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Genome-Wide Characterization and Expression Profiling of Phytosulfokine Receptor Genes (PSKRs) in Triticum aestivum with Docking Simulations of Their Interactions with Phytosulfokine (PSK): A Bioinformatics Study

Summary

This study mapped and analyzed receptor genes in wheat that respond to a natural plant hormone called phytosulfokine. Researchers identified 57 versions of these receptor genes distributed across wheat’s genome and found they are most active in roots and leaves at different growth stages. Computer modeling showed how the plant hormone binds to its receptors. These findings could help develop wheat varieties that grow better and handle stress more effectively.

Background

Phytosulfokine receptors (PSKRs) are crucial receptor-like kinases involved in plant growth, development, and stress response. Despite their importance, PSKRs have been limited explored in wheat (Triticum aestivum), a major staple crop.

Objective

This study aimed to comprehensively characterize the PSKR gene family in wheat through genome-wide identification, phylogenetic analysis, expression profiling, and molecular docking simulations to elucidate their functional roles in wheat development and stress responses.

Results

Analysis identified 57 TaPSKR members across three subgenomes representing 25 distinct genes. Hierarchical clustering of expression data revealed three gene clusters with distinct expression patterns across developmental stages and tissues. Molecular docking simulations demonstrated strong binding affinity between PSK-α and specific receptors (TaPSKR1A, TaPSKR3B, and TaPSKR13A), primarily through leucine-rich repeat domain interactions.

Conclusion

This comprehensive characterization reveals the complexity and diversity of the wheat PSKR gene family, with distinct functional roles in root development, leaf growth, and constitutive cellular processes. The findings provide a foundation for future functional studies and potential crop improvement through targeted manipulation of PSK signaling pathways.
  • Published in:Genes (Basel),
  • Study Type:Bioinformatics Study,
  • Source: PMID: 39457430
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