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      GWAS reveal a role for the central nervous system in regulating weight and weight change in response to exercise

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      Scientific Reports
      Nature Publishing Group UK
      Physiology, Genetics, Genetic association study

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          Abstract

          Body size and weight show considerable variation both within and between species. This variation is controlled in part by genetics, but also strongly influenced by environmental factors including diet and the level of activity experienced by the individual. Due to the increasing obesity epidemic in much of the world, there is considerable interest in the genetic factors that control body weight and how weight changes in response to exercise treatments. Here, we address this question in the Drosophila model system, utilizing 38 strains of the Drosophila Genetics Reference Panel. We use GWAS to identify the molecular pathways that control weight and weight changes in response to exercise. We find that there is a complex set of molecular pathways controlling weight, with many genes linked to the central nervous system (CNS). The CNS also plays a role in the weight change with exercise, in particular, signaling from the CNS. Additional analyses revealed that weight in Drosophila is driven by two factors, animal size, and body composition, as the amount of fat mass versus lean mass impacts the density. Thus, while the CNS appears to be important for weight and exercise-induced weight change, signaling pathways are particularly important for determining how exercise impacts weight.

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          PANTHER version 14: more genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools

          Abstract PANTHER (Protein Analysis Through Evolutionary Relationships, http://pantherdb.org) is a resource for the evolutionary and functional classification of genes from organisms across the tree of life. We report the improvements we have made to the resource during the past two years. For evolutionary classifications, we have added more prokaryotic and plant genomes to the phylogenetic gene trees, expanding the representation of gene evolution in these lineages. We have refined many protein family boundaries, and have aligned PANTHER with the MEROPS resource for protease and protease inhibitor families. For functional classifications, we have developed an entirely new PANTHER GO-slim, containing over four times as many Gene Ontology terms as our previous GO-slim, as well as curated associations of genes to these terms. Lastly, we have made substantial improvements to the enrichment analysis tools available on the PANTHER website: users can now analyze over 900 different genomes, using updated statistical tests with false discovery rate corrections for multiple testing. The overrepresentation test is also available as a web service, for easy addition to third-party sites.
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            The Epidemiology of Obesity: A Big Picture.

            The epidemic of overweight and obesity presents a major challenge to chronic disease prevention and health across the life course around the world. Fueled by economic growth, industrialization, mechanized transport, urbanization, an increasingly sedentary lifestyle, and a nutritional transition to processed foods and high-calorie diets over the last 30 years, many countries have witnessed the prevalence of obesity in its citizens double and even quadruple. A rising prevalence of childhood obesity, in particular, forebodes a staggering burden of disease in individuals and healthcare systems in the decades to come. A complex, multifactorial disease, with genetic, behavioral, socioeconomic, and environmental origins, obesity raises the risk of debilitating morbidity and mortality. Relying primarily on epidemiologic evidence published within the last decade, this non-exhaustive review discusses the extent of the obesity epidemic, its risk factors-known and novel-, sequelae, and economic impact across the globe.
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              Protocol Update for large-scale genome and gene function analysis with the PANTHER classification system (v.14.0)

              PANTHER Classification System ( www.pantherdb.org ) is a comprehensive system that combines genomes, gene function classifications, pathways and statistical analysis tools to enable biologists to analyze large-scale genome-wide experimental data. The current system (PANTHER v.14.0) covers 131 complete genomes organized into gene families and subfamilies; evolutionary relationships between genes are represented in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models, or HMMs). The families and subfamilies are annotated with Gene Ontology terms and sequences are assigned to PANTHER pathways. A suite of tools has been built to allow users to browse and query gene functions, and analyze large-scale experimental data with a number of statistical tests. PANTHER is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists. Since the protocol to use this tool (v8.0) was originally published in 2013, there have been significant improvements and updates in the areas of data quality, data coverage, statistical algorithms and user experience. This Protocol Update will provide a detailed description of how to analyze genome-wide experimental data in the PANTHER Classification System.
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                Author and article information

                Contributors
                riddlenc@uab.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                4 March 2021
                4 March 2021
                2021
                : 11
                : 5144
                Affiliations
                GRID grid.265892.2, ISNI 0000000106344187, Department of Biology, , The University of Alabama at Birmingham, ; Birmingham, AL 35294 USA
                Article
                84534
                10.1038/s41598-021-84534-w
                7933348
                33664357
                d2b6a6da-9f9e-4ca7-b65e-dda95b5432d4
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 29 October 2020
                : 17 February 2021
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                © The Author(s) 2021

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                physiology,genetics,genetic association study
                Uncategorized
                physiology, genetics, genetic association study

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