Molecular Plant Breeding 2025, Vol.16, No.5, 268-277 http://genbreedpublisher.com/index.php/mpb 273 combination of these technologies enables genomic information to be transformed into field performance more quickly, providing strong technical support for high-yield rice breeding (Bhat et al., 2021). 7.3 Farmer participatory breeding and real-world adoption challenges Farmer participatory breeding can make haplotype breeding more closely integrated with actual production demands. Allowing farmers to directly participate in variety selection and field trials can better identify excellent haplotype materials that not only meet agronomic requirements but also are suitable for the local environment. However, there are still many challenges in the actual promotion, such as farmers’ acceptance of new varieties, the matching of variety quality and market demand, technical services and policy support during the promotion process, etc. Although some farmers' selected strains have high yield and early maturity, they have deficiencies in terms of quality and other aspects, and ultimately failed to be widely promoted. This also reminds us that haplotype breeding must take into account multiple traits and market demands in practical applications (James et al., 2024). 8 Challenges and Research Gaps 8.1 Haplotype resolution limits in complex genomes The yield traits of rice are controlled by many genes, and there are also complex interactions and linkage disequilibrium among these genes. This makes haplotype analysis face the problem of insufficient resolution in the context of complex genomes. Although high-throughput sequencing and GWAS technologies have facilitated the localization of QTLS and candidate genes, polyalleles, gene interactions, and environmental influences have made the precise analysis and functional verification of haplotypes very difficult. Especially in the context of the introduction of intersubspecies or wild rice, genomic structural variations and segregation biases complicate the problem (Adam et al., 2023; Bharamappanavara et al., 2023; Sachdeva et al., 2024). 8.2 Data integration: linking genomics, transcriptomics, and phenomics At present, the integrated analysis of genomic, transcriptomic and phenome data is still insufficient, which hinders the in-depth understanding of the regulatory network of complex traits. Multi-omics joint analysis has been initially applied in candidate gene mining and functional annotation, but the efficiency of data standardization, heterogeneity processing and large-scale data integration remains a technical challenge. The significant variations in the field environment and the insufficient popularity of high-throughput phenotypic techniques have also affected the accuracy of genotype-phenotypic associations (Kiranmai, 2023; Bejjam and Basuthkar, 2024; Sachdeva et al., 2024). 8.3 Socio-economic and policy considerations for large-scale deployment In the field application and large-scale promotion of haplotype breeding, it is not only necessary to solve technical problems, but also to take into account multiple factors such as society, economy and policy. The promotion of superior haplotype varieties is restricted by farmers’ acceptance of new varieties, the construction of seed systems, intellectual property protection and policy support, etc. Especially in developing countries, insufficient resource allocation, inadequate technical training and weak infrastructure have all affected the implementation of haplotype breeding achievements. Moreover, policies on biodiversity conservation and sustainable agriculture have also put forward higher requirements for the promotion of new varieties (Demeke et al., 2022; Withanawasam et al., 2022; Pallavi et al., 2024). 9 Future Prospects 9.1 Multi-omics-driven haplotype discovery for complex traits By integrating multi-omics data, researchers can more comprehensively identify key genes and superior haplotypes related to complex traits such as yield and stress resistance. The combination of genome-wide association study (GWAS) and multi-omics platforms can reveal functional genes and their regulatory networks that regulate traits such as yield and drought resistance, providing theoretical basis and molecular markers for precision breeding (Mahmood et al., 2022). The combination of phenotype, genotype and multi-omics data can significantly improve the prediction accuracy of complex traits such as hybrid rice (Xu et al., 2020; Hu et al., 2021). In the future, with the rapid accumulation and analysis of multi-omics data, the discovery and application
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