Decoding the genomes of medicinal herb: The wild and cultivated Morinda officinalis

Imagine a plant that has been used for centuries in traditional medicine to treat everything from impotence to rheumatism. Now, imagine being able to unlock its genetic blueprint. That’s exactly what our team set out to achieve with Morinda officinalis, a vital yet endangered Chinese medicinal herb.
Decoding the genomes of medicinal herb: The wild and cultivated Morinda officinalis
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Why Study a “Weedy” Root? 

Imagine a plant so potent that its roots have been treasured for centuries to heal ailments, boost vitality, and soothe pain. Morinda officinalis, a vine native to the misty mountains of southern China and Vietnam, is exactly that—a botanical marvel woven into the fabric of traditional medicine. Known as bajitian, its dried roots are a cornerstone of herbal remedies, treating everything from arthritis to infertility (Fig. 1). The market value is ~51 USD/500 g. But this ancient healer is now at a crossroads. Rampant harvesting has pushed wild populations to the brink, while cultivated varieties, though abundant, lack the genetic roadmap to ensure their resilience and potency. 

Figure 1. Unlocking nature’s pharmacy: the genomic quest to save a healing legacy

Cracking the Code: From Leaves to Genomes

Securing wild specimens was no small feat. We collaborated with local experts to locate pristine populations of Morinda officinalis in remote, rugged regions of Guangdong, China. In contrast, cultivated samples were sourced from organized farms in Zhaoqing City. Meanwhile, the wild variety—originally discovered in the forests of Yunfu City—is now maintained at the experimental farm of South China Agricultural University in Guangzhou for further research. Back in the lab, we applied nanopore long-read sequencing and Hi-C technology to assemble their genomes. Nanopore sequencing enabled us to read long stretches of DNA like full sentences, while Hi-C provided the structural framework, organizing these sequences into complete chromosome-level assembly (Fig. 2)

Figure 2. From the lab bench to the command line - our first author Ms. Ruirui Li balances wet lab experiments and bioinformatics analyses to drive discoveries forward

Key Discoveries

  • Structural Divergence: The cultivated genome (425 Mb) was slightly larger than the wild (423 Mb), yet its scaffold N50 (10.99 Mb vs. 5.91 Mb) suggested superior assembly continuity—a win for agricultural genomics.
  • Gene Dynamics: Wild M. officinalis boasted 31,308 genes vs. 29,528 in cultivated, hinting at gene loss during domestication. These “missing genes” could hold keys to stress tolerance or medicinal compound synthesis.
  • Conservation Clues: High BUSCO scores (97%+) validated genome completeness, while Hi-C maps revealed synteny across chromosomes, underscoring evolutionary stability.


What’s Next?

These genomes are just the beginning. By understanding the genetics of wild and cultivated Morinda, future studies could:
Identify Medicinal Genes: Pinpoint the biosynthetic pathways responsible for anthraquinones and iridoids, the key compounds contributing to Bajitian's efficacy.
Boost Cultivation: Use genomic markers to enhance yield, disease resistance, or bioactive content in crops.
Conserve Wild Relatives: Track genetic diversity to prioritize conservation efforts.


A Call to Collaboration

This work is part of The 10,000 plants (10KP) genome sequencing project which aims to sequence over 10,000 genomes representing every major clade of plants (https://db.cngb.org/10kp/). Whether you’re a breeder, ecologist, or pharmacologist—dive into these data. Together, we can ensure M. officinalis thrives for generations, bridging tradition and innovation. We’ve deposited the genomes in public databases NCBI (http://identifiers.org/insdc:JBLRXP000000000) and CNGBdb (https://db.cngb.org/search/project/CNP0004857/) to empower researchers worldwide.


Read the Full Story

Want to dive deeper into work? Check out our paper:
Chromosome-scale genomes of wild and cultivated Morinda officinalis https://www.nature.com/articles/s41597-025-04776-5 

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Genomics
Life Sciences > Biological Sciences > Genetics and Genomics > Genomics
Bioinformatics
Life Sciences > Biological Sciences > Biological Techniques > Computational and Systems Biology > Bioinformatics

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