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      Modeling the genetic basis for human sleep disorders in Drosophila

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          Abstract

          Sleep research in Drosophila is not only here to stay, but is making impressive strides towards helping us understand the biological basis for and the purpose of sleep—perhaps one of the most complex and enigmatic of behaviors. Thanks to over a decade of sleep-related studies in flies, more molecular methods are being applied than ever before towards understanding the genetic basis of sleep disorders. The advent of high-throughput technologies that can rapidly interrogate whole genomes, epigenomes and proteomes, has also revolutionized our ability to detect genetic variants that might be causal for a number of sleep disorders. In the coming years, mutational studies in model organisms such as Drosophila will need to be functionally connected to information being generated from these whole-genome approaches in humans. This will necessitate the development of appropriate methods for interpolating data and increased analytical power to synthesize useful network(s) of sleep regulatory pathways—including appropriate discriminatory and predictive capabilities. Ultimately, such networks will also need to be interpreted in the context of fundamental neurobiological substrates for sleep in any given species. In this review, we highlight some emerging approaches, such as network analysis and mathematical modeling of sleep distributions, which can be applied to contemporary sleep research as a first step to achieving these aims. These methodologies should favorably impact not only a mechanistic understanding of sleep, but also future pharmacological intervention strategies to manage and treat sleep disorders in humans.

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          Most cited references 60

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          Using FlyAtlas to identify better Drosophila melanogaster models of human disease.

          FlyAtlas, a new online resource, provides the most comprehensive view yet of expression in multiple tissues of Drosophila melanogaster. Meta-analysis of the data shows that a significant fraction of the genome is expressed with great tissue specificity in the adult, demonstrating the need for the functional genomic community to embrace a wide range of functional phenotypes. Well-known developmental genes are often reused in surprising tissues in the adult, suggesting new functions. The homologs of many human genetic disease loci show selective expression in the Drosophila tissues analogous to the affected human tissues, providing a useful filter for potential candidate genes. Additionally, the contributions of each tissue to the whole-fly array signal can be calculated, demonstrating the limitations of whole-organism approaches to functional genomics and allowing modeling of a simple tissue fractionation procedure that should improve detection of weak or tissue-specific signals.
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            Environmental context explains Lévy and Brownian movement patterns of marine predators.

            An optimal search theory, the so-called Lévy-flight foraging hypothesis, predicts that predators should adopt search strategies known as Lévy flights where prey is sparse and distributed unpredictably, but that Brownian movement is sufficiently efficient for locating abundant prey. Empirical studies have generated controversy because the accuracy of statistical methods that have been used to identify Lévy behaviour has recently been questioned. Consequently, whether foragers exhibit Lévy flights in the wild remains unclear. Crucially, moreover, it has not been tested whether observed movement patterns across natural landscapes having different expected resource distributions conform to the theory's central predictions. Here we use maximum-likelihood methods to test for Lévy patterns in relation to environmental gradients in the largest animal movement data set assembled for this purpose. Strong support was found for Lévy search patterns across 14 species of open-ocean predatory fish (sharks, tuna, billfish and ocean sunfish), with some individuals switching between Lévy and Brownian movement as they traversed different habitat types. We tested the spatial occurrence of these two principal patterns and found Lévy behaviour to be associated with less productive waters (sparser prey) and Brownian movements to be associated with productive shelf or convergence-front habitats (abundant prey). These results are consistent with the Lévy-flight foraging hypothesis, supporting the contention that organism search strategies naturally evolved in such a way that they exploit optimal Lévy patterns.
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              General anesthesia, sleep, and coma.

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                Author and article information

                Journal
                Commun Integr Biol
                Commun Integr Biol
                CIB
                Communicative & Integrative Biology
                Landes Bioscience
                1942-0889
                01 January 2013
                01 January 2013
                01 January 2013
                : 6
                : 1
                Affiliations
                [1 ]Departments of Cell Biology and Neurology; Emory University School of Medicine; Atlanta, GA USA
                [2 ]Laboratory of Genetics; The Rockefeller University; New York, NY USA
                Author notes
                [†]

                Current affiliation: Department of Physics; University of Miami; Coral Gables, FL USA

                [* ]Correspondence to: Subhabrata Sanyal, Email: ssanya2@ 123456emory.edu
                Article
                2012CIB0108 22733
                10.4161/cib.22733
                3689575
                23802043
                Copyright © 2013 Landes Bioscience

                This is an open-access article licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License. The article may be redistributed, reproduced, and reused for non-commercial purposes, provided the original source is properly cited.

                Categories
                Review

                Molecular biology

                sleep, modeling, genetics, distribution, disease, drosophila, networks

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