[1]

Yuan Y, Liu L, Gao Y, Yang Q, Dong K, et al. 2022. Comparative analysis of drought-responsive physiological and transcriptome in broomcorn millet (Panicum miliaceum L.) genotypes with contrasting drought tolerance. Industrial Crops and Products 177:114498
[2]

Zhang M, Zhou X, Wang L, Liang X, Liu X, et al. 2025. A SnRK2-HAK regulatory module confers natural variation of salt tolerance in maize. Nature Communications 16:4026

doi: 10.1038/s41467-025-59332-x
[3]

Zhang Y, Lu Y, Li Z, Xie M, Wen F, et al. 2025. Non-sterile substrate cultivation of oyster mushrooms on fresh Giant Juncao Grass: a scalable strategy for sustainable nutrition in underdeveloped regions. Frontiers in Sustainable Food Systems 9:1582869

doi: 10.3389/fsufs.2025.1582869
[4]

Zheng H, Wang B, Hua X, Gao R, Wang Y, et al. 2023. A near-complete genome assembly of the allotetrapolyploid Cenchrus fungigraminus (JUJUNCAO) provides insights into its evolution and C4 photosynthesis. Plant Communications 4:100633

doi: 10.1016/j.xplc.2023.100633
[5]

Weng H, Wu M, Li X, Wu L, Li J, et al. 2023. High-throughput phenotyping salt tolerance in JUNCAOs by combining prompt chlorophyll a fluorescence with hyperspectral spectroscopy. Plant Science 330:111660

doi: 10.1016/j.plantsci.2023.111660
[6]

Mao F, Luo L, Ma N, Qu Q, Chen H, et al. 2024. A spatiotemporal transcriptome reveals stalk development in pearl millet. International Journal of Molecular Sciences 25:9798

doi: 10.3390/ijms25189798
[7]

Yan H, Sun M, Zhang Z, Jin Y, Zhang A, et al. 2023. Pangenomic analysis identifies structural variation associated with heat tolerance in pearl millet. Nature Genetics 55:507−518

doi: 10.1038/s41588-023-01302-4
[8]

Zhou J, Chen S, Shi W, David-Schwartz R, Li S, et al. 2021. Transcriptome profiling reveals the effects of drought tolerance in Giant Juncao. BMC Plant Biology 21:2

doi: 10.1186/s12870-020-02785-7
[9]

Zhang H, Zhu J, Gong Z, Zhu JK. 2022. Abiotic stress responses in plants. Nature Reviews Genetics 23:104−119

doi: 10.1038/s41576-021-00413-0
[10]

Jin Y, Yan H, Zhu X, Yang Y, Jia J, et al. 2025. Single-cell transcriptomes reveal spatiotemporal heat stress response in pearl millet leaves. New Phytologist 247:637−650

doi: 10.1111/nph.70232
[11]

Chen L, Song Y, Li S, Zhang L, Zou C, et al. 2012. The role of WRKY transcription factors in plant abiotic stresses. Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms 1819:120−128

doi: 10.1016/j.bbagrm.2011.09.002
[12]

Niu CF, Wei W, Zhou QY, Tian AG, Hao YJ, et al. 2012. Wheat WRKY genes TaWRKY2 and TaWRKY19 regulate abiotic stress tolerance in transgenic Arabidopsis plants. Plant, Cell & Environment 35:1156−1170

doi: 10.1111/j.1365-3040.2012.02480.x
[13]

Wang CT, Ru JN, Liu YW, Yang JF, Li M, et al. 2018. The maize WRKY transcription factor ZmWRKY40 confers drought resistance in transgenic Arabidopsis. International Journal of Molecular Sciences 19:2580

doi: 10.3390/ijms19092580
[14]

Xu YH, Sun PW, Tang XL, Gao ZH, Zhang Z, et al. 2020. Genome-wide analysis of WRKY transcription factors in Aquilaria sinensis (Lour.) Gilg. Scientific Reports 10:3018

doi: 10.1038/s41598-020-59597-w
[15]

Rushton PJ, Somssich IE, Ringler P, Shen QJ. 2010. WRKY transcription factors. Trends in Plant Science 15:247−258

doi: 10.1016/j.tplants.2010.02.006
[16]

Phukan UJ, Jeena GS, Shukla RK. 2016. WRKY transcription factors: molecular regulation and stress responses in plants. Frontiers in Plant Science 7:760

doi: 10.3389/fpls.2016.00760
[17]

Luo L, Qu Q, Cao M, Zhang Y, Sun Y, et al. 2025. Epigenetic maps of pearl millet reveal a prominent role for CHH methylation in regulating tissue-specific gene expression. aBIOTECH 6:394−410

doi: 10.1007/s42994-025-00243-2
[18]

Chanwala J, Satpati S, Dixit A, Parida A, Giri MK, et al. 2020. Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress. BMC Genomics 21:231

doi: 10.1186/s12864-020-6622-0
[19]

