Genomic map reveals keys to boosting flowering Chinese cabbage yields

Flowering Chinese cabbage, a staple leafy vegetable across Asia, has undergone decades of breeding to improve adaptability, productivity, and quality. Researchers have now conducted the most comprehensive genomic study of this crop to date, sequencing over 400 accessions and combining phenotypic and transcriptomic data. Their findings reveal more than 640 loci and thousands of candidate genes linked to essential agronomic traits such as plant architecture and yield. By tracking how alleles were selected during different breeding stages, the study illuminates how modern varieties adapted to diverse environments while retaining yield potential. These insights provide a powerful foundation for genomics-assisted breeding of improved cabbage cultivars.

Since humans began domesticating plants thousands of years ago, artificial selection has shaped crop traits for survival, nutrition, and productivity. Yet, for many vegetables, breeding still relies heavily on experience and observation, slowing progress. Advances in next-generation sequencing have transformed the ability to identify genetic signatures underlying desirable traits, as seen in rice, maize, and rapeseed. Flowering Chinese cabbage (Brassica rapa ssp. chinensis var. parachinensis), widely cultivated in Asia, has become an important test case. Despite its growing economic and nutritional value, traditional breeding methods remain time-consuming and limited. Due to these challenges, in-depth research is needed to uncover the genomic basis of agronomic traits in this crop.

A research team from South China Agricultural University and collaborators published (DOI: 10.1093/hr/uhae299) their findings on October 18, 2024, in Horticulture Research. The study presents a genome-wide analysis of 403 flowering Chinese cabbage accessions spanning different breeding periods. By integrating sequencing, phenotyping, and transcriptomic data, the researchers identified the genetic variations and selective sweeps associated with key agronomic traits. Their comprehensive results highlight how modern breeding shaped adaptation and yield improvement, and they provide a genomic roadmap for accelerating future crop enhancement.

The team generated 1.2 terabases of sequencing data, uncovering more than 2.5 million high-confidence single-nucleotide polymorphisms and 650,000 insertions/deletions. Population analyses divided the 403 accessions into three groups: landraces, early improved lines, and modern elite cultivars. Genetic diversity decreased with breeding progress, yet key alleles were retained, indicating only a mild bottleneck. Selection scans revealed two distinct breeding phases: first, improving environmental adaptability through genes linked to nitrate uptake and stress responses (such as NLP7, CLC-a, NPF7.2, and WRKY53), and later, enhancing yield via genes controlling organ growth and morphogenesis (including CUC2, DCAF1, RBR1, and PLL5). Genome-wide association studies linked 642 loci to 11 agronomic traits, ranging from plant height and leaf size to stalk weight and diameter. Importantly, overlapping signals between GWAS and selective sweeps pinpointed pleiotropic genes like Bra_cxA09g068050 (SRF3) and Bra_cxA01g042490 (DEM1), both strongly tied to multiple yield traits. Transcriptome analysis further identified 389 differentially expressed genes in stalk development, underscoring the complex network driving cabbage productivity. Collectively, these findings offer the first large-scale genetic map for targeted breeding of flowering Chinese cabbage.

“Our study demonstrates how modern genomics can decode the evolutionary story of a vegetable that millions rely on daily,” said corresponding author Prof. Changming Chen. “By sequencing hundreds of accessions, we traced the precise genetic changes that allowed flowering Chinese cabbage to thrive in wider environments while boosting yield. Identifying candidate genes for plant architecture, leaf development, and stalk growth opens new doors for breeders. With these genomic resources, we can design varieties tailored to both farmer needs and consumer preferences, speeding progress beyond traditional methods”.

The genomic roadmap established in this study provides practical tools for crop improvement. Marker-assisted and genomic selection can now be applied to accelerate the breeding of flowering Chinese cabbage varieties that combine high yield, stress tolerance, and quality. Insights into nitrate uptake and stress-response genes could guide development of cultivars requiring fewer chemical inputs, supporting sustainable agriculture. Meanwhile, loci linked to stalk weight and architecture will aid breeders in producing market-preferred traits. Beyond cabbage, the methods and resources generated here can be extended to other Brassica crops, strengthening global food security through precision breeding.

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References

DOI

10.1093/hr/uhae299

Original Source URL

https://doi.org/10.1093/hr/uhae299

Funding information

This work was funded by the Key-Area Research and Development Program of Guangdong Province (2022B0202080001), the Science and Technology Program of Guangzhou (202206010173, 2023B03J1270), the Seed Industry Revitalization Project of Guangdong Province Rural Revitalization Strategy Special Fund in 2022 (2024-NPY-03-001), the Guangdong Province Seed Industry Revitalization Project (2022-NJS-03-001), and the Guangzhou Agricultural Support Fund Project (Sui Cai Bian [2023] No. 1).

About Horticulture Research

Horticulture Research is an open access journal of Nanjing Agricultural University and ranked number one in the Horticulture category of the Journal Citation Reports ™ from Clarivate, 2023. The journal is committed to publishing original research articles, reviews, perspectives, comments, correspondence articles and letters to the editor related to all major horticultural plants and disciplines, including biotechnology, breeding, cellular and molecular biology, evolution, genetics, inter-species interactions, physiology, and the origination and domestication of crops.