Chromosome-scale assembly of the elite <i>Coptis chinensis</i> cultivar ‘Chulian No.1’ and decoding of fine clonal variations using geospatial-genomic machine learning to facilitate medicinal plant breeding

Abstract Genetic homogenization due to chronic clonal propagation poses a notable challenge to the sustainable utilization of Coptis chinensis Franch. We developed a novel elite cultivar, ‘Chulian No.1,’ with superior yield (+34%), disease resistance, and pharmacopoeia-standard alkaloid profiles through comprehensive agronomic evaluation. To understand the genetic basis of these traits, we constructed a high-quality chromosome-level genome assembly, revealing long terminal repeat (LTR) retrotransposon (comprising 41.92% of the genome) show significant enrichment near expanded stress/alkaloid biosynthesis genes. Whole-genome resequencing of 235 accessions indicated extreme genetic uniformity (π &amp;lt; 0.0018), but our novel geospatial-autoencoder model successfully identified three eco-geographic groups that could not be discriminated using traditional approaches. Genome-wide association analysis identified the leaf glossiness-associated gene CcHAB1 on chromosome 1. Comparative transcriptomics revealed correlations between CcHAB1 expression and cuticular wax biosynthesis gene regulation via ABA and phenylpropanoid pathways, potentially explaining enhanced disease resistance in glossy-leaf accessions. This work enables molecular breeding for medicinal plants with limited genetic diversity and provides insights into trait maintenance despite genetic homogenization.

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Publication Details

Journal
Horticulture Research
Published
2026-03-31
DOI
https://doi.org/10.1093/hr/uhag112
Primary Topic
Plant Surface Properties and Treatments
Type
article
Field-Weighted Citation Impact
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article

Chromosome-scale assembly of the elite Coptis chinensis cultivar ‘Chulian No.1’ and decoding of fine clonal variations using geospatial-genomic machine learning to facilitate medicinal plant breeding

Kaidi Yu, Xiaogang Jiang, Jingmao You, Yuying Yang et al.
Horticulture Research
Plant Surface Properties and Treatments
article

Chromosome-scale assembly of the elite Coptis chinensis cultivar ‘Chulian No.1’ and decoding of fine clonal variations using geospatial-genomic machine learning to facilitate medicinal plant breeding

Kaidi Yu, Xiaogang Jiang, Jingmao You, Yuying Yang, Jie Guo, Hua Wang
article en

Abstract

Abstract Genetic homogenization due to chronic clonal propagation poses a notable challenge to the sustainable utilization of Coptis chinensis Franch. We developed a novel elite cultivar, ‘Chulian No.1,’ with superior yield (+34%), disease resistance, and pharmacopoeia-standard alkaloid profiles through comprehensive agronomic evaluation. To understand the genetic basis of these traits, we constructed a high-quality chromosome-level genome assembly, revealing long terminal repeat (LTR) retrotransposon (comprising 41.92% of the genome) show significant enrichment near expanded stress/alkaloid biosynthesis genes. Whole-genome resequencing of 235 accessions indicated extreme genetic uniformity (π &amp;lt; 0.0018), but our novel geospatial-autoencoder model successfully identified three eco-geographic groups that could not be discriminated using traditional approaches. Genome-wide association analysis identified the leaf glossiness-associated gene CcHAB1 on chromosome 1. Comparative transcriptomics revealed correlations between CcHAB1 expression and cuticular wax biosynthesis gene regulation via ABA and phenylpropanoid pathways, potentially explaining enhanced disease resistance in glossy-leaf accessions. This work enables molecular breeding for medicinal plants with limited genetic diversity and provides insights into trait maintenance despite genetic homogenization.

Horticulture Research
Hubei Academy of Agricultural Sciences (CN)
Openalex Percentile: Top 32%
Plant Surface Properties and Treatments
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Chromosome-scale assembly of the elite <i>Coptis chinensis</i> cultivar ‘Chulian No.1’ and decoding of fine clonal variations using geospatial-genomic machine learning to facilitate medicinal plant breeding — Kaidi Yu, Xiaogang Jiang, et al. · Horticulture Research (2026) | TGRS Research Map | TGRS