Stability investigation of air-dried olive ribo nucleic acids for metavirome studies.

BACKGROUND: The application of ribo nucleic acids for molecular studies requires high integrity and quality of extracted total RNA samples. In addition, the need to transfer RNA samples at room temperature without special treatments such as ice and liquid nitrogen storage according to international transport laws highlights the importance of low cost alternative methods such as RNA air-drying, lyophilisation and transportable agents. In this study, the quality and quantity of air-dried RNA samples from leaf, petiole and bark tissues of different olive genotypes using several RNA extraction methods were compared with lyophilized ground leaves and RNAlater-stored tissue samples before precipitation. The quality of RNA and prepared libraries were checked by several techniques including agarose and polyacrylamide gel electrophoresis, Agilent quality control, RT-PCR amplification of housekeeping and viral genes and high throughput sequencing. RESULTS: Although RNA value varied amongst cultivars, RNA extraction with TRIzol™ Reagent in fresh extractions and samples stored in RNAlater before RNA extraction resulted in 455.26 ng/µL and 63.46 ng/µL (mean value of cultivars) as the highest RNA concentration averages, respectively. RNA samples extracted by TRIzol™ Reagents and stored for a short term at - 80 °C before air-drying showed the third highest concentration (44.87 ng/µL). The synthesized cDNAs quality for PCR amplification of housekeeping genes (Rbc 1 and Nad 5) and partial genomes of Arabis mosaic virus and Cucumber mosaic virus showed satisfactory results in RNA samples extracted by TRIzol™ Reagents despite its variation amongst cultivars. CONCLUSIONS: Considering the difficulties in the extraction of high quality and quantity RNA in olive for molecular analyses, this study demonstrated that RNA extraction method based on TRIzol™ Reagent can be considered for virobiome studies of both fresh and air-dried samples.

Evaluation of genetic stability in olive callus-induced and meristem-induced shoots using flow cytometry and amplified fragment length polymorphism techniques.

BACKGROUND: In vitro culture of olive, as an economically valuable tree, has fundamentally a genotype-dependant low micropropagation rate which needs to be improved in already established and newly released cultivars. Various plant tissue culture media, planting systems and growth factors were evaluated in two promissing Iranian olive cultivars 'Amin' and 'Meshkat' and the commercial Spanish cultivar 'Arbequina'. RESULTS: The results showed that cultivars have their specific optimal media, i.e. 'Amin' in the MS with 4 mg/L zeatin, 'Arbequina' in the OM with 1 mg/L zeatin, and 'Meshkat' in the OM and MS with 2 mg/L zeatin, which produced significantly a higher number of axillary shoots than other media. The results also indicated a significant improvement in the growth indices of 'Amin' (number of axillary shoots) when cultured using periodical mini bioreactor (PMB) in the VS medium. In comparison with VS, OM did not reveal any significant differences when both culturing systems (PMB and semi-solid media (SSM)) were used. Regarding the effect of carbon source and light intensity, mannitol and 2000 cd sr m-2 greatly enhanced 'Arbequina' growth indices (main shoot length and growth quality). The results of genetic stability of callus induced shoots (CIS) and meristem induced shoots (MIS) revealed that 2C DNA value assessed by partec flow cytometery (FCM) had 0.01, 0.03 and 0.08 pg discrepencies in 'Amin', 'Arbequina' and 'Meshkat', repectively. The Amplified Fragment Length Polymorphism (AFLP) results also indicated that the cultivars were classified regardless of the micropropagation origin (CIS or MIS), except for 'Arbequina'. The AFLP findings showed that 'Arbequina' had the highest dispersal (7-38%) in CIS and MIS, while the Iranian cultivar of 'Meshkat' (5-9%) had the highest stability. CONCLUSIONS: This study indicated the importance of in vitro growth parameters for improving the micropropagation indices of olive cultivars. It showed that optimized protocols (OM, PMB, zeatin, mannitol and 2000 cd sr m-2) co-produced larger calli resulting in indirect organogenesis. Based on FCM and AFLP analysis, it can be concluded that true-to-typeness of micropropagated olive was cultivar-dependent.

