了两个基因在复制后保持不变的机会。此外，以这种方式结合知识有可能提供一些特定基因在复制后如何保持的完整故事。当拟议的工作方案完成后，用于这些分析的数学理论和计算机程序可以应用于许多其他进化和功能问题，包括与遗传多样性在物种形成中的作用、后生动物躯体计划(HOX基因)的起源以及病原体与其宿主如何相互作用等问题。

Evolutionary theory ties together experimental observations from different organisms, providing a framework for understanding the natural world and how life came to be. Basic research in molecular biology and genetics, coupled with evolutionary theory, is directly responsible for many economic and medically important discoveries, ranging from predicting the strains of virus responsible for influenza epidemics to the engineering of organisms and proteins involved in industrial processes. This proposal uses evolutionary theory to study the origins of new genes, which are one of the main driving forces behind biological adaptation. The process of gene duplication is a major source of new genes, and is known to be responsible for a significant portion of the functional innovation and diversity seen across genomes. Duplication plays a crucial role in phenotypic diversity, speciation, and development. The proposed research will investigate the whole genome duplication that took place in yeast c100 million years ago, which offers a fantastic opportunity for learning more concerning the evolutionary mechanisms affecting gene duplication. The usual outcome of gene duplication is that one of the two copies of the gene is lost because they both initially have the same function. This proposal examines the portion of duplicates that are not lost post-duplication because they develop different functions and/or patterns of expression. Sometimes one of the duplicates acquires a novel function, resulting in the organism being better able to exploit its environment. Alternatively, existing functions and/or patterns are distributed between the pair of duplicates, meaning that both need to be kept for the organism to survive. The forces of natural selection responsible for these two outcomes remain to be fully elucidated, and understanding these forces is fundamental to addressing questions about the origins of gene function. The proposed research builds upon novel computational methods created by the PI, by creating tools that allow new questions to be addressed about these crucial evolutionary events. These methods use sophisticated statistical approaches to identify changes in the selective forces acting on genes during their evolutionary history, and where in the gene the selective forces have changed. The development of computational tools rather than laboratory experiment means that the whole genome of yeast can be examined, and the specific selective forces responsible for maintaining particular duplicates after the whole genome duplication can be identified. The results of huge numbers of laboratory studies on yeast species are housed in computer databases across the world. This proposal will link together these functional studies and the evolutionary events inferred from the new methodology. This will cast light on what biological factors affect the chances of both genes being maintained after duplication. Furthermore, combining knowledge in this manner has the potential to provide the complete story of how some specific genes have been maintained post-duplication. When the proposed programme of work is completed, the mathematical theory and computer programs used for these analyses could be applied to many other evolutionary and functional problems, including questions relating to the role of genetic diversification in speciation, the origins of the metazoan body plan (Hox genes), and how pathogenic organisms and their hosts interact.