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Integrated metabolomic and transcriptomic analyses identify MYB genes regulating key metabolites and agronomic traits in upland cotton Gossypium hirsutum

Nature Genetics volume 57, pages 2819–2830 (2025)Cite this article

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Abstract

Understanding early embryonic development is fundamental for unraveling plant cell differentiation and organogenesis. Here we integrate multiomics data from 403 upland cotton ovules to identify 2,960 metabolic quantitative trait loci and 24,485 expression quantitative trait loci. A key locus, ME_A07, influencing 252 known metabolite levels and expression of 4,293 genes, with the MYB gene GhTT2_A07 identified as central regulator, potentially regulated by a 520 kb inversion. GhTT2_A07 orchestrated both primary and secondary metabolite biosynthesis, influencing agronomic traits. Another locus, ME_A06, driven by the MYB gene Proanthocyanidin Regulator (GhPAR), modulates proanthocyanin content and suggests an ecological adaptation. GhTT2_A07 and GhPAR exhibit both shared and distinct expression profiles, contributing variably to fiber quality and yield. These findings highlight the critical role of MYB genes in the early development of cotton ovules and fibers, offering comprehensive multiomics resources that advance cotton research and molecular breeding.

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Fig. 1: Diversity analysis of 403 cotton population based on metabolic profiling and principal agronomic traits.
Fig. 2: Genomic basis of the early-stage ovule and fiber metabolome and their correlations with important agricultural traits.
Fig. 3: eGWAS analysis identifies ME_A07 as a key regulatory hotspot.
Fig. 4: Candidate gene of the hotspot ME_A07, GhTT2_A07, is regulated by promoter inversion and influences several important traits.
Fig. 5: Identification of GhPAR as the candidate gene regulating PA monomer and dimer.
Fig. 6: Effects of GhTT2_A07 and GhPAR on fiber traits and metabolic alterations.
Fig. 7: A proposed model illustrating the regulatory networks of GhPAR and GhTT2_A07 influencing phenotypes through regulating gene expression and metabolite abundance.

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Data availability

The raw RNA-seq data generated in this study are available in the NCBI BioProject database under accession number PRJNA776409. Genomic sequencing data can be accessed through the China National Center for Bioinformation (CNCB) under accession number PRJCA010331 or through the NCBI BioProject database under accession number PRJNA1277445, PRJNA412456, PRJNA497352, PRJNA605345 and PRJNA680449. Metabolomics data are also available from the CNCB under accession number PRJCA038211, and are also provided in the Supplementary Tables 2, 4 and 5. The assembled genome of the brown cotton cultivar ZMS81 can be downloaded from the CottonGVD database (https://db.cngb.org/cottonGVD/download/) or accessed through the NCBI BioProject database under accession number PRJNA1274689. Source data are provided with this paper.

Code availability

All software used in the study are publicly available and described in Methods and Reporting Summary.

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Acknowledgements

We thank Z. Lin of Huazhong Agricultural University for providing the cotton seeds of GhTT2_A07-OE lines and receptor plants, and R. Yang (the Sanya Institute of Nanjing Agricultural University) and X. Li (Institute of Cotton Research, Chinese Academy of Agricultural Sciences) for assisting in sample collection. We thank the National Cotton Germplasm Midterm Bank (Anyang) for providing the seeds. We thank the National Supercomputing Center in Zhengzhou for providing the computing resources. We thank the Wuhan Metware Biotechnology Co., Ltd. (Wuhan, China) for metabolomic results. This work was supported by the National Natural Science Foundation of China (grant nos. 32122062 to S.H., 32401819 to X.Z.), the National Key Research and Development Program of China (grant nos. 2022YFD1200300 to X.D., 2021YFF1000101 to S.H. and 2022YFF1001400 to Xueke Gao), Xinjiang Science and Technology Major Program (2023A02001 and 2024A02002), the Youth Innovation Program of Chinese Academy of Agricultural Sciences (grant no. Y2023QC23 to Xueke Gao), the Natural Science Foundation of Henan Province (252300421076), the Agricultural Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences and Xinjiang Tianchi Talents Program (S.H. and L.M.).

