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However, the coordinated regulatory network between metabolic disturbances and hormonal signaling that drives morphological adaptation under temperature fluctuations remains unclear.<\/jats:p>\n                      <\/jats:list-item>\n                      <jats:list-item>\n                        <jats:p>\n                          This study integrated machine learning\u2010driven multi\u2010omics analysis,\n                          <jats:italic>in situ<\/jats:italic>\n                          histochemical localization, and pharmacological validation to decipher the root adaptation strategies of wheat under temperature gradients.\n                        <\/jats:p>\n                      <\/jats:list-item>\n                      <jats:list-item>\n                        <jats:p>Wheat roots exhibited convergent morphological plasticity under temperature stress. However, this convergence was associated with distinct hormonal signaling pathways linked to iron homeostasis. Transcriptome data indicated that temperature stress generally down\u2010regulated genes associated with iron acquisition strategy II. Low\u2010temperature stress induced physiological iron deficiency, which triggered an auxin surge to promote compensatory root hair elongation, coinciding with the transcriptional upregulation of iron acquisition Strategy I. Conversely, high\u2010temperature stress induced jasmonic acid accumulation, which contributed to maintaining root hair growth while potentially mitigating iron overload by promoting iron compartmentalization and restricting local accumulation.<\/jats:p>\n                      <\/jats:list-item>\n                      <jats:list-item>\n                        <jats:p>Our findings support an \u2018iron\u2010dependent hormonal trade\u2010off\u2019 model and identified iron homeostasis as the core metabolic hub connecting environmental perception, hormonal regulation, and root architectural plasticity. This study highlights the powerful role of multi\u2010omics integration approaches in uncovering hidden metabolic targets, providing a theoretical basis for breeding climate\u2010adaptive crops with optimized root systems.<\/jats:p>\n                      <\/jats:list-item>\n                    <\/jats:list>\n                  <\/jats:p>","DOI":"10.1111\/nph.71336","type":"journal-article","created":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T05:15:06Z","timestamp":1780636506000},"page":"1947-1966","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Machine learning\u2010guided multi\u2010omics suggests iron\u2010dependent hormonal signaling drives root morphological plasticity in wheat under temperature stress"],"prefix":"10.1111","volume":"251","author":[{"given":"Wenyuan","family":"Shen","sequence":"first","affiliation":[{"name":"College of Bioscience and Biotechnology Yangzhou University  Yangzhou 225009 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