Distribution and Quantity of Sites of John Cunningham Virus Persistence in Immunologically Healthy Patients: Correlation With John Cunningham Virus Antibody and Urine John Cunningham Virus DNA.

Importance: Although seroepidemiological studies indicate that greater than 50% of the population has been infected with John Cunningham virus (JCV), the sites of JCV persistence remain incompletely characterized.

Objective: To determine sites of JCV persistence in immunologically healthy individuals.

Design, Setting, And Participants: Tissue specimens from multiple sites including brain, renal, and nonrenal tissues were obtained at autopsy performed in the Department of Pathology at the University of Kentucky from 12 immunologically healthy patients between February 9, 2011, and November 27, 2012.

Usf1, a suppressor of the circadian Clock mutant, reveals the nature of the DNA-binding of the CLOCK:BMAL1 complex in mice.

Genetic and molecular approaches have been critical for elucidating the mechanism of the mammalian circadian clock. Here, we demonstrate that the ClockΔ19 mutant behavioral phenotype is significantly modified by mouse strain genetic background. We map a suppressor of the ClockΔ19 mutation to a ∼900 kb interval on mouse chromosome 1 and identify the transcription factor, Usf1, as the responsible gene.

Non-laser capture microscopy approach for the microdissection of discrete mouse brain regions for total RNA isolation and downstream next-generation sequencing and gene expression profiling.

As technological platforms, approaches such as next-generation sequencing, microarray, and qRT-PCR have great promise for expanding our understanding of the breadth of molecular regulation. Newer approaches such as high-resolution RNA sequencing (RNA-Seq)(1) provides new and expansive information about tissue- or state-specific expression such as relative transcript levels, alternative splicing, and micro RNAs(2-4). Prospects for employing the RNA-Seq method in comparative whole transcriptome profiling(5) within discrete tissues or between phenotypically distinct groups of individuals affords new avenues for elucidating molecular mechanisms involved in both normal and abnormal physiological states.

Pharmacological validation of candidate causal sleep genes identified in an N2 cross.

Despite the substantial impact of sleep disturbances on human health and the many years of study dedicated to understanding sleep pathologies, the underlying genetic mechanisms that govern sleep and wake largely remain unknown. Recently, the authors completed large-scale genetic and gene expression analyses in a segregating inbred mouse cross and identified candidate causal genes that regulate the mammalian sleep-wake cycle, across multiple traits including total sleep time, amounts of rapid eye movement (REM), non-REM, sleep bout duration, and sleep fragmentation. Here the authors describe a novel approach toward validating candidate causal genes, while also identifying potential targets for sleep-related indications.

Identification of causal genes, networks, and transcriptional regulators of REM sleep and wake.

Study Objective: Sleep-wake traits are well-known to be under substantial genetic control, but the specific genes and gene networks underlying primary sleep-wake traits have largely eluded identification using conventional approaches, especially in mammals. Thus, the aim of this study was to use systems genetics and statistical approaches to uncover the genetic networks underlying 2 primary sleep traits in the mouse: 24-h duration of REM sleep and wake.

Design: Genome-wide RNA expression data from 3 tissues (anterior cortex, hypothalamus, thalamus/midbrain) were used in conjunction with high-density genotyping to identify candidate causal genes and networks mediating the effects of 2 QTL regulating the 24-h duration of REM sleep and one regulating the 24-h duration of wake.

Uncovering the genetic landscape for multiple sleep-wake traits.

Despite decades of research in defining sleep-wake properties in mammals, little is known about the nature or identity of genes that regulate sleep, a fundamental behaviour that in humans occupies about one-third of the entire lifespan. While genome-wide association studies in humans and quantitative trait loci (QTL) analyses in mice have identified candidate genes for an increasing number of complex traits and genetic diseases, the resources and time-consuming process necessary for obtaining detailed quantitative data have made sleep seemingly intractable to similar large-scale genomic approaches. Here we describe analysis of 20 sleep-wake traits from 269 mice from a genetically segregating population that reveals 52 significant QTL representing a minimum of 20 genomic loci.