Multielement stoichiometry of cotton (Gossypium genus) and its improvement potential through the use of genetic variation

Abstract

According to the geochemical niche hypothesis, different species have unique elemental compositions, but the elemental stoichiometry of cotton (Gossypium genus) has not been systematically studied. The rich variation and patterns in elemental stoichiometry within cotton can indicate potential directions for breeding. We studied the concentrations of 15 elements (carbon, nitrogen, calcium, potassium, sulfur, phosphorus, magnesium, iron, si-licon, manganese, boron, zinc, nickel, copper, and molybdenum) in the leaves of 18 different cotton species grown in a common garden and compared them with global plant averages. Compared with the global plant averages, the cotton had advantages in nitrogen, calcium, potassium, sulfur, phosphorus, boron, nickel, and molybdenum concentrations. Through redundancy analysis, we confirmed that the elemental stoichiometric variation in cotton was mainly influenced by ploidy level, domestication status, and genome type, which indicated that the elemental composition of cotton can be adjusted by changes in these aspects. Magnesium and calcium exhibited strong centrality in the elemental network of cotton, limiting the variation in the concentrations of sulfur, iron, zinc, nickel, and boron. These results enhance our understanding of cotton species and suggest that greater attention should be given to magnesium and calcium in future breeding.

Keywords

Cotton / Domestication status / Element stoichiometry / Genome type / Ploidy level

Authors' contribution

Ziliang Li: Writing-original draft, Formal analysis, Data curation. Zhangying Lei: Writing-review & editing, Funding acquisition, Data curation. Mengmeng Jia: Methodology, Data curation. Ülo Niinemets: Writing-review & editing, Supervision. Wangfeng Zhang: Writing-review & editing, Supervision. Fang Liu: Supervision, Resources. Yali Zhang: Writing-review & editing, Funding acquisition, Conceptualization.

Abbreviations

Not applicable.

Availability of data and materials

The data used for this study are attached in the Supporting Information and are freely accessible.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Author Yali Zhang (Editorial Board member) was not involved in the journal's review or decisions related to this manuscript.

Acknowledgements

This research was financially supported by the Natural Science Foundation of Xinjiang Production and Construction Corps (2024DA002), the Tianshan Talent Development Program for Yali Zhang, the Earmarked Fund for XJARS-Cotton (XJARS-03), the 111 Project (D20018), the National Natural Science Foundation of China (32301956), PhD Start-up Research Fund of Northwest A&F University (Z2452023053) for Zhangying Lei, and the funding of Estonian Ministry of Education and Science (Center of Excellence AgroCropFuture).

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.crope.2025.10.002.

References

[1] Ågren G.I., Weih M., 2020. Multi-dimensional plant element stoichiometry—looking beyond carbon, nitrogen, and phosphorus. Front. Plant Sci. 11, 23. https://doi.org/10.3389/fpls.2020.00023.

[2] Billard V., Maillard A., Coquet L., Jouenne T., Cruz F., Garcia-Mina J.M., Yvin J.C., Ourry A., Etienne P., 2016. Mg deficiency affects leaf Mg remobilization and the proteome in Brassica napus. Plant Physiol. Biochem. 107, 337-343. https://doi.org/10.1016/j.plaphy.2016.06.025.

[3] Bitomský M., Kobrlová L., Hroneš M., Klimešová J., Duchoslav M., 2022. Stoichiometry versus ecology: the relationships between genome size and guanine-cytosine content, and tissue nitrogen and phosphorus in grassland herbs. Ann. Bot. 130, 189-197. https://doi.org/10.1093/aob/mcac079.

[4] Blomberg S.P., Garland T., Ives A.R., 2003. Testing for phylogenetic signal in comparative data: behavioral traits are more labile. Evolution 57, 717-745. https://doi.org/10.1111/j.0014-3820.2003.tb00285.x.

[5] Bose J., Babourina O., Rengel Z., 2011. Role of magnesium in alleviation of aluminium toxicity in plants. J. Exp. Bot. 62, 2251-2264. https://doi.org/10.1093/jxb/erq456.

