High-quality reference genomes at the population scale are fundamental for advancing pan-genomic research. However, high-quality genome assembly at the population scale is costly and time-consuming. To overcome these limitations, we developed Reference-Assisted Genome Assembly (RAGA), a hybrid computational tool that combines de novo and reference-based assembly approaches. RAGA efficiently employs existing reference genomes from the same or closely related species in combination with PacBio HiFi reads to produce high-quality alternative long sequences. These sequences can be integrated with de novo assemblies to improve assembly quality across population-scale datasets. The performance of RAGA across various plant genomes demonstrated its ability to reduce the number of contigs, decrease gaps, and correct genome assembly errors. The implementation of RAGA (available at https://github.com/wzxie/RAGA) significantly streamlines population-scale genome assembly workflows, providing a robust foundation for comprehensive pan-genomic investigations. This tool represents a substantial advancement in making large-scale genomic studies more accessible and efficient.

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