Wani SH, Anand S, Singh B, Bohra A, Joshi R. 2021. WRKY transcription factors and plant defense responses: latest discoveries and future prospects. Plant Cell Reports 40:1071−1085

doi: 10.1007/s00299-021-02691-8
[20]

Mao C, Zhang J, Zhang Y, Wang B, Li W, et al. 2024. Genome-wide analysis of the WRKY gene family and their response to low-temperature stress in elephant grass. BMC Genomics 25:947

doi: 10.1186/s12864-024-10844-8
[21]

Javed T, Gao SJ. 2023. WRKY transcription factors in plant defense. Trends in Genetics 39:787−801

doi: 10.1016/j.tig.2023.07.001
[22]

Li T, Zeng W, Zhu F, Lü P. 2025. Cis-regulatory elements: systematic identification and horticultural applications. aBIOTECH 6:510−527

doi: 10.1007/s42994-025-00237-0
[23]

Ma N, Jiang D, Li T, Luo L, Chen H, et al. 2025. The specificity landscape of WRKY transcription factors reveals the bidirectional influence of non-CG methylation. Nucleic Acids Research 53:gkaf1168

doi: 10.1093/nar/gkaf1168
[24]

Chen F, Hu Y, Vannozzi A, Wu K, Cai H, et al. 2017. The WRKY transcription factor family in model plants and crops. Critical Reviews in Plant Sciences 36:311−335

doi: 10.1080/07352689.2018.1441103
[25]

Luo L, Lin D, Li J, Chen H, Qu Q, et al. 2025. EGDB: a comprehensive multi-omics database for energy grasses and the epigenomic atlas of pearl millet. iMeta 4:e263

doi: 10.1002/imt2.263
[26]

Blum M, Andreeva A, Florentino LC, Chuguransky SR, Grego T, et al. 2025. InterPro: the protein sequence classification resource in 2025. Nucleic Acids Research 53:D444−D456

doi: 10.1093/nar/gkae1082
[27]

Finn RD, Clements J, Eddy SR. 2011. HMMER web server: interactive sequence similarity searching. Nucleic Acids Research 39:W29−W37

doi: 10.1093/nar/gkr367
[28]

Letunic I, Khedkar S, Bork P. 2021. SMART: recent updates, new developments and status in 2020. Nucleic Acids Research 49:D458−D460

doi: 10.1093/nar/gkaa937
[29]

Gasteiger E, Hoogland C, Gattiker A, Duvaud S, Wilkins MR, et al. 2005. Protein identification and analysis tools on the ExPASy server. In The Proteomics Protocols Handbook, ed. Walker JM. Totowa, NJ: Humana Press. pp. 571−607 doi: 10.1385/1-59259-890-0:571
[30]

Jin J, Tian F, Yang DC, Meng YQ, Kong L, et al. 2017. PlantTFDB 4.0: toward a central hub for transcription factors and regulatory interactions in plants. Nucleic Acids Research 45:D1040−D1045

doi: 10.1093/nar/gkw982
[31]

Sun M, Yan H, Zhang A, Jin Y, Lin C, et al. 2023. Milletdb: a multi-omics database to accelerate the research of functional genomics and molecular breeding of millets. Plant Biotechnology Journal 21:2348−2357

doi: 10.1111/pbi.14136
[32]

Katoh K, Standley DM. 2013. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Molecular Biology and Evolution 30:772−780

doi: 10.1093/molbev/mst010
[33]

Minh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD, et al. 2020. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Molecular Biology and Evolution 37:1530−1534

doi: 10.1093/molbev/msaa015
[34]

Ross CA, Liu Y, Shen QJ. 2007. The WRKY gene family in rice (Oryza sativa). Journal of Integrative Plant Biology 49:827−842

doi: 10.1111/j.1744-7909.2007.00504.x
[35]

Letunic I, Bork P. 2024. Interactive Tree of Life (iTOL) v6: recent updates to the phylogenetic tree display and annotation tool. Nucleic Acids Research 52:W78−W82

doi: 10.1093/nar/gkae268
[36]

Chen C, Chen H, Zhang Y, Thomas HR, Frank MH, et al. 2020. TBtools: an integrative toolkit developed for interactive analyses of big biological data. Molecular Plant 13:1194−1202

doi: 10.1016/j.molp.2020.06.009
[37]

Hu B, Jin J, Guo AY, Zhang H, Luo J, et al. 2015. GSDS 2.0: an upgraded gene feature visualization server. Bioinformatics 31:1296−1297

doi: 10.1093/bioinformatics/btu817
[38]

Wang Y, Tang H, Debarry JD, Tan X, Li J, et al. 2012. MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Research 40:e49

doi: 10.1093/nar/gkr1293
[39]

Wang D, Zhang Y, Zhang Z, Zhu J, Yu J. 2010. KaKs_Calculator 2.0: a toolkit incorporating gamma-series methods and sliding window strategies. Genomics Proteomics Bioinformatics 8:77−80

doi: 10.1016/S1672-0229(10)60008-3
[40]