[6] Buchfink B., Reuter K., Drost H.G., 2021. Sensitive protein alignments at tree-of-life scale using DIAMOND. Nat. Methods 18, 366-368. https://doi.org/10.1038/s41592-021-01101-x.

[7] Chen Y., Xu Y., Deng B., Zhang S., Zheng D., Liao X., Wang K., Sun X., Jin S., 2021. Stoichiometric characteristics of silicon and calcium in leaves of woody plants on a global scale. Acta Ecol. Sin. 41, 8654-8663. https://doi.org/10.5846/stxb202008052045.

[8] Chen Z., Peng W., Li J., Liao H., 2018. Functional dissection and transport mechanism of magnesium in plants. Semin. Cell Dev. Biol. 74, 142-152. https://doi.org/10.1016/j.semcdb.2017.08.005.

[9] Cook A.M., Daughton C.D., 1981. Total phosphorus determination by spectrophotometry. In: Methods in Enzymology, Lipids Part D. Academic Press,pp.292-295. https://doi.org/10.1016/S0076-6879(81)72017-2.

[10] Csardi G., Nepusz T., 2006. The igraph software package for complex network research. Inter Journal, Complex Systems, 1695. https://igraph.org.

[11] de Villemereuil P., Gaggiotti O.E., Mouterde M., Till-Bottraud I., 2016. Common garden experiments in the genomic era: new perspectives and opportunities. Heredity 116, 249-254. https://doi.org/10.1038/hdy.2015.93.

[12] Delgado-Baquerizo M., Reich P.B., García-Palacios P., Milla R., 2016. Biogeographic bases for a shift in crop C:N:P stoichiometries during domestication. Ecol. Lett. 19, 564-575. https://doi.org/10.1111/ele.12593.

[13] Dixon P., 2003. VEGAN, a package of R functions for community ecology. J. Veg. Sci. 14, 927-930. https://doi.org/10.1111/j.1654-1103.2003.tb02228.x.

[14] Dordas C., 2009. Dry matter, nitrogen and phosphorus accumulation, partitioning and remobilization as affected by N and P fertilization and source-sink relations. Eur. J. Agron. 30, 129-139. https://doi.org/10.1016/j.eja.2008.09.001.

[15] Elser J.J., Sterner R.W., Gorokhova E., Fagan W.F., Markow T.A., Cotner J.B., Harrison J. F., Hobbie S.E., Odell G.M., Weider L.W., 2000. Biological stoichiometry from genes to ecosystems. Ecol. Lett. 3, 540-550. https://doi.org/10.1046/j.1461-0248.2000.00185.x.

[16] Emms D.M., Kelly S., 2019. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 20, 238. https://doi.org/10.1186/s13059-019-1832-y.

[17] Epstein E., 1999. Silicon. Annu. Rev. Plant Physiol. Plant Molec. Biol. 50, 641-664. https://doi.org/10.1146/annurev.arplant.50.1.641.

[18] Faizullah L., Morton J.A., Hersch-Green E.I., Walczyk A.M., Leitch A.R., Leitch I.J., 2021. Exploring environmental selection on genome size in angiosperms. Trends Plant Sci. 26, 1039-1049. https://doi.org/10.1016/j.tplants.2021.06.001.

[19] Fryxell P.A., 1992. A revised taxonomic interpretation of Gossypium L. (Malvaceae). Rheedea 2, 108-165.

[20] Furey G.N., Tilman D., 2023. Plant chemical traits define functional and phylogenetic axes of plant biodiversity. Ecol. Lett. 26, 1394-1406. https://doi.org/10.1111/ele.14262.

[21] Galili T., 2015. dendextend: an R package for visualizing, adjusting and comparing trees of hierarchical clustering. Bioinformatics 31, 3718-3720. https://doi.org/10.1093/bioinformatics/btv428.

[22] García-Palacios P., Milla R., Delgado-Baquerizo M., Martín-Robles N., Á lvaro-Sánchez M., Wall D.H., 2013. Side-effects of plant domestication: ecosystem impacts of changes in litter quality. New Phytol. 198, 504-513. https://doi.org/10.1111/nph.12127.