High throughput mathematical modeling and multi-objective evolutionary algorithms for plant tissue culture media formulation: Case study of pear rootstocks.

Simplified prediction of the interactions of plant tissue culture media components is of critical importance to efficient development and optimization of new media. We applied two algorithms, gene expression programming (GEP) and M5' model tree, to predict the effects of media components on in vitro proliferation rate (PR), shoot length (SL), shoot tip necrosis (STN), vitrification (Vitri) and quality index (QI) in pear rootstocks (Pyrodwarf and OHF 69). In order to optimize the selected prediction models, as well as achieving a precise multi-optimization method, multi-objective evolutionary optimization algorithms using genetic algorithm (GA) and particle swarm optimization (PSO) techniques were compared to the mono-objective GA optimization technique. A Gamma test (GT) was used to find the most important determinant input for optimizing each output factor. GEP had a higher prediction accuracy than M5' model tree. GT results showed that BA (Γ = 4.0178), Mesos (Γ = 0.5482), Mesos (Γ = 184.0100), Micros (Γ = 136.6100) and Mesos (Γ = 1.1146), for PR, SL, STN, Vitri and QI respectively, were the most important factors in culturing OHF 69, while for Pyrodwarf culture, BA (Γ = 10.2920), Micros (Γ = 0.7874), NH4NO3 (Γ = 166.410), KNO3 (Γ = 168.4400), and Mesos (Γ = 1.4860) were the most important influences on PR, SL, STN, Vitri and QI respectively. The PSO optimized GEP models produced the best outputs for both rootstocks.

Combining gene expression programming and genetic algorithm as a powerful hybrid modeling approach for pear rootstocks tissue culture media formulation.

BACKGROUND: Predicting impact of plant tissue culture media components on explant proliferation is important especially in commercial scale for optimizing efficient culture media. Previous studies have focused on predicting the impact of media components on explant growth via conventional multi-layer perceptron neural networks (MLPNN) and Multiple Linear Regression (MLR) methods. So, there is an opportunity to find more efficient algorithms such as Radial Basis Function Neural Network (RBFNN) and Gene Expression Programming (GEP). Here, a novel algorithm, i.e. GEP which has not been previously applied in plant tissue culture researches was compared to RBFNN and MLR for the first time. Pear rootstocks (Pyrodwarf and OHF) were used as case studies on predicting the effect of minerals and some hormones in the culture medium on proliferation indices. RESULTS: Generally, RBFNN and GEP showed extremely higher performance accuracy than the MLR. Moreover, GEP models as the most accurate models were optimized using genetic algorithm (GA). The improvement was mainly due to the RBFNN and GEP strong estimation capability and their superior tolerance to experimental noises or improbability. CONCLUSIONS: GEP as the most robust and accurate prospecting procedure to achieve the highest proliferation quality and quantity has also the benefit of being easy to use.

Genetic diversity analysis and population structure of some Iranian Fenugreek (Trigonella foenum-graecum L.) landraces using SRAP Markers.

Fenugreek is one of the important edible and medicinal vegetables that have a long history of cultivation and consumption. Characterize the extent of the genetic diversity among landraces will provide a good context for future breeding programs and genetic resource preservation. Genetic diversity and population structure of 88 individuals of eight landraces of Iranian fenugreek evaluated based on SRAP markers. Seventy-two bands generated from 6 primers in which 56 (80.11%) band were polymorph. Hamadan landrace showed the lowest values of percentage of polymorphic loci (67.86), Nei's gene diversity index (0.24), number of effective alleles (1.40) and Shannon's Information index (0.36). Nei's genetic distance matrix revealed the highest genetic distance between Hamadan and Yazd (0.203) and the highest genetic similarity between Mahallat and Varamin (0.036) landraces. The most gene flow was between Mahallat and Varamin landraces (Nm=8.36) and the least was between Shiraz and Hamadan landraces (Nm=0.66). An extent admixture of alleles between the Iranian fenugreek landraces was observed by the population structure. Mantel test indicated that the genetic differentiation and gene flow is not associated with geographic distance in Iranian fenugreek landraces. Our observations indicated SRAP is an efficient technique to reveal genetic diversity and population structure of Iranian fenugreek landrace.

