NEW APPROACHES TO THE MODELING OF SPECIATION

形态建模的新方法

• 批准号: 6627215
• 负责人: SERGEY Y GAVRILETS
• 金额: $ 12.75万
• 依托单位: UNIVERSITY OF TENNESSEE KNOXVILLE
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-01-01 至 2004-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6627215
• 关键词: analytical method; biochemical evolution; computer simulation; genetic models; genetic polymorphism; genetic recombination; genotype; mathematical model; natural selections; physical fitness; population genetics; quantitative trait loci; species difference; systematic biology

The overall aim of this project is to better understand biological processes leading to speciation and diversification through a study of the dynamic and static behavior of various multilocus models. Existing approaches to the modeling of speciation are deficient in several ways. Usually a small number of loci or quantitative traits are considered, selection is assumed to be weak, population size is considered to be constant, and only a very limited number of selection regimes mostly reflecting the dominant paradigm of "rugged adaptive landscapes" have been studied. Recently a new metaphor of "holey adaptive landscapes" (Gavrilets 1997) has been put forward as a plausible alternative to the conventional view of rugged adaptive landscapes. This metaphor is the core of the research proposed here. This project will investigate: (i) dynamics of genetic and morphological diversification in (growing) populations and clades, (ii) evolutionary dynamics of metapopulations and hybrid zones, (iii) coevolutionary dynamics. The biological questions to be approached here are very diverse. However, there is a unifying theme underlying the methods to be used. This theme is that biological organisms can be viewed as very long sequences with thousands and millions elements (e.g. genes or DNA base pairs). Thus, from a mathematical point of view, biological evolution takes place in a space with an enormous number of dimensions. Consequently, a significant proportion of evolutionary changes are expected to happen along nearly neutral networks and on holey adaptive landscapes. Chance and contingency should play a major role in evolutionary dynamics. Here, a combination of analytical methods recently developed in theoretical evolutionary biology, mathematics, and physics and extensive numerical simulations will be used to take into account various factors operating in natural populations (selection, mutation, recombination, random drift, migration, extinction, colonization etc).

该项目的总体目的是通过研究各种多焦点模型的动态和静态行为来更好地理解导致物种和多样化的生物学过程。现有的形成建模方法在几种方面都缺乏。通常，认为少数基因座或定量性状被认为是弱的，人口大小被认为是恒定的，只有非常有限的选择制度主要反映了“坚固的自适应景观”的主要范式。最近，提出了一种新的“孔自适应景观”（Gavrilets 1997）的隐喻，作为崎vision的自适应景观的传统视图的合理替代方法。这个隐喻是这里提出的研究的核心。该项目将研究：（i）（增长）种群和进化枝中遗传和形态多样化的动力学，（ii）跨化和混合区域的进化动力学，（iii）共同进化动力学。这里要解决的生物学问题非常多样化。但是，要使用的方法存在一个统一的主题。这个主题是，生物生物可以被视为具有数千和数百万个元素（例如基因或DNA碱基对）的很长序列。因此，从数学的角度来看，生物进化发生在具有大量维度的空间中。因此，预计将在几乎中立的网络和洞的自适应景观上发生很大一部分的进化变化。机会和偶然性应在进化动力学中起主要作用。在这里，在理论进化生物学，数学和物理学中最近开发的分析方法以及物理学以及广泛的数值模拟都将考虑在自然种群中运行的各种因素（选择，突变，重组，随机漂移，迁移，灭绝，灭绝，结肠化等）。