Evidence map›Paper›PMID 42283857›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2026

Genetic characteristics and agronomic traits in leafy head Chinese cabbage breeding.

Yancan Li, Bing Cui, Yihui Zhang, Qian Ding, Faujiah Nurhasanah Ritonga, Fengde Wang, Han Zheng, Cheng Li, Yiran Xu, Xingfu Liu and 3 more

Abstract read
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In one paragraph

Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Yancan Li *Shandong Key Laboratory of Bulk Open-field Vegetable Breeding, Institute of Vegetables, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
Bing Cui *Shandong Key Laboratory of Bulk Open-field Vegetable Breeding, Institute of Vegetables, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
Yihui ZhangShandong Key Laboratory of Bulk Open-field Vegetable Breeding, Institute of Vegetables, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
Qian DingWeifang Engineering Vocational College, College of A&F Science and Technology, Weifang, 261000, China.
Faujiah Nurhasanah RitongaFaculty of Forestry, Universitas Sumatera Utara, USU 2 Bekala Campus, Pancurbatu, Deli Serdang, 20355, Indonesia.
Fengde WangShandong Key Laboratory of Bulk Open-field Vegetable Breeding, Institute of Vegetables, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
Han ZhengShandong Key Laboratory of Bulk Open-field Vegetable Breeding, Institute of Vegetables, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
Cheng LiShandong Key Laboratory of Bulk Open-field Vegetable Breeding, Institute of Vegetables, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
Yiran XuShandong Key Laboratory of Bulk Open-field Vegetable Breeding, Institute of Vegetables, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
Xingfu LiuShandong Key Laboratory of Bulk Open-field Vegetable Breeding, Institute of Vegetables, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
Lixia WangShandong Key Laboratory of Bulk Open-field Vegetable Breeding, Institute of Vegetables, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
Jianwei GaoShandong Key Laboratory of Bulk Open-field Vegetable Breeding, Institute of Vegetables, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
Jingjuan LiShandong Key Laboratory of Bulk Open-field Vegetable Breeding, Institute of Vegetables, Shandong Academy of Agricultural Sciences, Jinan, 250100, China. lijj0620@163.com.ORCID http://orcid.org/0000-0002-4983-0924

Funding

Key Technology Research and Development Program of Shandong Province No. 2024LZGC032
6 · The paper itself

Abstract

Chinese cabbage (Brassica rapa L. ssp. pekinensis) is an economically important leafy vegetable cultivated widely in East Asia. Most key agronomic traits in Chinese cabbage are complex quantitative traits, and their underlying genetic regulatory mechanisms remain largely unclear. In this study, we performed a genome-wide association study (GWAS) for 15 agronomic traits using 149 homozygous inbred lines evaluated across three years of field trials. Phenotypic analysis revealed abundant variation for all 15 traits, with coefficients of variation ranging from 16.54% to 44.70% and broad-sense heritability from 0.35 to 0.81 (average = 0.62). RAD-seq yielded 260.19 Gb of clean data, from which 255,001 high-confidence variants were identified. Population structure analysis classified 149 lines into 11 genetic subpopulations, among which Pop2 represented the ancestral group. A total of 60 significant trait-associated loci were detected, several of which showed pleiotropy, while loci associated with individual traits exhibited polygenic additive effects. We predicted 66 candidate genes belonging to various gene families, including protein kinases, ubiquitin ligases, and transcription factors, which participate in key biological processes such as plant growth and development, hormone signal transduction, and cell wall biosynthesis. KASP markers for six associated loci were developed and validated in 96 accessions, and the results were highly consistent with the GWAS findings. The significant loci and candidate genes identified in this study provide novel insights into the molecular basis of agronomic traits in Chinese cabbage and offer valuable genetic resources for molecular breeding.

Indexed as

Brassica rapaPlant BreedingQuantitative Trait LociChromosome MappingGenome-Wide Association StudyPhenotypePolymorphism, Single Nucleotide

Identifiers

PMID42283857

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.