Maize Genomics and Genetics 2024, Vol.15, No.4, 182-190 http://cropscipublisher.com/index.php/mgg 185 3.2 Population genomics Population genomics involves the study of genetic variations within and between populations of maize. High-quality genomic sequences from diverse maize lines have been produced to map important traits and demonstrate the genetic diversity of maize (Hufford et al., 2021). This approach has revealed significant variation in gene content, genome structure, and DNA methylation across different maize accessions. By leveraging whole-genome sequencing (WGS) and whole genome bisulfite sequencing (WGBS), researchers have investigated the adaptive and phenotypic consequences of methylation variations in maize populations, providing insights into the evolutionary forces acting on DNA methylation patterns (Xu et al., 2020). These population genomics studies are essential for understanding the extent and impact of gene flow in maize. 3.3 Phylogeographic approaches Phylogeographic approaches combine phylogenetic and geographic data to study the historical processes that have shaped the genetic structure of maize populations. Phylogenetic analysis based on complete genome sequences has been used to reveal evolutionary relationships among MDMV isolates, highlighting the divergence of isolates from different regions (Wijayasekara et al., 2021). Such analyses help trace the movement and spread of genetic variants across geographical landscapes, providing a historical context for gene flow events. By integrating phylogenetic data with geographic information, researchers can infer the origins and migration patterns of maize populations, thereby elucidating the evolutionary dynamics of gene flow. 3.4 Experimental and observational studies Experimental and observational studies are crucial for validating hypotheses about gene flow in maize. For example, the development and validation of the 5.5 K SNP markers panel using GBTS technology involved extensive genetic analyses of two maize populations, revealing genetic divergences and prediction accuracies for various traits (Ma et al., 2022). These studies provide empirical data on the genetic structure and diversity of maize populations, which are essential for understanding gene flow. Observational studies, such as the analysis of DNA methylation patterns in modern maize, landrace, and teosinte populations, have also shed light on the role of epigenetic variations in adaptive evolution (Xu et al., 2020). Together, these experimental and observational approaches contribute to a comprehensive understanding of gene flow dynamics in maize. 4 Patterns of Gene Flow in Maize 4.1 Gene flow between wild relatives and cultivated maize Gene flow between wild relatives and cultivated maize is a critical factor in the evolutionary dynamics of maize. Wild relatives of crops, such as teosinte, serve as reservoirs of genetic diversity that can be introgressed into cultivated maize. This gene flow can introduce beneficial traits, such as disease resistance and environmental adaptability, into the cultivated gene pool. For instance, the study on crop wild relatives (CWRs) emphasizes the importance of capturing genetic variation from wild relatives to enhance crop improvement efforts (Egan et al., 2018). Similarly, research on wheat has shown that introgression from wild relatives significantly contributes to the adaptive diversity of modern crops, suggesting a parallel importance in maize. 4.2 Introgression and hybridization events Introgression and hybridization events play a pivotal role in shaping the genetic landscape of maize. These processes involve the incorporation of genetic material from one species into the gene pool of another through repeated backcrossing. The study on wheat highlights how introgression from wild relatives has historically contributed to the adaptive evolution of crops by increasing genetic diversity and reducing deleterious alleles(He et al., 2019). This phenomenon is likely mirrored in maize, where hybridization with wild relatives can introduce new alleles that enhance agronomic traits and environmental adaptability. 4.3 Spatial and temporal patterns The spatial and temporal patterns of gene flow in maize are influenced by various factors, including geographic isolation and environmental conditions. The research on woodland strawberry demonstrates that landscape isolation and mesoclimatic variation are significant determinants of genetic variation in wild populations (Egan et al., 2018). These findings suggest that similar spatial proxies could be used to predict gene flow patterns in maize.
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