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      Sex-dimorphic and age-dependent organization of 24-hour gene expression rhythms in humans

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      Science
      American Association for the Advancement of Science (AAAS)

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          Abstract

          The circadian clock modulates human physiology. However, the organization of tissue-specific gene expression rhythms and how these depend on age and sex is not defined in humans. We combined data from the Genotype-Tissue Expression (GTEx) project with an algorithm that assigns circadian phases to 914 donors, by integrating temporal information from multiple tissues in each individual, to identify messenger RNA (mRNA) rhythms in 46 tissues. Clock transcripts showed conserved timing relationships and tight synchrony across the body. mRNA rhythms varied in breadth, covering global and tissue-specific functions, including metabolic pathways and systemic responses. The clock structure was conserved across sexes and age groups. However, overall gene expression rhythms were highly sex-dimorphic and more sustained in females. Rhythmic programs generally dampened with age across the body.

          Tracking human circadian gene expression

          Rhythmic circadian changes in gene expression have been well documented in model organisms, but data are limited from primates and particularly humans. Talamanca et al . developed an algorithm that allowed them to assign a circadian phase to each individual in a set of about 900 human donors. This approach allowed them to detect circadian changes in gene expression in samples from 46 tissues. Women showed higher rhythmicity of transcripts, especially in liver and the adrenal gland. The results also confirmed that rhythmicity was generally damped in older individuals. —LBR

          Abstract

          Daily rhythms of gene expression in humans vary according to sex and age.

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          Most cited references49

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            Is Open Access

            edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

            Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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              Complex heatmaps reveal patterns and correlations in multidimensional genomic data.

              Parallel heatmaps with carefully designed annotation graphics are powerful for efficient visualization of patterns and relationships among high dimensional genomic data. Here we present the ComplexHeatmap package that provides rich functionalities for customizing heatmaps, arranging multiple parallel heatmaps and including user-defined annotation graphics. We demonstrate the power of ComplexHeatmap to easily reveal patterns and correlations among multiple sources of information with four real-world datasets.
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                Author and article information

                Contributors
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                Journal
                Science
                Science
                American Association for the Advancement of Science (AAAS)
                0036-8075
                1095-9203
                February 03 2023
                February 03 2023
                : 379
                : 6631
                : 478-483
                Affiliations
                [1 ]Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland.
                Article
                10.1126/science.add0846
                36730411
                fd294d35-5f5c-4fd1-96a7-3887d0e705f4
                © 2023
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