Patterns of inbreeding depression and architecture of the load in subdivided populations.
Patterns of inbreeding depression and architecture of the load in subdivided populations.
复制标题
近交衰退的模式和细分群体中的负荷结构。
作者：
S. Glémin;J. Ronfort;T. Bataillon
近交衰退是一种普遍现象，主要是由于隐性有害突变，即所谓的突变负荷。理论上已经有很多研究。然而，直到最近，人口结构一直没有得到考虑，尽管它可能是人口演变的一个重要因素。种群细分改变了有害突变的动态，因为选择的结果取决于种群内（选择和漂移）和种群之间（迁移）的过程。在这里，我们提出了一个通用的模型，使我们能够深入了解模式的近交衰退，杂种优势，并在细分群体的负载。我们表明，它们可以解释参考单种群理论，使用适当的本地有效人口规模，整合漂移，选择和迁移的影响。我们将其称为“选择的有效群体规模”（NS（e））。例如，对于无限岛模型，它等于NS（e）= N1 + m/hs，其中N是当地种群大小，m是迁移率，h和s是有害突变的优势系数和选择系数。我们的研究结果的估计和解释的近交衰退细分人群，特别是关于保护问题的影响。我们还讨论了迁移和细分对交配系统进化的可能影响。
Inbreeding depression is a general phenomenon that is due mainly to recessive deleterious mutations, the so-called mutation load. It has been much studied theoretically. However, until very recently, population structure has not been taken into account, even though it can be an important factor in the evolution of populations. Population subdivision modifies the dynamics of deleterious mutations because the outcome of selection depends on processes both within populations (selection and drift) and between populations (migration). Here, we present a general model that permits us to gain insight into patterns of inbreeding depression, heterosis, and the load in subdivided populations. We show that they can be interpreted with reference to single-population theory, using an appropriate local effective population size that integrates the effects of drift, selection, and migration. We term this the "effective population size of selection" (NS(e)). For the infinite island model, for example, it is equal to NS(e) = N1 + m/hs, where N is the local population size, m the migration rate, and h and s the dominance and selection coefficients of deleterious mutation. Our results have implications for the estimation and interpretation of inbreeding depression in subdivided populations, especially regarding conservation issues. We also discuss the possible effects of migration and subdivision on the evolution of mating systems.
影响因子：
3.3
作者：
Hong Wen Deng;Michael Lynch
通讯作者：
Hong Wen Deng;Michael Lynch
影响因子：
3.3
作者：
Deng,HW
通讯作者：
Deng,HW