GENETIC VARIATION INFLUENCING SLEEP REGULATION

该提案旨在确定参与小鼠睡眠和睡眠EEG正常表达和调节的基因。 我们已经确定了几种睡眠和EEG相关的表型，这些表型在近交系小鼠中随基因型而强烈变化。 在这个建议中，我们打算遵循这些候选表型，分离来自这些表型差异最大的近交系的后代。 我们建议首先研究分离的“候选人”表型在一组21重组近交系（RI）的小鼠，来自两个祖株（即AKR × DBA/2）。 随后的表型和基因分型的间和/或回交后代将产生更详细的信息，基因组定位，可用于解释基因型变异的特点（QTL定位和连锁分析）。 此外，我们可以利用这些自发的物种内睡眠差异来回答基本的睡眠生理学问题。 这些问题涉及SWS和REMS的稳态调节，它们彼此之间的相互作用和与脑温的相互作用，以及通过EEG Δ功率测量的SWS强度的神经生理学底物。 我们发现，AKR和DBA/2之间SWS δ功率的觉醒依赖性增加的时间常数存在很大差异，这一点特别令人感兴趣，因为它表明睡眠需求的积累受遗传控制。 识别睡眠和睡眠EEG的正常表达和调节的遗传因素将进一步加深我们对控制睡眠的神经生理学机制的理解，并可能对一般睡眠障碍以及具有遗传易感性的睡眠障碍产生重大影响。

This proposal seeks to identify genes implicated in the normal expression and regulation of sleep and the sleep EEG in mice. We have identified several sleep and EEG related phenotypes that strongly vary with genotype in inbred strains of mice. In this proposal, we intend to follow these candidate phenotypes in segregating progeny derived from the inbred strains for which these phenotypes differed the most. We propose to first study the segregation of "candidate" phenotypes in a set of 21 recombinant inbred (RI) strains of mice that were derived from two progenitor strains (i.e. AKR x DBA/2). Subsequent pheno- and genotyping of inter-and/or backcross progeny will yield more detailed information on genomic localizations that may be used to explain genotypic variance in the traits of interest (QTL-mapping and linkage analysis). Furthermore, we can make use of these spontaneous intra-species differences in sleep to answer basic sleep physiology issues. These issues concern the homeostatic regulation of SWS and REMS, their interaction with each other and with brain temperature, and the neurophysiological substrate of SWS intensity measured by EEG delta power. The large difference in the time constant of the wakefulness-dependent increase in SWS delta power between AKR and DBA/2 that we have found, is of special interest because it suggests that the accumulation of sleep need is under genetic control. Identifying genetic factors underlying the normal expression and regulation of sleep and the sleep EEG will further our understanding of the neurophysiological mechanisms that govern sleep and will potentially have large implications for sleep disorders in general and those with a genetic predisposition in particular.