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      Somatic Maintenance Resources in the Honeybee Worker Fat Body Are Distributed to Withstand the Most Life-Threatening Challenges at Each Life Stage

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          Abstract

          In a global transcriptome analysis of three natural and three manipulated honeybee worker phenotypes at different ages, we have investigated the distribution of investment in somatic maintenance of the fat body. Gene expression is modulated so that the bees are able to resist the most life-threatening challenges at the actual life stage. Different modes of maintenance and repair are regulated, apparently to meet the environmental challenges most detrimental to survival and reproductive potential for the hive. We observed a broad down-regulation of genomic and cellular maintenance in the short-lived foragers and nurse bees compared to the long-lived winter bees. Our results show that survival and reproduction of the entire hive is given priority over the individual bees, hence supporting the idea of the honeybee society as a superorganism. Our results also fit the disposable soma theory of aging.

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          Most cited references15

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          Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments.

          One of the main objectives in the analysis of microarray experiments is the identification of genes that are differentially expressed under two experimental conditions. This task is complicated by the noisiness of the data and the large number of genes that are examined simultaneously. Here, we present a novel technique for identifying differentially expressed genes that does not originate from a sophisticated statistical model but rather from an analysis of biological reasoning. The new technique, which is based on calculating rank products (RP) from replicate experiments, is fast and simple. At the same time, it provides a straightforward and statistically stringent way to determine the significance level for each gene and allows for the flexible control of the false-detection rate and familywise error rate in the multiple testing situation of a microarray experiment. We use the RP technique on three biological data sets and show that in each case it performs more reliably and consistently than the non-parametric t-test variant implemented in Tusher et al.'s significance analysis of microarrays (SAM). We also show that the RP results are reliable in highly noisy data. An analysis of the physiological function of the identified genes indicates that the RP approach is powerful for identifying biologically relevant expression changes. In addition, using RP can lead to a sharp reduction in the number of replicate experiments needed to obtain reproducible results.
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            Evolution of ageing

            T Kirkwood (1977)
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              A deficit of detoxification enzymes: pesticide sensitivity and environmental response in the honeybee

              The honeybee genome has substantially fewer protein coding genes (≈ 11 000 genes) than Drosophila melanogaster (≈ 13 500) and Anopheles gambiae (≈ 14 000). Some of the most marked differences occur in three superfamilies encoding xenobiotic detoxifying enzymes. Specifically there are only about half as many glutathione-S-transferases (GSTs), cytochrome P450 monooxygenases (P450s) and carboxyl/cholinesterases (CCEs) in the honeybee. This includes 10-fold or greater shortfalls in the numbers of Delta and Epsilon GSTs and CYP4 P450s, members of which clades have been recurrently associated with insecticide resistance in other species. These shortfalls may contribute to the sensitivity of the honeybee to insecticides. On the other hand there are some recent radiations in CYP6, CYP9 and certain CCE clades in A. mellifera that could be associated with the evolution of the hormonal and chemosensory processes underpinning its highly organized eusociality.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                5 August 2013
                : 8
                : 8
                : e69870
                Affiliations
                [1 ]Department of Aquaculture and Animal Sciences, Norwegian University of Life Sciences, Aas, Norway
                [2 ]Queen Maud University College, Early Childhood Education, Trondheim, Norway
                [3 ]Centre for Integrative Genetics (CIGENE), Norwegian University of Life Sciences, Aas, Norway
                [4 ]Computational Biology Unit, Uni Computing, Uni Research AS, Bergen, Norway
                Leibniz Institute for Age Research – Fritz Lipmann Institute (FLI), Germany
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: SCS RA. Performed the experiments: SCS RA. Analyzed the data: SCS ST KP RA. Contributed reagents/materials/analysis tools: SCS ST KP RA. Wrote the paper: SCS RA.

                Article
                PONE-D-13-03386
                10.1371/journal.pone.0069870
                3734224
                23940531
                398b5742-bc43-4fd1-b03e-7cc4336493db
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 15 January 2013
                : 12 June 2013
                Page count
                Pages: 14
                Funding
                Siri-Christine Seehuus was funded by the Norwegian Research Council grant number 186362/V40. Simon Taylor was funded by the National Program for Research in Functional Genomics (FUGE) granted by the Norwegian Research Council. Kjell Petersen was funded by the FUGE 2 program, National Bioinformatics Platform, Norwegian Research Council. Randi Aamodt was funded by the Norwegian Research Council grant number 159951/V40 and the EU funded Network of Excellence LifeSpan (FP6 03689). None of the authors or funding institutions has any conflict of interest in the publishing of this paper. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Evolutionary Biology
                Aging
                Evolutionary Theory
                Genetics
                Gene Expression
                DNA transcription
                Animal Genetics
                Gene Networks
                Genomics
                Genome Analysis Tools
                Transcriptomes
                Functional Genomics
                Genome Expression Analysis
                Model Organisms
                Animal Models
                Zoology
                Entomology

                Uncategorized
                Uncategorized

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