Towards testable quantitative models for the evolution of caste specific ageing part II: integrating theory and experiment
Towards testable quantitative models for the evolution of caste specific ageing part II: integrating theory and experiment
批准号:
276417925
负责人:
Professor Dr. Ido Pen
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Units
财政年份:
2015
资助国家:
德国
项目状态:
已结题
起止时间:
2014-12-31 至 2021-12-31
中文摘要
进化论的一个主要挑战是解释在群居昆虫中,生殖种姓如何进化出比工人种姓和类似大小的非群居昆虫长得多的寿命。虽然经典进化衰老理论的口头论证-突变累积(MA)、拮抗多效性(AP)、可处置体细胞(DS)-已被用来定性解释种姓特定的衰老,但经典模型不适用,因为它们的假设与社会昆虫生物学相冲突。该项目的目的是(1)开发种姓特定老化演变的通用和特定物种的量化模型,以及(2)将模型与研究单位(RU)的实验数据结合起来,以严格测试和完善模型,并帮助指导进一步的实验研究。在第一个筹资阶段,我们在种姓老龄化方面取得了几项概念上的突破。首先,我们已经从数学上证明,经典老龄化理论的基本原理之一--自然选择的力量随着年龄的增长而下降--不适用于社会昆虫生殖种姓。取而代之的是,王后存活的选择可以在首次繁殖年龄之后很长一段时间内继续发挥最大作用。这可以从“超有机体”的观点来理解,蜂王实际上扮演着“生殖系”的角色,工蚁的生产等同于“躯体生长”而不是生殖。其次,我们已经证明,种姓之间的选择强度差异确实可以触发显著增加的女王/工蚁寿命比率的进化,但问题仍然是需要什么机制的组合(MA和/或SA和/或DS和/或其他)来解释在自然界中观察到的数量上的极端差异。对于第一阶段的剩余部分,我们打算进一步分析这个问题,并开始将模型与来自其他RU项目的转录组数据集成,方法是将表达水平上的逐个种姓的相关性映射到模型中的权衡,这将为特定种姓的衰老特征产生第一个定量预测。对于第二阶段,我们有两个主要目标。第一个目标是通过以下方式对我们目前的模型进行更机械化的扩展:(A)纳入作为资源分配过程基础的明确可进化的遗传调控网络,这些网络导致种姓内和种姓之间的健康成分之间的权衡;以及(B)允许种姓专业化的程度和种姓的数量与种姓特定的老化表型共同进化。第二个目标是进一步将来自RU其他项目的生命历史、社会和生物信息学数据与模型结合起来。这应该允许对进化衰老模型进行前所未有的定量测试,我们希望这将大大推动进化衰老领域的总体发展,超越我们对社会昆虫的应用。
英文摘要
A major challenge for evolutionary theory is to explain how in social insects the reproductive caste has evolved a lifespan much greater than that of the worker caste and that of similar-sized non-social insects. Although verbal arguments from classical evolutionary ageing theories – mutation accumulation (MA), antagonistic pleiotropy (AP), disposable soma (DS) – have been used to qualitatively explain caste-specific ageing, the classical models cannot apply because their assumptions clash with social insect biology. The aims of this project are to (1) develop general and species-specific quantitative models for the evolution of caste-specific ageing, and (2) integrate the models with experimental data from the Research Unit (RU), in order to rigorously test and refine the models and to help guide further experimental research. During the 1st funding phase we achieved several conceptual breakthroughs regarding caste-specific ageing. First, we have shown mathematically that one of the bedrock principles of classical ageing theory – the declining force of natural selection with age – does not apply to the social insect reproductive caste. Instead, selection on queen survival can continue to act at maximal strength long after the age of first reproduction. This can be understood from a “superorganism” viewpoint, with queens acting as de facto “germline”, and the production of workers amounting to “somatic growth” rather than reproduction. Secondly, we have shown that the between-caste divergence in the strength of selection can indeed trigger the evolution of strongly increased queen/worker lifespan ratios, but the question remains what combination of mechanisms (MA and/or SA and/or DS and/or others) is required to explain the quantitatively extreme divergence observed in nature.For the remainder of the 1st phase we intend to further analyse this question, and to start integrating the models with transcriptome data from the other RU projects by mapping age-by-caste correlations in expression levels to trade-offs in the models, which will yield the first quantitative predictions for caste-specific ageing profiles. For the 2nd phase we have two main goals. The first goal is to develop more mechanistic extensions of our current models by (a) incorporating explicitly evolvable genetic regulatory networks underlying the resource allocation processes that cause trade-offs between fitness components, both at the within-caste and between-caste levels; and (b) by allowing the degree of caste specialization and the number of castes to co-evolve with caste-specific ageing phenotypes. The second goal is to further integrate life historical, social and bioinformatics data from other RU projects with the models. This should allow an unprecedented degree of quantitative testing of evolutionary ageing models, which we hope will considerably advance the evolutionary ageing field in general, beyond our applications to social insects.
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