The evolutionary origins of multicellularity and development in experimental populations of digital organisms

该项目研究了进化如何产生变化的基本问题，以及这些变化如何影响随后的进化。个体生物的个体差异很大。对于细菌，个体由单个细胞组成，而在哺乳动物中，个体可能有数万亿个细胞，所有细胞都协调不同的角色（血液，皮肤等）有些物种，如蜜蜂，形成高度协调的群体（与蜂王，觅食者，警卫等），表现得像一个单独的有机体。以前不同的实体（细胞或昆虫）进化成新类型的统一个体（身体或群体）是具有挑战性的研究，因为进化发生在很长的时间尺度上。相反，研究人员将使用计算机模拟，在其中他们将操纵环境条件，看看它们如何促进或限制复杂个体的进化。研究人员还将开发基于网络的软件，让其他人轻松探索这些进化转变，目的是简化研究人员的实验，促进学生学习，促进公民科学。本计画将分为三个概念阶段：（1）形成：在什麽样的选择条件下，原本孤立的生物体结合成一个更高层次的个体单位？(2)差异化：一旦形成了较高层次的单位，较低层次个体的预先存在的特征（如表型可塑性或环境相互作用）如何影响分工策略的演变？(3)复杂化：不同类型的分工机制如何促进新的、更复杂的特征（如发展模式或紧密协调的任务表现）的进化？研究人员将使用一种实验进化方法，研究在2D虚拟世界中运行的数字生物。数字进化系统允许研究人员观察种群中的所有基因组，跟踪所有相互作用，并记录完美的遗传。每个数字细胞都有一个功能齐全的遗传程序，理论上能够执行任何算法过程。这些系统中的进化经常产生意想不到的生存策略，具有复杂的环境和细胞间的相互作用，远远超出了传统的模拟。探索在开放和透明的系统中产生重大转变的条件将有助于更深入地了解我们的自然起源，产生许多可以在实验室实验中进行简洁测试的假设，并促进如何产生计算算法的想法，这些算法可以在与生物系统相当的规模上进行协调。

This project investigates fundamental questions about how evolution produces shifts in what it means to be an individual organism and how those shifts affect subsequent evolution. What is an individual organism varies greatly. With bacteria, an individual consists of a single cell, while in mammals individuals might have trillions of cells, all coordinating different roles (blood, skin, and so forth) Some species, such as the honey bee, form highly coordinated colonies (with queens, foragers, guards, and so forth) that behave like an individual organism. The evolution of previously distinct entities (cells or insects) into new types of unified individuals (bodies or colonies) are challenging to study because evolution occurs over long time scales. Instead, the researchers will use computer simulations in which they will manipulate environmental conditions to see how they promote or constrain the evolution of complex individuals. The researchers will also develop web-based software to let others easily explore these evolutionary transitions, with a goal of simplifying experimentation by fellow researchers, facilitating student learning, and promoting citizen science. This project will be divided into three conceptual stages: (1) Formation: Under what selective conditions do formerly solitary organisms unite to form a higher-level individual unit? (2) Differentiation: Once higher-level units have been formed, how do the preexisting traits of the lower-level individuals (such as phenotypic plasticity or environmental interactions) influence the evolution of division-of-labor strategies? (3) Complexification: How do different types of division-of-labor mechanisms facilitate the evolution of new, more complex features (such as developmental patterns or tightly-coordinated task performance)? The researchers will use an experimental-evolution approach with digital study organisms that operate in a 2D virtual world. Digital evolution systems allow the researchers to observe all genomes in a population, track all interactions, and record perfect phylogenies. Each digital cell has a fully-functional genetic program, theoretically capable of performing any algorithmic processes. Evolution in these systems frequently produce unexpected survival strategies with complex environmental and inter-cellular interactions, far beyond a traditional simulation. Probing the conditions that produce major transitions in an open-ended and transparent system will contribute to a deeper understanding of our natural origins, generate numerous hypotheses that can be tested concisely in laboratory experiments, and promote ideas for how computational algorithms can be produced that coordinate at a scale comparable to biological systems.