Modeling and Optimizing a New Culture Medium for In Vitro Rooting of G×N15 Prunus Rootstock using Artificial Neural Network-Genetic Algorithm.

The main aim of the present investigation is modeling and optimization of a new culture medium for in vitro rooting of G×N15 rootstock using an artificial neural network-genetic algorithm (ANN-GA). Six experiments for assessing different media culture, various concentrations of Indole - 3- butyric acid, different concentrations of Thiamine and Fe-EDDHA were designed. The effects of five ionic macronutrients (NH4+, NO3-, Ca2+, K+ and Cl-) on five growth parameters [root number (RN), root length (RL), root percentage (R%), fresh (FW) and dry weight (DW)] were evaluated using the ANN-GA method. The R2 correlation values of 0.88, 0.88, 0.98, 0.94 and 0.87 between observed and predicted values were acquired for all five growth parameters, respectively. The ANN-GA results indicated that among the input variables, K+ (7.6) and NH4+ (4.4), K+ (7.7) and Ca2+ (2.8), K+ (36.7) and NH4+ (4.3), K+ (14.7) and NH4+ (4.4) and K+ (7.6) and NH4+ (4.3) had the highest values of variable sensitivity ratio (VSR) in the data set, for RN, RL, R%, FW and DW, respectively. ANN-GA optimized LS medium for G×N15 rooting contained optimized amounts of 1 mg L-1 IBA, 100, 150, or 200 mg L-1 Fe-EDDHA and 1.6 mg L-1 Thiamine. The efficiency of the optimized culture media was compared to other standard media for Prunus rooting and the results indicated that the optimized medium is more efficient than the others.

Development of an Artificial Neural Network as a Tool for Predicting the Targeted Phenolic Profile of Grapevine (Vitis vinifera) Foliar Wastes.

High performance liquid chromatography data related to the concentrations of 12 phenolic compounds in vegetative parts, measured at four sampling times were processed for developing prediction models, based on the cultivar, grapevine organ, growth stage, total flavonoid content (TFC), total reducing capacity (TRC), and total antioxidant activity (TAA). 12 Artificial neural network (ANN) models were developed with 79 input variables and different number of neurons in the hidden layer, for the prediction of 12 phenolics. The results confirmed that the developed ANN-models (R2 = 0.90 - 0.97) outperform the stepwise regression models (R2 = 0.05 - 0.78). Moreover, the sensitivity of the model outputs against each input variable was computed by using ANN and it was revealed that the key determinant of phenolic concentration was the source organ of the grapevine. The ANN prediction technique represents a promising approach to predict targeted phenolic levels in vegetative parts of the grapevine.

Mathematical Modeling and Optimizing of in Vitro Hormonal Combination for G × N15 Vegetative Rootstock Proliferation Using Artificial Neural Network-Genetic Algorithm (ANN-GA).

