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Meta-Analysis of Influence of Diversity of Parental Forms on Heterosis and Specific Combining Ability of Their Hybrids

2023, Bocianowski, Jan, Nowosad, Kamila, Bujak, Henryk

An important stage in any breeding activity is selection of suitable individuals for further breeding. Thus, the main goal of breeders becomes such a selection of parental forms that leads to the consolidation and maximization of the value of traits of significant utility and economic importance. Heterosis and specific combining ability are very important parameters in plant and animal breeding. The ability to predict their value and relevance could significantly shorten the breeding process. One way to predict the effects of heterosis and specific combining ability is to select parental forms for crosses. This selection can be made on the basis of variation in parental forms. An analysis was made of publicly available data that contain information about the effects of heterosis, the effects of specific combining ability, and phenotypic and genetic diversity of parental forms. Preliminary studies show that the best approach for obtaining favorable hybrids would be selection of parental forms that are very genetically diverse while being phenotypically equal.

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Analysis of Physio-Biochemical Responses and Expressional Profiling Antioxidant-Related Genes in Some Neglected Aegilops Species under Salinity Stress

2023, Jamshidi, Bita, Pour-Aboughadareh, Alireza, Bocianowski, Jan, Shooshtari, Lia, Bujak, Henryk, Türkoğlu, Aras, Nowosad, Kamila

Wild common wheat species represent a significant pool of resistance genes to various environmental stresses. In this study, we examined several physiological traits and the activity of three antioxidant enzymes—namely, catalase (CAT), superoxide dismutase (SOD), and ascorbate peroxidase (APX)—as well as the expression patterns of their encoding genes in three neglected Aegilops species with alien genomes (including Ae. triuncialis (UUCC-genome), Ae. neglecta (UUMM-genome) and Ae. umbellulata (UU-genome)) under two control (0 mM NaCl) and salinity (250 mM NaCl) conditions. The results of the analysis of variance (ANOVA) showed highly significant effects of salinity stress, accessions, and their interaction on most physio-biochemical traits, root and shoot dry biomasses, and antioxidant-related gene expression level. As a result of comparison between Aegilops species and a bread wheat cultivar (cv. Narin as a salt-tolerant reference variety), Ae. triuncialis responded well to salinity stress, maintaining both ionic homeostasis capability and biochemical ability. Moreover, transcriptional data revealed the prominence of Ae. triuncialis over other Aegilops species and salt-tolerant bread wheat [cv. Narin] in terms of the level of expression of antioxidant genes (APX, SOD, and CAT). This result was further supported by a biplot rendered based on principal component analysis (PCA), where this wild relative showed a positive association with most measured traits under salinity stress. Moreover, we speculate that this accession can be subjected to physiological and molecular studies, and that it can provide new insights into the use of the alien genomes in future wheat breeding programs.

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Revealing Genetic Diversity and Population Structure in Türkiye’s Wheat Germplasm Using iPBS-Retrotransposon Markers

2024, Demirel, Fatih, Yıldırım, Bünyamin, Eren, Barış, Demirel, Serap, Türkoğlu, Aras, Haliloğlu, Kamil, Nowosad, Kamila, Bujak, Henryk, Bocianowski, Jan

Investigating the genetic diversity and population structure of wheat germplasm is crucial for understanding the underlying variability essential for breeding programs and germplasm preservation. This research aims to contribute novel insights with respect to the genetic makeup and relationships among these wheat genotypes, shedding light on the diversity present within the Turkish wheat germplasm. In this study, iPBS-retrotransposon markers were employed to analyze 58 wheat genotypes, encompassing 54 landraces and 4 cultivars sourced from Türkiye. These markers serve as genetic indicators that can be used to evaluate genetic variation, build genealogical trees, and comprehend evolutionary connections. The PCR products were visualized on agarose gel, and bands were scored as present/absent. The ten iPBS primers collectively yielded an average of 16.3 alleles, generating a total of 163 polymorphic bands. The number of alleles produced by individual markers ranged from 4 (iPBS-2386) to 29 (iPBS-2219). The genetic parameters were calculated using the popgen and powermarker programs. The genetic relationships and population structures were assessed using the ntsys and structure programs. Polymorphism information content (PIC) per marker varied from 0.13 (iPBS-2390) to 0.29 (iPBS-2386), with an average value of 0.22. Shannon’s information index (I) was calculated as 1.48, while the number of effective alleles (Ne) and Nei’s genetic diversity (H) were determined to be 0.26 and 0.31, respectively. Genotype numbers 3 (Triticum dicoccum) and 10 (Triticum monococcum) exhibited the maximum genetic distance of 0.1292, signifying the highest genetic disparity. Population structure analysis revealed the segregation of genotypes into three distinct subpopulations. Notably, a substantial portion of genotypes clustered within populations correlated with the wheat species. This population structure result was consistent with the categorization of genotypes based on wheat species. The comprehensive assessment revealed noteworthy insights with respect to allele distribution, polymorphism content, and population differentiation, offering valuable implications for wheat breeding strategies and germplasm conservation efforts. In addition, the iPBS markers and wheat genotypes employed in this study hold significant potential for applications in wheat breeding research and germplasm preservation.

