Skip to Content
You are currently on the new version of our website. Access the old version .
MDPIMDPI

Advanced

AgronomyAgronomy
PDF
  • Editor’s Choice
  • Review
  • Open Access

19 June 2025

28 Pages

Somaclonal Variation and Clonal Fidelity in Commercial Micropropagation: Challenges and Perspectives

,
and
1
St. John’s Research and Development Centre, Agriculture and Agri-Food Canada, St. John’s, NL A1E 0B2, Canada
2
Department of Biology, Memorial University of Newfoundland, St. John’s, NL A1C 5S7, Canada
*
Author to whom correspondence should be addressed.
Agronomy2025, 15(6), 1489;https://doi.org/10.3390/agronomy15061489
This article belongs to the Section Plant-Crop Biology and Biochemistry
Version Notes
Order Reprints

Abstract

Plant tissue culture has been recognized as an essential technology in plant science research. This process is widely used to regenerate and conserve phenotypically and genetically identical plant resources. The advancements in tissue culture methods have become a feasible option for the micropropagation of plants at the commercial level. The success of commercial micropropagation necessitates genetic stability among regenerated plants. Sometimes, in vitro-grown plants show genetic and epigenetic alterations due to stressful artificial culture conditions, media compositions, and explant types. As a result, it is essential to ensure genetic stability among tissue culture-derived plantlets at a very early stage. Somaclonal variations can be detected by phenotypic assessment, cytogenetic, DNA-based molecular markers, bisulfite sequencing, and RNA sequencing. This review aims to describe the causes behind somaclonal variation, the selection of somaclonal variants, and their uses in crop and plant improvement at the commercial level. This study discusses the optimization processes of undesirable genetic and epigenetic variation among micropropagated plants and their application in global horticulture, agriculture, and forestry.

1. Introduction

The global demand for high-quality plant material for food and medicine is constantly rising owing to the growing global population [1]. Although conventional plant propagation methods, such as budding, grafting, cuttings, and seed propagation, act as the fundamental of the plant production system [1,2]. These methods often fail to fulfill the current and expected demands of efficient and cost-effective plant propagation systems due to insufficient agricultural land, requiring a long time to obtain progenies, dependence on seasons, and limitations in the consistency of the resulting plant material [3]. Nowadays, plant tissue culture is a powerful tool for reproducing identical plants of a genotype from a single plant part without dependence on geographical and climatic factors [4]. Thus, plant tissue culture is an alternative method of conventional vegetative propagation [4,5]. Micropropagation, initially applied to ornamental plants [5], has expanded to include various crops, fruit plants, vegetables, trees, and medicinal and aromatic plants, and is now a multibillion-dollar industry worldwide [6].
Tissue-based propagation, commonly known as micropropagation, is a rapid and efficient method that can be achieved in limited space [7]. In this process, a small segment of plant collected from selected plant species, known as explant, such as leaf sections, shoot tips, nodal segments, and root tips, are aseptically cultured on an artificial nutrient-rich medium. In the micropropagation process, plants can regenerate via organogenesis and somatic embryogenesis (SE) [8]. Organogenesis is generally classified into two distinct pathways: direct organogenesis, in which shoot buds are formed directly from the explant tissue, and indirect organogenesis, where shoot regeneration occurs through an intermediate callus formation phase [9]. Consequently, micropropagation has noticeably increased the mass production of genetically uniform and high-quality plant materials, contributing significantly to agriculture, horticulture, and forestry. However, despite these advancements, a critical drawback of in vitro propagation is the occurrence of somaclonal variation—heritable genetic and epigenetic modifications induced by the artificial conditions of tissue culture. Such variations can threaten clonal fidelity, deteriorate crop performance and quality, and complicate regulatory approval and market acceptance, especially in commercially sensitive crop systems [6,8].

2. Clonal Fidelity and Commercial Micropropagation

Micropropagation is a highly efficient method for producing genetically identical plant materials [9,10]. The genetically identical individuals ensure uniformity in yield, growth, and quality, which is essential for commercial consistency. This uniformity simplifies cultivation, reduces production costs, and enhances market appeal. Moreover, it allows rapid multiplication of elite genotypes while preserving desirable traits [10]. The first commercial micropropagation technology started with orchids in the 1970s [11]; it was later observed in numerous fruit plants, trees, spices, ornamentals, and crops [12]. Between the 1970s and 1980s, the commercial micropropagation process experienced significant growth due to the rise in commercial laboratories involved in these activities [12]. Micropropagation is an effective biotechnology technique used in the horticulture, forestry, and agriculture sectors that allows for the rapid and large-scale reproduction of traits that are true-to-type, disease-free, and genetically superior varieties [12,13]. Clonal fidelity—the capacity of a clone to maintain its genetic identity over time—is vital in in vitro propagation because the success of this process depends on producing large numbers of genetically identical, true-to-type plants from a small segment of a donor plant [14]. For example, in bananas, the clonal fidelity of micropropagated plants via axillary buds was observed when cultured under cytokinin-rich conditions [15]. Similarly, confirmed genetic uniformity in bioreactor-derived strawberry (Fragaria × ananassa) plants and correlated clonal fidelity with enhanced anthocyanin content and antioxidant activity compared to conventionally propagated plants [16]. Kundu et al. developed a high-fidelity somatic embryogenesis protocol in Vaccinium vitis-idaea (lingonberry). This study revealed that the regenerated plants retained genetic uniformity while also showing increased concentrations of flavonoids, anthocyanins, and antioxidant activity in comparison to the original donor plants [17]. In apple, 92–100% genetic similarity was observed in apple rootstock EMLA 111 [18]. Genetically unstable, off-type micropropagated plants are a primary cause of financial loss, especially in high-demand crops where uniformity and predictability are essential [19]. For example, variations in color, shape, and size can drastically reduce the market value of commercially important plant species. Growers face substantial losses when dealing with poor-quality, low-yield plants [19]. A further complication arises with perennial plants like woody ornamental plants, woody trees, medicinal plants, and fruit trees, where the effects of genetic instability may not become visible until several years after planting, leading to delayed losses after considerable resources have already been invested [19,20]. These regenerated plants may display a range of undesirable phenotypic variations, including sterility, precocious flowering, altered internodal length, leaf abnormalities such as albino or chlorotic leaves, increased salt resistance, and changes in fruit or flower color [21]. Additionally, somaclonal variation-induced genetic changes threaten plant health and the production of disease-resistant, uniform plant material [21]. This genetic instability can increase vulnerability to insect pests, pathogens, and environmental stresses, significantly reducing crop productivity and increasing disease outbreaks. To manage these risks, growers must invest heavily in advanced disease and pest management systems [22]. However, the costs associated with these disease control measures in affected micropropagated crops and plant species further diminish the economic advantages of micropropagation [23].

3. Somaclonal Variation in Micropropagated Plants

Although micropropagation offers numerous benefits, prolonged stress conditions during growth may sometimes lead to genetic instability in micropropagated plants [24]. Larkin and Scowcroft first introduced the term “Somaclonal variation” to describe the variation observed in plants regenerated through tissue or cell culture [25]. Somaclonal variation is unpredictable and uncontrollable, and most of the variation has no direct agronomic or commercial significance [26]. However, other names such as protoclonal, gametoclonal, and mericlonal variation are often used to describe variants from protoplast, anther, and meristem cultures, respectively [27]. Somaclonal variations result from the genetic and epigenetic changes that can occur in tissue culture-induced regenerated plants [28]. Genetic variation remains stable throughout the sexual cycle or repeated asexual propagation, whereas epigenetic variation may be unstable even during asexual propagation [29]. The presence of unexpected, uncontrolled, and spontaneous changes during the tissue culture is undesired in commercial micropropagation [30]. The types of explants, the number of subcultures, plant growth regulators, and the regeneration pathway are responsible for somaclonal variation [31,32,33,34]. However, somaclonal variation is considered as a limitation in micropropagation technique, it also offers valuable opportunities for producing novel disease-resistant and high-yielding variants, namely rice [35], tomatoes [36], eggplants [37], cucumber [38], carrot [39], bananas [40], and grape [41]. There are numerous techniques for determining and defining somaclonal variants, primarily based on various morphological features, numerical and structural variations in the chromosomes, and biochemical and molecular DNA markers. Understanding somaclonal variation is essential for optimizing micropropagation protocols and producing true-to-type plants. That can ensure the economic viability and quality of this valuable technology [42].

3.1. Mechanisms of Somaclonal Variation

Somaclonal variation is a complicated phenomenon, and it remains difficult to fully understand the ways in which genetic and epigenetic mechanisms interact within in vitro culture environments (Figure 1) [27,28]. A significant factor contributing to this variability is oxidative stress, which is frequently induced by different parameters such as the composition and pH of the medium, concentrations of plant growth regulators, hormonal imbalances, and fluctuations in temperature and humidity. These adverse conditions lead to the overproduction of reactive oxygen species (ROS), which are known to cause a variety of molecular disruptions, including alterations in DNA methylation patterns, chromosomal aberrations, strand breakages, and point mutations [43]. Consequently, the degree of somaclonal variation is closely associated with the specific conditions of the in vitro environment, emphasizing the necessity of developing and maintaining optimized, tightly controlled culture protocols to safeguard genetic integrity and clonal uniformity.
Figure 1. Schematic overview of tissue-culture induced somaclonal variations.

3.1.1. Genetic Mechanisms

One of the primary contributors to somaclonal variation involves genetic mechanisms, which include modifications at the DNA level that result in permanent genetic [43,44]. These genetic alterations can take several forms, including insertions, deletions, point mutations, chromosomal rearrangements, and ploidy level changes (Figure 2) [44]. Chromosomal rearrangements play a significant role in generating genetic variability. Point mutations alter individual nucleotides within gene coding sequences, which can subsequently change the structure and function of the proteins they encode [45]. Additionally, translocations, insertions, and deletions involving specific DNA regions can disrupt gene function and expression, further contributing to somaclonal variation [46]. Such chromosomal structural abnormalities have been widely reported in various plant species. In bread wheat, Karp et al. observed that its chromosome number increased when grown in high concentrations of 2,4-D (2,4-dichlorophenoxyacetic acid) [47]. In lily, chromosomal variation was induced during prolonged callus culture on MS medium with 1 mg/L picloram. The extended exposure to auxin led to polyploidization, resulting in tetraploid plantlets. Lily [48], demonstrating the prevalence and importance of these genetic mechanisms in plant tissue culture systems.
Figure 2. Mechanisms of genetic modification during the micropropagation process.

3.1.2. Epigenetic Mechanisms

Epigenetics involves studying heritable changes in gene activity that occur without alterations to the underlying DNA sequence [49]. In vitro conditions can regulate these epigenetic modifications in plant tissue culture systems, which profoundly influence plant phenotype and contribute to somaclonal variation [50]. Three major types of epigenetic changes have been identified: DNA methylation, histone modifications, and small RNA-mediated regulation. DNA methylation involves the covalent attachment of methyl groups to cytosine nucleotides, primarily resulting in three types of methylated bases: 5-methylcytosine (5 mC), N6-methyladenine (6 mA), and N4-methylcytosine (4 mC) [51]. The tissue culture environment influences methylation patterns, frequently causing hypermethylation or hypomethylation in specific genomic regions, which can result in somaclonal variation [52]. In addition to DNA methylation, histone modifications also play a significant role in regulating gene expression. Histone proteins, which help package and organize DNA within chromosomes, can undergo chemical modifications that alter chromatin structure and transcriptional activity, thereby contributing to phenotypic variability in micropropagated plants [52,53]. Histone modifications such as acetylation and methylation are dynamic and reversible processes, primarily controlled by distinct groups of enzymes, including families, namely histone acetyltransferases (HATs), histone deacetylases (HDACs), and histone lysine methyltransferases (HKMTs) [54]. In plants, HATs are organized into five structural subgroups, while HDACs are mainly grouped as HDA1 and HDA6—the latter being crucial for maintaining DNA methylation, suppressing transposable elements, and guiding development [55]. Two prominent histone H3 methylation marks, H3K4me3 and H3K27me3, are well-characterized for their opposing roles in gene regulation—H3K4me3 is linked to transcriptional activation, while H3K27me3 is associated with gene repression. The deposition of H3K4me3 at the 5′ regions of actively transcribed genes is facilitated by trithorax group (trxG) protein complexes in coordination with the initiating form of RNA polymerase [56,57]. Zhang et al. highlighted the widespread silencing role of H3K27me3, identifying its regulation of approximately 4400 genes in Arabidopsis, independent of small RNAs or DNA methylation pathways [58]. Another key epigenetic mechanism involves small RNA pathways, especially microRNAs (miRNAs) and small interfering RNAs (siRNAs), which play a vital role in regulating gene expression at both transcriptional and post-transcriptional levels, influencing essential processes such as cell fate in eukaryotes [59,60]. For example, in micropropagated strawberries, miR156 is notably upregulated, which facilitates juvenile leaf development and regulates developmental transitions [61]. Other studies have found that miR169a and miR169b are downregulated, whereas miR535 and miR390 are upregulated in micropropagated plants [62]. During micropropagation, these small RNA pathways can become disrupted, leading to the misregulation of critical genes and, consequently, the emergence of somaclonal [63] (Figure 3).
Figure 3. Mechanism of epigenetic modification in somaclonal variation. (‘X’—Gene A, B, C, D stopped expression, and Gene E was normally expressed).