[23] Grusak M.A., Broadley M.R., White P.J., 2016. Plant macro-and micronutrient minerals. In: Encyclopedia of Life Sciences. John Wiley & Sons, Ltd, pp. 1-6. https://doi.org/10.1002/9780470015902.a0001306.pub2.

[24] Han W., Fang J., Reich P.B., Ian Woodward F., Wang Z., 2011. Biogeography and variability of eleven mineral elements in plant leaves across gradients of climate, soil and plant functional type in China. Ecol. Lett. 14, 788-796. https://doi.org/10.1111/j.1461-0248.2011.01641.x.

[25] Hao Z., Kuang Y., Kang M., 2015. Untangling the influence of phylogeny, soil and climate on leaf element concentrations in a biodiversity hotspot. Funct. Ecol. 29, 165-176. https://doi.org/10.1111/1365-2435.12344.

[26] Hu G., Grover C.E., Jareczek J., Yuan D., Dong Y., Miller E., Conover J.L., Wendel J. F., 2021. Evolution and diversity of the cotton genome. In: Rahman M.u., Zafar Y., Zhang T. (Cotton Precision Breeding.Eds.), Springer, Cham, pp. 25-78. https://doi.org/10.1007/978-3-030-64504-5_2.

[27] Huang G., Wu Z., Percy R.G., Bai M., Li Y., Frelichowski J.E., Hu J., Wang K., Yu J. Z., Zhu Y., 2020. Genome sequence of Gossypium herbaceum and genome updates of Gossypium arboreum and Gossypium hirsutum provide insights into cotton A-genome evolution. Nat. Genet. 52, 516-524. https://doi.org/10.1038/s41588-020-0607-4.

[28] Huang H., 2021. linkET: Everything is Linkable. R Package Version 0.0.3.

[29] Huang X., Ouyang K., Luo Y., Xie G., Yang Y., Zhang J., 2022. A comparative study of characteristics in diploid and tetraploid Anoectochilus roxburghii. Front. Nutr. 9, 1034751.

[30] Kaiser B.N., Gridley K.L., Ngaire Brady J., Phillips T., Tyerman S.D., 2005. The role of molybdenum in agricultural plant production. Ann. Bot. 96, 745-754. https://doi.org/10.1093/aob/mci226.

[31] Kastori R., Putnik-Delić M., Maksimović I., 2022. Functions of nickel in higher plants: a review. Acta Agric. Serbica 27, 89-101. https://doi.org/10.5937/AASer2253089K.

[32] Keck F., Rimet F., Bouchez A., Franc A., 2016. Phylosignal: an R package to measure, test, and explore the phylogenetic signal. Ecol. Evol. 6, 2774-2780. https://doi.org/10.1002/ece3.2051.

[33] Kirkby E.A., 2023. Introduction, definition, and classification of nutrients. In: Rengel Z., Cakmak I., White P.J. (Marschner's Mineral Nutrition of Plants, fourth ed..Eds.), Academic Press, San Diego, pp. 3-9. https://doi.org/10.1016/B978-0-12-819773-8.00016-2.

[34] Lei Z., Li Z., Zhang W., He D., Zhang Y., 2024. From wild to cultivated crops: general shift in morphological and physiological traits for yield enhancement following domestication. Crop Environ. 3, 138-146. https://doi.org/10.1016/j.crope.2024.03.001.

[35] Lei Z., Liu F., Wright I.J., Carriquí M., Niinemets Ü., Han J., Jia M., Atwell B.J., Cai X., Zhang W., Zhou Z., Zhang Y., 2022. Comparisons of photosynthetic and anatomical traits between wild and domesticated cotton. J. Exp. Bot. 73, 873-885. https://doi.org/10.1093/jxb/erab293.

[36] Lei Z., Wang H., Wright I.J., Zhu X., Niinemets Ü., Li Z., Sun D., Dong N., Zhang W., Zhou Z., Liu F., Zhang Y., 2021. Enhanced photosynthetic nitrogen use efficiency and increased nitrogen allocation to photosynthetic machinery under cotton domestication. Photosynth. Res. 150, 239-250. https://doi.org/10.1007/s11120-021-00872-w.

