ORIGINAL RESEARCH article
Front. Plant Sci.
Sec. Plant Systematics and Evolution
Volume 16 - 2025 | doi: 10.3389/fpls.2025.1629553
Population Structure and Genetic Diversity Analysis of Coffee Germplasm Based on RAD-seq in China
Provisionally accepted
Xinlei Jiang
Cheng LiuGuanrun MaMingzhu ZhaoMeifang LiTianming ChenPingxiang ZhaoJingmin WangQin LuoTieying GuoLinlin SuZhirun ZhangJiayi WangZiwei XiaoBing XiaoHua ZhouJinhong Li*Xuehui Bai*- Dehong Tropical Agriculture Research Institute of Yunnan, Ruili, China
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Coffee (Coffea spp.), a globally important crop, faces challenges in germplasm conservation due to habitat loss, climate change, and limited genetic diversity validation. This study aimed to evaluate the genetic representativeness of a coffee germplasm col-lection (CCGC, n=185) spanning major global varieties and wild relatives using re-striction-site associated DNA sequencing (RAD-seq). We performed genome-wide SNP profiling (37,729 loci), population structure analysis (STRUCTURE, PCA), and selection sweep detection (π) to assess genetic diversity, differentiation, and functional gene coverage. Results demonstrated that CCGC captured 98% of known dis-ease-resistance loci (e.g., SH3, RppM) and exhibited high genetic diversity (π=0.1456, He=0.3014), aligning closely with the World Coffee Genetic Resources (WCGR) dataset (similarity >95%). Population structure (K=3) revealed three distinct subgroups, with Group 2 showing the highest diversity (He=0.3014) and complete coverage of Hemileia vastatrix resistance loci. The SNP density (7.5× higher than 5K SNP arrays) enabled precise identification of 47 selective sweep regions linked to domestication and adaptation. These findings validate CCGC as a genomically representative resource for coffee breeding and conservation. This work advances coffee genetic research by bridging resource preservation with molecular breeding strategies to address climate resilience and sustainable production.
Keywords: Coffea1, germplasm collection2, RAD-seq3, SNP markers4, genetic diversity analysis5, population structure analysis6, Sustainable Agriculture7
Received: 16 May 2025; Accepted: 18 Jul 2025.
Copyright: © 2025 Jiang, Liu, Ma, Zhao, Li, Chen, Zhao, Wang, Luo, Guo, Su, Zhang, Wang, Xiao, Xiao, Zhou, Li and Bai. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Jinhong Li, Dehong Tropical Agriculture Research Institute of Yunnan, Ruili, China
Xuehui Bai, Dehong Tropical Agriculture Research Institute of Yunnan, Ruili, China
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