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      Selection of Reference Genes for Quantitative Real-Time PCR in Bamboo ( Phyllostachys edulis)

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          Abstract

          Background

          The Moso bamboo ( Phyllostachys edulis) is one of the most important forestry resources and plays essential ecological roles in southern China. A draft nuclear genome sequence is expected to be publicly available in the near future; an explosion of gene expression data related to the unique traits of Moso bamboo will undoubtedly follow. Reverse transcription quantitative real-time PCR ((RT-)qPCR) is a widely used method for gene expression analysis. A necessary prerequisite of exact and reliable data is the accurate choice of reference genes.

          Result

          In this study, 14 candidate reference genes were chosen, and their expression levels were assessed by (RT-)qPCR in a set of six tissue samples (root, stem, mature stem, leaf, flower, and leaf sheath) and at two developmental stages (before and after flowering) in bamboo specimens obtained in three locations. The stability and suitability of the candidate reference genes were validated using the geNorm, NormFinder and BestKeeper programs. The results showed that TIP41 and NTB were suitable reference genes across all the tissues and at the different developmental stages examined in this study. While the expression of the NTB, TIP41 and UBQ were the mostly stable in different plant tissues samples, the expression of the TIP41, NTB and CAC were ranked the most stable in bamboo plants at various developmental stages. AP2-like gene was further assessed by using the reference genes TIP41 and NTB in comparison to ACT. Significant difference of the expression profile of AP2-like demonstrated the importance of choosing adequate reference genes in bamboo.

          Conclusion

          TIP41 and NTB were found to be homogeneously expressed and were adequate for normalization purposes, showing equivalent transcript levels in different samples. They are therefore the recommended reference genes for measuring gene expression in P. edulis.

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          Most cited references22

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          Actin, a central player in cell shape and movement.

          The protein actin forms filaments that provide cells with mechanical support and driving forces for movement. Actin contributes to biological processes such as sensing environmental forces, internalizing membrane vesicles, moving over surfaces, and dividing the cell in two. These cellular activities are complex; they depend on interactions of actin monomers and filaments with numerous other proteins. Here, we present a summary of the key questions in the field and suggest how those questions might be answered. Understanding actin-based biological phenomena will depend on identifying the participating molecules and defining their molecular mechanisms. Comparisons of quantitative measurements of reactions in live cells with computer simulations of mathematical models will also help generate meaningful insights.
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            miR156-regulated SPL transcription factors define an endogenous flowering pathway in Arabidopsis thaliana.

            The FT gene integrates several external and endogenous cues controlling flowering, including information on day length. A complex of the mobile FT protein and the bZIP transcription factor FD in turn has a central role in activating genes that execute the switch from vegetative to reproductive development. Here we reveal that microRNA156-targeted SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) genes not only act downstream of FT/FD, but also define a separate endogenous flowering pathway. High levels of miR156 in young plants prevent precocious flowering. A subsequent day length-independent decline in miR156 abundance provides a permissive environment for flowering and is paralleled by a rise in SPL levels. At the shoot apex, FT/FD and SPLs converge on an overlapping set of targets, with SPLs directly activating flower-promoting MADS box genes, providing a molecular substrate for both the redundant activities and the feed-forward action of the miR156/SPL and FT/FD modules in flowering control.
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              Twenty-five years of quantitative PCR for gene expression analysis.

              Following its invention 25 years ago, PCR has been adapted for numerous molecular biology applications. Gene expression analysis by reverse-transcription quantitative PCR (RT-qPCR) has been a key enabling technology of the post-genome era. Since the founding of BioTechniques, this journal has been a resource for the improvements in qPCR technology, experimental design, and data analysis. qPCR and, more specifically, real-time qPCR has become a routine and robust approach for measuring the expression of genes of interest, validating microarray experiments, and monitoring biomarkers. The use of real-time qPCR has nearly supplanted other approaches (e.g., Northern blotting, RNase protection assays). This review examines the current state of qPCR for gene expression analysis now that the method has reached a mature stage of development and implementation. Specifically, the different fluorescent reporter technologies of real-time qPCR are discussed as well as the selection of endogenous controls. The conceptual framework for data analysis methods is also presented to demystify these analysis techniques. The future of qPCR remains bright as the technology becomes more rapid, cost-effective, easier to use, and capable of higher throughput.
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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
                20 February 2013
                : 8
                : 2
                : e56573
                Affiliations
                [1 ]State Key Laboratory of Tree Genetics and Breeding, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, People’s Republic of China
                [2 ]Research Institute of Tropical Forestry, chinese Academy of Forestry, Guangzhou, People’s Republic of China
                [3 ]Beijing Genomics Institute-Shenzhen, Shenzhen, People’s Republic of China
                [4 ]International Centre for Bamboo and Rattan, Beijing, People’s Republic of China
                [5 ]Guilin Research Institute of Forestry, Guilin, People’s Republic of China
                [6 ]Centre for Ecology and Hydrology, Natural Environment Research Council, Wallingford, United Kingdom
                Instituto de Biología Molecular y Celular de Plantas, Spain
                Author notes

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

                Conceived and designed the experiments: CJF MZL HW. Performed the experiments: CJF. Analyzed the data: CJF JMM. Contributed reagents/materials/analysis tools: QRG XTL CJF. Wrote the paper: CJF MZL HW.

                Article
                PONE-D-12-27368
                10.1371/journal.pone.0056573
                3577859
                23437174
                f12db532-1aa0-4ac9-9c4e-a32c77339335
                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
                : 4 September 2012
                : 11 January 2013
                Page count
                Pages: 8
                Funding
                Funding provided by the National Natural Science Foundation of China (China, grant no. 31028004), Ministry of Science and Technology of the Peoplés Republic of China (China, grant no. S2012ZR0137) and Natural Environment Research Council (United Kingdom, grant no. NE/I000593/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Agriculture
                Forestry
                Biology
                Genetics
                Plant Genetics
                Genomics
                Genome Analysis Tools
                Genetic Maps
                Genome Databases
                Sequence Databases
                Plant Science
                Plant Genetics

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