Maize Genomics and Genetics 2024, Vol.15, No.3, 111-122 http://cropscipublisher.com/index.php/mgg 118 5.4 Challenges and Limitations Despite the successes, several challenges and limitations remain in the application of genomics-assisted breeding in maize. One major challenge is the need for large, well-characterized populations for accurate genomic selection, which can be resource-intensive to develop and maintain (Miedaner et al., 2020). Additionally, the complexity of quantitative traits, which are often controlled by multiple genes with small effects, poses a challenge for effective selection and breeding (Gaikpa and Miedaner, 2019). The integration of diverse data types, such as phenotypic, genotypic, and environmental data, into genomic selection models also requires sophisticated computational tools and expertise, which may not be readily available in all breeding programs (Rice and Lipka, 2021). Finally, the adoption of advanced genomic technologies in developing countries is often hindered by limited infrastructure and funding, highlighting the need for international collaboration and support (Guo et al., 2019). While genomics-assisted breeding has revolutionized maize breeding with notable successes and economic benefits, ongoing efforts are needed to address the challenges and ensure the broad adoption and sustainability of these advanced breeding technologies. 6 Future Prospects 6.1 Advances in genomic technologies The future of genomics-assisted breeding in maize is poised to benefit significantly from advances in genomic technologies. High-throughput sequencing technologies (HSTs) have revolutionized crop breeding by enabling the identification of beneficial quantitative trait loci (QTL), genes, and alleles for crop improvement (Farooqi et al., 2022). The integration of doubled haploid production, genomic selection, and genome optimization is expected to facilitate the evolution of maize breeding from an art to a science, and eventually to intelligence, in the Breeding 4.0 era (Jiang et al., 2019). These advancements will allow for the precise manipulation of allelic variation, creating novel diversity and facilitating rapid incorporation into crop improvement programs (Varshney et al., 2021). 6.2 Integration of multi-omics data The integration of multi-omics data, including genomics, transcriptomics, proteomics, and metabolomics, is crucial for enhancing the predictive ability of hybrid performance and improving crop traits (Schrag et al., 2018). Multi-omics approaches have been successfully implemented in various crops, including maize, to elucidate growth, senescence, yield, and responses to biotic and abiotic stress (Yang et al., 2021). The combination of different omics data can improve the prediction of hybrid performance, thereby contributing to more efficient selection of hybrid candidates. This integration is expected to address the challenges of abiotic stresses and enhance maize productivity (Farooqi et al., 2022). 6.3 Precision breeding Precision breeding techniques, such as genome editing and synthetic biology, are set to play a pivotal role in the future of maize breeding. These techniques enable the precise assembly of desired alleles, allowing for the development of climate-resilient and nutrient-sufficient crops (Mahmood et al., 2022). The use of genomic tools and bioinformatics will further aid in the development of high-performance and well-adapted maize hybrids (Muntean et al., 2022). The concept of genomic design breeding, which incorporates genomic selection and genome optimization, will facilitate the creation of optimized genomes expressing optimal phenotypes (Jiang et al., 2019). 6.4 Regulatory and ethical considerations As genomic technologies and precision breeding techniques advance, regulatory and ethical considerations will become increasingly important. The manipulation of genetic material raises questions about the safety and ethical implications of genetically modified organisms (GMOs). It is essential to establish robust regulatory frameworks to ensure the safe and responsible use of these technologies. Additionally, ethical considerations regarding the equitable distribution of benefits and access to advanced breeding technologies must be addressed to prevent disparities between different regions and communities.
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