[37] Lesturgez G., Poss R., Noble A., Grünberger O., Chintachao W., Tessier D., 2006. Soil acidification without pH drop under intensive cropping systems in Northeast Thailand. Agric. Ecosyst. Environ. 114, 239-248. https://doi.org/10.1016/j.agee.2005.10.020.

[38] Li L., Stoeckert C.J., Roos D.S., 2003. OrthoMCL: identification of ortholog groups for eukaryotic genomes. Genome Res. 13, 2178-2189. https://doi.org/10.1101/gr.1224503.

[39] Li Y., Cui S., Chang S.X., Zhang Q., 2019. Liming effects on soil pH and crop yield depend on lime material type, application method and rate, and crop species: a global meta-analysis. J. Soils Sediments 19, 1393-1406. https://doi.org/10.1007/s11368-018-2120-2.

[40] Li Y., Zhang Q., Wang R., Gou X., Wang H., Wang S., 2012. Temperature changes the dynamics of trace element accumulation in Solanum tuberosum L. Clim. Change 112, 655-672. https://doi.org/10.1007/s10584-011-0251-1.

[41] Li Z., Lei Z., Jia M., Niinemets Ü., Zhang W., Liu F., Zhang Y., 2025. Patterns of domestication in upland cotton (Gossypium hirsutum): a perspective from multielement stoichiometry. BMC Plant Biol. 25, 1093. https://doi.org/10.1186/s12870-025-07154-w.

[42] Liao P., Huang S., Zeng Y., Shao H., Zhang J., van Groenigen K.J., 2021. Liming increases yield and reduces grain cadmium concentration in rice paddies: a meta-analysis. Plant Soil 465, 157-169. https://doi.org/10.1007/s11104-021-05004-w.

[43] Liu G., Ye X., Huang Z., Dong M., Cornelissen J.H.C., 2019. Leaf and root nutrient concentrations and stoichiometry along aridity and soil fertility gradients. J. Veg. Sci. 30, 291-300. https://doi.org/10.1111/jvs.12717.

[44] Ma S., He F., Tian D., Zou D., Yan Z., Yang Y., Zhou T., Huang K., Shen H., Fang J., 2018. Variations and determinants of carbon content in plants: a global synthesis. Biogeosciences 15, 693-702. https://doi.org/10.5194/bg-15-693-2018.

[45] Mao B., Wang Y., Zhao T., Zhao Q., San Y., Xiao S., 2022. Response of carbon, nitrogen and phosphorus concentration and stoichiometry of plants and soils during a soybean growth season to O₃ stress and straw return in Northeast China. Sci. Total Environ. 822, 153573. https://doi.org/10.1016/j.scitotenv.2022.153573.

[46] Marschner H., 1995. Mineral Nutrition of Higher Plants, second ed.ed. Academic Press, London. https://doi.org/10.1016/B978-012473542-2/50003-1.

[47] Martín-Robles N., Morente-López J., Freschet G.T., Poorter H., Roumet C., Milla R., 2019. Root traits of herbaceous crops: Pre-adaptation to cultivation or evolution under domestication? Funct. Ecol. 33, 273-285. https://doi.org/10.1111/1365-2435.13231.

[48] Meng Q., Gu J., Xu Z., Zhang J., Tang J., Wang A., Wang P., Liu Z., Rong Y., Xie P., Hui L., Udall J.A., Grover C.E., Wendel J.F., Jin S., Zhang X., Yuan D., 2023. Comparative analysis of genome sequences of the two cultivated tetraploid cottons, Gossypium hirsutum (L.) and G. barbadense (L.). Ind. Crops Prod. 196, 116471. https://doi.org/10.1016/j.indcrop.2023.116471.

[49] Mondolot L., Marlas A., Barbeau D., Gargadennec A., Pujol B., McKey D., 2008. Domestication and defence: Foliar tannins and C/N ratios in cassava and a close wild relative. Acta Oecol. 34, 147-154. https://doi.org/10.1016/j.actao.2008.05.009.

