In-silico identification and characterization of biotic and abiotic stress-responsive transcription factors in okra (Abelmoschus esculentus L.)

Transcription factors (TFs) play a central role in regulating stress-responsive gene networks; however, comprehensive information on stress-associated TFs in okra remains limited. In the present study, an in-silico approach was employed to identify and characterize transcription factors involved in biotic and abiotic stress tolerance in okra using transcriptome-derived unigene sequences. A total of 153,414 unigene sequences obtained from the World Vegetable Center were analyzed using PlantTFDB, leading to the identification of 962 transcription factors. Based on sequence similarity, BLAST E-values, and functional annotation against Arabidopsis thaliana, 17 transcription factors belonging to the WRKY, NAC, ERF, and bZIP families were shortlisted as putatively stress-responsive. Among these, WRKY and NAC families were predominantly associated with biotic stress responses, while ERF and bZIP families were mainly linked to abiotic stress tolerance. Further characterization of these transcription factors was performed through conserved protein motif analysis using the MEME Suite (GLAM2). A total of 17 gapped protein motifs were identified, exhibiting family-specific conservation patterns. Comparative motif analysis using TOMTOM revealed strong similarity between the predicted motifs and known transcription factor binding motifs, confirming their regulatory relevance. Overall, this study provides a comprehensive in-silico framework for identifying stress-responsive transcription factors in okra and highlights candidate genes that may be exploited for functional validation and crop improvement strategies aimed at enhancing stress tolerance.