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Author notes

  1. These authors contributed equally: Xiaomeng Zhang, Xinquan Tian, Xueke Gao.

Authors and Affiliations

  1. State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China

    Xiaomeng Zhang, Xinquan Tian, Xueke Gao, Zhen Peng, Xiaoli Geng, Jun Peng, Hongge Li, Zhenzhen Wang, Zhaoe Pan, Yinhua Jia, Baojun Chen, Daowu Hu, Liru Wang, Baoyin Pang, Aishuang Xing, Xi Wei, Haobo Zhang, Jinjie Cui, Shoupu He, Lei Ma & Xiongming Du

  2. Anyang Institute of Technology, Anyang, China

    Xiaomeng Zhang, Gaofei Sun & Panhong Dai

  3. State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Zhengzhou Research Base, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, China

    Zhen Peng, Hongge Li, Congyang Dai, Shoupu He, Lei Ma & Xiongming Du

  4. National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, China

    Jun Peng, Daowu Hu, Shoupu He & Xiongming Du

  5. State Key Laboratory of Crop Stress Adaptation and Improvement, Henan Joint International Laboratory for Crop Multi-Omics Research, School of Life Sciences, Henan University, Kaifeng, China

    Xiao Wang

  6. National Supercomputing Center in Zhengzhou, Zhengzhou University, Zhengzhou, China

    Shuai Lu & Xu Gao

Authors
  1. Xiaomeng Zhang
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  2. Xinquan Tian
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  3. Xueke Gao
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Contributions

X.D., L.M., J.C. and S.H. conceived of and conceptualized the study. X.Z. performed the bioinformatics analysis and data analysis. X.T. and Xueke Gao designed and performed the experiments. G.S., P.D., X. Wang, S.L., J.P., H.Z. and Xu Gao performed the bioinformatics analysis. Z. Peng, X. Geng, H.L., Z.W., Z. Pan, Y.J., B.C., L.W., D.H., A.X., C.D. and B.P. participated in the phenotype data investigation. X. Wei performed the EMSA experiment. X.Z., X.D., L.M., J.C. and S.H. wrote and revised the paper.

Corresponding authors

Correspondence to Jinjie Cui, Shoupu He, Lei Ma or Xiongming Du.

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Nature Genetics thanks Xueying Guan, Tianzhen Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Distributions of metabolite variation and heritability.

a,b, Coefficient of variation (CV) (a) and broad-sense heritability (H2) (b) for all detected metabolites. Histograms show the distribution of metabolites (vertical axes) against CV and H2 values (horizontal axes), respectively.

Extended Data Fig. 2 Genetic diversity of 403 accessions based on genotype data.

a, Population structure analysis when K = 2, 3 and 4. The x-axis represents the 403 accessions, with G1 (red), G2 (yellow), and G3 (blue) distinguished by different colors. b, Principal component analysis (PCA) conducted on all 403 accessions. c, The phylogenetic tree of the 403 accessions. The colored fiber cottons (brown) were marked.

Extended Data Fig. 3 Analysis of eQTL and their regulated genes.

a, The distribution of eQTL and eGenes, which eQTL regulated. b, Comparison of association significance among local eQTL (n = 8,367), distal eQTL in the same chromosome (distal_intralChr, n = 4,921), and distal eQTL in the different chromosome (distal_interChr, n = 89,352). Box limits and center lines indicate quartiles and medians, respectively. Whiskers denote 1.5× interquartile range and points show outliers. Significances are tested by the two-tailed Student’s t-test. c-d, GO enrichment of Dt-eGenes, which eQTL regulated in subgenome A (c), and subgenome A excluding ME_A07 (d).

Extended Data Fig. 4 The downstream genes regulated by GhTT2_A07 and GhPAR.

a, The Yeast One-Hybrid (Y1H) assay indicates that GhTT2_A07 binds to the promoter regions of GhG6PDH, GhSK1, GhADT6, GhDFR, GhANR, GhLAR, and GhGT. b, The electrophoretic mobility shift assay (EMSA) has confirmed GhTT2_A07’s binding to the promoters of GhSK1, GhANR, and GhLAR in vitro. c, The Yeast One-Hybrid (Y1H) assay demonstrates GhPAR’s binding to the promoter regions of GhDFR, GhANR, GhLAR, and GhGT. d, The electrophoretic mobility shift assay (EMSA) confirms GhPAR’s binding to the promoters of GhDFR, GhANR, GhLAR, and GhGT in vitro. Each experiment was conducted with three independent biological replicates (a-d).

