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      Gene Expression Dynamics in Major Endocrine Regulatory Pathways along the Transition from Solitary to Social Life in a Bumblebee, Bombus terrestris

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          Abstract

          Understanding the social evolution leading to insect eusociality requires, among other, a detailed insight into endocrine regulatory mechanisms that have been co-opted from solitary ancestors to play new roles in the complex life histories of eusocial species. Bumblebees represent well-suited models of a relatively primitive social organization standing on the mid-way to highly advanced eusociality and their queens undergo both, a solitary and a social phase, separated by winter diapause. In the present paper, we characterize the gene expression levels of major endocrine regulatory pathways across tissues, sexes, and life-stages of the buff-tailed bumblebee, Bombus terrestris, with special emphasis on critical stages of the queen's transition from solitary to social life. We focused on fundamental genes of three pathways: (1) Forkhead box protein O and insulin/insulin-like signaling, (2) Juvenile hormone (JH) signaling, and (3) Adipokinetic hormone signaling. Virgin queens were distinguished by higher expression of forkhead box protein O and downregulated insulin-like peptides and JH signaling, indicated by low expression of methyl farnesoate epoxidase ( MFE) and transcription factor Krüppel homolog 1 ( Kr-h1). Diapausing queens showed the expected downregulation of JH signaling in terms of low MFE and vitellogenin ( Vg) expressions, but an unexpectedly high expression of Kr-h1. By contrast, reproducing queens revealed an upregulation of MFE and Vg together with insulin signaling. Surprisingly, the insulin growth factor 1 (IGF-1) turned out to be a queen-specific hormone. Workers exhibited an expression pattern of MFE and Vg similar to that of reproducing queens. Males were characterized by high Kr-h1 expression and low Vg level. The tissue comparison unveiled an unexpected resemblance between the fat body and hypopharyngeal glands across all investigated genes, sexes, and life stages.

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          Most cited references 95

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          A new mathematical model for relative quantification in real-time RT-PCR.

           M. Pfaffl (2001)
          Use of the real-time polymerase chain reaction (PCR) to amplify cDNA products reverse transcribed from mRNA is on the way to becoming a routine tool in molecular biology to study low abundance gene expression. Real-time PCR is easy to perform, provides the necessary accuracy and produces reliable as well as rapid quantification results. But accurate quantification of nucleic acids requires a reproducible methodology and an adequate mathematical model for data analysis. This study enters into the particular topics of the relative quantification in real-time RT-PCR of a target gene transcript in comparison to a reference gene transcript. Therefore, a new mathematical model is presented. The relative expression ratio is calculated only from the real-time PCR efficiencies and the crossing point deviation of an unknown sample versus a control. This model needs no calibration curve. Control levels were included in the model to standardise each reaction run with respect to RNA integrity, sample loading and inter-PCR variations. High accuracy and reproducibility (<2.5% variation) were reached in LightCycler PCR using the established mathematical model.
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            Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets.

            Accurate normalization is an absolute prerequisite for correct measurement of gene expression. For quantitative real-time reverse transcription-PCR (RT-PCR), the most commonly used normalization strategy involves standardization to a single constitutively expressed control gene. However, in recent years, it has become clear that no single gene is constitutively expressed in all cell types and under all experimental conditions, implying that the expression stability of the intended control gene has to be verified before each experiment. We outline a novel, innovative, and robust strategy to identify stably expressed genes among a set of candidate normalization genes. The strategy is rooted in a mathematical model of gene expression that enables estimation not only of the overall variation of the candidate normalization genes but also of the variation between sample subgroups of the sample set. Notably, the strategy provides a direct measure for the estimated expression variation, enabling the user to evaluate the systematic error introduced when using the gene. In a side-by-side comparison with a previously published strategy, our model-based approach performed in a more robust manner and showed less sensitivity toward coregulation of the candidate normalization genes. We used the model-based strategy to identify genes suited to normalize quantitative RT-PCR data from colon cancer and bladder cancer. These genes are UBC, GAPD, and TPT1 for the colon and HSPCB, TEGT, and ATP5B for the bladder. The presented strategy can be applied to evaluate the suitability of any normalization gene candidate in any kind of experimental design and should allow more reliable normalization of RT-PCR data.
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              Insect fat body: energy, metabolism, and regulation.

              The fat body plays major roles in the life of insects. It is a dynamic tissue involved in multiple metabolic functions. One of these functions is to store and release energy in response to the energy demands of the insect. Insects store energy reserves in the form of glycogen and triglycerides in the adipocytes, the main fat body cell. Insect adipocytes can store a great amount of lipid reserves as cytoplasmic lipid droplets. Lipid metabolism is essential for growth and reproduction and provides energy needed during extended nonfeeding periods. This review focuses on energy storage and release and summarizes current understanding of the mechanisms underlying these processes in insects.
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                Author and article information

                Contributors
                Journal
                Front Physiol
                Front Physiol
                Front. Physiol.
                Frontiers in Physiology
                Frontiers Media S.A.
                1664-042X
                24 November 2016
                2016
                : 7
                Affiliations
                1Department of Chemistry of Social Insects, The Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences Prague, Czechia
                2Agricultural Research Ltd. Troubsko, Czechia
                3Research Group of Infochemicals, The Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences Prague, Czechia
                Author notes

                Edited by: Xanthe Vafopoulou, York University, Canada

                Reviewed by: Takashi Koyama, Instituto Gulbenkian de Ciência, Portugal; David Dolezel, Biology Centre ASCR, Czechia

                *Correspondence: Pavel Jedlička Pavel.Jedlicka@ 123456uochb.cas.cz

                This article was submitted to Invertebrate Physiology, a section of the journal Frontiers in Physiology

                Article
                10.3389/fphys.2016.00574
                5121236
                Copyright © 2016 Jedlička, Ernst, Votavová, Hanus and Valterová.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                Page count
                Figures: 10, Tables: 0, Equations: 0, References: 104, Pages: 20, Words: 11379
                Funding
                Funded by: Grantová Agentura České Republiky 10.13039/501100001824
                Award ID: 14-04291S
                Categories
                Physiology
                Original Research

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