The efficiency of a hybrid systems method which combined artificial neural networks (ANNs) as a modeling tool and genetic algorithms (GAs) as an optimizing method for input variables used in ANN modeling was assessed. Hence, as a new technique, it was applied for the prediction and optimization of the plant hormones concentrations and combinations for in vitro proliferation of Garnem (G × N15) rootstock as a case study. Optimizing hormones combination was surveyed by modeling the effects of various concentrations of cytokinin-auxin, i.e., BAP, KIN, TDZ, IBA, and NAA combinations (inputs) on four growth parameters (outputs), i.e., micro-shoots number per explant, length of micro-shoots, developed callus weight (CW) and the quality index (QI) of plantlets. Calculation of statistical values such as R2 (coefficient of determination) related to the accuracy of ANN-GA models showed a considerably higher prediction accuracy for ANN models, i.e., micro-shoots number: R2 = 0.81, length of micro-shoots: R2 = 0.87, CW: R2 = 0.88, QI: R2 = 0.87. According to the results, among the input variables, BAP (19.3), KIN (9.64), and IBA (2.63) showed the highest values of variable sensitivity ratio for proliferation rate. The GA showed that media containing 1.02 mg/l BAP in combination with 0.098 mg/l IBA could lead to the optimal proliferation rate (10.53) for G × N15 rootstock. Another objective of the present study was to compare the performance of predicted and optimized cytokinin-auxin combination with the best optimized obtained concentrations of our other experiments. Considering three growth parameters (length of micro-shoots, micro-shoots number, and proliferation rate), the last treatment was found to be superior to the rest of treatments for G × N15 rootstock in vitro multiplication. Very little difference between the ANN predicted and experimental data confirmed high capability of ANN-GA method in predicting new optimized protocols for plant in vitro propagation.

Artificial Neural Network Genetic Algorithm As Powerful Tool to Predict and Optimize In vitro Proliferation Mineral Medium for G × N15 Rootstock.

One of the major obstacles to the micropropagation of Prunus rootstocks has, up until now, been the lack of a suitable tissue culture medium. Therefore, reformulation of culture media or modification of the mineral content might be a breakthrough to improve in vitro multiplication of G × N15 (garnem). We found artificial neural network in combination of genetic algorithm (ANN-GA) as a very precise and powerful modeling system for optimizing the culture medium, So that modeling the effects of MS mineral salts ([Formula: see text], [Formula: see text], [Formula: see text], Ca2+, K+, [Formula: see text], Mg2+, and Cl-) on in vitro multiplication parameters (the number of microshoots per explant, average length of microshoots, weight of calluses derived from the base of stem explants, and quality index of plantlets) of G × N15. Showed high R2 correlation values of 87, 91, 87, and 74 between observed and predicted values were found for these four growth parameters, respectively. According to the ANN-GA results, among the input variables, [Formula: see text] and [Formula: see text] had the highest values of VSR in data set for the parameters studied. The ANN-GA showed that the best proliferation rate was obtained from medium containing (mM) 27.5 [Formula: see text], 14 [Formula: see text], 5 Ca2+, 25.9 K+, 0.7 Mg2+, 1.1 [Formula: see text], 4.7 [Formula: see text], and 0.96 Cl-. The performance of the medium optimized by ANN-GA, denoted as YAS (Yadollahi, Arab and Shojaeiyan), was compared to that of standard growth media for all Prunus rootstock, including the Murashige and Skoog (MS) medium, (specific media) EM, Quoirin and Lepoivre (QL) medium, and woody plant medium (WPM) Prunus. With respect to shoot length, shoot number per cultured explant and productivity (number of microshoots × length of microshoots), YAS was found to be superior to other media for in vitro multiplication of G × N15 rootstocks. In addition, our results indicated that by using ANN-GA, we were able to determine a suitable culture medium formulation to achieve the best in vitro productivity.

Red-fleshed Apples: Old Autochthonous Fruits as a Novel Source of Anthocyanin Antioxidants.

