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      Housekeeping in Tephritid insects: the best gene choice for expression analyses in the medfly and the olive fly

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          Abstract

          Real-time quantitative-PCR has been a priceless tool for gene expression analyses. The reaction, however, needs proper normalization with the use of housekeeping genes (HKGs), whose expression remains stable throughout the experimental conditions. Often, the combination of several genes is required for accurate normalization. Most importantly, there are no universal HKGs which can be used since their expression varies among different organisms, tissues or experimental conditions. In the present study, nine common HKGs ( RPL19, tbp, ubx, GAPDH, α-TUB, β-TUB, 14-3-3zeta, RPE and actin3) are evaluated in thirteen different body parts, developmental stages and reproductive and olfactory tissues of two insects of agricultural importance, the medfly and the olive fly. Three software programs based on different algorithms were used ( geNorm, NormFinder and BestKeeper) and gave different ranking of HKG stabilities. This confirms once again that the stability of common HKGs should not be taken for granted and demonstrates the caution that is needed in the choice of the appropriate HKGs. Finally, by estimating the average of a standard score of the stability values resulted by the three programs we were able to provide a useful consensus key for the choice of the best HKG combination in various tissues of the two insects.

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          miRDeepFinder: a miRNA analysis tool for deep sequencing of plant small RNAs.

          miRDeepFinder is a software package developed to identify and functionally analyze plant microRNAs (miRNAs) and their targets from small RNA datasets obtained from deep sequencing. The functions available in miRDeepFinder include pre-processing of raw data, identifying conserved miRNAs, mining and classifying novel miRNAs, miRNA expression profiling, predicting miRNA targets, and gene pathway and gene network analysis involving miRNAs. The fundamental design of miRDeepFinder is based on miRNA biogenesis, miRNA-mediated gene regulation and target recognition, such as perfect or near perfect hairpin structures, different read abundances of miRNA and miRNA*, and targeting patterns of plant miRNAs. To test the accuracy and robustness of miRDeepFinder, we analyzed a small RNA deep sequencing dataset of Arabidopsis thaliana published in the GEO database of NCBI. Our test retrieved 128 of 131 (97.7%) known miRNAs that have a more than 3 read count in Arabidopsis. Because many known miRNAs are not associated with miRNA*s in small RNA datasets, miRDeepFinder was also designed to recover miRNA candidates without the presence of miRNA*. To mine as many miRNAs as possible, miRDeepFinder allows users to compare mature miRNAs and their miRNA*s with other small RNA datasets from the same species. Cleaveland software package was also incorporated into miRDeepFinder for miRNA target identification using degradome sequencing analysis. Using this new computational tool, we identified 13 novel miRNA candidates with miRNA*s from Arabidopsis and validated 12 of them experimentally. Interestingly, of the 12 verified novel miRNAs, a miRNA named AC1 spans the exons of two genes (UTG71C4 and UGT71C3). Both the mature AC1 miRNA and its miRNA* were also found in four other small RNA datasets. We also developed a tool, "miRNA primer designer" to design primers for any type of miRNAs. miRDeepFinder provides a powerful tool for analyzing small RNA datasets from all species, with or without the availability of genome information. miRDeepFinder and miRNA primer designer are freely available at http://www.leonxie.com/DeepFinder.php and at http://www.leonxie.com/miRNAprimerDesigner.php , respectively. A program (called RefFinder: http://www.leonxie.com/referencegene.php ) was also developed for assessing the reliable reference genes for gene expression analysis, including miRNAs.
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            Quantitative real-time reverse transcription polymerase chain reaction: normalization to rRNA or single housekeeping genes is inappropriate for human tissue biopsies.

            Careful normalization is essential when using quantitative reverse transcription polymerase chain reaction assays to compare mRNA levels between biopsies from different individuals or cells undergoing different treatment. Generally this involves the use of internal controls, such as mRNA specified by a housekeeping gene, ribosomal RNA (rRNA), or accurately quantitated total RNA. The aim of this study was to compare these methods and determine which one can provide the most accurate and biologically relevant quantitative results. Our results show significant variation in the expression levels of 10 commonly used housekeeping genes and 18S rRNA, both between individuals and between biopsies taken from the same patient. Furthermore, in 23 breast cancers samples mRNA and protein levels of a regulated gene, vascular endothelial growth factor (VEGF), correlated only when normalized to total RNA, as did microvessel density. Finally, mRNA levels of VEGF and the most popular housekeeping gene, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), were significantly correlated in the colon. Our results suggest that the use of internal standards comprising single housekeeping genes or rRNA is inappropriate for studies involving tissue biopsies.
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              Synthetic lethal interaction between oncogenic KRAS dependency and STK33 suppression in human cancer cells.

              An alternative to therapeutic targeting of oncogenes is to perform "synthetic lethality" screens for genes that are essential only in the context of specific cancer-causing mutations. We used high-throughput RNA interference (RNAi) to identify synthetic lethal interactions in cancer cells harboring mutant KRAS, the most commonly mutated human oncogene. We find that cells that are dependent on mutant KRAS exhibit sensitivity to suppression of the serine/threonine kinase STK33 irrespective of tissue origin, whereas STK33 is not required by KRAS-independent cells. STK33 promotes cancer cell viability in a kinase activity-dependent manner by regulating the suppression of mitochondrial apoptosis mediated through S6K1-induced inactivation of the death agonist BAD selectively in mutant KRAS-dependent cells. These observations identify STK33 as a target for treatment of mutant KRAS-driven cancers and demonstrate the potential of RNAi screens for discovering functional dependencies created by oncogenic mutations that may enable therapeutic intervention for cancers with "undruggable" genetic alterations.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                03 April 2017
                2017
                : 7
                : 45634
                Affiliations
                [1 ]Department of Biochemistry and Biotechnology, University of Thessaly , Larissa, Greece
                [2 ]Department of Economic Sciences, National and Kapodistrian University of Athens , Athens, 10559, Greece
                Author notes
                Article
                srep45634
                10.1038/srep45634
                5377319
                28368031
                07287a73-2664-49be-800d-d8011c8bea6d
                Copyright © 2017, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 22 August 2016
                : 01 March 2017
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