4. Factors Affecting Somaclonal Variation

Somaclonal variation in micropropagated plants arises from a complex interaction of genetic and epigenetic alterations, influenced by several key factors such as genotype, explant type, culture conditions, and medium compositions (Table 1) [64]. Understanding these factors is crucial for commercial micropropagation to reduce somaclonal variation and maintain genetic uniformity [64,65]. Notably, plant genotypes significantly influence this process, as their susceptibility to somaclonal variation varies [65,66]. Some genotypes possess greater genetic instability in tissue culture, mainly due to differences in genome size, ploidy levels, and genes involved in DNA repair and stress response mechanisms [67]. Therefore, selecting genetically stable genotypes—those less prone to genetic changes during tissue culture—can significantly reduce somaclonal variation [68]. Additionally, the choice of explant influences genetic stability, with meristematic tissues such as axillary buds [69], shoot tips [66], and root tips [22] generally exhibiting higher genetic stability among regenerated and donor plants compared to differentiated tissues like leaves [70] and stems [71], which are more susceptible to genetic alterations during culture. This is because meristematic cells, being less differentiated and divided more slowly, are less prone to genetic and epigenetic changes. However, Hesami et al. reported that in Cannabis sativa, somaclonal variation was more pronounced in meristematic regions compared to differentiated tissues, indicating a higher susceptibility of actively dividing cells to in vitro-induced genetic and epigenetic changes [72]. Culture conditions also profoundly impact, as in vitro environments differ significantly from natural conditions, subjecting plant cells to stresses that can alter their metabolism and trigger somaclonal variation [72,73]. Factors such as media composition, hormonal imbalances, culture cycles, and physical or chemical stressors collectively contribute to this. For example, nutrient imbalances in artificial media can cause cellular stress, affect metabolism, and increase mutation rates [73]. Likewise, hormonal imbalances caused by the frequent use of high concentrations of auxins and cytokinins, though vital for shoot initiation and proliferation, can destabilize the plant’s hormonal equilibrium and trigger genetic instability [73,74]. The age and frequency of culture also matter, with somaclonal variation increasing with prolonged subculturing. In bananas, for instance, somaclonal variants significantly increased after the eighth subculture while propagation rates declined [75], and similar patterns were noted in callus cultures [76,77]. Physical and chemical factors such as light intensity, temperature, and toxic substances can induce genetic changes [78]. Mechanical disruptions during subculturing also introduce stress and potential mutations. These interrelated factors dictate the frequency and type of somaclonal variation, emphasizing the need to carefully optimize genotype selection, explant sourcing, culture media, environmental controls, and subculture protocols to minimize variability in micropropagated plant populations [79,80].
Table 1. Summary of factors affecting somaclonal variation during the micropropagation of some essential crops and plant species.

5. Detection and Assessment of Somaclonal Variation in Micropropagated Plants

5.1. Detection of Genetic Variation in Micropropagated Plants

Selecting somaclonal variants early and excluding undesirable traits are crucial challenges in successful commercial micropropagation (Table 2). However, various methods are available to detect somaclonal variation and confirm clonal fidelity in progeny. Phenotypic observation is a traditional method for identifying somaclonal variations, focusing on external traits such as plant height, leaf shape, flower color, fruit size, and overall morphology [103]. This method, though widely used, is often influenced by environmental factors, such as light, temperature, and humidity, which may obscure genetic changes and lead to missed genetic alterations [103,104]. For example, in Solanum viarum [105], variations in flower color and fruit shape were observed through phenotypic observation, though some genetic changes were not detectable due to environmental influences. While phenotypic observation is an initial step in variant selection, it is insufficient for identifying genetic changes, especially in perennial crops where the plants must be observed until maturity [105,106]. The long maturation period required to detect somaclonal variations in perennial crops renders phenotypic observation a time-consuming and expensive method [106]. Conventional cytogenetic analysis, which involves light microscopy to observe stained chromosomes, is another widely used approach. However, this method is limited when plants have small chromosomes, as their structural or numerical variations are difficult to detect and require complex and time-consuming techniques [107]. For instance, in Citrus sp., chromosome analysis revealed variations, but this approach became problematic due to the small size of the chromosomes [108]. To overcome these limitations, more advanced techniques like flow cytometry have gained popularity. This method allows for precisely counting chromosomes and determining ploidy and nuclear DNA content, providing a more sensitive, rapid, and reliable approach to detecting genetic variation [109]. For instance, flow cytometry has been used to analyze the ploidy levels of Fragaria × ananassa, and no variation was observed between meristem-derived and conventionally propagated plants [110]. In Curcuma angustifolia, the mean 2C DNA content of conventionally propagated and micropropagated plants was estimated to be 2.26 pg and 2.31 pg, respectively. Somaclonal variations were absent in both the tissue-cultured plantlets and the donor plants [111]. Additionally, physiological and biochemical tests offer faster alternatives for identifying somaclonal variants, such as analyzing the plant’s response to hormones like gibberellic acid and evaluating pigment synthesis (e.g., chlorophyll and carotenoids [112]. Gibberellic acid, known for its role in plant growth regulation, has been shown to affect somaclonal variation in crops like bananas, making it a valuable marker for early detection [113]. The synthesis of pigments such as chlorophyll is also a key indicator of genetic stability, as variations in pigment levels are often linked to genetic changes [113]. Isozyme analysis has been another approach for detecting somaclonal variation. Isozymes are distinct forms of enzymes that regulate various metabolic activities, and changes in their activity can reflect genetic variation in the plant [111,113]. This method has been beneficial in soybeans [114], beans [115], and bananas [116], where specific isozymes, such as esterase or alcohol dehydrogenase, have been studied for their role in somaclonal variation. In addition to these traditional methods, molecular markers have become a cornerstone of somaclonal variation detection [114]. These markers offer greater precision and reliability, helping to identify even subtle genetic variations that may go unnoticed by phenotypic or cytogenetic methods [116]. Techniques such as RFLP (restriction fragment length polymorphism), RAPD (random amplified polymorphic DNA), AFLP (amplified fragment length polymorphism), ISSR (inter-simple sequence repeat), SSR (simple sequence repeat), and SCoT (Start Codon Targeted) markers are widely employed to detect somaclonal variations. RFLP detects polymorphisms in DNA by analyzing changes in the length of restriction enzyme-digested fragments, providing high-resolution detection of mutations [117]. For example, RFLP analysis revealed that soybean genetic variation mainly involves two alleles per locus. Tissue cultures generated new alleles, often matching those in other cultivars, suggesting stress-induced recombinational events [118]. Likewise, in rice, RFLP analysis of rice regenerants revealed DNA polymorphisms among plants from different callus cultures and siblings from a single callus. Longer incubation periods (67 days) led to higher genetic instability, with DNA rearrangements and methylation changes observed in some regenerants, affecting both structural and housekeeping genes [76]. However, the technique’s high cost, technical complexity, and requirement for large amounts of DNA have limited its widespread use [119]. RAPD is a more straightforward and affordable method that uses random primers to amplify DNA, quickly identifying somaclonal variation [120]. In orange, RAPD analysis showed that 99% of nucellar-derived plantlets were genetically identical to the mother plant, while 20–30% of ovary-derived plantlets exhibited somaclonal variation. The explant source and method influence genetic stability during in vitro regeneration [31]. Similarly, 38.33% polymorphism in Populus was revealed by using RAPD markers, demonstrating that alterations in tissue culture medium composition can induce genetic variation [32]. RAPD and ISSR analyses confirmed somaclonal variation during indirect organogenesis in sugarcane, with true-to-type rates above 86% in varieties (Co 86,032 and Q117) [77]. Moreover, orchids cultured in basal medium without phytohormones exhibited complete genetic uniformity (100% monomorphism), while regenerated in hormone-enriched medium showed low levels of genetic polymorphism, with 1.52% (RAPD), 1.19% (ISSR), and 3.97% (SCoT) variation [81]. In banana, the genetic uniformity of the micropropagated plantlets was assessed using RAPD and ISSR markers. A total of 50 RAPD and 12 ISSR primers produced 625 distinct bands, and all markers showed uniform patterns. The band intensity histograms confirmed the monomorphic nature of the plantlets, with no genetic variation detected [15]. RAPD analysis revealed genetic variation among three somaclones in chili pepper, with traits like early flowering and increased yield components. Tissue culture-induced variants in cultivars such as Shishitou and Takanotsume suggest potential for improvement through somaclonal variation [15]. Similarly, RAPD markers were used to screen genetic stability among regenerants in peach cultivars ‘Sunhigh’ and ‘Redhaven’, revealing polymorphism in some regenerants [121]. The in vitro raised plantlets of guava were assessed for genetic fidelity using RAPD, ISSR, and SSR markers, generating 2171 scorable bands. No polymorphism was observed between the somatic embryogenesis-derived plants and their respective donor mother plants, indicating genetic uniformity [122]. Despite its simplicity and low cost, RAPD can sometimes yield inconsistent results and may not be as reproducible as other methods, such as AFLP and SSR [121,122]. AFLP is another widely used technique that involves DNA digestion with restriction enzymes, ligation of adapters, PCR amplification, and gel electrophoresis. This method provides a detailed genetic fingerprint and can detect variations arising from mutations in restriction enzyme recognition sites [123]. ISSR markers amplify regions between microsatellites and offer a powerful method for detecting genetic variations. In Cucumis sativus, ISSR markers assessed somaclonal variation in three cultivars, revealing 75% genetic similarity between regenerated plantlets and in vivo plants of the Beith Alpha cultivar. Five primers produced 34 distinct band patterns, averaging 6.8 bands per primer [123]. Likewise, the genetic integrity of in vitro and field-grown plants of Curcuma angustifolia was revealed using ISSR primers. A total of 12 ISSR primers generated a total of 1260 well-resolved bands, showing monomorphic banding patterns across all plants analyzed [124]. Moreover, the plantlets regenerated from embryo axis, half-seed, axillary meristem, and cotyledonary node explants of Cicer arietinum were morphologically like the mother plants. Genetic fidelity, assessed using Start Codon Targeted and ISSR markers, confirmed that the in vitro regenerated plants were true to type with their mother plants [125], and 95.9% genetic similarity between the plantlets and the mother plant of Ficus palmata, confirming high uniformity and true-to-type regeneration [126]. SSR markers, also known as microsatellite markers, are highly informative and can detect variations at specific loci, providing precise genetic analysis [127]. The amplified fragment corresponds to the microsatellite itself, unlike the previously described ISSR, as the primers complement the repeated motif’s flanking regions. Because of the change in the number of motif repeats, the amplified fragments vary in size [126]. In Citrus madurensis, no variability was observed in BAP or hormone-free media using this marker, while phenylurea derivatives enhanced embryogenic potential and increased somaclonal variability [70]. Similarly, SSR marker assays generated a consistent amplification profile in both tissue culture and donor control plants, validating the clonal fidelity of bioreactor-derived micropropagated plants in the Latham, Heritage, Festival, and Nova cultivars of Rubus idaeus [82]. In Cannabis sativa, SSR analysis confirmed the genetic stability of micropropagated and regenerated plants, with monomorphic banding patterns matching the mother plants [128]. Moreover, Monomorphic bands in micropropagated shoots and plants of the lingonberry hybrid H1 and cultivar Erntedank were observed using SSR markers, confirming their genetic integrity [129]. In Hevea brasiliensis, the assessment of gene stability using SSR markers showed no variation between mother plants and in vitro plantlets [88], and no variation was observed in Magnolia dealbata using this technique [87]. SCoT (Start Codon Targeted) markers, which target conserved regions near the start codon, offer a cost-effective and efficient way to detect genetic consistency. Collard and McKeill first designed this technique for detecting variation in rice genotypes; recently, this technique has been used for various plant species, e.g., using SCoT primers targeting conserved regions [130]. The PCR amplification uses a single 18-mer primer to target the highly conserved region flanking the start codon ATG in plants [7]. Somaclonal variants were identified by this method in some plant species. For example, the genetic stability of in vitro-grown plants, assessed using SCoT primers, showed a close genetic relationship to the mother plant of Malus domestica [83]. Similarly, the genetic fidelity of in vitro regenerated plants was evaluated using 12 SCoT markers, revealing a genetic similarity of 0.987 between the tissue culture-derived plants and the mother plants of Coffea arabica [71]. In Tylophora indica, the SCoT marker produced a high percentage of monomorphic bands (94%), indicating genetic fidelity and similarity between regenerated and mother plants [131]. The application of SCoT primers to detect genetic consistency has grown dramatically due to their affordability, convenience, and effectiveness. The application of these molecular techniques has become increasingly essential in the micropropagation process, enabling early detection and precise elimination of somaclonal variants. Combined with traditional methods, these tools provide a comprehensive approach to enhancing clonal fidelity and ensuring the success of commercial micropropagation [129,131]. Moreover, Quantitative PCR (qPCR) is a valuable tool for detecting somaclonal variation by analyzing the expression of key genes in some plant species. For example, in Artemisia annua, qPCR was used to examine the expression of artemisinin biosynthetic genes (ADS, CYP71AV1, DBR2, and ALDH1) in somaclonal variants ASV1 to ASV13. Among these variants, ASV12 was found to produce significantly more artemisinin than the wild type, with an even greater increase when cultivated in saline soils [132]. Adly et al. [133] used qPCR to analyze starch-synthesis-related genes in the somaclonal variant Ros 119 of Solanum tuberosum, which showed a 42% increase in fresh tuber weight and a 75% increase in starch content compared to the parent cv Lady Rosetta. The enhanced starch accumulation was linked to the upregulated expression of AGPase, SSs, GBSS, and SBE genes. These findings demonstrate the potential of somaclonal variation and qPCR as effective tools for improving starch content and genetic diversity in potato breeding programs [133]. Similarly, this method was also employed to investigate somaclonal variation in Fragaria × ananassa between the parent cultivar ‘Benihoppe’ and its mutant ‘Xiaobai’ [134]. The results revealed elevated levels of volatile compounds such as ethyl isovalerate, ethyl hexanoate, and linalool in ‘Xiaobai’, which correlated with significantly increased expression of genes including FaLOX6, FaHPL, FaADH, FaAAT, FaAAT1, FaDXS, FaMCS, and FaHDR. In contrast, the content of eugenol was higher in ‘Benihoppe’, likely due to enhanced expression of FaEGS1a, highlighting the genetic basis of somaclonal variation in volatile compound profiles and offering potential for improving strawberry quality through genetic manipulation [134].
Table 2. Compilation of genetic variation reports, their causes, and detection methods in important agricultural and horticultural species.