In order to promote breeding programs and a full reintroduction into production of two local red-fleshed apple varieties grown in Bekran and Bastam (Iran), the evaluation of their antioxidant properties was of interest. LC-MS(n) based metabolic fingerprinting analyses were applied to investigate the anthocyanin content of both peel and flesh components of the fruits. Cyanidin-3-O-hexoside isomers were present in both 'Bekran' and 'Bastam' apples, whereas 'Bekran' apple was a valuable source of anthocyanin rutinose derivatives. Employing DPPH(•), ABTS(•+), and ORAC methods, the antiradical efficacy was evaluated. The ability of the investigated fruit components to scavenge OH(•), and O(2) (•-) reactive species was also assessed. ID(50) values highlighted the massive antioxidant response of 'Bekran' peel component, able to counteract by 50 % OH(•), and O(2) (•-) at 130.3 and 91.6 µg/mL, respectively. The cytoprotective screening towards HeLa, HepG2, A549, SH-5YSY, and SK-N-BE(2)-C cell lines evidenced that the investigated Iranian red-fleshed apple fruits were able to exert a significant antioxidant response in hydrogen peroxide oxidized cell systems. Data collected suggested that the revaluation of 'Bekran' and 'Bastam' apple cultivars could represent a precious source of antioxidant compounds whose dietary intake could improve the human well-being reducing risks of free radical related chronic and degenerative diseases.

A seed coat cyanohydrin glucosyltransferase is associated with bitterness in almond (Prunus dulcis) kernels.

The secondary metabolite amygdalin is a cyanogenic diglucoside that at high concentrations is associated with intense bitterness in seeds of the Rosaceae, including kernels of almond (Prunus dulcis (Mill.), syn. Prunus amygdalus D. A. Webb Batsch). Amygdalin is a glucoside of prunasin, itself a glucoside of R-mandelonitrile (a cyanohydrin). Here we report the isolation of an almond enzyme (UGT85A19) that stereo-selectively glucosylates R-mandelonitrile to produce prunasin. In a survey of developing kernels from seven bitter and 11 non-bitter genotypes with polyclonal antibody raised to UGT85A19, the enzyme was found to accumulate to higher levels in the bitter types in later development. This differential accumulation of UGT85A19 is associated with more than three-fold greater mandelonitrile glucosyltransferase activity in bitter kernels compared with non-bitter types, and transcriptional regulation was demonstrated using quantitative-PCR analysis. UGT85A19 and its encoding transcript were most concentrated in the testa (seed coat) of the kernel compared with the embryo, and prunasin and amygdalin were differentially compartmentalised in these tissues. Prunasin was confined to the testa and amygdalin was confined to the embryo. These results are consistent with the seed coat being an important site of synthesis of prunasin as a precursor of amygdalin accumulation in the kernel. The presence of UGT85A19 in the kernel and other tissues of both bitter and non-bitter types indicates that its expression is unlikely to be a control point for amygdalin accumulation and suggests additional roles for the enzyme in almond metabolism.

Erratum to: A seed coat cyanohydrin glucosyltransferase is associated with bitterness in almond (Prunus dulcis) kernels.

The secondary metabolite amygdalin is a cyanogenic diglucoside that at high concentrations is associated with intense bitterness in seeds of the Rosaceae, including kernels of almond (Prunus dulcis (Mill.), syn. Prunus amygdalus D. A. Webb Batsch). Amygdalin is a glucoside of prunasin, itself a glucoside of R-mandelonitrile (a cyanohydrin). Here we report the isolation of an almond enzyme (UGT85A19) that stereo-selectively glucosylates R-mandelonitrile to produce prunasin. In a survey of developing kernels from seven bitter and 11 non-bitter genotypes with polyclonal antibody raised to UGT85A19, the enzyme was found to accumulate to higher levels in the bitter types in later development. This differential accumulation of UGT85A19 is associated with more than three-fold greater mandelonitrile glucosyltransferase activity in bitter kernels compared with non-bitter types, and transcriptional regulation was demonstrated using quantitative-PCR analysis. UGT85A19 and its encoding transcript were most concentrated in the testa (seed coat) of the kernel compared with the embryo, and prunasin and amygdalin were differentially compartmentalised in these tissues. Prunasin was confined to the testa and amygdalin was confined to the embryo. These results are consistent with the seed coat being an important site of synthesis of prunasin as a precursor of amygdalin accumulation in the kernel. The presence of UGT85A19 in the kernel and other tissues of both bitter and non-bitter types indicates that its expression is unlikely to be a control point for amygdalin accumulation and suggests additional roles for the enzyme in almond metabolism.