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      Ex vitro hairy root induction in detached peanut leaves for plant–nematode interaction studies

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          Abstract

          Background

          Peanut ( Arachis hypogaea) production is largely affected by a variety of abiotic and biotic stresses, including the root-knot nematode (RKN) Meloidogyne arenaria that causes yield losses worldwide. Transcriptome studies of wild Arachis species, which harbor resistance to a number of pests and diseases, disclosed several candidate genes for M. arenaria resistance. Peanut is recalcitrant to genetic transformation, so the use of Agrobacterium rhizogenes-derived hairy roots emerged as an alternative for in-root functional characterization of these candidate genes.

          Results

          The present report describes an ex vitro methodology for hairy root induction in detached leaves based on the well-known ability of peanut to produce roots spontaneously from its petiole, which can be maintained for extended periods under high-humidity conditions. Thirty days after infection with the A. rhizogenes ‘K599’ strain, 90% of the detached leaves developed transgenic hairy roots with 5 cm of length in average, which were then inoculated with M. arenaria. For improved results, plant transformation, and nematode inoculation parameters were adjusted, such as bacterial cell density and growth stage; moist chamber conditions and nematode inoculum concentration. Using this methodology, a candidate gene for nematode resistance, AdEXLB8, was successfully overexpressed in hairy roots of the nematode-susceptible peanut cultivar ‘Runner’, resulting in 98% reduction in the number of galls and egg masses compared to the control, 60 days after M. arenaria infection.

          Conclusions

          This methodology proved to be more practical and cost-effective for functional validation of peanut candidate genes than in vitro and composite plant approaches, as it requires less space, reduces analysis costs and displays high transformation efficiency. The reduction in the number of RKN galls and egg masses in peanut hairy roots overexpressing AdEXLB8 corroborated the use of this strategy for functional characterization of root expressing candidate genes. This approach could be applicable not only for peanut–nematode interaction studies but also to other peanut root diseases, such as those caused by fungi and bacteria, being also potentially extended to other crop species displaying similar petiole-rooting competence.

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          Most cited references50

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          Comprehensive algorithm for quantitative real-time polymerase chain reaction.

          Quantitative real-time polymerase chain reactions (qRT-PCR) have become the method of choice for rapid, sensitive, quantitative comparison of RNA transcript abundance. Useful data from this method depend on fitting data to theoretical curves that allow computation of mRNA levels. Calculating accurate mRNA levels requires important parameters such as reaction efficiency and the fractional cycle number at threshold (CT) to be used; however, many algorithms currently in use estimate these important parameters. Here we describe an objective method for quantifying qRT-PCR results using calculations based on the kinetics of individual PCR reactions without the need of the standard curve, independent of any assumptions or subjective judgments which allow direct calculation of efficiency and CT. We use a four-parameter logistic model to fit the raw fluorescence data as a function of PCR cycles to identify the exponential phase of the reaction. Next, we use a three-parameter simple exponent model to fit the exponential phase using an iterative nonlinear regression algorithm. Within the exponential portion of the curve, our technique automatically identifies candidate regression values using the P-value of regression and then uses a weighted average to compute a final efficiency for quantification. For CT determination, we chose the first positive second derivative maximum from the logistic model. This algorithm provides an objective and noise-resistant method for quantification of qRT-PCR results that is independent of the specific equipment used to perform PCR reactions.
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            Q-Gene: processing quantitative real-time RT-PCR data.

            Q-Gene is an application for the processing of quantitative real-time RT-PCR data. It offers the user the possibility to freely choose between two principally different procedures to calculate normalized gene expressions as either means of Normalized Expressions or Mean Normalized Expressions. In this contribution it will be shown that the calculation of Mean Normalized Expressions has to be used for processing simplex PCR data, while multiplex PCR data should preferably be processed by calculating Normalized Expressions. The two procedures, which are currently in widespread use and regarded as more or less equivalent alternatives, should therefore specifically be applied according to the quantification procedure used. Web access to this program is provided at http://www.biotechniques.com/softlib/qgene.html
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              Agrobacterium rhizogenes-mediated transformation of soybean to study root biology.

              This protocol is used to induce transgenic roots on soybean to study the function of genes required in biological processes of the root. Young seedlings with unfolded cotyledons are infected at the cotyledonary node and/or hypocotyl with Agrobacterium rhizogenes carrying the gene construct to be tested and the infection sites are kept in an environment of high humidity. When the emerged hairy roots can support the plants, the main roots are removed and the transgenic roots can be tested. Using this method, almost 100% of the infected plants form hairy roots within 1 month from the start of the experiments.
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                Author and article information

                Contributors
                larissaarrais@gmail.com
                bruagro6@gmail.com
                ana-claudia.guerra@embrapa.br
                patricia.guimaraes@embrapa.br
                +55.61.3448-4901 , ana.brasileiro@embrapa.br
                Journal
                Plant Methods
                Plant Methods
                Plant Methods
                BioMed Central (London )
                1746-4811
                11 April 2017
                11 April 2017
                2017
                : 13
                : 25
                Affiliations
                [1 ]Parque Estação Biológica, Embrapa Recursos Genéticos e Biotecnologia, CP 02372, Final W5 Norte, Brasília, DF Brazil
                [2 ]GRID grid.7632.0, , Universidade de Brasília, ; Campus Darcy Ribeiro, Brasília, DF Brazil
                Article
                176
                10.1186/s13007-017-0176-4
                5387216
                28400855
                6ba068d2-4e3b-40d7-9e8f-756db7028eef
                © The Author(s) 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 20 October 2016
                : 2 April 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100003046, Empresa Brasileira de Pesquisa Agropecuária;
                Funded by: FundRef http://dx.doi.org/10.13039/501100003593, Conselho Nacional de Desenvolvimento Científico e Tecnológico;
                Funded by: FundRef http://dx.doi.org/10.13039/501100005668, Fundação de Apoio à Pesquisa do Distrito Federal;
                Funded by: FundRef http://dx.doi.org/10.13039/501100002322, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior;
                Categories
                Methodology
                Custom metadata
                © The Author(s) 2017

                Plant science & Botany
                meloidogyne,arachis,agrobacterium rhizogenes,genetic transformation,expansin like-b

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