[50] Nguyen L.T., Schmidt H.A., von Haeseler A., Minh B.Q., 2015. IQ-TREE: A fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268-274. https://doi.org/10.1093/molbev/msu300.

[51] Onoda Y., Wright I.J., Evans J.R., Hikosaka K., Kitajima K., Niinemets Ü., Poorter H., Tosens T., Westoby M., 2017. Physiological and structural tradeoffs underlying the leaf economics spectrum. New Phytol. 214, 1447-1463. https://doi.org/10.1111/nph.14496.

[52] Ouyang M., Tian D., Niklas K.J., Yan Z., Han W., Yu Q., Chen G., Ji C., Tang Z., Fang J., 2024. The scaling of elemental stoichiometry and growth rate over the course of bamboo ontogeny. New Phytol. 241, 1088-1099. https://doi.org/10.1111/nph.19408.

[53] Pagel M., 1999. Inferring the historical patterns of biological evolution. Nature 401, 877-884. https://doi.org/10.1038/44766.

[54] Pandey N., 2018. Role of plant nutrients in plant growth and physiology. In: Hasanuzzaman M., Fujita M., Oku H., Nahar K., Hawrylak-Nowak B. (Plant Nutrients and Abiotic Stress Tolerance.Eds.), Springer, Singapore, pp. 51-93. https://doi.org/10.1007/978-981-10-9044-8_2.

[55] Paterson A.H., Wendel J.F., Gundlach H., Guo H., Jenkins J., Jin D., Llewellyn D., Showmaker K.C., Shu S., Udall J., Yoo M., Byers R., Chen W., Doron-Faigenboim A., Duke M.V., Gong L., Grimwood J., Grover C., Grupp K., Hu G., Lee T., Li J., Lin L., Liu T., Marler B.S., Page J.T., Roberts A.W., Romanel E., Sanders W.S., Szadkowski E., Tan X., Tang H., Xu C., Wang J., Wang Z., Zhang D., Zhang L., Ashrafi H., Bedon F., Bowers J.E., Brubaker C.L., Chee P.W., Das S., Gingle A.R., Haigler C.H., Harker D., Hoffmann L.V., Hovav R., Jones D. C., Lemke C., Rahman S., Rainville L.N., Rambani A., Reddy U.K., Rong J., Saranga Y., Scheffler B.E., Scheffler J.A., Stelly D.M., Triplett B.A., Van Deynze A., Vaslin M.F.S., Waghmare V.N., Walford S.A., Wright R.J., Zaki E.A., Zhang T., Dennis E.S., Mayer K.F.X., Peterson D.G., Rokhsar D.S., Wang X., Schmutz J., 2012. Repeated polyploidization of Gossypium genomes and the evolution of spinnable cotton fibres. Nature 492, 423-427. https://doi.org/10.1038/nature11798.

[56] Peñuelas J., Fernández-Martínez M., Ciais P., Jou D., Piao S., Obersteiner M., Vicca S., Janssens I.A., Sardans J., 2019. The bioelements, the elementome, and the biogeochemical niche. Ecology 100, e02652. https://doi.org/10.1002/ecy.2652.

[57] Pereira G.L., Siqueira J.A., Batista-Silva W., Cardoso F.B., Nunes-Nesi A., Araújo W. L., 2021. Boron: more than an essential element for land plants? Front. Plant Sci. 11, 610307. https://doi.org/10.3389/fpls.2020.610307.

[58] R Core Team, 2024. R: a Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.

[59] Revell L.J., 2024. Phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). Peer J. 12, e16505. https://doi.org/10.7717/peerj.16505.

[60] Rietra R.P.J.J., Heinen M., Dimkpa C.O., Bindraban P.S., 2017. Effects of nutrient antagonism and synergism on yield and fertilizer use efficiency. Commun. Soil Sci. Plant Anal. 48, 1895-1920. https://doi.org/10.1080/00103624.2017.1407429.

