Maize Genomics and Genetics 2024, Vol.15, No.5, 257-269 http://cropscipublisher.com/index.php/mgg 262 which are crucial for improving maize resilience to abiotic stresses (Labuschagne, 2020; Benavente and Giménez, 2021; Kamali and Singh, 2023). Additionally, transcriptomic approaches, including RNA-seq, have provided insights into the gene expression dynamics under stress conditions, revealing novel stress-responsive genes and pathways (Li et al., 2017; Kamali and Singh, 2023). The integration of these genomic tools with advanced breeding techniques, such as CRISPR-Cas9, has further enhanced the precision and efficiency of developing stress-tolerant maize cultivars (Kamali and Singh, 2023). Research has extensively focused on both biotic and abiotic stress resistance in maize. For abiotic stresses, studies have highlighted the importance of transcription factors (TFs) in regulating stress responses. Specific TF families and their downstream target genes have been identified as crucial players in enhancing maize's tolerance to drought, salinity, heat, and cold (Li et al., 2017; Kimotho et al., 2019). For instance, RNA-seq analysis has identified differentially expressed genes (DEGs) involved in hormone metabolism, transcription regulation, and lipid signaling, which are common to multiple abiotic stresses (Li et al., 2017). In terms of biotic stress resistance, maize has been studied for its responses to arthropod herbivory and diseases. The physiological, biochemical, and molecular responses to these biotic factors involve complex defense mechanisms, including inducible and constitutive defenses. The simultaneous occurrence of abiotic and biotic stresses poses additional challenges, necessitating a comprehensive understanding of the interplay between different stress factors (Chávez-Arias et al., 2021). 4.5 Nutritional enhancement through genomics Genomic research has also been directed towards enhancing the nutritional quality of maize. Efforts have included the identification and manipulation of genes involved in nutrient biosynthesis and accumulation. Techniques such as marker-assisted selection and genomic selection have been employed to improve traits related to nutritional quality, such as increased vitamin and mineral content (Benavente and Giménez, 2021; Prasanna et al., 2021). The use of transcriptomics and other omics technologies has further facilitated the understanding of the molecular mechanisms underlying nutrient biosynthesis, enabling targeted breeding for enhanced nutritional traits (Kamali and Singh, 2023). Biofortification efforts in maize have led to the development of varieties with increased levels of essential vitamins and minerals. For example, genomic approaches have been used to enhance the content of provitamin A, iron, and zinc in maize kernels. These biofortified varieties aim to address micronutrient deficiencies in populations that rely heavily on maize as a staple food. The integration of genomic tools with traditional breeding methods has accelerated the development of nutritionally enhanced maize varieties, contributing to improved food security and public health (Benavente and Giménez, 2021; Prasanna et al., 2021). 5 Challenges in Maize Genomic Research 5.1 Technical and methodological challenges Maize genomics faces significant technical challenges due to the complexity of its genome. The maize genome is characterized by a high content of repetitive elements, which complicates sequencing and assembly processes. For instance, the assembly of the maize genome using single-molecule real-time sequencing revealed over 130 000 intact transposable elements, highlighting the intricate nature of the genome (Jiao et al., 2017). Additionally, the presence of structural variations and methylation patterns across different maize lines adds another layer of complexity to data analysis, as demonstrated by the comparative analysis of 26 diverse maize genomes (Figure 2) (Hufford et al., 2021). Assembling and annotating the maize genome is particularly challenging due to its large size and repetitive sequences. Efforts to create gapless assemblies of maize chromosomes using long-read technologies have shown promise, but the process remains arduous. For example, a study achieved gapless assemblies of certain maize chromosomes, yet the overall assembly still required merging multiple contigs and dealing with highly repetitive regions (Liu et al., 2020). Moreover, the annotation of gene models and transposable elements requires integrating various data types, such as RNA-seq and bisulfite sequencing, to achieve accurate results (Springer et al., 2018).
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