5.2. Detection of Epigenetic Variation in Micropropagated Plants

In plant tissue culture, stress conditions can influence the epigenetic stability and genetic makeup of plant materials, often triggering epigenetic modifications that regulate plant responses to environmental cues [29,50]. Various molecular techniques have been developed to assess epigenetic stability under these conditions, with modified AFLP-based methods like methylation-sensitive amplified polymorphism (MSAP) and methylation-sensitive AFLP (metAFLP) being widely employed (Table 3). The MSAP technique is an adaptation of AFLP, where genomic DNA is digested using methylation-sensitive restriction enzymes. The DNA is divided into two aliquots, each digested with EcoRI, which targets the GAATTC sequence and is largely unaffected by cytosine methylation, and either MspI or HpaII, isoschizomers that both recognize the CCGG sequence but differ in sensitivity to methylation [145]. Following ligation to adapters and amplification with selective primers, the resulting fragments are separated and compared to reveal methylation changes [145]. For instance, epigenetic variation, including demethylation and CG methylation, was most pronounced in the first six months of micropropagation, with these changes stabilizing thereafter. MSAP analysis identified coding sequences and LTR Gypsy retrotransposons, indicating that epigenetic modifications contribute to somaclonal variation in Allium sativum [34]. In Vaccinium vitis-idaea, through MSAP analysis, the highest methylation was observed in leaf regenerants (LC1), which also showed the highest levels of secondary metabolites. Micropropagated plants (NC1, NC2, NC3, LC1) exhibited more methylation than cutting-propagated (ED) plants, but ED plants had higher levels of secondary metabolites, indicating a trade-off between methylation and metabolite production [93]. Similarly, AFLP and MSAP analyses of 145 three-year-old somatic embryogenesis-derived plants showed extremely low polymorphism between mother plants and embryos of Coffea arabica, with ranges of 0–0.003% and 0.07–0.18%, respectively. No significant differences were found between proliferation systems for the two hybrids, and no correlation was observed between variant phenotypes and specific MSAP patterns [94]. Moreover, global DNA methylation was assessed in lowbush blueberry (Vaccinium angustifolium) wild clone QB9C and cultivar Fundy, propagated via softwood cutting (SC) and tissue culture (TC) using MSAP. The results revealed higher DNA methylation in micropropagated plants (29% for QB9C and 20% for Fundy) compared to those propagated by SC (25% for QB9C and 19% for Fundy). These findings indicate that tissue culture promotes greater methylation events, suggesting that DNA methylation may play a role in regulating plant growth and development under different propagation methods [95]. Similarly, Epigenetic diversity in six sugarcane genotype groups (commercial cultivars, S. officinarum, S. spontaneum, S. robustum, S. barberi, and Erianthus sp.) was assessed using methylation-sensitive amplification polymorphism (MSAP). A total of 1341 MSAP loci were analyzed, with 83.29% showing cytosine methylation, contributing significantly to overall genetic diversity. The genotypes were divided into two subpopulations with high differentiation, and methylated fragments were found near CpG islands and regulatory sequences, suggesting their role in stress adaptation [146]. Moreover, a study on 21 maize progeny lines from tissue cultures of inbred strain A188 revealed 39% of families had altered methylation patterns, all showing a decrease in methylation. These changes were stably inherited across two generations, suggesting demethylation as a major contributor to tissue culture-induced variation, with certain probes detecting methylation changes more frequently [100]. Similarly, the metAFLP method involves DNA digestion with Acc65I/MseI or KpnI/MseI, enzymes with differing sensitivity to methylation, and follows a protocol comparable to MSAP [147]. In winter triticale, the impact of Cu2+ and Ag+ ions and incubation time on tissue culture-induced variation and the genetic homogeneity was examined. These results showed a 51% variation, including 43% sequence variation, 5% demethylation, and 3% de novo methylation using metAFLP. The findings suggest that modifications in the culture medium affect both DNA sequence changes and methylation, offering a way to control the level of variation in tissue culture-derived regenerants [79]. Beyond AFLP-based methods, high-performance liquid chromatography (HPLC) and high-performance capillary electrophoresis (HPCE) are highly sensitive techniques for quantifying global DNA methylation levels, especially by measuring 5-methylcytosine after enzymatic digestion of genomic DNA [146,147]. For example, DNA methylation levels varied across different tissues, cultivars, and growth stages in Camellia sinensis. Higher methylation levels were observed in tender leaves (38.34%) and pistils (38.19%), while lower levels were found in capillary roots (19.45%), stamens (19.61%), and old leaves (20.70%). The methylation levels followed a saddle curve during bud growth, with the lowest point at the one-leaf and bud stage. Additionally, DNA methylation levels in adventitious buds decreased as pruning intensity increased, suggesting a link between methylation and tea plant development [148]. Another advanced method is Chromatin Immunoprecipitation (ChIP), including ChIP-chip and ChIP-seq approaches, which map interactions between DNA and specific proteins to determine methylation patterns. However, the large volume of resulting data poses challenges for analysis [149]. In Arabidopsis, this method includes a nuclear isolation step before chromatin shearing, improving DNA yield (15 g from 0.2–0.4 g of tissue), sufficient for analyzing 25 or more genes. This cost-effective and efficient protocol has been successfully applied to Arabidopsis thaliana and can be adapted to other systems for epigenetic research [150]. Among the most precise techniques, Whole-Genome Bisulfite Sequencing (WGBS) enables base-pair resolution analysis of 5-methylcytosine by treating genomic DNA with sodium bisulfite, converting unmethylated cytosines to uracil while leaving methylated cytosines unchanged, followed by PCR amplification and NGS analysis [151]. For example, the study found that tissue culture induces consistent homozygous DNA methylation changes inherited across multiple independent lines. These changes, including both gains and losses of DNA methylation in CG and CHG contexts, suggest that specific loci may act as hotspots for epigenetic variation. While not all changes in callus plants are observed in primary regenerants, most methylation alterations in primary regenerants are passed onto subsequent generations. WGBS has revealed methylation changes in several micropropagated species of maize [152]. Moreover, WGBS was used to examine genomic DNA methylation changes in Fragaria nilgerrensis across six stages, from explants to out planting and acclimation. CG sites showed the highest methylation (49.5%), followed by CHG (33.2%) and CHH (12.4%). CHH methylation changes were most prominent, particularly in transposable element regions. Methylation levels fluctuated throughout the tissue culture process, with non-uniform distribution across different genetic regions [96]. Similarly, epigenetic variation examined in rice using WGBS exhibits distinct differences, particularly in chromosomal distribution, compared to variations that occur under natural conditions [80]. In pineapple, WGBS was used to analyze context-specific DNA methylation changes in the pineapple genome between the cutting seedlings and five somaclonal variation plants [97]. Similarly, in apple, the DNA methylome and transcriptome of rejuvenated apple rootstock M9T337 cuttings were induced by in vitro shoot culture. It is found that DNA hypomethylation enhances adventitious rooting by upregulating rooting-related genes, while DNA hypermethylation represses rooting-inhibiting genes. These results emphasize the significant role of DNA methylation changes in regulating rooting ability in apple rootstock [153]. Additionally, RNA sequencing has emerged as a practical approach for identifying tissue culture-induced epigenetic variations [154]. Recently, this method was used to detect altered methylation levels in strawberries’ long-term in vitro shoot cultures. The results showed increased DNA methylation in specific sequence contexts (CG, CHG, CHH), with changes linked to the expression of regeneration-related genes. Inhibition of DNA methylation with 5′-azacytidine (5′-Aza) disrupted callus formation and regeneration, highlighting the critical role of DNA methylation in these processes [155]. These molecular and biochemical techniques collectively provide powerful tools for assessing epigenetic variation in tissue-cultured plants, contributing to a better understanding of somaclonal variation and ensuring the epigenetic fidelity of regenerants.
Table 3. List of reported epigenetic variations, their causes, and detection methods in major crops, fruit plants, and trees.

6. Methods for Optimizing Somaclonal Variation

Several strategies have been developed and successfully applied in various plant systems to optimize somaclonal variation control and maintain clonal fidelity during micropropagation. One of the most critical factors is explant selection, as explants derived from meristematic tissues such as axillary buds, shoot tips, and root tips are less prone to somaclonal variation than highly differentiated tissues like roots, leaves, and stems [162]. By carefully choosing appropriate explants, it is possible to reduce the incidence of unwanted variation. In addition, optimization of culture conditions plays a vital role in minimizing somaclonal variation. This involves adjusting the nutrient composition of culture media, fine-tuning the ratios of plant growth regulators (PGRs), and limiting the number of subcultures, as excessive subculturing increases the chance of genetic and epigenetic alterations, particularly in callus and cell suspension cultures [79,106]. Rodrigues et al. showed that somaclonal variants appeared from the fifth subculture (1.3%) onwards and increased to 3.8% after 11 subcultures in Musa spp. [163]. Studies have shown that reducing PGR concentrations can significantly decrease the likelihood of somaclonal variation [68,162], while optimizing environmental conditions such as temperature and light intensity can further stabilize cultures by avoiding stress-induced changes [68]. Bioreactor systems have also demonstrated potential in reducing the frequency of somaclonal variation by providing uniform and controlled culture environments [16]. For example, in Uncaria guianensis, the RITA (Recipient for Automated Temporary Immersion) system has been identified as the most effective bioreactor design. These micropropagation systems ensure efficient propagation and genome stability in Uncaria guianensis [164]. Another crucial approach involves favoring direct organogenesis over indirect methods, as indirect organogenesis typically consists of a callus phase associated with prolonged cell proliferation and extended culture exposure, increasing the risk of genetic instability [158]. In contrast, direct organogenesis produces shoots or roots directly from explants without intermediate callus formation, thus minimizing variation and preserving genetic fidelity [165]. Furthermore, cryopreservation has proven to be an effective long-term strategy for preserving plant tissues, embryogenic lines, and somatic embryos at ultra-low temperatures (−196 °C) without compromising their genetic integrity [69]. This technique reduces maintenance time and costs and minimizes the accumulation of somaclonal variation or contamination risks over time [166]. Finally, Molecular Marker-Assisted Selection (MAS) is a powerful tool for early detection and elimination of somaclonal variants during micropropagation [26]. Various molecular markers such as RAPD, ISSR, AFLP, SSR, and SNPs have been successfully applied for screening and identifying somaclonal variants in different plant species [11,26], allowing for the maintenance of genetic uniformity and selection of true-to-type regenerants. Together, these complementary strategies provide a comprehensive framework for minimizing somaclonal variation and enhancing the reliability of plant micropropagation systems.

