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

研究重复基因进化命运的时间隐马尔可夫模型方法

• 批准号: BB/H000445/1
• 负责人: Simon Whelan
• 金额: $ 36.15万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2010
• 资助国家: 英国
• 起止时间: 2010 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FH000445%2F1
• 关键词: temporal; hidden; Markov; model; approach

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.

进化论将来自不同生物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，加上进化理论，直接导致了许多经济和医学上的重要发现，从预测流感流行的病毒株到工业过程中涉及的生物和蛋白质的工程。该提案使用进化理论来研究新基因的起源，这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，并且已知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。拟议中的研究将调查1亿年前发生在酵母中的全基因组复制，这为了解更多关于影响基因复制的进化机制提供了极好的机会。基因复制的通常结果是基因的两个拷贝中的一个丢失，因为它们最初都具有相同的功能。本提案审查了复制后没有丢失的部分复制品，因为它们发展了不同的功能和/或表达模式。有时，其中一个复制品获得了新的功能，导致生物体能够更好地利用其环境。或者，现有的功能和/或模式分布在一对复制品之间，这意味着生物体需要保留这两种功能和/或模式才能生存。自然选择的力量负责这两个结果仍有待充分阐明，了解这些力量是解决基因功能的起源问题的基础。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，允许解决有关这些关键进化事件的新问题。这些方法使用复杂的统计方法来确定在进化历史中作用于基因的选择力的变化，以及选择力在基因中的变化。计算工具而不是实验室实验的发展意味着可以检查酵母的整个基因组，并且可以确定负责在整个基因组复制后保持特定复制的特定选择力。大量关于酵母物种的实验室研究的结果被保存在世界各地的计算机数据库中。这项建议将把这些功能研究和从新方法学中推断出的进化事件联系起来。这将有助于了解哪些生物因素会影响两种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，包括与物种形成中遗传多样性的作用有关的问题，后生动物身体计划（Hox基因）的起源，以及病原生物与其宿主如何相互作用。

项目成果

Evidence of Statistical Inconsistency of Phylogenetic Methods in the Presence of Multiple Sequence Alignment Uncertainty.

• DOI: 10.1093/gbe/evv127
• 发表时间: 2015-07-01
• 期刊: Genome biology and evolution
• 影响因子: 3.3
• 作者: Md Mukarram Hossain AS;Blackburne BP;Shah A;Whelan S
• 通讯作者: Whelan S

ModelOMatic: fast and automated model selection between RY, nucleotide, amino acid, and codon substitution models.

ModelOMatic：在 RY、核苷酸、氨基酸和密码子替换模型之间进行快速、自动化的模型选择。

• DOI: 10.1093/sysbio/syu062
• 发表时间: 2015
• 期刊: Systematic biology
• 影响因子: 6.5
• 作者: Whelan S

Phylogenetic substitution models for detecting heterotachy during plastid evolution.

用于检测质体进化过程中异速性的系统发育替代模型。

• DOI: 10.1093/molbev/msq215
• 发表时间: 2011
• 期刊: Molecular biology and evolution
• 影响因子: 10.7
• 作者: Whelan S