Maize Genomics and Genetics 2024, Vol.15, No.4, 182-190 http://cropscipublisher.com/index.php/mgg 188 bioinformatics tools, will likely provide even deeper insights into the mechanisms and consequences of gene flow inmaize. Figure 2 MVs clustering with germplasm from different breeding programs (Adopted from Rojas-Barrera et al., 2019) Image caption: (A): Genotype distribution of MV1 and MV2 sampled in sympatry with LRs. LRs are colored by sampling period: earlier than 1960 (LR<1960), dark blue; between 1960 and 1980 (LR 1960 to 1980); light blue; and later than 2000 (LR>2000), purple. (B): Distribution for MV1, MV2, and the LRs collected for this work with a sample subset from the US national maize inbred seed bank (2 578 genotypes and 13 953 SNPs); (C): Clustering of genotypes colored by the breeding program (1 002 genotypes, 13 953 SNPs); ExPVP, expired plant variety protection. (D) Tropical breeding pools from Mexico, Nigeria, Cameroon, MV1, and MV2 (463 genotypes and 13 953 SNPs) (Adopted from Rojas-Barrera et al., 2019) 7.2 Integrative approaches combining ecology and genomics Combining ecological data with genomic information offers a comprehensive understanding of how gene flow impacts maize evolution. Studies have shown that the geographical distribution and environmental adaptation of maize are influenced by both genetic and ecological factors (Wisser et al., 2019). Integrative approaches that merge ecological modeling with genomic data can elucidate how environmental pressures shape genetic diversity and adaptation in maize populations. Such approaches can also help identify key genes involved in adaptation to specific ecological niches, thereby informing breeding programs aimed at developing climate-resilient maize varieties. 7.3 Implications for breeding and conservation The insights gained from gene flow studies have profound implications for maize breeding and conservation. Understanding the genetic basis of adaptation and the impact of gene flow from MVs into LRs and WRs can guide the development of new maize varieties that are both high-yielding and resilient to environmental stresses (Rojas-Barrera et al., 2019; Wisser et al., 2019). Additionally, conservation strategies can be informed by genomic data to maintain and enhance the genetic diversity of maize. This is crucial for preserving the evolutionary potential of maize and ensuring its long-term sustainability as a crop.
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