Source data

Extended Data Fig. 5 Characterization of GhTT2_A07 genetic engineered lines.

a, Fiber morphology of GhTT2_A07 overexpression (GhTT2_A07-OE) lines compared to the wild type. b, Comparative analysis of fiber strength, fiber micronaire, and the expression levels of downstream genes regulated by GhTT2_A07 between GhTT2_A07-OE lines and Jin668. c, Fiber morphology of GhTT2_A07-silenced lines compared to the control plants (acc. ZMS81). d, Comparative analysis of the expression levels of downstream genes regulated by GhTT2_A07 between GhTT2_A07-silenced lines and the control plants. Data are presented as mean values +/- SD (b, d). Statistical significances were determined using the two-tailed Student’s t-test (b, d). e, Comparison of GA3 content between GhTT2_A07-silenced lines and the control plants. All comparative analyses were conducted using three independent biological replicates (b, d-e).

Extended Data Fig. 6 Generation and characterization of GhPAR knockout (GhPAR-KO) lines using CRISPR/Cas9.

a, CRISPR/Cas9-mediated generation of GhPAR-KO lines using two distinct single-guide RNAs (sgRNA1 and sgRNA2), with the protospacer-adjacent motif (PAM) highlighted in blue. b. Comparison of fiber strength and fiber micronaire between the wild types, GhPAR-KO-1 lines and GhPAR-KO-4 lines. c, Sequence alterations in GhPAR-KO lines, with deletions and insertions represented by dashes and red texts, respectively. d. qRT-PCR analysis comparing the expression levels of GhDFR, GhANR, GhLAR, and GhGT in ovules (5 DPA) of the wild type, GhPAR-KO-1 lines and GhPAR-KO-4 lines. e, Quantification of various auxins and gibberellin (GA) in ovules (5 DPA) of the wild type, GhPAR-KO-1 lines and GhPAR-KO-4 lines. Data are presented as mean values +/- SD (b, d). Statistical significances are determined using a two-tailed Student’s t-test (b, d). All comparative analyses were conducted with three independent biological replicates (b, d-e).

Extended Data Fig. 7 GWAS for coumarins and identification of the candidate gene GhF6’H1.

a, Manhattan plots showing the SV-GWAS and SNP-GWAS results for scopoline (mws1077_P), scopoletin (pme2993), and scoparone (pme3569). The red rectangle denotes the genomic location of the trait locus on chromosome D08. Comparison of the relative content of three metabolites between two haplotypes. b, Local Manhattan plot (top) and LD heat map (bottom) between 65,705,310 and 65,723,000 bp. The statistical analysis was performed with Bonferroni correction. c, Haplotypes of coumarin locus in the 403 panel. d, Comparison of GhF6’H1 expression between the two haplotypes. n represents the sample size in each haplotype. Box limits and center lines indicate quartiles and medians, respectively, whiskers denote 1.5× interquartile range and points show outliers (a, d). Significances are tested by the two-tailed Student’s t-test (a, d). e, Association between D08 haplotypes and genotypes of the 9.3 kb deletion (DEL) and SNP in the GWAS population. The mapping reads were analyzed using both manual observation (IGV) and software (DELLY).

Extended Data Fig. 8 GWAS for phenolamides and identification of the candidate gene GhAIH.

a, Manhattan plots showing the GWAS results for N-acetylputrescine (pme2693) and agmatine (pmb0501). The red rectangle denotes the genomic location of the trait locus on chromosome D07. b, Local Manhattan plot (top) and LD heat map (bottom) between 6,835,563 and 6,895,484 bp. c, Haplotypes of phenolamide locus in the 403 panel. d-e, Comparison expression levels of GhAIH (d), and the relative content of two metabolites (e), between the two haplotypes. n represents the sample size in each haplotype. Significances are tested by the two-tailed Student’s t-test. Data are presented as median with interquartile range (d). Box limits and center lines indicate quartiles and medians, respectively, whiskers denote 1.5× interquartile range and points show outliers (e). f, Association between D07 haplotypes and genotypes of the 45 bp deletion and SNP in the GWAS population determined by resequencing mapping reads. The significance threshold is P = 0.05/n (where n is the independent SNP number), and the statistical analysis was performed with Bonferroni correction (a-b).