7. Application of Somaclonal Variation as a Crop Improvement Tool

However, somaclonal variation is generally considered undesirable in clonal propagation. It can be a valuable tool for crop improvement [45]. The induced variation can be screened for desired traits to create new cultivars with desirable quality, known as somaclonal selection [68]. This process successfully selects elite genotypes in crops and plant species with improved quality, such as insect, pest, disease resistance, stress tolerance, or increased production rate [167]. However, selecting new variants requires careful consideration and ensuring that only desirable characteristics are selected, and harmful variants are removed [168]; using molecular markers is one of the reliable methods to identify and characterize desirable variants that prevent the propagation of deleterious variants [169]. In recent years, somaclonal variation has been used to improve agricultural crops, primarily for drought tolerance. Some desirable somaclonal variants used in plant breeding programs are presented in Table 4.
Table 4. List of some desirable somaclonal variants used in plant breeding programs.

8. Future Prospects

The integration of high-throughput molecular techniques such as MASP, WGBS, RNA sequencing, and CRISPR/Cas9 is revolutionizing the detection and minimizing of somaclonal variation in the agriculture, horticulture, and forest sectors [177]. Although CRISPR/Cas9 introduces targeted mutations, it actually supports the maintenance of clonal fidelity by offering precise and controlled gene editing, unlike the random and widespread genetic alterations associated with somaclonal variation [178]. Commercial micropropagation companies frequently employ these revolutionary techniques to validate planting materials, especially for high-value crops and nursery stocks intended for export. However, some challenges remain in making these molecular assays routine and affordable for experimental and commercial uses. To overcome these obstacles, it needs to optimize culture protocols, minimize the subculture cycle, select genotypes, and use meristematic explants with direct organogenesis [26]. The bioreactor system provides a controlled environment that provides consistent growth conditions for plant tissues, thereby minimizing somaclonal variation [16,82]. Moreover, cryopreservation techniques, which store plant tissues at extremely low temperatures, help maintain genetic stability over time [179]. While unstable epigenetic changes may have limited and reversible effects on plant phenotype, the integration of genetic and epigenetic screening in the micropropagation process is essential for reliably maintaining clonal fidelity for harnessing beneficial somaclonal variation in commercial micropropagation.

9. Conclusions

Somaclonal variation is significantly influenced by micropropagation techniques, with direct organogenesis generally producing more genetically stable plants compared to indirect organogenesis. Key factors contributing to this variation include the composition of the culture medium, the ratio and type of plant growth regulators (PGRs), explant source, frequency and type of subcultures, as well as environmental conditions such as light intensity and temperature. To optimize economic loss in commercial micropropagation, it is essential to identify and eradicate variants at the very early stages of their growth. Different approaches, like morphological analysis, cytological analysis, and molecular markers, are used to detect genetic and epigenetic variations. However, a few somaclonal variants are used as a new agronomic trait in crop improvement; at the same time, it is also a crucial problem in micropropagated plants. Numerous studies are being conducted on somaclonal variations during tissue culture, but a comprehensive understanding remains elusive.

Author Contributions

S.M., conceptualization, writing—original draft, and writing—review and editing. S.C.D., conceptualization, writing—original draft, writing—review and editing, and funding acquisition. A.U.I., conceptualization, writing—original draft, writing—review and editing, and funding acquisition. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare that there are no conflicts of interest.

