Selection of internal control genes for quantitative real-time RT-PCR studies during tomato development process

<p>Abstract</p> <p>Background</p> <p>The elucidation of gene expression patterns leads to a better understanding of biological processes. Real-time quantitative RT-PCR has become the standard method for in-depth studies of gene expression. A biologically meaningful reporting of target mRNA quantities requires accurate and reliable normalization in order to identify real gene-specific variation. The purpose of normalization is to control several variables such as different amounts and quality of starting material, variable enzymatic efficiencies of retrotranscription from RNA to cDNA, or differences between tissues or cells in overall transcriptional activity. The validity of a housekeeping gene as endogenous control relies on the stability of its expression level across the sample panel being analysed. In the present report we describe the first systematic evaluation of potential internal controls during tomato development process to identify which are the most reliable for transcript quantification by real-time RT-PCR.</p> <p>Results</p> <p>In this study, we assess the expression stability of 7 traditional and 4 novel housekeeping genes in a set of 27 samples representing different tissues and organs of tomato plants at different developmental stages. First, we designed, tested and optimized amplification primers for real-time RT-PCR. Then, expression data from each candidate gene were evaluated with three complementary approaches based on different statistical procedures. Our analysis suggests that SGN-U314153 (<it>CAC</it>), SGN-U321250 (<it>TIP41</it>), SGN-U346908 ("<it>Expressed</it>") and SGN-U316474 (<it>SAND</it>) genes provide superior transcript normalization in tomato development studies. We recommend different combinations of these exceptionally stable housekeeping genes for suited normalization of different developmental series, including the complete tomato development process.</p> <p>Conclusion</p> <p>This work constitutes the first effort for the selection of optimal endogenous controls for quantitative real-time RT-PCR studies of gene expression during tomato development process. From our study a tool-kit of control genes emerges that outperform the traditional genes in terms of expression stability.</p

Tomato- Fusarium oxysporum interactions: II. Chitosan and MSB induced resistance against fol in young tomato plants

Qitosna, hidrolizados de quitosana y menadiona bisulfito de sodio (MBS), fueron aplicados al suelo y asperjados sobre plantas de tomate en diferentes experimentos, para evaluar su efecto combinado sobre el desarrollo de la enfermedad. Los tres productos protegieron con efectividad las plantas contra la enfermedad, mostrando los mejores resultados la aspersión al follaje con hidrolizados de quitosana y MBS (0.25 + 0.05 g.L$ respectivamente), sugiriendo que la inducción de resitencia sistémica juega un papel importante como mecanismop de defensa del tomate contra el ataque de Fusarium oxysporum f.sp lycopersicil (FOL). Se midierojn algunos mecanismos enzimáticos relacionados con la defensa en plantas tratadas con elicitores e inoculadas con FOL como marcadores de resistencia a la enfermedad.We gratefully acknowledge the fine technical assistance of Oligosaccharins Laboratory and the collaboration of the Technological Development Laboratory from CIGB. Special acknowledge to Maritza Mora Ruiz.Peer reviewe

Molecular analysis of menadione-induced resistance against biotic stress in Arabidopsis

19 páginas, 6 figuras, 2 tablas.Menadione sodium bisulphite (MSB) is a water-soluble derivative of vitamin K3, or menadione, and has been previously demonstrated to function as a plant defence activator against several pathogens in several plant species. However, there are no reports of the role of this vitamin in the induction of resistance in the plant model Arabidopsis thaliana. In the current study, we demonstrate that MSB induces resistance by priming in Arabidopsis against the virulent strain Pseudomonas syringae pv. tomato DC3000 (Pto) without inducing necrosis or visible damage. Changes in gene expression in response to 0.2 mm MSB were analysed in Arabidopsis at 3, 6 and 24 h post-treatment using microarray technology. In general, the treatment with MSB does not correlate with other publicly available data, thus MSB produces a unique molecular footprint. We observed 158 differentially regulated genes among all the possible trends. More up-regulated genes are included in categories such as 'response to stress' than the background, and the behaviour of these genes in different treatments confirms their role in response to biotic and abiotic stress. In addition, there is an over-representation of the G-box in their promoters. Some interesting functions are represented among the individual up-regulated genes, such as glutathione S-transferases, transcription factors (including putative regulators of the G-box) and cytochrome P450s. This work provides a wide insight into the molecular cues underlying the effect of MSB as a plant resistance inducer.This work was partially funded by an INVESCAN, S.L. grant (No.OTT2001438) to the CSIC and by a BIO2006-02168 grant of MICINN to PT. The microarrays were funded in part by the “Genome España” Foundation. MER was supported by a research contract (ID-TF-06/002) from the Consejería de Industria, Comercio y Nuevas Tecnologías (Gobierno de Canarias). The authors thank CajaCanarias for their research support. We also thank Lorena Perales for her help in performing the bacterial growth curves, Dr. Héctor Cabrera for his useful advice on writing the manuscript, the English translation service of the Universidad Politécnica de Valencia and Mrs. Pauline Agnew whose endeavoured to edit the English translation of this paper.Peer reviewe

