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      High-throughput sleep phenotyping produces robust and heritable traits in Diversity Outbred mice and their founder strains

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          Abstract

          Study Objectives

          This study describes high-throughput phenotyping strategies for sleep and circadian behavior in mice, including examinations of robustness, reliability, and heritability among Diversity Outbred (DO) mice and their eight founder strains.

          Methods

          We performed high-throughput sleep and circadian phenotyping in male mice from the DO population (n = 338) and their eight founder strains: A/J (n = 6), C57BL/6J (n = 14), 129S1/SvlmJ (n = 6), NOD/LtJ (n = 6), NZO/H1LtJ (n = 6), CAST/EiJ (n = 8), PWK/PhJ (n = 8), and WSB/EiJ (n = 6). Using infrared beam break systems, we defined sleep as at least 40 s of continuous inactivity and quantified sleep–wake amounts and bout characteristics. We developed assays to measure sleep latency in a new environment and during a modified Murine Multiple Sleep Latency Test, and estimated circadian period from wheel-running experiments. For each trait, broad-sense heritability (proportion of variability explained by all genetic factors) was derived in founder strains, while narrow-sense heritability (proportion of variability explained by additive genetic effects) was calculated in DO mice.

          Results

          Phenotypes were robust to different inactivity durations to define sleep. Differences across founder strains and moderate/high broad-sense heritability were observed for most traits. There was large phenotypic variability among DO mice, and phenotypes were reliable, although estimates of heritability were lower than in founder mice. This likely reflects important nonadditive genetic effects.

          Conclusions

          A high-throughput phenotyping strategy in mice, based primarily on monitoring of activity patterns, provides reliable and heritable estimates of sleep and circadian traits. This approach is suitable for discovery analyses in DO mice, where genetic factors explain some proportion of phenotypic variation.

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          Most cited references62

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          The Measurement of Observer Agreement for Categorical Data

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            Least-squares frequency analysis of unequally spaced data

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              Is Open Access

              Genome-wide association study identifies genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates

              Sleep is an essential state of decreased activity and alertness but molecular factors regulating sleep duration remain unknown. Through genome-wide association analysis in 446,118 adults of European ancestry from the UK Biobank, we identify 78 loci for self-reported habitual sleep duration (p < 5 × 10−8; 43 loci at p < 6 × 10−9). Replication is observed for PAX8, VRK2, and FBXL12/UBL5/PIN1 loci in the CHARGE study (n = 47,180; p < 6.3 × 10−4), and 55 signals show sign-concordant effects. The 78 loci further associate with accelerometer-derived sleep duration, daytime inactivity, sleep efficiency and number of sleep bouts in secondary analysis (n = 85,499). Loci are enriched for pathways including striatum and subpallium development, mechanosensory response, dopamine binding, synaptic neurotransmission and plasticity, among others. Genetic correlation indicates shared links with anthropometric, cognitive, metabolic, and psychiatric traits and two-sample Mendelian randomization highlights a bidirectional causal link with schizophrenia. This work provides insights into the genetic basis for inter-individual variation in sleep duration implicating multiple biological pathways.
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                Author and article information

                Contributors
                Journal
                Sleep
                Oxford University Press (OUP)
                0161-8105
                1550-9109
                May 2020
                May 12 2020
                February 19 2020
                May 2020
                May 12 2020
                February 19 2020
                : 43
                : 5
                Affiliations
                [1 ]Division of Sleep Medicine, Department of Medicine, University of Pennsylvania, Philadelphia, PA
                [2 ]Central European Institute of Technology, Masaryk University, Brno, Czech Republic
                [3 ]Jackson Laboratory, Bar Harbor, ME
                Article
                10.1093/sleep/zsz278
                7215270
                32074270
                ced14b84-fcb0-4d30-90b4-9d7205dd00b3
                © 2020

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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