Advances in Rootstock Breeding of Nut Trees: Objectives and Strategies.

The production and consumption of nuts are increasing in the world due to strong economic returns and the nutritional value of their products. With the increasing role and importance given to nuts (i.e., walnuts, hazelnut, pistachio, pecan, almond) in a balanced and healthy diet and their benefits to human health, breeding of the nuts species has also been stepped up. Most recent fruit breeding programs have focused on scion genetic improvement. However, the use of locally adapted grafted rootstocks also enhanced the productivity and quality of tree fruit crops. Grafting is an ancient horticultural practice used in nut crops to manipulate scion phenotype and productivity and overcome biotic and abiotic stresses. There are complex rootstock breeding objectives and physiological and molecular aspects of rootstock-scion interactions in nut crops. In this review, we provide an overview of these, considering the mechanisms involved in nutrient and water uptake, regulation of phytohormones, and rootstock influences on the scion molecular processes, including long-distance gene silencing and trans-grafting. Understanding the mechanisms resulting from rootstock × scion × environmental interactions will contribute to developing new rootstocks with resilience in the face of climate change, but also of the multitude of diseases and pests.

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.

Genome-wide patterns of population structure and association mapping of nut-related traits in Persian walnut populations from Iran using the Axiom J. regia 700K SNP array.

Persian plateau (including Iran) is considered as one of the primary centers of origin of walnut. Sampling walnut trees originating from this arena and exploiting the capabilities of next-generation sequencing (NGS) can provide new insights into the degree of genetic variation across the walnut genome. The present study aimed to explore the population structure and genomic variation of an Iranian collection of Persian walnut (Juglans regia L.) and identify loci underlying the variation in nut and kernel related traits using the new Axiom J. regia 700K SNP genotyping array. We genotyped a diversity panel including 95 walnut genotypes from eight Iranian provinces with a variety of climate zones. A majority of the SNPs (323,273, 53.03%) fell into the "Poly High Resolution" class of polymorphisms, which includes the highest quality variants. Genetic structure assessment, using several approaches, divided the Iranian walnut panel into four principal clusters, reflecting their geographic partitioning. We observed high genetic variation across all of the populations (HO = 0.34 and HE = 0.38). The overall level of genetic differentiation among populations was moderate (FST = 0.07). However, the Semnan population showed high divergence from the other Iranian populations (on average FST = 0.12), most likely due to its geographical isolation. Based on parentage analysis, the level of relatedness was very low among the Iranian walnuts examined, reflecting the geographical distance between the Iranian provinces considered in our study. Finally, we performed a genome-wide association study (GWAS), identifying 55 SNPs significantly associated with nut and kernel-related traits. In conclusion, by applying the novel Axiom J. regia 700K SNP array we uncovered new unexplored genetic diversity and identified significant marker-trait associations for nut-related traits in Persian walnut that will be useful for future breeding programs in Iran and other countries.

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.

Molecular and physiological responses of Iranian Perennial ryegrass as affected by Trinexapac ethyl, Paclobutrazol and Abscisic acid under drought stress.

Drought stress is the major limiting factor which affects turfgrass management in area with restricted rainfall or irrigation water supply. Trinexapac ethyl (TE), Paclobutrazol (PAC) and Abscisic acid (ABA) are three plant growth regulators (PGRs) that are commonly used on turf species for increasing their tolerance to different environmental stresses such as drought. However, little is known about the impact of PGRs on stress tolerance of Iranian Perennial ryegrass (Lolium perenne). The present study was conducted to examine the visual and physiological changes of Iranian Perennial ryegrass in response to foliar application of TE, PAC, and ABA under drought stress conditions. According to the obtained results, application of all three PGRs considerably restored visual quality of drought exposed plants. TE treatment increased chlorophyll content, proline content and resulted in less malondialdehyde (MDA) in drought stressed Perennial ryegrass. Application of all PGRs enhanced the relative water content (RWC) and decreased the electrolyte leakage (EL) and Hydrogen peroxide contents (H2O2 content) of plants under drought stress, though the impact of TE was more pronounced. Throughout the experiment, TE- and ABA-treated plant showed greater soluble sugar (SSC) content as compared to the control. Antioxidant enzymes activities of drought exposed plants were considerably increased by PGRs application. Catalase (CAT) and Superoxide dismutase (SOD) activities were greater in TE-treated grasses followed by PAC-treated plants. Ascorbate peroxidase (APX) and peroxidase (POD) activities were significantly enhanced by TE and ABA application. The results of the present investigation suggest that application of TE, ABA and PAC enhances drought tolerance in Perennial ryegrass. TE, PAC and ABA were all effective in mitigating physiological damages resulting from drought stress, however the beneficial effects of TE were more pronounced. The result obtained of real time-PCR suggested that regulation of CAT, APX, POD and SOD genes expression at translational levels highly depended on the application of TE, PAC and ABA. Also, the results showed that deletion mutation in SOD and POD genes were not leading to enzyme inactivation.