Bioinformatics Discovery of Vertebrate Cathelicidins from the Mining of Available Genomes

Due to the worrying increase in antimicrobial resistance to conventional antibiotics, the search for alternatives is becoming increasingly important. Antimicrobial peptides (AMPs), originating from natural resources, have been recognised as a novel class of antibiotics. An advantage of peptides over antibiotics is that the resistance is more difficult to attain than for conventional antibiotics. With the increasing number of genomes sequenced and available in the public domain, one alternative methodology to obtain novel AMPs is to analyse genes and proteins from genomic databases to predict and identify amino acid sequences that share similarities and molecular features with natural bioactive antimicrobial peptides. In this chapter, we summarise some of our recent results on the production of antimicrobial peptides, particularly, how we managed to identify a family of antimicrobial peptides: cathelicidins, through bioinformatics tools, from the genomes of two lower vertebrates (a reptile and a bird) available in public databases. We hope that our preliminary investigation with these novel peptides could be useful for the design of future strategies that pursue the production of antimicrobial peptides through biotechnology

Biostimulant activity of Galaxaura rugosa seaweed extracts against water deficit stress in tomato seedlings involves activation of ABA signaling

Water scarcity is a serious constraint for agriculture, and global warming and climate change can exacerbate it in many areas. Therefore, sustainable approaches must be implemented to deal with current and future water scarcity scenarios. Genetic and chemical approaches are being applied to manage this limitation and maintain crop yields. In particular, biostimulants obtained from natural sources such as marine algae are promising aids for coping with water deficit stress in agriculture. Here we present a bioprospection study of extracts of the macroalgae Bonnemaisonia hamifera, Galaxaura rugosa, Dasycladus vermicularis, Ulva clathrata, Cystoseira foeniculacea, Cystoseira humilis, Lobophora dagamae, Colpomenia sinuosa and Halopteris scoparia from the north coast of Tenerife, in the Canary Islands. The aqueous extracts of Bonnemaisonia hamifera, Galaxaura rugosa, Dasycladus vermicularis and Cystoseira humilis show biostimulant activity against water deficit stress in tomato seedlings under controlled conditions, providing higher tolerance than the mock-treated control. The Galaxaura rugosa extract showed the highest biostimulant activity against water deficit stress. We demonstrate that this positive effect involves the activation of the abscisic acid (ABA) pathway in Arabidopsis thaliana (arabidopsis) and Solanum lycopersicum (tomato). Application of G. rugosa extract to the root system by drenching tomato seedlings subjected to water deficit leads to improved CO2 assimilation and water use efficiency (WUEp), compared to mock-treated plants. These results highlight a new potential seaweed source of substances with osmoprotectant properties, useful for biostimulant development. Future studies may provide further insight into which components of the seaweed extract induce activation of the ABA pathway

Abscisic acid mimic-fluorine derivative 4 alleviates water deficit stress by regulating ABA-responsive genes, proline accumulation, CO2 assimilation, water use efficiency and better nutrient uptake in tomato plants

