Genome wide identification and in silico mRNA expression profiling of the WRKY transcription factor gene family in Salvia hispanica
- 1Department of Integrated and Advanced Technology, School of Engineering and Sciences, Sir Padampat Singhania University
Abstract
This study presents the first comprehensive in silico genome-wide identification, characterization, and mRNA expression profiling of the WRKY transcription factor (TF) gene family in Salvia hispanica L. (chia), a nutritious crop of the family Lamiaceae. A total of 35 CsWRKY genes were identified from the chia reference genome and classified into 7 phylogenetic groups (I, IIa–IIe, III) based on WRKY domain number and zinc-finger motif type. Mean protein length, molecular weight and isoelectric point were 332.8 aa, 37,499 Da and 7.62, respectively, and protein length was almost perfectly correlated with molecular weight (r = 0.9995). Subcellular-localization prediction indicated predominantly nuclear and cytoplasmic distribution. Gene-structure analysis revealed 2–7 exons, and MEME identified 15 conserved motifs including the invariant WRKYGQK heptapeptide. Segmental duplication predominated and has evolved under purifying selection. Promoter analysis detected 20 cis-acting regulatory element classes, and a maximum-likelihood phylogeny grouped CsWRKYs with orthologs from Arabidopsis thaliana, Oryza sativa, Glycine max, Medicago truncatula and Physcomitrella patens. In silico expression profiling used only verified, publicly available S. hispanica RNA-Seq datasets and was therefore restricted to tissue-specific and developmental patterns; because no abiotic-stress RNA-Seq dataset is currently available for chia, no stress-responsive expression analysis was performed. Homology models were built and docked with in silico predictions identifying CsWRKY3 as the strongest binder. These in silico predictions provide a preliminary genomic framework that requires future experimental validation and may guide the study of WRKY-mediated processes in chia.
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BibTeX
@article{tiwari2026genome,
title = {{Genome wide identification and in silico mRNA expression profiling of the WRKY transcription factor gene family in Salvia hispanica}},
author = {Shivani Tiwari},
journal = {Discover Plants},
year = {2026},
month = oct,
doi = {10.1007/s44372-026-00972-8},
url = {https://doi.org/10.1007/s44372-026-00972-8},
note = {CC BY},
}
RIS
TY - JOUR
TI - Genome wide identification and in silico mRNA expression profiling of the WRKY transcription factor gene family in Salvia hispanica
AU - Shivani Tiwari
PY - 2026
DA - 2026/10/25
JO - Discover Plants
DO - 10.1007/s44372-026-00972-8
UR - https://doi.org/10.1007/s44372-026-00972-8
AB - This study presents the first comprehensive in silico genome-wide identification, characterization, and mRNA expression profiling of the WRKY transcription factor (TF) gene family in Salvia hispanica L. (chia), a nutritious crop of the family Lamiaceae. A total of 35 CsWRKY genes were identified from the chia reference genome and classified into 7 phylogenetic groups (I, IIa–IIe, III) based on WRKY domain number and zinc-finger motif type. Mean protein length, molecular weight and isoelectric point were 332.8 aa, 37,499 Da and 7.62, respectively, and protein length was almost perfectly correlated with molecular weight (r = 0.9995). Subcellular-localization prediction indicated predominantly nuclear and cytoplasmic distribution. Gene-structure analysis revealed 2–7 exons, and MEME identified 15 conserved motifs including the invariant WRKYGQK heptapeptide. Segmental duplication predominated and has evolved under purifying selection. Promoter analysis detected 20 cis-acting regulatory element classes, and a maximum-likelihood phylogeny grouped CsWRKYs with orthologs from Arabidopsis thaliana, Oryza sativa, Glycine max, Medicago truncatula and Physcomitrella patens. In silico expression profiling used only verified, publicly available S. hispanica RNA-Seq datasets and was therefore restricted to tissue-specific and developmental patterns; because no abiotic-stress RNA-Seq dataset is currently available for chia, no stress-responsive expression analysis was performed. Homology models were built and docked with in silico predictions identifying CsWRKY3 as the strongest binder. These in silico predictions provide a preliminary genomic framework that requires future experimental validation and may guide the study of WRKY-mediated processes in chia.
SN - 3005-1207
ER -