[61] Rivas-Ubach A., Sardans J., Pérez-Trujillo M., Estiarte M., Pen-uelas J., 2012. Strong relationship between elemental stoichiometry and metabolome in plants. Proc. Natl. Acad. Sci. U. S. A. 109, 4181-4186. https://doi.org/10.1073/pnas.1116092109.

[62] Schuman G.E., Stanley M.A., Knudsen D., 1973. Automated total nitrogen analysis of soil and plant samples. Soil Sci. Soc. Am. J. 37, 480-481. https://doi.org/10.2136/sssaj1973.03615995003700030045x.

[63] Sistla S.A., Appling A.P., Lewandowska A.M., Taylor B.N., Wolf A.A., 2015. Stoichiometric flexibility in response to fertilization along gradients of environmental and organismal nutrient richness. Oikos 124, 949-959. https://doi.org/10.1111/oik.02385.

[64] Sterner R.W., Elser J.J., 2017. Ecological Stoichiometry:the Biology of Elements from Molecules to the Biosphere, Ecological Stoichiometry. Princeton University Press. https://doi.org/10.1515/9781400885695.

[65] Syngelaki E., Paetzold C., Hörandl E., 2021. Gene expression profiles suggest a better cold acclimation of polyploids in the alpine species Ranunculus kuepferi (Ranunculaceae). Genes 12, 1818. https://doi.org/10.3390/genes12111818.

[66] Therby-Vale R., Lacombe B., Rhee S.Y., Nussaume L., Rouached H., 2022. Mineral nutrient signaling controls photosynthesis: focus on iron deficiency-induced chlorosis. Trends Plant Sci. 27, 502-509. https://doi.org/10.1016/j.tplants.2021.11.005.

[67] Tian D., Reich P.B., Chen H.Y.H., Xiang Y., Luo Y., Shen Y., Meng C., Han W., Niu S., 2019. Global changes alter plant multi-element stoichiometric coupling. New Phytol. 221, 807-817. https://doi.org/10.1111/nph.15428.

[68] Tian D., Yan Z., Fang J., 2021. Review on characteristics and main hypotheses of plant ecological stoichiometry. Chin. J. Plant Ecol. 45, 682-713. https://doi.org/10.17521/cjpe.2020.0331.

[69] Tian D., Yan Z., Schmid B., Kattge J., Fang J., Stocker B.D., 2024. Environmental versus phylogenetic controls on leaf nitrogen and phosphorous concentrations in vascular plants. Nat. Commun. 15, 5346. https://doi.org/10.1038/s41467-024-49665-4.

[70] Valverde-Barrantes O.J., Smemo K.A., Blackwood C.B., 2015. Fine root morphology is phylogenetically structured, but nitrogen is related to the plant economics spectrum in temperate trees. Funct. Ecol. 29, 796-807. https://doi.org/10.1111/1365-2435.12384.

[71] Vonk J.A., Smulders F.O.H., Christianen M.J.A., Govers L.L., 2018. Seagrass leaf element content: A global overview. Mar. Pollut. Bull. 134, 123-133. https://doi.org/10.1016/j.marpolbul.2017.09.066.

[72] Wang M., Li J., Qi Z., Long Y., Pei L., Huang X., Grover C.E., Du X., Xia C., Wang P., Liu Z., You J., Tian X., Ma Y., Wang R., Chen X., He X., Fang D.D., Sun Y., Tu L., Jin S., Zhu L., Wendel J.F., Zhang X., 2022. Genomic innovation and regulatory rewiring during evolution of the cotton genus Gossypium. Nat. Genet. 54, 1959-1971. https://doi.org/10.1038/s41588-022-01237-2.

[73] Wang M., Tu L., Lin M., Lin Z., Wang P., Yang Q., Ye Z., Shen C., Li J., Zhang L., Zhou X., Nie X., Li Z., Guo K., Ma Y., Huang C., Jin S., Zhu L., Yang X., Min L., Yuan D., Zhang Q., Lindsey K., Zhang X., 2017. Asymmetric subgenome selection and cis-regulatory divergence during cotton domestication. Nat. Genet. 49, 579-587. https://doi.org/10.1038/ng.3807.