Water deficit represents a serious limitation for agriculture and both genetic and chemical approaches are being used to cope with this stress and maintain plant yield. Next-generation agrochemicals that control stomatal aperture are promising for controlling water use efficiency. For example, chemical control of abscisic acid (ABA) signaling through ABA-receptor agonists is a powerful method to activate plant adaptation to water deficit. Such agonists are molecules able to bind and activate ABA receptors and, although their development has experienced significant advances in the last decade, few translational studies have been performed in crops. Here, we describe protection by the ABA mimic-fluorine derivative 4 (AMF4) agonist of the vegetative growth in tomato plants subjected to water restriction. Photosynthesis in mock-treated plants is markedly impaired under water deficit conditions, whereas AMF4 treatment notably improves CO2 assimilation, the relative plant water content and growth. As expected for an antitranspirant molecule, AMF4 treatment diminishes stomatal conductance and transpiration in the first phase of the experiment; however, when photosynthesis declines in mock-treated plants as stress persists, higher photosynthetic and transpiration parameters are recorded in agonist-treated plants. Additionally, AMF4 increases proline levels over those achieved in mock-treated plants in response to water deficit. Thus water deficit and AMF4 cooperate to upregulate P5CS1 through both ABA-independent and ABA-dependent pathways, and therefore, higher proline levels are produced Finally, analysis of macronutrients reveals higher levels of Ca, K and Mg in AMF4- compared to mock-treated plants subjected to water deficit. Overall, these physiological analyses reveal a protective effect of AMF4 over photosynthesis under water deficit and enhanced water use efficiency after agonist treatment. In summary, AMF4 treatment is a promising approach for farmers to protect the vegetative growth of tomatoes under water deficit stress

Coefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regression

Copyright © 2009 The Authors. Copyright © ECOGRAPHY 2009.A major focus of geographical ecology and macro ecology is to understand the causes of spatially structured ecological patterns. However, achieving this understanding can be complicated when using multiple regressions, because the relative importance of explanatory variables, as measured by regression coefficients, can shift depending on whether spatially explicit or non-spatial modelling is used. However, the extent to which coefficients may shift and why shifts occur are unclear. Here, we analyze the relationship between environmental predictors and the geographical distribution of species richness, body size, range size and abundance in 97 multi-factorial data sets. Our goal was to compare standardized partial regression coefficients of non-spatial ordinary least squares regressions (i.e. models fitted using ordinary least squares without taking autocorrelation into account; “OLS models” hereafter) and eight spatial methods to evaluate the frequency of coefficient shifts and identify characteristics of data that might predict when shifts are likely. We generated three metrics of coefficient shifts and eight characteristics of the data sets as predictors of shifts. Typical of ecological data, spatial autocorrelation in the residuals of OLS models was found in most data sets. The spatial models varied in the extent to which they minimized residual spatial autocorrelation. Patterns of coefficient shifts also varied among methods and datasets, although the magnitudes of shifts tended to be small in all cases. We were unable to identify strong predictors of shifts, including the levels of autocorrelation in either explanatory variables or model residuals. Thus, changes in coefficients between spatial and non-spatial methods depend on the method used and are largely idiosyncratic, making it difficult to predict when or why shifts occur. We conclude that the ecological importance of regression coefficients cannot be evaluated with confidence irrespective of whether spatially explicit modelling is used or not. Researchers may have little choice but to be more explicit about the uncertainty of models and more cautious in their interpretation

VDES J2325−5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning

We present the discovery and preliminary characterization of a gravitationally lensed quasar with a source redshift zs = 2.74 and image separation of 2.9 arcsec lensed by a foreground zl = 0.40 elliptical galaxy. Since optical observations of gravitationally lensed quasars showthe lens system as a superposition of multiple point sources and a foreground lensing galaxy, we have developed a morphology-independent multi-wavelength approach to the photometric selection of lensed quasar candidates based on Gaussian Mixture Models (GMM) supervised machine learning. Using this technique and gi multicolour photometric observations from the Dark Energy Survey (DES), near-IR JK photometry from the VISTA Hemisphere Survey (VHS) and WISE mid-IR photometry, we have identified a candidate system with two catalogue components with iAB = 18.61 and iAB = 20.44 comprising an elliptical galaxy and two blue point sources. Spectroscopic follow-up with NTT and the use of an archival AAT spectrum show that the point sources can be identified as a lensed quasar with an emission line redshift of z = 2.739 ± 0.003 and a foreground early-type galaxy with z = 0.400 ± 0.002.We model the system as a single isothermal ellipsoid and find the Einstein radius θE ∼ 1.47 arcsec, enclosed mass Menc ∼ 4 × 1011 M and a time delay of ∼52 d. The relatively wide separation, month scale time delay duration and high redshift make this an ideal system for constraining the expansion rate beyond a redshift of 1