References

  1. Bahar, N.H.A.; Lo, M.; Sanjaya, M.; Van Vianen, J.; Alexander, P.; Ickowitz, A.; Sunderland, T. Meeting the Food Security Challenge for Nine Billion People in 2050: What Impact on Forests? Glob. Environ. Chang. 2020, 62, 102056. [Google Scholar] [CrossRef] [Scilit]
  2. Hemanthakumar, A.S.; Preetha, T.S. Macro- and Micropropagation of Plants for Income Generation. In Conservation and Sustainable Utilization of Bioresources; Springer Nature: Singapore, 2023; pp. 409–450. [Google Scholar]
  3. Lasley, B.L.; Loskutoff, N.M.; Anderson, G.B. The limitation of conventional breeding programs and the need and promise of assisted 548 reproduction in nondomestic species. Theriogenology 1994, 41, 119–132. [Google Scholar] [CrossRef] [Scilit]
  4. Chandran, H.; Meena, M.; Barupal, T.; Sharma, K. Plant Tissue Culture as a Perpetual Source for Production of Industrially Important Bioactive Compounds. Biotechnol. Rep. 2020, 26, e00450. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  5. Abdalla, N.; El-Ramady, H.; Seliem, M.K.; El-Mahrouk, M.E.; Taha, N.; Bayoumi, Y.; Shalaby, T.A.; Dobránszki, J. An Academic and Technical Overview on Plant Micropropagation Challenges. Horticulturae 2022, 8, 677. [Google Scholar] [CrossRef] [Scilit]
  6. Bertsouklis, K.; Kartsonas, E.; Carra, A. Seed Germination and Micropropagation of Ornamental Plants. Horticulturae 2024, 10, 541. [Google Scholar] [CrossRef] [Scilit]
  7. Bettoni, J.C.; Wang, M.-R.; Wang, Q.-C. In Vitro Regeneration, Micropropagation and Germplasm Conservation of Horticultural Plants. Horticulturae 2024, 10, 45. [Google Scholar] [CrossRef] [Scilit]
  8. George, I.E.F.; Hall, M.A.; De Klerk, G.-J.; (Eds.). Plant Propagation by Tissue Culture. In Plant Cell Tiss Organ Cult, 3rd ed.; Springer: Dordrecht, The Netherlands, 2008; Volume 1, The Background; pp. 353–355. [Google Scholar] [CrossRef] [Scilit]
  9. Ozyigit, I.I.; Dogan, I.; Hocaoglu-Ozyigit, A.; Yalcin, B.; Erdogan, A.; Yalcin, I.E.; Cabi, E.; Kaya, Y. Production of Secondary Metabolites Using Tissue Culture-Based Biotechnological Applications. Front. Plant Sci. 2023, 14, 1132555. [Google Scholar] [CrossRef] [Scilit]
  10. Debnath, S.C.; Vyas, P.; Goyali, J.C.; Igamberdiev, A.U. Morphological and Molecular Analyses in Micropropagated Berry Plants Acclimatized under Ex Vitro Condition. Can. J. Plant Sci. 2012, 92, 1065–1073. [Google Scholar] [CrossRef] [Scilit]
  11. Taji, A.; Kumar, P.; Lakshmanan, P. In Vitro Plant Breeding; CRC Press: Boca Raton, FL, USA, 2024. [Google Scholar]
  12. Yancheva, S.; Kondakova, V. Plant Tissue Culture Technology: Present and Future Development. In Bioprocessing of Plant In Vitro Systems; Springer: Cham, Switzerland, 2018; pp. 39–63. [Google Scholar]
  13. Costa, G.F.D.; Cabral, P.D.S.; Silva, F.G.; Rubio Neto, A.; Mendonça, M.A.C. Clonal Fidelity and Genetic Diversity of Micropropagated Hancornia Speciosa Gomes (Apocynaceae) as Evaluated by Molecular Markers. Forests 2022, 13, 1645. [Google Scholar] [CrossRef] [Scilit]
  14. Debnath, S.C. Molecular Markers for Genetic Fidelity During In Vitro Propagation of Horticultural Crops. Acta Hortic. 2012, 929, 459–465. [Google Scholar] [CrossRef] [Scilit]
  15. Venkatachalam, L.; Sreedhar, R.V.; Bhagyalakshmi, N. Micropropagation in Banana Using High Levels of Cytokinins Does Not Involve Any Genetic Changes as Revealed by RAPD and ISSR Markers. Plant Growth Regul. 2007, 51, 193–205. [Google Scholar] [CrossRef] [Scilit]
  16. Debnath, S. Bioreactors and Molecular Analysis in Berry Crop Micropropagation—A Review. Can. J. Plant Sci. 2011, 91, 147–157. [Google Scholar] [CrossRef] [Scilit]
  17. Kundu, S.; Barua, R.; Marshall, H.D.; Siow, Y.L.; Igamberdiev, A.U.; Debnath, S.C. Somatic Embryogenesis in Vaccinium vitis-Idaea L.: A High-Fidelity Micropropagation Approach Producing True-to-Type Plants with Enhanced Phytochemical Profiles. Plant Cell Tissue Organ Cult. (PCTOC) 2025, 161, 37. [Google Scholar] [CrossRef] [Scilit]
  18. Gupta, R.; Modgil, M.; Chakrabarti, S.K. Assessment of Genetic Fidelity of Micropropagated Apple Rootstock Plants, EMLA 111, Using RAPD Markers. Indian J. Exp. Biol. 2009, 47, 925–928. [Google Scholar] [PubMed]
  19. Amin, A.; Sharma, N.; Sultan, P.; Gandhi, S.G.; Srinivas, K.; Hassan, Q.P.; Ahmed, Z. In Vitro Propagation of Bergenia Stracheyi: An Alternative Approach for Higher Production of Valuable Bioactive Compounds. Vegetos 2024, 1–10. [Google Scholar] [CrossRef] [Scilit]
  20. Khezri, M.; Asghari-Zakaria, R.; Zare, N. Plant Cell and Tissue Culture: Propagation, Improvement, and Conservation of Medicinal Plants. In Biosynthesis of Natural Products in Plants; Springer Nature: Singapore, 2024; pp. 267–291. [Google Scholar]
  21. Mohapatra, P.; Ray, A.; Jena, S. Evaluation of Genetic Stability of In Vitro Raised Orchids Using Molecular-Based Markers. In Commercial Scale Tissue Culture for Horticulture and Plantation Crops; Springer Nature: Singapore, 2022; pp. 293–316. [Google Scholar]
  22. Dorani, E.; Dehghanian, Z.; Gougerdchi, V.; Hamedpour-Darabi, M. Application of Somaclonal Variation in Crop Improvements. In Plant Mutagenesis; Springer: Cham, Switzerland, 2024; pp. 93–109. [Google Scholar]
  23. Nath, J.; Kumari, A.; Joshi, S.; Gusain, S.; Kumari, K.; Patial, M.; Rawat, M.; Joshi, R. Micropropagation Technology for Improvement of Ornamental Plants. In Ornamental Horticulture: Latest Cultivation Practices and Breeding Technologies; Springer Nature: Singapore, 2024; pp. 121–149. [Google Scholar]
  24. Reuveni, O.; Golubowicz, S.; Israeli, Y. Factors Influencing the Occurrence of Somaclonal Variations in Micropropagated Bananas. Acta Hortic. 1993, 336, 357–364. [Google Scholar] [CrossRef] [Scilit]
  25. Larkin, P.J.; Scowcroft, W.R. Somaclonal Variation—A Novel Source of Variability from Cell Cultures for Plant Improvement. Theor. Appl. Genet. 1981, 60, 197–214. [Google Scholar] [CrossRef] [Scilit]
  26. Bairu, M.W.; Aremu, A.O.; Van Staden, J. Somaclonal Variation in Plants: Causes and Detection Methods. Plant Growth Regul. 2011, 63, 147–173. [Google Scholar] [CrossRef] [Scilit]
  27. Leva, A.R.; Petruccelli, R.; Rinaldi, L.M.R. Somaclonal Variation in Tissue Culture: A Case Study with Olive. In Recent Advances in Plant In Vitro Culture; InTech: London, UK, 2012. [Google Scholar]
  28. Duta-Cornescu, G.; Constantin, N.; Pojoga, D.-M.; Nicuta, D.; Simon-Gruita, A. Somaclonal Variation—Advantage or Disadvantage in Micropropagation of the Medicinal Plants. Int. J. Mol. Sci. 2023, 24, 838. [Google Scholar] [CrossRef] [Scilit]
  29. Lindner, M.; Verhagen, I.; Mateman, A.C.; van Oers, K.; Laine, V.N.; Visser, M.E. Genetic and Epigenetic Differentiation in Response to Genomic Selection for Avian Lay Date. Evol. Appl. 2024, 17, e13703. [Google Scholar] [CrossRef] [Scilit]
  30. Hasnain, A.; Naqvi, S.A.H.; Ayesha, S.I.; Khalid, F.; Ellahi, M.; Iqbal, S.; Hassan, M.Z.; Abbas, A.; Adamski, R.; Markowska, D.; et al. Plants In Vitro Propagation with Its Applications in Food, Pharmaceuticals and Cosmetic Industries; Current Scenario and Future Approaches. Front. Plant Sci. 2022, 13, 1009395. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  31. Savita; Pati, P.K.; Virk, G.S.; Nagpal, A. An Efficient Somatic Embryogenesis Protocol for Citrus jambhiri and Assessment of Clonal Fidelity of Plantlets Using RAPD Markers. J. Plant Growth Regul. 2015, 34, 309–319. [Google Scholar] [CrossRef] [Scilit]
  32. Hussien, E.T.; Ahmed, M.F.; Ahmed, E.Z. Biometric Measurements and Genetic Instability Assessment of In Vitro Micro-Shoots Culture of Populus alba. Plant Physiol. Rep. 2022, 27, 398–406. [Google Scholar] [CrossRef] [Scilit]
  33. Shukla, S.; Bhutani, R.; Gupta, N.; Shukla, S.K.; Raman, T.; El-Sheikh, M.A.; Elansary, H.O.; Moussa, I.M. Studies on banana for propagation, conservation and genome analysis. Cogent Food Agric. 2025, 11, 2447898. [Google Scholar] [CrossRef] [Scilit]
  34. Gimenez, M.D.; Yañez-Santos, A.M.; Paz, R.C.; Quiroga, M.P.; Marfil, C.F.; Conci, V.C.; García-Lampasona, S.C. Assessment of Genetic and Epigenetic Changes in Virus-Free Garlic (Allium sativum L.) Plants Obtained by Meristem Culture Followed by In Vitro Propagation. Plant Cell Rep. 2016, 35, 129–141. [Google Scholar] [CrossRef] [Scilit]
  35. Verma, D.; Ansari, M.W.; Agrawal, G.K.; Rakwal, R.; Shukla, A.; Tuteja, N. In Vitro Selection and Field Responses of Somaclonal Variant Plants of Rice Cv PR113 for Drought Tolerance. Plant Signal. Behav. 2013, 8, e23519. [Google Scholar] [CrossRef] [Scilit]
  36. Ali, A.; El-Denary, M.; El-Gendy, A.; Galal, O.; Mohamed, M.; El Sayed, T. Morphological Evaluation of Some Tomato Somaclones Variation under Field Conditions. J. Plant Prod. 2018, 9, 833–838. [Google Scholar] [CrossRef] [Scilit]
  37. Hannachi, S.; Werbrouck, S.; Bahrini, I.; Abdelgadir, A.; Affan Siddiqui, H. Agronomical, Physiological and Biochemical Characterization of In Vitro Selected Eggplant Somaclonal Variants under NaCl Stress. Plants 2021, 10, 2544. [Google Scholar] [CrossRef] [Scilit]
  38. Biernacik, B.; Słomnicka, R.; Kaźmińska, K.; Mużacz, S.; Bartoszewski, G. A Single Nucleotide Substitution Introducing Premature Stop Codon within CsTFL1 Explains the Determinate-2 Phenotype in Cucumber (Cucumis sativus L.). Sci. Rep. 2024, 14, 25368. [Google Scholar] [CrossRef] [Scilit]
  39. Geem, K.R.; Lee, Y.-J.; Lee, J.; Hong, D.; Kim, G.-E.; Sung, J. Role of Carrot (Daucus carota L.) Storage Roots in Drought Stress Adaptation: Hormonal Regulation and Metabolite Accumulation. Metabolites 2025, 15, 56. [Google Scholar] [CrossRef] [Scilit]
  40. Ferreira, M.d.S.; Rebouças, T.A.; Rocha, A.d.J.; Oliveira, W.D.d.S.; Santos, A.C.L.S.d.; Jesus, J.P.F.L.d.; Ramos, A.P.d.S.; Ferreira, C.F.; Santos-Serejo, J.A.d.; Haddad, F.; et al. Selection and Characterization of Somaclonal Variants of Prata Banana (AAB) Resistant to Fusarium Wilt. Agronomy 2024, 14, 1740. [Google Scholar] [CrossRef] [Scilit]
  41. Cui, X.; Liu, Q.; Luo, Y.; Zhu, P.; Guan, P.; Zhang, J. Study on Influencing Factors of Embryo Rescue and Germplasm Innovation in Seedless Grape. Plant Cell Tissue Organ Cult. (PCTOC) 2024, 157, 24. [Google Scholar] [CrossRef] [Scilit]
  42. Joshi, A.; Tripathi, A.; Sharma, N.; Tailor, A. Somaclonal Variation for the Improvement of Tree Species. In Biotechnological Approaches for Sustaining Forest Trees and Their Products; Springer Nature: Singapore, 2024; pp. 77–102. [Google Scholar]
  43. Huang, H.; Ullah, F.; Zhou, D.-X.; Yi, M.; Zhao, Y. Mechanisms of ROS Regulation of Plant Development and Stress Responses. Front. Plant Sci. 2019, 10, 800. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  44. Mirani, A.A.; Teo, C.H.; Markhand, G.S.; Abul-Soad, A.A.; Harikrishna, J.A. Detection of Somaclonal Variations in Tissue Cultured Date Palm (Phoenix dactylifera L.) Using Transposable Element-Based Markers. Plant Cell Tissue Organ Cult. (PCTOC) 2020, 141, 119–130. [Google Scholar] [CrossRef] [Scilit]
  45. Ferreira, M.d.S.; Rocha, A.d.J.; Nascimento, F.d.S.; Oliveira, W.D.d.S.; Soares, J.M.d.S.; Rebouças, T.A.; Morais Lino, L.S.; Haddad, F.; Ferreira, C.F.; Santos-Serejo, J.A.d.; et al. The Role of Somaclonal Variation in Plant Genetic Improvement: A Systematic Review. Agronomy 2023, 13, 730. [Google Scholar] [CrossRef] [Scilit]
  46. Purohit, S.D.; Sharma, P.; Nagori, R. Assessment of Molecular Diversity and In Vitro Clonal Fidelity in Some Indian Medicinal Plants. Acta Hortic. 2015, 1098, 47–60. [Google Scholar] [CrossRef] [Scilit]
