RAGA: a reference-assisted genome assembly tool for efficient population-scale assembly

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 <i>de novo</i> 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 <i>de novo</i> 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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Publication Details

Journal
Horticulture Research
Published
2025-08-09
DOI
https://doi.org/10.1093/hr/uhaf207
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

RAGA: a reference-assisted genome assembly tool for efficient population-scale assembly

Dongao Li, Yong-Qing Qian, Xingtan Zhang, Jiana Li et al.
Horticulture Research
Genomics and Phylogenetic Studies
article

RAGA: a reference-assisted genome assembly tool for efficient population-scale assembly

Dongao Li, Yong-Qing Qian, Xingtan Zhang, Jiana Li, Ru-Peng Zhao, Shuang Yuan, Yuhong Luo, Zu-Wen Zhou, Jia‐Ming Song, Kun Lu, Wen‐Zhao Xie, Ling‐Ling Chen
article en

Abstract

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 <i>de novo</i> 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 <i>de novo</i> 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.

Horticulture ResearchVol. 12(11)
Southwest University (CN), Guangxi University (CN), Agricultural Genomics Institute at Shenzhen (CN), Ministry of Agriculture Livestock and Fisheries (KE), Ministère de l'Agriculture et de la Souveraineté alimentaire (FR), Nihon Nohyaku (Japan) (JP), Chinese Academy of Agricultural Sciences (CN), State Key Laboratory For Conservation and Utilization of Subtropical Agro-Bioresources (CN), Hebei Normal University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Guangxi Province, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 81%
Genomics and Phylogenetic Studies
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