The miniJPAS survey: stellar atmospheric parameters from 56 optical filters

With a unique set of 54 overlapping narrow-band and two broader filters covering the entire optical range, the incoming Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) will provide a great opportunity for stellar physics and near-field cosmology. In this work, we use the miniJPAS data in 56 J-PAS filters and 4 complementary SDSS-like filters to explore and prove the potential of the J-PAS filter system in characterizing stars and deriving their atmospheric parameters. We obtain estimates for the effective temperature with a good precision (<150 K) from spectral energy distribution fitting. We have constructed the metallicity-dependent stellar loci in 59 colours for the miniJPAS FGK dwarf stars, after correcting certain systematic errors in flat-fielding. The very blue colours, including uJAVA − r, J0378 − r, J0390 − r, uJPAS − r, show the strongest metallicity dependence, around 0.25 mag dex−1. The sensitivities decrease to about 0.1 mag dex−1 for the J0400 − r, J0410 − r, and J0420 − r colours. The locus fitting residuals show peaks at the J0390, J0430, J0510, and J0520 filters, suggesting that individual elemental abundances such as [Ca/Fe], [C/Fe], and [Mg/Fe] can also be determined from the J-PAS photometry. Via stellar loci, we have achieved a typical metallicity precision of 0.1 dex. The miniJPAS filters also demonstrate strong potential in discriminating dwarfs and giants, particularly the J0520 and J0510 filters. Our results demonstrate the power of the J-PAS filter system in stellar parameter determinations and the huge potential of the coming J-PAS survey in stellar and Galactic studies. © 2022 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.This work is supported by the National Natural Science Foundation of China through the projects NSFC 12222301, 12173007, 11603002, National Key Basic R & D Program of China via 2019YFA0405500, and Beijing Normal University grant no. 310232102. We acknowledge the science research grants from the China Manned Space Project with NO. CMS-CSST-2021-A08 and CMS-CSST-2021-A09. This research has made use of the Spanish Virtual Observatory (https://svo.cab.inta-csic.es) project funded by MCIN/AEI/10.13039/501100011033/ through grant PID2020-112949GB-I00. PC acknowledges financial support from the Government of Comunidad Autónoma de Madrid (Spain), via postdoctoral grant ‘Atracción de Talento Investigador’2019-T2/TIC-14760. The work of VMP is supported by NOIRLab, which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. FJE acknowledges financial support by the Spanish grant MDM-2017-0737 at Centro de Astrobiología (CSIC-INTA), Unidad de Excelencia María de Maeztu. CAG acknowledges financial support from the CAPES through scholarship for developing his PhD project and any related research. Part of this work was supported by institutional research funding IUT40-2, JPUT907, and PRG1006 of the Estonian Ministry of Education and Research. We acknowledge the support by the Centre of Excellence ‘Dark side of the Universe’ (TK133) financed by the European Union through the European Regional Development Fund.With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S).Peer reviewe

Redshift distributions of galaxies in the Dark Energy Survey Science Verification shear catalogue and implications for weak lensing

We present photometric redshift estimates for galaxies used in the weak lensing analysis of the Dark Energy Survey Science Verification (DES SV) data. Four model- or machine learning-based photometric redshift methods—ANNZ2, BPZ calibrated against BCC-Ufig simulations, SKYNET, and TPZ—are analyzed. For training, calibration, and testing of these methods, we construct a catalogue of spectroscopically confirmed galaxies matched against DES SV data. The performance of the methods is evaluated against the matched spectroscopic catalogue, focusing on metrics relevant for weak lensing analyses, with additional validation against COSMOS photo-z’s. From the galaxies in the DES SV shear catalogue, which have mean redshift 0.72 0.01 over the range 0.3 < z < 1.3, we construct three tomographic bins with means of z ¼ f0.45; 0.67; 1.00g. These bins each have systematic uncertainties δz ≲ 0.05 in the mean of the fiducial SKYNET photo-z nðzÞ. We propagate the errors in the redshift distributions through to their impact on cosmological parameters estimated with cosmic shear, and find that they cause shifts in the value of σ8 of approximately 3%. This shift is within the one sigma statistical errors on σ8 for the DES SV shear catalogue. We further study the potential impact of systematic differences on the critical surface density, Σcrit, finding levels of bias safely less than the statistical power of DES SV data. We recommend a final Gaussian prior for the photo-z bias in the mean of nðzÞ of width 0.05 for each of the three tomographic bins, and show that this is a sufficient bias model for the corresponding cosmology analysis