  47. Karp, A.; Wu, Q.S.; Steele, S.H.; Jones, M.G.K. Chromosome Variation in Dividing Protoplasts and Cell Suspensions of Wheat. Theor. Appl. Genet. 1987, 74, 140–146. [Google Scholar] [CrossRef] [Scilit]
  48. Sangthong, R.; Mii, M.; Soonthornchainaksaeng, P.; Supaibulwatana, K. Characteristics of The Tetraploid Plant Derived as A Somaclonal Variation in Lilium longiflorum. Acta Hortic. 2005, 673, 167–174. [Google Scholar] [CrossRef] [Scilit]
  49. Arnholdt-Schmitt, B. Rapid Changes in Amplification and Methylation Pattern of Genomic DNA in Cultured Carrot Root Explants (Daucus carota L.). Theor. Appl. Genet. 1993, 85, 793–800. [Google Scholar] [CrossRef] [Scilit]
  50. Lu, X.; Liu, Y.; Xu, J.; Liu, X.; Chi, Y.; Li, R.; Mo, L.; Shi, L.; Liang, S.; Yu, W.; et al. Recent Progress of Molecular Mechanisms of DNA Methylation in Plant Response to Abiotic Stress. Environ. Exp. Bot. 2024, 218, 105599. [Google Scholar] [CrossRef] [Scilit]
  51. Liu, Z.; Liu, C.; Wang, C.; Pan, X.; Zhang, H.; Yao, Y.; Huang, D.; Liao, W. The Involvement of DNA Methylation in Plant Growth Regulators-Mediated Growth in Tomato (Solanum lycopersicum) Seedlings. J. Plant Growth Regul. 2024, 43, 1287–1303. [Google Scholar] [CrossRef] [Scilit]
  52. Fang, J.; Jiang, J.; Leichter, S.M.; Liu, J.; Biswal, M.; Khudaverdyan, N.; Zhong, X.; Song, J. Mechanistic Basis for Maintenance of CHG DNA Methylation in Plants. Nat. Commun. 2022, 13, 3877. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  53. Gao, Y.; Wang, Q.-M.; An, Q.; Cui, J.; Zhou, Y.; Qi, X.; Zhang, L.; Li, L. A Novel Micropropagation of Lycium ruthenicum and Epigenetic Fidelity Assessment of Three Types of Micropropagated Plants In Vitro and Ex Vitro. PLoS ONE 2021, 16, e0247666. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  54. Abdulraheem, M.I.; Xiong, Y.; Moshood, A.Y.; Cadenas-Pliego, G.; Zhang, H.; Hu, J. Mechanisms of Plant Epigenetic Regulation in Response to Plant Stress: Recent Discoveries and Implications. Plants 2024, 13, 163. [Google Scholar] [CrossRef] [Scilit]
  55. Berr, A.; Shafiq, S.; Shen, W.-H. Histone Modifications in Transcriptional Activation during Plant Development. Biochim. Biophys. Acta (BBA)—Gene Regul. Mech. 2011, 1809, 567–576. [Google Scholar] [CrossRef] [Scilit]
  56. Pikaard, C.S.; Mittelsten Scheid, O. Epigenetic Regulation in Plants. Cold Spring Harb. Perspect. Biol. 2014, 6, a019315. [Google Scholar] [CrossRef] [Scilit]
  57. Santos-Rosa, H.; Schneider, R.; Bannister, A.J.; Sherriff, J.; Bernstein, B.E.; Emre, N.C.T.; Schreiber, S.L.; Mellor, J.; Kouzarides, T. Active Genes Are Tri-Methylated at K4 of Histone H3. Nature 2002, 419, 407–411. [Google Scholar] [CrossRef] [Scilit]
  58. Zhang, X.; Clarenz, O.; Cokus, S.; Bernatavichute, Y.V.; Pellegrini, M.; Goodrich, J.; Jacobsen, S.E. Whole-Genome Analysis of Histone H3 Lysine 27 Trimethylation in Arabidopsis. PLoS Biol. 2007, 5, e129. [Google Scholar] [CrossRef] [Scilit]
  59. Carlsbecker, A.; Lee, J.-Y.; Roberts, C.J.; Dettmer, J.; Lehesranta, S.; Zhou, J.; Lindgren, O.; Moreno-Risueno, M.A.; Vatén, A.; Thitamadee, S.; et al. Cell Signalling by MicroRNA165/6 Directs Gene Dose-Dependent Root Cell Fate. Nature 2010, 465, 316–321. [Google Scholar] [CrossRef] [Scilit]
  60. Ivey, K.N.; Srivastava, D. MicroRNAs as Regulators of Differentiation and Cell Fate Decisions. Cell Stem Cell 2010, 7, 36–41. [Google Scholar] [CrossRef] [Scilit]
  61. Li, H.; Zhao, X.; Dai, H.; Wu, W.; Mao, W.; Zhang, Z. Tissue Culture Responsive MicroRNAs in Strawberry. Plant Mol. Biol. Rep. 2012, 30, 1047–1054. [Google Scholar] [CrossRef] [Scilit]
  62. Zhang, Z. Epigenetic and Genetic Variation in Micro-Propagated Strawberry Plants. Acta Hortic. 2014, 1049, 13–18. [Google Scholar] [CrossRef] [Scilit]
  63. Li, H.; Zhang, Z.; Huang, F.; Chang, L.; Ma, Y. MicroRNA Expression Profiles in Conventional and Micropropagated Strawberry (Fragaria × Ananassa Duch.) Plants. Plant Cell Rep. 2009, 28, 891–902. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  64. Ali, S.; Tang, Y. Noncoding RNA-Mediated Regulation of DNA Methylation: Insights into Plant Epigenetic Mechanisms. J. Plant Growth Regul. 2025, 44, 373–388. [Google Scholar] [CrossRef] [Scilit]
  65. Krishna, H.; Alizadeh, M.; Singh, D.; Singh, U.; Chauhan, N.; Eftekhari, M.; Sadh, R.K. Somaclonal Variations and Their Applications in Horticultural Crops Improvement. 3 Biotech 2016, 6, 54. [Google Scholar] [CrossRef] [Scilit]
  66. Sianipar, N.F. Somaclonal variations induced by benzylaminopurine to enhance the fruit morphology of horn banana. SABRAO J. Breed. Genet 2024, 56, 2045–2055. [Google Scholar] [CrossRef] [Scilit]
  67. Miguel, C.; Marum, L. An Epigenetic View of Plant Cells Cultured In Vitro: Somaclonal Variation and Beyond. J. Exp. Bot. 2011, 62, 3713–3725. [Google Scholar] [CrossRef] [Scilit]
  68. Bayati, E.; Gomarian, M.; Mirzaie-Nodousha, H.; Changizi, M.; Khaghani, S. Producing a Superior Genotype from Agria Potato Cultivar Using Somaclonal Variation. Nexo Rev. Científica 2021, 34, 671–681. [Google Scholar] [CrossRef] [Scilit]
  69. Vidyagina, E.O.; Kharchenko, N.N.; Shestibratov, K.A. Efficient Cryopreservation of Populus tremula by In Vitro-Grown Axillary Buds and Genetic Stability of Recovered Plants. Plants 2021, 10, 77. [Google Scholar] [CrossRef] [Scilit]
  70. Siragusa, M.; Carra, A.; Salvia, L.; Puglia, A.M.; De Pasquale, F.; Carimi, F. Genetic Instability in Calamondin (Citrus madurensis Lour.) Plants Derived from Somatic Embryogenesis Induced by Diphenylurea Derivatives. Plant Cell Rep. 2007, 26, 1289–1296. [Google Scholar] [CrossRef] [Scilit]
  71. Bychappa, M.; Mishra, M.K.; Jingade, P.; Huded, A.K.C. Genomic Alterations in Coding Region of Tissue Culture Plants of Coffea arabica Obtained through Somatic Embryogenesis Revealed by Molecular Markers. Plant Cell Tissue Organ Cult. (PCTOC) 2019, 139, 91–103. [Google Scholar] [CrossRef] [Scilit]
  72. Hesami, M.; Adamek, K.; Pepe, M.; Jones, A.M.P. Effect of Explant Source on Phenotypic Changes of In Vitro Grown Cannabis Plantlets over Multiple Subcultures. Biology 2023, 12, 443. [Google Scholar] [CrossRef] [Scilit]
  73. Miryeganeh, M.; Armitage, D.W. Epigenetic Responses of Trees to Environmental Stress in the Context of Climate Change. Biol. Rev. 2025, 100, 131–148. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  74. Kaya, C.; Uğurlar, F.; Adamakis, I.-D.S. Epigenetic Modifications of Hormonal Signaling Pathways in Plant Drought Response and Tolerance for Sustainable Food Security. Int. J. Mol. Sci. 2024, 25, 8229. [Google Scholar] [CrossRef] [Scilit]
  75. Rudolf, J.; Tomovicova, L.; Panzarova, K.; Fajkus, J.; Hejatko, J.; Skalak, J. Epigenetics and Plant Hormone Dynamics: A Functional and Methodological Perspective. J. Exp. Bot. 2024, 75, 5267–5294. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  76. Müller, E.; Brown, P.T.H.; Hartke, S.; Lörz, H. DNA Variation in Tissue-Culture-Derived Rice Plants. Theor. Appl. Genet. 1990, 80, 673–679. [Google Scholar] [CrossRef] [Scilit]
  77. Thorat, A.S.; Sonone, N.A.; Choudhari, V.V.; Devarumath, R.M.; Babu, K.H. Plant Regeneration from Cell Suspension Culture in Saccharum officinarum L. and Ascertaining of Genetic Fidelity through RAPD and ISSR Markers. 3 Biotech 2017, 7, 16. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  78. Eissa, S.S.; Sayed, A.E.; MM Abd Allah, M.M.; EL-shaer, H.F. Molecular Genetic Studies on (Ficus palmata & Ficus carica Subsp Rupestris.) Under the Effect of Gamma Radiation by Tissue Culture Techniques. Al-Azhar J. Agric. Res. 2021, 46, 128–138. [Google Scholar] [CrossRef] [Scilit]
  79. Pachota, K.A.; Orłowska, R.; Bednarek, P.T. Medium Composition Affects the Tissue Culture-Induced Variation in Triticale Regenerants. Plant Cell Tissue Organ Cult. (PCTOC) 2022, 151, 35–46. [Google Scholar] [CrossRef] [Scilit]
  80. Zhang, D.; Wang, Z.; Wang, N.; Gao, Y.; Liu, Y.; Wu, Y.; Bai, Y.; Zhang, Z.; Lin, X.; Dong, Y.; et al. Tissue Culture-Induced Heritable Genomic Variation in Rice, and Their Phenotypic Implications. PLoS ONE 2014, 9, e96879. [Google Scholar] [CrossRef] [Scilit]
  81. Tikendra, L.; Potshangbam, A.M.; Dey, A.; Devi, T.R.; Sahoo, M.R.; Nongdam, P. RAPD, ISSR, and SCoT Markers Based Genetic Stability Assessment of Micropropagated Dendrobium Fimbriatum Lindl. Var. Oculatum Hk. f.- an Important Endangered Orchid. Physiol. Mol. Biol. Plants 2021, 27, 341–357. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  82. Debnath, S.C. Bioreactor-Induced Adventitious Shoot Regeneration Affects Genotype-Dependent Morphology but Maintains Clonal Fidelity in Red Raspberry. Vitr. Cell. Dev. Biol.-Plant 2014, 50, 777–788. [Google Scholar] [CrossRef] [Scilit]
  83. Bisht, V.; Rawat, J.M.; Gaira, K.S.; Purohit, S.; Anand, J.; Sinha, S.; Mitra, D.; Ataya, F.S.; Elgazzar, A.M.; El-Saber Batiha, G.; et al. Assessment of Genetic Homogeneity of In-Vitro Propagated Apple Root Stock MM 104 Using ISSR and SCoT Primers. BMC Plant Biol. 2024, 24, 240. [Google Scholar] [CrossRef] [Scilit]
  84. Rathore, M.S.; Chikara, J.; Mastan, S.G.; Rahman, H.; Anand, K.G.V.; Shekhawat, N.S. Assessment of Genetic Stability and Instability of Tissue Culture-Propagated Plantlets of Aloe vera L. by RAPD and ISSR Markers. Appl. Biochem. Biotechnol. 2011, 165, 1356–1365. [Google Scholar] [CrossRef] [Scilit]
  85. Vishal; Sidhu, G.S.; Gaikwad, P.N.; Mann, S.S.; Gill, M.S.; Manchanda, P. Optimized Protocol for High-Frequency Papaya Propagation: Morpho-Stereomicroscopic Analysis and Genetic Fidelity Assessment. Plant Cell Tissue Organ Cult. (PCTOC) 2024, 156, 81. [Google Scholar] [CrossRef] [Scilit]
  86. Dyduch-Siemińska, M.; Wawerska, K.; Gawroński, J. The Potential of Plant Tissue Cultures to Improve the Steviol Glycoside Profile of Stevia (Stevia rebaudiana Bertoni) Regenerants. Int. J. Mol. Sci. 2024, 25, 13584. [Google Scholar] [CrossRef] [Scilit]
  87. Chavez-Cortazar, A.; Mata-Rosas, M.; Oyama, K.; Samain, M.S.; Quesada, M. Induction of Somatic Embryogenesis and Evaluation of Genetic Stability in Regenerated Plants of Magnolia Dealbata. Biol. Plant 2020, 64, 224–233. [Google Scholar] [CrossRef] [Scilit]
  88. Tongtape, K.; Te-chato, S.; Yenchon, S. Somatic Embryo (SE) Formation from Culturing Floral Explants of Rubber Tree (Hevea brasiliensis Muell. Arg.) and Assessment of Genetic Stability by RAPD and SSR Markers. Trends Sci. 2023, 20, 6728. [Google Scholar] [CrossRef] [Scilit]
  89. Skała, E.; Olszewska, M.A.; Makowczyńska, J.; Kicel, A. Effect of Sucrose Concentration on Rhaponticum carthamoides (Willd.) Iljin Transformed Root Biomass, Caffeoylquinic Acid Derivative, and Flavonoid Production. Int. J. Mol. Sci. 2022, 23, 13848. [Google Scholar] [CrossRef] [Scilit]
  90. Safarpour, M.; Sinniah, U.R.; Subramaniam, S.; Swamy, M.K. A Novel Technique for Musa Acuminata Colla ‘Grand Naine’ (AAA) Micropropagation through Transverse Sectioning of the Shoot Apex. Vitr. Cell. Dev. Biol.-Plant 2017, 53, 226–238. [Google Scholar] [CrossRef] [Scilit]
  91. Ramírez-Mosqueda, M.A.; Iglesias-Andreu, L.G. Indirect Organogenesis and Assessment of Somaclonal Variation in Plantlets of Vanilla planifolia Jacks. Plant Cell Tissue Organ Cult. (PCTOC) 2015, 123, 657–664. [Google Scholar] [CrossRef] [Scilit]