[74] Watanabe T., Broadley M.R., Jansen S., White P.J., Takada J., Satake K., Takamatsu T., Tuah S.J., Osaki M., 2007. Evolutionary control of leaf element composition in plants. New Phytol. 174, 516-523. https://doi.org/10.1111/j.1469-8137.2007.02078.x.

[75] Wendel J.F., Brubaker C.L., Seelanan T., 2010. The origin and evolution of Gossypium. In: Stewart J.M., Eds.),Oosterhuis, D.M., Heitholt, J.J., Mauney, J.R. (Physiology of Cotton. Springer, Dordrecht, Netherlands, pp. 1-18. https://doi.org/10.1007/978-90-481-3195-2_1.

[76] Wendel J.F., Grover C.E., 2015. Taxonomy and evolution of the cotton genus, Gossypium. In: Cotton. John Wiley & Sons, Ltd, pp. 25-44. https://doi.org/10.2134/agronmonogr57.2013.0020.

[77] Weng J.K., Chapple C., 2010. The origin and evolution of lignin biosynthesis. New Phytol. 187, 273-285. https://doi.org/10.1111/j.1469-8137.2010.03327.x.

[78] White P.J., 2003. Calcium in plants. Ann. Bot. 92, 487-511. https://doi.org/10.1093/aob/mcg164.

[79] Xie Y., Li F., Xie Y., 2023. Contrasting global patterns and trait controls of major mineral elements in leaf. Glob. Ecol. Biogeogr. 32, 1452-1461. https://doi.org/10.1111/geb.13697.

[80] Xing K., Zhao M., Niinemets Ü., Niu S., Tian J., Jiang Y., Chen H.Y.H., White P.J., Guo D., Ma Z., 2021. Relationships between leaf carbon and macronutrients across woody species and forest ecosystems highlight how carbon is allocated to leaf structural function. Front. Plant Sci. 12, 674932. https://doi.org/10.3389/fpls.2021.674932.

[81] Xu S., Li L., Luo X., Chen M., Tang W., Zhan L., Dai Z., Lam T.T., Guan Y., Yu G., 2022. Ggtree: A serialized data object for visualization of a phylogenetic tree and annotation data. iMeta 1, e56. https://doi.org/10.1002/imt2.56.

[82] Xu Y., Wei Y., Zhou Z., Cai X., Boden S.A., Umer M.J., Safdar L.B., Liu Y., Jin D., Hou Y., Wang Y., Wall S.B., Wang K., Yu S., Zhang B., Peng R., Liu F., 2024. Widespread incomplete lineage sorting and introgression shaped adaptive radiation in the Gossypium genus. Plant Commun. 5, 100728. https://doi.org/10.1016/j.xplc.2023.100728.

[83] Ye Y., Liang X., Chen Y., Li L., Ji Y., Zhu C., 2014. Carbon, nitrogen and phosphorus accumulation and partitioning, and C:N:P stoichiometry in late-season rice under different water and nitrogen managements. PLoS One 9, e101776. https://doi.org/10.1371/journal.pone.0101776.

[84] Yu J., Jung S., Cheng C., Lee T., Zheng P., Buble K., Crabb J., Humann J., Hough H., Jones D., Campbell J.T., Udall J., Main D., 2021. CottonGen: The community database for cotton genomics, genetics, and breeding Research. Plants 10 (2805). https://doi.org/10.3390/plants10122805.

[85] Yuan D., Grover C.E., Hu G., Pan M., Miller E.R., Conover J.L., Hunt S.P., Udall J.A., Wendel J.F., 2021. Parallel and intertwining threads of domestication in allopolyploid cotton. Adv. Sci. 8, 2003634. https://doi.org/10.1002/advs.202003634.

[86] Zhang L., Zuo Z., Qiao X., Liu Y., Qu R., Zhao H., Wang Y., Zhao P., Zhang L., Wu Z., Wang Z., 2024. Global leaf sulfur stoichiometry and the relationships with nitrogen and phosphorus: phylogeny, growth form and environmental controls. Proc. R. Soc. B-Biol. Sci. 291, 20240206. https://doi.org/10.1098/rspb.2024.0206.