Extended Data Fig. 9 The effect assessment of two MYB homologous genes.

a, Changes in the contents of metabolites due to changes in GhPAR and GhTT2_A07 expression. The rounded rectangle shadow represents metabolites located on ME_A07, and the rectangular shadow represents metabolites on ME_A06. Asterisk indicates DAMs between Group I and Group II. The red-highlighted genes represent critical genes in the metabolic pathway. The solid-line arrows indicate genes verified to be regulated by GhTT2_A07 or GhPAR. b, The relative content of PA monomers and dimers among different haplotypes. The red and blue box indicates a significant increase and decrease in the accumulation of corresponding metabolites in A06HapII or A07 HapII genotypes. The sample size for each haplotype combination, from left to right, is represented as n = 343, 29, 18, 6. Box limits and center lines indicate quartiles and medians, respectively. Whiskers denote 1.5× interquartile range and points show outliers. Significances are tested by the two-tailed Student’s t-test.

Extended Data Fig. 10 Haplotype combination effects of ME_A06 and ME_A07 loci in the F2 population.

a, Fiber morphology of the parent lines Z128 (shorter fiber, carrying A06HapII and A07HapII) and Liao 96-23-30 (longer fiber, carrying both A06HapI and A07HapI), and F2 population (with a range of fiber colors and haplotype combinations). b-c, Heatmap of haplotypes on ME_A06 locus (b) and ME_A07 locus (c) in the F2 population. d, Comparison in agronomic traits among F2 individuals with different haplotype combinations. The sample size for each haplotype combination, from left to right, is represented as n = 23, 30, 19, 25. Box limits and center lines indicate quartiles and medians, respectively. Whiskers denote 1.5× interquartile range and points show outliers. All statistical significances were determined using the two-tailed Student’s t-test.

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Supplementary Figs. 1–19 and source data for Supplementary Figs. 14 and 17.

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Supplementary Tables 1–21 (download XLSX )

Supplementary Table 1. The 32 representative Upland cotton accessions used for the MS2T library construction in this study. Supplementary Table 2. The 4,050 metabolites detected in the MS2T library constructed in this study. Supplementary Table 3. The 403 Upland cotton accessions used in this study. Supplementary Table 4. The raw dataset of metabolites. Supplementary Table 5. The 2,951 metabolites detected in 403 Upland cotton accessions in the study. Supplementary Table 6. The DAMs between Group I (WC) and Group II (brown cotton). Supplementary Table 7. The mGWAS signals (−log P > 7.31) for all the metabolites. Supplementary Table 8. The list of mQTL hotspots. Supplementary Table 9. Pearson’s correlation of 498 known metabolites and fiber traits (P < 10−9). Supplementary Table 10. GO enrichment of genes in the tan module. Supplementary Table 11. The information of genes in the tan module. Supplementary Table 12. The list of eQTL hotspots. Supplementary Table 13. The colocalization results of mGWAS and eGWAS. Supplementary Table 14. Pearson’s correlation of colocated metabolites and eGenes (P < 10−8). Supplementary Table 15. GO enrichment of 4,293 eGenes, which were correlated significantly with 252 metabolites and colocated on the ME_A07. Supplementary Table 16. Loci colocalized for fiber traits, genes and metabolites. Supplementary Table 17. Comparison of Fiber traits located on ME_A07 between two haplotypes. Supplementary Table 18. Comparison of key metabolites between two haplotypes. Supplementary Table 19. Comparison of metabolites located on ME_A07 between two haplotypes. Supplementary Table 20. The primer sequences used in this study. Supplementary Table 21. Whole-genome resequencing information of F2 population used in this study.

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Zhang, X., Tian, X., Gao, X. et al. Integrated metabolomic and transcriptomic analyses identify MYB genes regulating key metabolites and agronomic traits in upland cotton Gossypium hirsutum. Nat Genet 57, 2819–2830 (2025). https://doi.org/10.1038/s41588-025-02363-3

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