  92. Han, Z.; Crisp, P.A.; Stelpflug, S.; Kaeppler, S.M.; Li, Q.; Springer, N.M. Heritable Epigenomic Changes to the Maize Methylome Resulting from Tissue Culture. Genetics 2018, 209, 983–995. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  93. Sikdar, A.; Sharma, U.; Barua, R.; Igamberdiev, A.U.; Debnath, S.C. Epigenomic Insight of Lingonberry and Health-Promoting Traits during Micropropagation. Sci. Rep. 2022, 12, 12487. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  94. Bobadilla Landey, R.; Cenci, A.; Georget, F.; Bertrand, B.; Camayo, G.; Dechamp, E.; Herrera, J.C.; Santoni, S.; Lashermes, P.; Simpson, J.; et al. High Genetic and Epigenetic Stability in Coffea arabica Plants Derived from Embryogenic Suspensions and Secondary Embryogenesis as Revealed by AFLP, MSAP and the Phenotypic Variation Rate. PLoS ONE 2013, 8, e56372. [Google Scholar] [CrossRef] [Scilit]
  95. Goyali, J.C.; Igamberdiev, A.U.; Debnath, S.C. DNA Methylation in Lowbush Blueberry (Vaccinium angustifolium Ait.) Propagated by Softwood Cutting and Tissue Culture. Can. J. Plant Sci. 2018, 98, 1035–1044. [Google Scholar] [CrossRef] [Scilit]
  96. Cao, Q.; Feng, Y.; Dai, X.; Huang, L.; Li, J.; Tao, P.; Crabbe, M.J.C.; Zhang, T.; Qiao, Q. Dynamic Changes of DNA Methylation During Wild Strawberry (Fragaria nilgerrensis) Tissue Culture. Front. Plant Sci. 2021, 12, 765383. [Google Scholar] [CrossRef] [Scilit]
  97. Lin, W.; Xiao, X.; Zhang, H.; Li, Y.; Liu, S.; Sun, W.; Zhang, X.; Wu, Q. Whole-Genome Bisulfite Sequencing Reveals a Role for DNA Methylation in Variants from Callus Culture of Pineapple (Ananas comosus L.). Genes 2019, 10, 877. [Google Scholar] [CrossRef] [Scilit]
  98. Orłowska, R. Barley Somatic Embryogenesis-an Attempt to Modify Variation Induced in Tissue Culture. J. Biol. Res.-Thessalon. 2021, 28, 9. [Google Scholar] [CrossRef] [Scilit]
  99. Himmen, F.D.A.; de Souza, F.A.; de Araújo Silva-Cardoso, I.M.; de Souza, A.L.X.; Scherwinski-Pereira, J.E. Micropropagation, Estimation of DNA Methylation during Multiplication Cycles and Mycorrhization of Seed-Derived Dendrocalamus asper (Schultes f.) Backer Ex Heyne. Plant Cell Tissue Organ Cult. (PCTOC) 2023, 155, 41–56. [Google Scholar] [CrossRef] [Scilit]
  100. Kaeppler, S.M.; Phillips, R.L. Tissue Culture-Induced DNA Methylation Variation in Maize. Proc. Natl. Acad. Sci. USA 1993, 90, 8773–8776. [Google Scholar] [CrossRef] [Scilit]
  101. Cao, S.; Sawettalake, N.; Li, P.; Fan, S.; Shen, L. DNA Methylation Variations Underlie Lettuce Domestication and Divergence. Genome Biol. 2024, 25, 158. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  102. Nic-Can, G.I.; López-Torres, A.; Barredo-Pool, F.; Wrobel, K.; Loyola-Vargas, V.M.; Rojas-Herrera, R.; De-la-Peña, C. New Insights into Somatic Embryogenesis: LEAFY COTYLEDON1, BABY BOOM1 and WUSCHEL-RELATED HOMEOBOX4 Are Epigenetically Regulated in Coffea canephora. PLoS ONE 2013, 8, e72160. [Google Scholar] [CrossRef] [Scilit]
  103. Linacero, R.; Ballesteros, I. Genetic Basis of Somaclonal Variation. In Somaclonal Variation: Basic and Practical Aspects; Springer International Publishing: Cham, Switzerland, 2024; pp. 1–20. [Google Scholar]
  104. Noack, F.; Engist, D.; Gantois, J.; Gaur, V.; Hyjazie, B.F.; Larsen, A.; M’Gonigle, L.K.; Missirian, A.; Qaim, M.; Sargent, R.D.; et al. Environmental Impacts of Genetically Modified Crops. Science 2024, 385, eado9340. [Google Scholar] [CrossRef] [Scilit]
  105. Pandey, S.; Patel, P.; Prasad, A.; Sawant, S.V.; Misra, P. Assessment of Direct Shoot Organogenesis and Genetic Fidelity in Solanum viarum Dunal—A Commercially Important Medicinal Plant. Vitr. Cell. Dev. Biol.-Plant 2020, 56, 538–547. [Google Scholar] [CrossRef] [Scilit]
  106. Singer, S.D.; Laurie, J.D.; Bilichak, A.; Kumar, S.; Singh, J. Genetic Variation and Unintended Risk in the Context of Old and New Breeding Techniques. CRC Crit. Rev. Plant Sci. 2021, 40, 68–108. [Google Scholar] [CrossRef] [Scilit]
  107. Rani, V.; Raina, S.N. Genetic Fidelity of Organized Meristem-Derived Micropropagated Plants: A Critical Reappraisal. Vitr. Cell. Dev. Biol.-Plant 2000, 36, 319–330. [Google Scholar] [CrossRef] [Scilit]
  108. Ding, J.; Deng, X.-X.; Zhang, H.; Cheng, Y.; Xu, Q.; Liu, Q. Somaclonal Variation with Early Juice-Sac Granulation Obtained by Inter-Specific Protoplast Fusion in Citrus. J. Hortic. Sci. Biotechnol. 2009, 84, 567–573. [Google Scholar] [CrossRef] [Scilit]
  109. Pellicer, J.; Powell, R.F.; Leitch, I.J. The Application of Flow Cytometry for Estimating Genome Size, Ploidy Level Endopolyploidy, and Reproductive Modes in Plants. In Molecular Plant Taxonomy; Humana: New York, NY, USA, 2021; pp. 325–361. [Google Scholar]
  110. Naing, A.H.; Kim, S.H.; Chung, M.Y.; Park, S.K.; Kim, C.K. In Vitro Propagation Method for Production of Morphologically and Genetically Stable Plants of Different Strawberry Cultivars. Plant Methods 2019, 15, 36. [Google Scholar] [CrossRef] [Scilit]
  111. Jena, S.; Ray, A.; Sahoo, A.; Sahoo, S.; Kar, B.; Panda, P.C.; Nayak, S. High-Frequency Clonal Propagation of Curcuma Angustifolia Ensuring Genetic Fidelity of Micropropagated Plants. Plant Cell Tissue Organ Cult. (PCTOC) 2018, 135, 473–486. [Google Scholar] [CrossRef] [Scilit]
  112. Hasanuzzaman, M.; Nahar, K.; Alam, M.M.; Roychowdhury, R.; Fujita, M. Physiological, Biochemical, and Molecular Mechanisms of Heat Stress Tolerance in Plants. Int. J. Mol. Sci. 2013, 14, 9643–9684. [Google Scholar] [CrossRef] [Scilit]
  113. Sandoval, J.; Kerbellec, F.; Cote, F.; Doumas, P. Distribution of Endogenous Gibberellins in Dwarf and Giant Off-Types Banana (Musa AAA, Cv.Grand Nain) Plants from In Vitro Propagation. Plant Growth Regul. 1995, 17, 219–224. [Google Scholar] [CrossRef] [Scilit]
  114. Amberger, L.A.; Shoemaker, R.C.; Palmer, R.G. Inheritance of Two Independent Isozyme Variants in Soybean Plants Derived from Tissue Culture. Theor. Appl. Genet. 1992, 84, 600–607. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  115. González, A.M.; De la Fuente, M.; De Ron, A.M.; Santalla, M. Protein Markers and Seed Size Variation in Common Bean Segregating Populations. Mol. Breed. 2010, 25, 723–740. [Google Scholar] [CrossRef] [Scilit]
  116. Mandal, A.B.; Maiti, A.; Chowdhury, B.; Elanchezhian, R. Isoenzyme Markers in Varietal Identification of Banana. Vitr. Cell. Dev. Biol.-Plant 2001, 37, 599–604. [Google Scholar] [CrossRef] [Scilit]
  117. Biswas, P.; Kumar, N. Application of Molecular Markers for the Assessment of Genetic Fidelity of In Vitro Raised Plants: Current Status and Future Prospects. In Molecular Marker Techniques; Springer Nature: Singapore, 2023; pp. 233–256. [Google Scholar]
  118. Roth, E.J.; Frazier, B.L.; Apuya, N.R.; Lark, K.G. Genetic Variation in an Inbred Plant: Variation in Tissue Cultures of Soybean (Glycine max (L.) Merrill). Genetics 1989, 121, 359–368. [Google Scholar] [CrossRef] [Scilit]
  119. Mohammad, N.; Dahayat, A.; Agrahari, H. Molecular Markers in the Management and Improvement of Forest Genetic Resources. In Biotechnological Approaches for Sustaining Forest Trees and Their Products; Springer Nature: Singapore, 2024; pp. 181–198. [Google Scholar]
  120. Orbović, V.; Ćalović, M.; Viloria, Z.; Nielsen, B.; Gmitter, F.G.; Castle, W.S.; Grosser, J.W. Analysis of Genetic Variability in Various Tissue Culture-Derived Lemon Plant Populations Using RAPD and Flow Cytometry. Euphytica 2008, 161, 329–335. [Google Scholar] [CrossRef] [Scilit]
  121. Hashmi, G.; Huettel, R.; Meyer, R.; Krusberg, L.; Hammerschlag, F. RAPD Analysis of Somaclonal Variants Derived from Embryo Callus Cultures of Peach. Plant Cell Rep. 1997, 16, 624–627. [Google Scholar] [CrossRef]
  122. Kamle, M.; Kumar, P.; Bajpai, A.; Kalim, S.; Chandra, R. Assessment of Genetic Fidelity of Somatic Embryogenesis Regenerated Guava (Psidium guajava L.) Plants Using DNA-Based Markers. N. Zeal. J. Crop Hortic. Sci. 2014, 42, 1–9. [Google Scholar] [CrossRef] [Scilit]
  123. Martín, C.; González-Benito, M.E. Molecular Markers for the Detection and Analysis of Somaclonal Variation. In Somaclonal Variation: Basic and Practical Aspects; Springer International Publishing: Cham, Switzerland, 2024; pp. 57–82. [Google Scholar]
  124. Sahoo, A.; Behura, S.; Singh, S.; Jena, S.; Ray, A.; Dash, B.; Kar, B.; Panda, P.C.; Nayak, S. EST-SSR Marker-Based Genetic Diversity and Population Structure Analysis of Indian Curcuma Species: Significance for Conservation. Braz. J. Bot. 2021, 44, 411–428. [Google Scholar] [CrossRef] [Scilit]
  125. Sadhu, S.; Jogam, P.; Thampu, R.K.; Abbagani, S.; Penna, S.; Peddaboina, V. High Efficiency Plant Regeneration and Genetic Fidelity of Regenerants by SCoT and ISSR Markers in Chickpea (Cicer arietinum L.). Plant Cell Tissue Organ Cult. (PCTOC) 2020, 141, 465–477. [Google Scholar] [CrossRef] [Scilit]
  126. Al-Aizari, A.A.; Dewir, Y.H.; Ghazy, A.H.; Al-Doss, A.; Al-Obeed, R.S. Micropropagation and Genetic Fidelity of Fegra Fig (Ficus palmata Forssk.) and Grafting Compatibility of the Regenerated Plants with Ficus Carica. Plants 2024, 13, 1278. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  127. Hu, L.; Wang, Y.; Yu, S.; Li, S.; Cai, X. Genetic Stability Evaluation of Caladium Somaclonal Variants by Morphological, Cytological, and SSR Analysis in Three Successive Generations. Not. Bot. Horti Agrobot. Cluj-Napoca 2024, 52, 13746. [Google Scholar] [CrossRef] [Scilit]
  128. Ioannidis, K.; Tomprou, I.; Mitsis, V.; Koropouli, P. Genetic Evaluation of In Vitro Micropropagated and Regenerated Plants of Cannabis sativa L. Using SSR Molecular Markers. Plants 2022, 11, 2569. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  129. Sharma, U.; Sikdar, A.; Igamberdiev, A.U.; Debnath, S.C. Exploring Genetic and Epigenetic Changes in Lingonberry Using Molecular Markers: Implications for Clonal Propagation. Curr. Issues Mol. Biol. 2023, 45, 6296–6310. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  130. Collard, B.C.Y.; Mackill, D.J. Start Codon Targeted (SCoT) Polymorphism: A Simple, Novel DNA Marker Technique for Generating Gene-Targeted Markers in Plants. Plant Mol. Biol. Rep. 2009, 27, 86–93. [Google Scholar] [CrossRef] [Scilit]
  131. Mamgain, J.; Mujib, A.; Ejaz, B.; Gulzar, B.; Malik, M.Q.; Syeed, R. Flow Cytometry and Start Codon Targeted (SCoT) Genetic Fidelity Assessment of Regenerated Plantlets in Tylophora indica (Burm.f.) Merrill. Plant Cell Tissue Organ Cult. (PCTOC) 2022, 150, 129–140. [Google Scholar] [CrossRef] [Scilit]
  132. Pandey, N.; Meena, R.P.; Rai, S.K.; Pandey-Rai, S. In vitro generation of high artemisinin yielding salt tolerant somaclonal variant and development of SCAR marker in Artemisia annua L. Plant Cell Tiss. Organ Cult. (PCTOC) 2016, 127, 301–314. [Google Scholar] [CrossRef] [Scilit]
  133. Adly, W.M.R.M.; Niedbała, G.; EL-Denary, M.E.; Mohamed, M.A.; Piekutowska, M.; Wojciechowski, T.; Abd El-Salam, E.-S.T.; Fouad, A.S. Somaclonal Variation for Genetic Improvement of Starch Accumulation in Potato (Solanum tuberosum) Tubers. Plants 2023, 12, 232. [Google Scholar] [CrossRef] [Scilit]
  134. Zhang, Z.; Yu, S.; Zhang, Z.; Zhang, J.; Li, H. Comparative Characterization of Fruit Volatiles and Volatile-Related Genes Expression of ‘Benihoppe’ Strawberry and Its Somaclonal Mutant. Plants 2023, 12, 1109. [Google Scholar] [CrossRef] [Scilit]
  135. Ting, N.-C.; Jansen, J.; Nagappan, J.; Ishak, Z.; Chin, C.-W.; Tan, S.-G.; Cheah, S.-C.; Singh, R. Identification of QTLs Associated with Callogenesis and Embryogenesis in Oil Palm Using Genetic Linkage Maps Improved with SSR Markers. PLoS ONE 2013, 8, e53076. [Google Scholar] [CrossRef] [Scilit]
  136. Siril, E.A.; Joseph, N. Micropropagation of Annatto (Bixa orellana L.) from Mature Tree and Assessment of Genetic Fidelity of Micropropagated Plants with RAPD Markers. Physiol. Mol. Biol. Plants 2013, 19, 147–155. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  137. Martins, S.; Silva, A.P.; Santos, A.A.; Carnide, V. Diversity in Hazelnut Using RAPD and ISSR Markers. Acta Hortic. 2009, 845, 145–150. [Google Scholar] [CrossRef] [Scilit]
