Effects of mammalian sex hormones on in vitro organogenesis of common bean (Phaseolus vulgaris L.)

Haliloğlu, Kamil; Türkoğlu, Aras; Balpınar, Özge; Öztürk, Halil İbrahim; Özkan, Güller; Poczai, Péter

doi:10.1038/s41598-023-30090-4

Cited by 4 publications

(6 citation statements)

References 24 publications

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“…Our result indicated that the highest mean value of the types of explants undergoing morphogenesis was obtained in plumule but the lowest was obtained in the radicle explant. Our results con rm with ndings of Haliloğlu et al (2023). The plumule explant divides actively and rapidly in the presence of exogenous MSH in the medium with result of generating multiple root and shoots.…”

Section: Discussionsupporting

confidence: 90%

“…For this reason, it is important to conduct studies on the use of MSHs on plants and to reveal the effects of these hormones on plant growth in vitro. Previously, MSHs and their concentrations have been developed for in vitro grown of some plants, such as wheat (Turkoglu 2022) and bean (Haliloğlu et al 2023).…”

Section: Introductionmentioning

confidence: 99%

“…Whereas Janeczko et al(Janeczko et al 2002) studied the effect of mammalian sex hormones on the development of immature embryos and calli isolated from winter wheat. Also,Haliloğlu et al (2023) found that callus development was mainly observed in embryo explants treated with testosterone in bean plants.Different MSH and concentrations were used in the study. Selection of suitable hormone and concentration is of chief signi cance to produce normal root and shoots(Aasim et al 2013).…”

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confidence: 98%

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Understanding the effects of mammalian sex hormones in the in vitro regeneration of Chickpea (Cicer arietinum L.) using machine learning techniques

Haliloğlu,

Turkoglu,

Pour-Aboughadareh

et al. 2023

Preprint

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The purpose of this study was to determine the effect of certain mammalian sex hormones (MSH) as an alternative to synthetic hormones in chickpea (Cicer arietinum L.) tissue culture using mathematical models. In this research four different types of explants, including embryo, hypocotyl, plumule and radicle, were treated with four different concentrations (0, 0.1, 0.001 and 0.00001 µM) of four mammalian sex hormones (17β-estradiol, estrogen, progesterone and testosterone). It was found that different explants, MSH and their concentrations had a significant effect on the formation of morphogenesis. The type of explant significantly affected shoot and root formation, and the effect of MSH concentration on root formation. Based on the results of the study, it was concluded that it would be expedient to use plumula as a source of explants in chickpea tissue culture. As a result, the use of 0.001 µM progesterone showed positive effects in chickpea in vitro culture medium. The XGBoost model outperformed in predicting all variables based on high R-squared values, low mean square error, and mean absolute deviation. Sensitivity analysis within the XGBoost model revealed that plumule was the most influential variable for predicting the number of explants undergoing morphogenesis (40.29%) and the number of shoots–forming explants (33.83%), while concentration 0.001 µM played a significant role in determining the number of roots–forming explants (47.49%). Consequently, it was shown that mammalian sex hormones have the potential for use in the in vitro cultivation of chickpeas. Additionally, the utilization of the XGBoost model was found to be effective in forecasting outcomes and facilitating optimization in this context.

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Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 98%

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Understanding the effects of mammalian sex hormones in the in vitro regeneration of Chickpea (Cicer arietinum L.) using machine learning techniques

Haliloğlu,

Turkoglu,

Pour-Aboughadareh

et al. 2023

Preprint

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“…In vitro studies on plants are vital for agriculture, plant science, and biotechnology, enhancing cultivation, biodiversity conservation, and sustainability [20][21][22][23][24]. Developing species-specific tissue culture methods is essential due to variations in plant species [24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Usage of Machine Learning Algorithms for Establishing an Effective Protocol for the In Vitro Micropropagation Ability of Black Chokeberry (Aronia melanocarpa (Michx.) Elliott)

