Tree Genetics and Molecular Breeding 2024, Vol.14, No.5, 239-246 http://genbreedpublisher.com/index.php/tgmb 241 use of SSR markers has facilitated the genetic identification and selection of pitaya accessions with superior traits, aiding in the development of improved cultivars (Nashima et al., 2021). Furthermore, the integration of QTL mapping and MAS allows for the targeted improvement of specific traits, such as fruit size, color, and stress resistance, ultimately leading to the production of high-quality pitaya varieties that meet market demands (Chen et al., 2021; Wu et al., 2021). 4 Genetic Transformation Techniques 4.1 Overview of transformation methods Genetic transformation techniques are pivotal in enhancing the genetic makeup of pitaya (Hylocereus spp.), facilitating the introduction of desirable traits such as improved stress tolerance and enhanced nutritional content. Various biotechnological tools have been employed, including cell and tissue culture, micropropagation, and molecular marker technology, which have been instrumental in the development of pitaya germplasm (Shah et al., 2023). These methods enable the manipulation of genetic material to produce new varieties with improved characteristics, thereby supporting the breeding programs aimed at optimizing pitaya's horticultural potential (Xi et al., 2019; Tel-Zur, 2022). 4.2 CRISPR-Cas systems The CRISPR-Cas system represents a revolutionary tool in genetic engineering, offering precise genome editing capabilities. Although specific applications of CRISPR-Cas in pitaya are not extensively documented in the current literature, the system’s potential for targeted gene modification could significantly advance pitaya breeding. This technology could be used to enhance traits such as betalain biosynthesis, which is crucial for the fruit's coloration and nutritional value (Figure 1) (Zhang et al., 2021). The development of a chromosome-scale genome sequence for pitaya provides a foundational resource that could facilitate the application of CRISPR-Cas systems in future breeding efforts (Chen et al., 2021). Figure 1 Silencing of HmoWRKY40 inhibits betalain production: (A) Virus-induced gene silencing of HmoWRKY40 in red scales. Bars = 2 cm, (B) Betalain contents in pitaya scales after virus-induced silencing of HmoWRKY40 (* indicates p < 0.05). Three independent experiments were conducted (n= 3). The error bars indicate one standard error, (C) RT-qPCR analyses of HmoWRKY40 in virus-induced gene silencing (VIGS) treatment scales. The expression level of pTRV2-HmoWRKY40 was used as the calibrator (set as 1). The data represent mean values from three biological replicates (±S.D.). ** indicates significant differences at p value < 0.01 using a two-tailed t-test and (D) RT-qPCR analyses of HmoCYP76AD1 in VIGS treatment scales. The expression level of pTRV2-HmoCYP76AD1 was used as the calibrator (set as 1).The data represent mean values from three biological replicates (±S.D.). ** indicates significant differences at p value < 0.01 using a two-tailedt-test (Adopted from Zhang et al., 2021)
RkJQdWJsaXNoZXIy MjQ4ODYzMg==