  138. Yu, S.; Zhao, X.; Wang, Y.; Jiang, D.; Zhang, Y.; Hu, L.; Liu, Y.; Cai, X. Morphological, Cytological, and Molecular-Based Genetic Stability Analysis of In Vitro-Propagated Plants from Newly Induced Aneuploids in Caladium. Agriculture 2022, 12, 1708. [Google Scholar] [CrossRef] [Scilit]
  139. Ploetz, R.C. Management of Fusarium Wilt of Banana: A Review with Special Reference to Tropical Race 4. Crop Prot. 2015, 73, 7–15. [Google Scholar] [CrossRef] [Scilit]
  140. Swain, D.; Lenka, S.; Hota, T.; Rout, G.R. Micro-Propagation of Hypericum gaitii Haines, an Endangered Medicinal Plants: Assessment of Genetic Fidelity. Nucleus 2016, 59, 7–13. [Google Scholar] [CrossRef] [Scilit]
  141. Sathish, D.; Vasudevan, V.; Theboral, J.; Elayaraja, D.; Appunu, C.; Siva, R.; Manickavasagam, M. Efficient Direct Plant Regeneration from Immature Leaf Roll Explants of Sugarcane (Saccharum officinarum L.) Using Polyamines and Assessment of Genetic Fidelity by SCoT Markers. Vitr. Cell. Dev. Biol.-Plant 2018, 54, 399–412. [Google Scholar] [CrossRef] [Scilit]
  142. Jogam, P.; Sandhya, D.; Shekhawat, M.S.; Alok, A.; Abbagani, S.; Allini, V.R. Genetic Stability Analysis Using DNA Barcoding and Molecular Markers and Foliar Micro-Morphological Analysis of In Vitro Regenerated and In Vivo Grown Plants of Artemisia Vulgaris L. Ind. Crops Prod. 2020, 151, 112476. [Google Scholar] [CrossRef] [Scilit]
  143. Monica, H.; Kumaria, S. Exogenous Application of Chitosan, a Potent Biotic Elicitor Enhances Micropropagation Efficiency of Cymbidium aloifolium (L.) Sw., an Orchid of Medicinal and Horticultural Importance. Vegetos 2024, 38, 58–69. [Google Scholar] [CrossRef] [Scilit]
  144. Oliya, B.K.; Chand, K.; Thakuri, L.S.; Baniya, M.K.; Sah, A.K.; Pant, B. Assessment of Genetic Stability of Micropropagated Plants of Rhynchostylis retusa (L.) Using RAPD Markers. Sci. Hortic. 2021, 281, 110008. [Google Scholar] [CrossRef] [Scilit]
  145. Zhang, L.; Cheng, Z.; Khan, M.A.; Zhou, Y. In Vitro Selection of Resistant Mutant Garlic Lines by Using Crude Pathogen Culture Filtrate of Sclerotium cepivorum. Australas. Plant Pathol. 2012, 41, 211–217. [Google Scholar] [CrossRef] [Scilit]
  146. Martins, A.A.; da Silva, M.F.; Pinto, L.R. Epigenetic Diversity of Saccharum Spp. Accessions Assessed by Methylation-Sensitive Amplification Polymorphism (MSAP). 3 Biotech 2020, 10, 265. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  147. Fraga, M.F.; Rodríguez, R.; Cañal, M.J. Rapid quantification of DNA methylation by high performance capillary electrophoresis. Electrophoresis 2000, 21, 2990–2994. [Google Scholar] [CrossRef] [PubMed]
  148. Gao, Y.; Hao, J.-L.; Wang, Z.; Song, K.-J.; Ye, J.-H.; Zheng, X.-Q.; Liang, Y.-R.; Lu, J.-L. DNA Methylation Levels in Different Tissues in Tea Plant via an Optimized HPLC Method. Hortic. Environ. Biotechnol. 2019, 60, 967–974. [Google Scholar] [CrossRef] [Scilit]
  149. Zhao, L.; Xie, L.; Zhang, Q.; Ouyang, W.; Deng, L.; Guan, P.; Ma, M.; Li, Y.; Zhang, Y.; Xiao, Q.; et al. Integrative Analysis of Reference Epigenomes in 20 Rice Varieties. Nat. Commun. 2020, 11, 2658. [Google Scholar] [CrossRef] [Scilit]
  150. Saleh, A.; Alvarez-Venegas, R.; Avramova, Z. An Efficient Chromatin Immunoprecipitation (ChIP) Protocol for Studying Histone Modifications in Arabidopsis Plants. Nat. Protoc. 2008, 3, 1018–1025. [Google Scholar] [CrossRef] [Scilit]
  151. Gong, Z.; Zheng, J.; Yang, N.; Li, X.; Qian, S.; Sun, F.; Geng, S.; Liang, Y.; Wang, J. Whole-Genome Bisulfite Sequencing (WGBS) Analysis of Gossypium hirsutum under High-Temperature Stress Conditions. Genes 2024, 15, 1241. [Google Scholar] [CrossRef] [Scilit]
  152. Stelpflug, S.C.; Eichten, S.R.; Hermanson, P.J.; Springer, N.M.; Kaeppler, S.M. Consistent and Heritable Alterations of DNA Methylation Are Induced by Tissue Culture in Maize. Genetics 2014, 198, 209–218. [Google Scholar] [CrossRef] [Scilit]
  153. Wang, Z.; Li, Z.; Wu, D.; Tian, Q.; Su, S.; Cheng, C.; Nie, J.; Yuan, Y.; Wang, Y.; Xu, X. DNA Methylation Variation Is Crucial to Restore Adventitious Rooting Ability during In Vitro Shoot Culture-induced Rejuvenation in Apple Rootstock. Plant J. 2023, 114, 554–569. [Google Scholar] [CrossRef] [Scilit]
  154. Mueller, S.A.; Merondun, J.; Lečić, S.; Wolf, J.B.W. Epigenetic Variation in Light of Population Genetic Practice. Nat. Commun. 2025, 16, 1028. [Google Scholar] [CrossRef] [Scilit]
  155. Liu, D.; Mu, Q.; Li, X.; Xu, S.; Li, Y.; Gu, T. The Callus Formation Capacity of Strawberry Leaf Explant Is Modulated by DNA Methylation. Hortic. Res. 2022, 9, uhab073. [Google Scholar] [CrossRef] [Scilit]
  156. Machczyńska, J.; Zimny, J.; Bednarek, P.T. Tissue Culture-Induced Genetic and Epigenetic Variation in Triticale (× Triticosecale Spp. Wittmack Ex A. Camus 1927) Regenerants. Plant Mol. Biol. 2015, 89, 279–292. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  157. Peredo, E.L.; Revilla, M.A.; Arroyo-García, R. Assessment of Genetic and Epigenetic Variation in Hop Plants Regenerated from Sequential Subcultures of Organogenic Calli. J. Plant Physiol. 2006, 163, 1071–1079. [Google Scholar] [CrossRef] [Scilit]
  158. Kitimu, S.R.; Taylor, J.; March, T.J.; Tairo, F.; Wilkinson, M.J.; Rodríguez López, C.M. Meristem Micropropagation of Cassava (Manihot esculenta) Evokes Genome-Wide Changes in DNA Methylation. Front. Plant Sci. 2015, 6, 590. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  159. Orłowska, R.; Machczyńska, J.; Oleszczuk, S.; Zimny, J. DNA Methylation Changes and TE Activity Induced in Tissue Cultures of Barley (Hordeum vulgare L.). J. Biol. Res.-Thessaloniki 2016, 23, 19. [Google Scholar] [CrossRef] [Scilit]
  160. Kastelec, D.; Troha, S.; Svetik, S.; Trafela, T.; Murovec, J. Optimization of Micropropagation Protocols and Assessment of Epigenetic Changes in Tissue Cultures of Diverse Medical Cannabis (Cannabis sativa L.) Genotypes. Ind. Crops Prod. 2025, 229, 121015. [Google Scholar] [CrossRef] [Scilit]
  161. Khodaeiaminjan, M.; Gomes, C.; Pagano, A.; Kruszka, D.; Sulima, P.; Przyborowski, J.A.; Krajewski, P.; Paiva, J.A.P. Impacts of In-Vitro Zebularine Treatment on Genome-Wide DNA Methylation and Transcriptomic Profiles in Salix purpurea L. Physiol. Plant 2024, 176, e14403. [Google Scholar] [CrossRef] [Scilit]
  162. Rai, M.K. Somaclonal Variation in Improvement of Agricultural Crops: Recent Progress. In Agricultural Biotechnology: Latest Research and Trends; Springer Nature: Singapore, 2021; pp. 129–146. [Google Scholar]
  163. Rodrigues, P.H.V.; Tulmann Neto, A.; Cassieri Neto, P.; Mendes, B.M.J. Influence of the Number of Subcultures on Somaclonal Variation in Micropropagated Nanicão (Musa spp., aaa group). Acta Hortic. 1998, 490, 469–474. [Google Scholar] [CrossRef] [Scilit]
  164. Gomes, H.T.; Monteiro, T.R.; Camillo, J.; Nogueira, G.F.; da Silva Costa, F.H.; de Araújo Silva-Cardoso, I.M.; Scherwinski-Pereira, J.E. Integrated Seed Cryopreservation, Bioreactor and Conventional Micropropagation, and Genetic Stability Assessment by Flow Cytometry of Uncaria guianensis (Aubl.) J.F.Gmel, a High-Value Amazonian Medicinal Plant. Plant Cell Tissue Organ Cult. (PCTOC) 2025, 161, 45. [Google Scholar] [CrossRef] [Scilit]
  165. Rajeswari, S.; Thirugnanakumar, S.; Anandan, A.; Krishnamurthi, M. Somaclonal Variation in Sugarcane through Tissue Culture and Evaluation for Quantitative and Quality Traits. Euphytica 2009, 168, 71. [Google Scholar] [CrossRef] [Scilit]
  166. Kessel-Domini, A.; Pérez-Brito, D.; Guzmán-Antonio, A.; Barredo-Pool, F.A.; Mijangos-Cortés, J.O.; Iglesias-Andreu, L.G.; Cortés-Velázquez, A.; Canto-Flick, A.; Avilés-Viñas, S.A.; Rodríguez-Llanes, Y.; et al. Indirect Somatic Embryogenesis: An Efficient and Genetically Reliable Clonal Propagation System for Ananas comosus L. Merr. Hybrid “MD2.”. Agriculture 2022, 12, 713. [Google Scholar] [CrossRef] [Scilit]
  167. Kukreja, A.K.; Dhawan, O.P.; Mathur, A.K.; Ahuja, P.S.; Mandal, S. Screening and Evaluation of Agronomically Useful Somaclonal Variations in Japanese Mint (Mentha arvensis L.). Euphytica 1991, 53, 183–191. [Google Scholar] [CrossRef] [Scilit]
  168. Cioloca, M.; Tican, A.; Popa, M. Evaluation of Virus-Free Potato Minitubers Derived from “in Vitro” Meristem Cultures for High-Quality Seed Potato Production. Rom. J. Hortic. 2024, 5, 15–22. [Google Scholar] [CrossRef] [Scilit]
  169. Kritskaya, T.A.; Kashin, A.S.; Kasatkin, M.Y. Micropropagation and Somaclonal Variation of Tulipa Suaveolens (Liliaceae) in Vitro. Russ. J. Dev. Biol. 2019, 50, 209–215. [Google Scholar] [CrossRef] [Scilit]
  170. Sridhar, R.; Harish Babu, B.N. A Novel Pomegranate (Punica granatum L.) Variant with High Anthocyanin Content. Acta Hortic. 2019, 1255, 149–152. [Google Scholar] [CrossRef] [Scilit]
  171. Ghag, S.B.; Shekhawat, U.K.S.; Ganapathi, T.R. Characterization of Fusarium Wilt Resistant Somaclonal Variants of Banana Cv. Rasthali by CDNA-RAPD. Mol. Biol. Rep. 2014, 41, 7929–7935. [Google Scholar] [CrossRef] [Scilit]
  172. Khadijat, S.J.; Maimuna, A.M.; Sagir, M.M. Screening for Drought Tolerance in Cotton (Gossypium Hirsutum L.) Using In Vitro Technique. J. Dryland Agric. 2021, 7, 52–59. [Google Scholar] [CrossRef] [Scilit]
  173. Popoola, A.R.; Durosomo, A.H.; Afolabi, C.G.; Idehen, E.O. Regeneration of Somaclonal Variants of Tomato (Solanum lycopersicum L.) for Resistance to Fusarium Wilt. J. Crop Improv. 2015, 29, 636–649. [Google Scholar] [CrossRef] [Scilit]
  174. Dhurve, L.; Ajith Kumar, K.; Bhaskar, J.; Sobhana, A.; Francies, R.M.; Mathew, D. Wide Variability among the ‘Mauritius’ Somaclones Demonstrates Somaclonal Variation as a Promising Improvement Strategy in Pineapple (Ananas comosus L.). Plant Cell Tissue Organ Cult. (PCTOC) 2021, 145, 701–705. [Google Scholar] [CrossRef] [Scilit]
  175. Arun, B.; Singh, B.D.; Sharma, S.; Paliwal, R.; Joshi, A.K. Development of Somaclonal Variants of Wheat (Triticum aestivum L.) for Yield Traits and Disease Resistance Suitable for Heat Stressed and Zero-till Conditions. Field Crops Res. 2007, 103, 62–69. [Google Scholar] [CrossRef] [Scilit]
  176. Dolcet-Sanjuan, R.; Clavería, E.; Llauradó, L.; Ortigosa, A.; Arús, P. Carnation (Dianthus caryophyllus L.) Dihaploid Lines Resistant to Fusarium oxysporum f.sp. dianthi. Acta Hortic. 2001, 560, 145–148. [Google Scholar] [CrossRef] [Scilit]
  177. Ramasamy, Y.; Arunachalam, S.; Dasgupta, M.; Nambiar-Veetil, M. Genetic Markers, Genomics and Genetic Modification in Forest Trees: Current Status and Prospects. In Textbook of Forest Science; Mandal, A.K., Nicodemus, A., Eds.; Springer: Singapore, 2025. [Google Scholar] [CrossRef] [Scilit]
  178. Guo, C.; Ma, X.; Gao, F.; Guo, Y. Off-Target Effects in CRISPR/Cas9 Gene Editing. Front. Bioeng. Biotechnol. 2023, 11, 1143157. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  179. Ballesteros, D.; Martínez, M.T.; Sánchez-Romero, C.; Montalbán, I.A.; Sales, E.; Moncaleán, P.; Arrillaga, I.; Corredoira, E. Current Status of the Cryopreservation of Embryogenic Material of Woody Species. Front. Plant Sci. 2024, 14, 1337152. [Google Scholar] [CrossRef] [Scilit] [PubMed]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Article Metrics

Citations

Article Access Statistics

Journal Statistics
Multiple requests from the same IP address are counted as one view.
Alternating Wetting and Moderate Drying Irrigation Promotes Phosphorus Uptake and Transport in Rice
Previous
Assessing the Sustainability of Miscanthus and Willow as Global Bioenergy Crops: Current and Future Climate Conditions (Part 2)
Next