Demirel,

Uğur,

Popescu

et al. 2023

Horticulturae

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The primary objective of this research was to ascertain the optimal circumstances for the successful growth of black chokeberry (Aronia melanocarpa (Michx.) Elliott) using tissue culture techniques. Additionally, the study aimed to explore the potential use of machine learning algorithms in this context. The present research investigated a range of in vitro parameters such as total number of roots (TNR), longest root length (LRL), average root length (ARL), number of main roots (NMR), number of siblings (NS), shoot length (SL), shoot diameter (SD), leaf width (LW), and leaf length (LL) for Aronia explants cultivated in different media (Murashige and Skoog (MS) and woody plant medium (WPM)) with different concentrations (0, 0.5, 1, 1.5, and 2 mg L−1) of indole-3-butyric acid (IBA). The study showed that IBA hormone levels may affect WPM properties, affecting the LRL and ARL variables. Aronia explant media treated with 2 mg L−1 IBA had the greatest TNR, NMR, NS, SL, and SD values; 31.67 pieces, 2.37 pieces, 5.25 pieces, 66.60 mm, and 2.59 mm, in that order. However, Aronia explants treated with 1 mg L−1 IBA had the highest LW (9.10 mm) and LL (14.58 mm) values. Finally, Aronia explants containing 0.5 mg L−1 IBA had the greatest LRL (89.10 mm) and ARL (57.57 mm) values. In general, the results observed (TNR, LRL, ARL, NMR, NS, SL, SD, LW, and LL) indicate that Aronia explants exhibit superior growth and development in WPM (25.68 pieces, 68.10 mm, 51.64 mm, 2.17 pieces, 4.33 pieces, 57.95 mm, 2.49 mm, 8.08 mm, and 14.26 mm, respectively) as opposed to MS medium (20.27 pieces, 59.92 mm, 47.25 mm, 1.83 pieces, 3.57 pieces, 49.34 mm, 2.13 mm, 6.99 mm, and 12.21 mm, respectively). In the context of the in vitro culturing of Aronia explants utilizing MS medium and WPM, an analysis of machine learning models revealed that the XGBoost and SVM models perform better than the RF, KNN, and GP models when it comes to making predictions about those variables. In particular, the XGBoost model stood out due to the fact that it had the greatest R-squared value, and showed higher predictive ability in terms of properly forecasting values in comparison to actual outcomes. The findings of a linear regression (LR) analysis were used in order to conduct an efficacy study of the XGBoost model. The LR results especially confirmed the findings for the SD, NS, and NMR variables, whose R-squared values were more than 0.7. This demonstrates the extraordinary accuracy that XGboost has in predicting these particular variables. As a consequence of this, it is anticipated that it will be beneficial to make use of the XGboost model in the dosage optimization and estimation of in vitro parameters in micropropagation studies of the Aronia plant for further scientific investigation.

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“…The number of studies on the existence of MSHs in plants has increased, prompting the need to investigate the role these hormones play in plant life [9]. Recent studies have focused on evaluating the effects of exogenous application of these compounds on plant growth and development, as well as their tolerance to various abiotic and biotic stimuli and their metabolic mechanism of action [10,11].…”

Section: Introductionmentioning

confidence: 99%

Mammalian Sex Hormones as Steroid-Structured Compounds in Wheat Seedling: Template of the Cytosine Methylation Alteration and Retrotransposon Polymorphisms with iPBS and CRED-iBPS Techniques

Demirel,

Türkoğlu,

Haliloğlu

et al. 2023

Applied Sciences

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Phytohormones are chemical compounds found naturally in plants that have a significant effect on their growth and development. The increase in research on the occurrence of mammalian sex hormones (MSHs) in plants has prompted the need to investigate the functions performed by these hormones in plant biology. In the present study, we investigated the effects of MSHs on DNA damage and DNA methylation of wheat (Triticum aestivum L.) during the seedling growth stage, using the CRED-iPBS (coupled restriction enzyme digestion/inter primer binding site) assay and iPBS analysis to determine DNA methylation status. Exogenous treatment with four MSHs (17-β-estradiol, estrogen, progesterone, and testosterone) was carried out at four different concentrations (0, 0.05, 0.5, and 5 µM). The highest genomic template stability (GTS) value (80%) was observed for 5 µM 17-β-estradiol, 0.5 µM testosterone, and 0.05 µM estrogen, while the lowest value (70.7%) was observed for 5 µM progesterone and 0.5 µM estrogen. The results of the CRED-iPBS analysis conducted on MspI indicate that the 0.05 µM estrogen-treated group had the highest polymorphism value of 40%, while the 5 µM progesterone-treated group had the lowest value of 20%. For HpaII, treatment with 0.5 µM 17-β-estradiol had the highest polymorphism value of 33.3%, while the group treated with 0.05 µM 17-β-estradiol and 0.05 µM progesterone had the lowest value of 19.4%. In conclusion, MSH treatments altered the stability of the genomic template of wheat plants and affected the cytosine methylation status at the seedling growth stage. Upon comprehensive examination of the results, it was seen that the employed methodology successfully detected alterations in cytosine methylation of genomic DNA (gDNA), as well as changes in the pattern of genomic instability.

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Effects of mammalian sex hormones on in vitro organogenesis of common bean (Phaseolus vulgaris L.)

Cited by 4 publications

References 24 publications

Understanding the effects of mammalian sex hormones in the in vitro regeneration of Chickpea (Cicer arietinum L.) using machine learning techniques

Understanding the effects of mammalian sex hormones in the in vitro regeneration of Chickpea (Cicer arietinum L.) using machine learning techniques

Usage of Machine Learning Algorithms for Establishing an Effective Protocol for the In Vitro Micropropagation Ability of Black Chokeberry (Aronia melanocarpa (Michx.) Elliott)

Mammalian Sex Hormones as Steroid-Structured Compounds in Wheat Seedling: Template of the Cytosine Methylation Alteration and Retrotransposon Polymorphisms with iPBS and CRED-iBPS Techniques

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