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Prediction of Grain Yield in Wheat by CHAID and MARS Algorithms Analyses

2023, Demirel, Fatih, Eren, Baris, Yilmaz, Abdurrahim, Türkoğlu, Aras, Haliloğlu, Kamil, Niedbała, Gniewko, Bujak, Henryk, Jamshidi, Bita, Pour-Aboughadareh, Alireza, Bocianowski, Jan, Nowosad, Kamila

Genetic information obtained from ancestral species of wheat and other registered wheat has brought about critical research, especially in wheat breeding, and shown great potential for the development of advanced breeding techniques. The purpose of this study was to determine correlations between some morphological traits of various wheat (Triticum spp.) species and to demonstrate the application of MARS and CHAID algorithms to wheat-derived data sets. Relationships among several morphological traits of wheat were investigated using a total of 26 different wheat genotypes. MARS and CHAID data mining methods were compared for grain yield prediction from different traits using cross-validation. In addition, an optimal CHAID tree structure with minimum RMSE was obtained and cross-validated with nine terminal nodes. Based on the smallest RMSE of the cross-validation, the eight-element MARS model was found to be the best model for grain yield prediction. The MARS algorithm proved superior to CHAID in grain yield prediction and accounted for 95.7% of the variation in grain yield among wheats. CHAID and MARS analyses on wheat grain yield were performed for the first time in this research. In this context, we showed how MARS and CHAID algorithms can help wheat breeders describe complex interaction effects more precisely. With the data mining methodology demonstrated in this study, breeders can predict which wheat traits are beneficial for increasing grain yield. The adaption of MARS and CHAID algorithms should benefit breeding research.

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Investigation of the Influence of Polyamines on Mature Embryo Culture and DNA Methylation of Wheat (Triticum aestivum L.) Using the Machine Learning Algorithm Method

2023, Eren, Barış, Türkoğlu, Aras, Haliloğlu, Kamil, Demirel, Fatih, Nowosad, Kamila, Özkan, Güller, Niedbała, Gniewko, Pour-Aboughadareh, Alireza, Bujak, Henryk, Bocianowski, Jan

Numerous factors can impact the efficiency of callus formation and in vitro regeneration in wheat cultures through the introduction of exogenous polyamines (PAs). The present study aimed to investigate in vitro plant regeneration and DNA methylation patterns utilizing the inter-primer binding site (iPBS) retrotransposon and coupled restriction enzyme digestion–iPBS (CRED–iPBS) methods in wheat. This investigation involved the application of distinct types of PAs (Put: putrescine, Spd: spermidine, and Spm: spermine) at varying concentrations (0, 0.5, 1, and 1.5 mM). The subsequent outcomes were subjected to predictive modeling using diverse machine learning (ML) algorithms. Based on the specific polyamine type and concentration utilized, the results indicated that 1 mM Put and Spd were the most favorable PAs for supporting endosperm-associated mature embryos. Employing an epigenetic approach, Put at concentrations of 0.5 and 1.5 mM exhibited the highest levels of genomic template stability (GTS) (73.9%). Elevated Spd levels correlated with DNA hypermethylation while reduced Spm levels were linked to DNA hypomethylation. The in vitro and epigenetic characteristics were predicted using ML techniques such as the support vector machine (SVM), extreme gradient boosting (XGBoost), and random forest (RF) models. These models were employed to establish relationships between input variables (PAs, concentration, GTS rates, Msp I polymorphism, and Hpa II polymorphism) and output parameters (in vitro measurements). This comparative analysis aimed to evaluate the performance of the models and interpret the generated data. The outcomes demonstrated that the XGBoost method exhibited the highest performance scores for callus induction (CI%), regeneration efficiency (RE), and the number of plantlets (NP), with R2 scores explaining 38.3%, 73.8%, and 85.3% of the variances, respectively. Additionally, the RF algorithm explained 41.5% of the total variance and showcased superior efficacy in terms of embryogenic callus induction (ECI%). Furthermore, the SVM model, which provided the most robust statistics for responding embryogenic calluses (RECs%), yielded an R2 value of 84.1%, signifying its ability to account for a substantial portion of the total variance present in the data. In summary, this study exemplifies the application of diverse ML models to the cultivation of mature wheat embryos in the presence of various exogenous PAs and concentrations. Additionally, it explores the impact of polymorphic variations in the CRED–iPBS profile and DNA methylation on epigenetic changes, thereby contributing to a comprehensive understanding of these regulatory mechanisms.