GENETIC VARIATION INFLUENCING SLEEP REGULATION IN MICE

本研究旨在确定与小鼠睡眠和睡眠脑电图的正常表达和调节有关的基因。我们已经确定了几种睡眠和脑电图相关表型，这些表型在自交系小鼠中随基因型强烈变化。在这一建议中，我们打算遵循这些候选表型在分离这些表型差异最大的自交系衍生的后代中。我们建议首先研究从两个祖菌株（即AKR x DBA/2）衍生的21个重组自交系（RI）小鼠中“候选”表型的分离。后续的间交和/或回交后代的表型和基因分型将产生更详细的基因组定位信息，可用于解释感兴趣性状的基因型差异（qtl定位和连锁分析）。此外，我们可以利用这些自发的物种间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的内稳态调节，它们之间的相互作用以及与脑温度的相互作用，以及由EEG δ功率测量的SWS强度的神经生理基础。我们发现，AKR和DBA/2之间的觉醒依赖性SWS δ功率增加的时间常数的巨大差异是特别有趣的，因为它表明睡眠需求的积累是在遗传控制下的。识别睡眠正常表达和调节的遗传因素以及睡眠脑电图将进一步加深我们对控制睡眠的神经生理机制的理解，并可能对一般的睡眠障碍，特别是那些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.