Plant Gene and Trait 2024, Vol.15, No.6, 285-294 http://genbreedpublisher.com/index.php/pgt 287 Figure 1 Heat map diagram of expression patterns for 116 DEGs (differentially expressed genes) between the males and the females of Eucommia ulmoides (Adopted from Wang and Zhang, 2017) Image caption: The color from red to green indicates the gene expression level towards small. EUCO_M: Males, EUCO_F: Females; the numbers 1/2/3 represent different individuals (Adopted from Wang and Zhang, 2017) 3 Approaches for Marker Identification and Validation 3.1 Plant material selection and DNA sample preparation The selection of appropriate plant material and the preparation of high-quality DNA samples are critical first steps in the identification of sex-specific markers in Eucommia ulmoides. For instance, in the study by a total of 64 AFLP primer combinations were screened to identify a male-specific marker (Wang et al., 2011). Similarly, utilized 20 male and female individual plants to screen for sex-linked molecular markers using ddRAD-seq. These studies highlight the importance of selecting a diverse and representative sample set to ensure the reliability and applicability of the identified markers (Wang et al., 2020; You et al., 2023). 3.2 Molecular techniques for marker development Various molecular techniques have been employed to develop sex-specific markers in Eucommia ulmoides. AFLP and SCAR markers were successfully used in to identify a 350 bp male-specific marker (Wang et al., 2011), which was later converted into a 247 bp SCAR marker. RAPD and SCAR techniques were also utilized in to develop a 569 bp pistillate-specific SCAR marker (Xu et al., 2004). Additionally, ddRAD-seq was applied in to identify a 479 bp male-specific locus (Wang et al., 2020), MSL4, which was validated through PCR and Sanger sequencing. These techniques demonstrate the versatility and effectiveness of different molecular approaches in marker development (Guo et al., 2023). 3.3 Data analysis for marker identification Data analysis plays a crucial role in the identification of sex-specific markers. In bioinformatics analysis was used to predict five candidate male-specific loci from a large dataset of ddRAD-seq data (Figure 2) (Wang et al., 2020). Similarly, employed transcriptome analysis to identify key genes involved in sex differentiation (Du et al., 2023), such as EuAP3 and EuAG. Comparative transcriptome analyses in revealed 116 differentially expressed genes between male and female plants (Wang and Zhang, 2017; Zhang et al., 2023), further aiding in the identification of sex-associated markers. These studies underscore the importance of robust data analysis techniques in marker identification.
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