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      Meta-analysis of transcriptomic datasets identifies genes enriched in the mammalian circadian pacemaker

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          Abstract

          The master circadian pacemaker in mammals is located in the suprachiasmatic nuclei (SCN) which regulate physiology and behaviour, as well as coordinating peripheral clocks throughout the body. Investigating the function of the SCN has often focused on the identification of rhythmically expressed genes. However, not all genes critical for SCN function are rhythmically expressed. An alternative strategy is to characterize those genes that are selectively enriched in the SCN. Here, we examined the transcriptome of the SCN and whole brain (WB) of mice using meta-analysis of publicly deposited data across a range of microarray platforms and RNA-Seq data. A total of 79 microarrays were used (24 SCN and 55 WB samples, 4 different microarray platforms), alongside 17 RNA-Seq data files (7 SCN and 10 WB). 31 684 MGI gene symbols had data for at least one platform. Meta-analysis using a random effects model for weighting individual effect sizes (derived from differential expression between relevant SCN and WB samples) reliably detected known SCN markers. SCN-enriched transcripts identified in this study provide novel insights into SCN function, including identifying genes which may play key roles in SCN physiology or provide SCN-specific drivers.

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          Coordinated transcription of key pathways in the mouse by the circadian clock.

          In mammals, circadian control of physiology and behavior is driven by a master pacemaker located in the suprachiasmatic nuclei (SCN) of the hypothalamus. We have used gene expression profiling to identify cycling transcripts in the SCN and in the liver. Our analysis revealed approximately 650 cycling transcripts and showed that the majority of these were specific to either the SCN or the liver. Genetic and genomic analysis suggests that a relatively small number of output genes are directly regulated by core oscillator components. Major processes regulated by the SCN and liver were found to be under circadian regulation. Importantly, rate-limiting steps in these various pathways were key sites of circadian control, highlighting the fundamental role that circadian clocks play in cellular and organismal physiology.
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            A gene expression atlas of the central nervous system based on bacterial artificial chromosomes.

            The mammalian central nervous system (CNS) contains a remarkable array of neural cells, each with a complex pattern of connections that together generate perceptions and higher brain functions. Here we describe a large-scale screen to create an atlas of CNS gene expression at the cellular level, and to provide a library of verified bacterial artificial chromosome (BAC) vectors and transgenic mouse lines that offer experimental access to CNS regions, cell classes and pathways. We illustrate the use of this atlas to derive novel insights into gene function in neural cells, and into principal steps of CNS development. The atlas, library of BAC vectors and BAC transgenic mice generated in this screen provide a rich resource that allows a broad array of investigations not previously available to the neuroscience community.
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              The evolution of gene expression levels in mammalian organs.

              Changes in gene expression are thought to underlie many of the phenotypic differences between species. However, large-scale analyses of gene expression evolution were until recently prevented by technological limitations. Here we report the sequencing of polyadenylated RNA from six organs across ten species that represent all major mammalian lineages (placentals, marsupials and monotremes) and birds (the evolutionary outgroup), with the goal of understanding the dynamics of mammalian transcriptome evolution. We show that the rate of gene expression evolution varies among organs, lineages and chromosomes, owing to differences in selective pressures: transcriptome change was slow in nervous tissues and rapid in testes, slower in rodents than in apes and monotremes, and rapid for the X chromosome right after its formation. Although gene expression evolution in mammals was strongly shaped by purifying selection, we identify numerous potentially selectively driven expression switches, which occurred at different rates across lineages and tissues and which probably contributed to the specific organ biology of various mammals.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                29 September 2017
                18 August 2017
                18 August 2017
                : 45
                : 17
                : 9860-9873
                Affiliations
                [1 ]Sleep and Circadian Neuroscience Institute (SCNi), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX1 3RE, UK
                [2 ]MRC Harwell Institute, Harwell Campus, Oxfordshire OX11 0RD, UK
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +44 0 1865 618 674; Email: stuart.peirson@ 123456eye.ox.ac.uk . Correspondence may also be addressed to Russell G. Foster. Tel: +44 0 1865 618 661; Email: russell.foster@ 123456eye.ox.ac.uk
                Article
                gkx714
                10.1093/nar/gkx714
                5737434
                28973476
                21ae2666-11a3-460c-8b31-1b45a2585ac6
                © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 04 August 2017
                : 27 July 2017
                : 07 September 2016
                Page count
                Pages: 14
                Categories
                Data Resources and Analyses

                Genetics
                Genetics

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