Bailey TL, Williams N, Misleh C, Li WW. 2006. MEME: discovering and analyzing DNA and protein sequence motifs. Nucleic Acids Research 34:W369−W373

doi: 10.1093/nar/gkl198
[41]

Lescot M, Déhais P, Thijs G, Marchal K, Moreau Y, et al. 2002. PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences. Nucleic Acids Research 30:325−327

doi: 10.1093/nar/30.1.325
[42]

Love MI, Huber W, Anders S. 2014. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology 15:550

doi: 10.1186/s13059-014-0550-8
[43]

Ginestet C. 2011. ggplot2: elegant graphics for data analysis. Journal of the Royal Statistical Society Series A: Statistics in Society 174:245−246

doi: 10.1111/j.1467-985x.2010.00676_9.x
[44]

Chen H, Boutros PC. 2011. VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R. BMC Bioinformatics 12:35

doi: 10.1186/1471-2105-12-35
[45]

Lex A, Gehlenborg N, Strobelt H, Vuillemot R, Pfister H. 2014. UpSet: visualization of intersecting sets. IEEE Transactions on Visualization and Computer Graphics 20:1983−1992

doi: 10.1109/TVCG.2014.2346248
[46]

Langfelder P, Horvath S. 2008. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 9:559

doi: 10.1186/1471-2105-9-559
[47]

Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, et al. 2003. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Research 13:2498−2504

doi: 10.1101/gr.1239303
[48]

Cantalapiedra CP, Hernández-Plaza A, Letunic I, Bork P, Huerta-Cepas J. 2021. eggNOG-mapper v2: functional annotation, orthology assignments, and domain prediction at the metagenomic scale. Molecular Biology and Evolution 38:5825−5829

doi: 10.1093/molbev/msab293
[49]

Yu G, Wang LG, Han Y, He QY. 2012. clusterProfiler: an R package for comparing biological themes among gene clusters. Omics 16:284−287

doi: 10.1089/omi.2011.0118
[50]

Javed T, Zhou JR, Li J, Hu ZT, Wang QN, et al. 2022. Identification and expression profiling of WRKY family genes in sugarcane in response to bacterial pathogen infection and nitrogen implantation dosage. Frontiers in Plant Science 13:917953

doi: 10.3389/fpls.2022.917953
[51]

He Y, Mao S, Gao Y, Zhu L, Wu D, et al. 2016. Genome-wide identification and expression analysis of WRKY transcription factors under multiple stresses in Brassica napus. PLoS One 11:e0157558

doi: 10.1371/journal.pone.0157558
[52]

Dong T, Su J, Li H, Du Y, Wang Y, et al. 2024. Genome-wide identification of the WRKY gene family in four cotton varieties and the positive role of GhWRKY31 in response to salt and drought stress. Plants 13:1814

doi: 10.3390/plants13131814
[53]

Fu M, Li H, Chen Y, Wang L, Liu Z, et al. 2019. Genome-wide investigation of WRKY transcription factors in Gossypium barbadense and their expression patterns in response to Verticillium dahliae infection. Journal of Plant Genetic Resources 20:1289−1300 (in Chinese)

doi: 10.13430/j.cnki.jpgr.20181210004
[54]

Zhou Y, Wang Y, Gao T, Cao Y, Yao Y, et al. 2025. Characteristics and expression profiles of identified WRKY genes in barley landraces under cold stress. International Journal of Molecular Sciences 26:6948

doi: 10.3390/ijms26146948
[55]

Cannon SB, Mitra A, Baumgarten A, Young ND, May G. 2004. The roles of segmental and tandem gene duplication in the evolution of large gene families in Arabidopsis thaliana. BMC Plant Biology 4:10

doi: 10.1186/1471-2229-4-10
[56]

Hu W, Ren Q, Chen Y, Xu G, Qian Y. 2021. Genome-wide identification and analysis of WRKY gene family in maize provide insights into regulatory network in response to abiotic stresses. BMC Plant Biology 21:427

doi: 10.1186/s12870-021-03206-z
[57]

Du H, Zhou J, Liang X, Chen Y, Liu X, et al. 2025. Genome-wide identification and expression analysis of the WRKY gene families in Vaccinium bracteatum. International Journal of Molecular Sciences 26:7835

doi: 10.3390/ijms26167835
[58]

Yang Y, Liu J, Zhou X, Liu S, Zhuang Y. 2020. Identification of WRKY gene family and characterization of cold stress-responsive WRKY genes in eggplant. PeerJ 8:e8777

doi: 10.7717/peerj.8777
[59]

Chen C, Chen X, Han J, Lu W, Ren Z. 2020. Genome-wide analysis of the WRKY gene family in the cucumber genome and transcriptome-wide identification of WRKY transcription factors that respond to biotic and abiotic stresses. BMC Plant Biology 20:443

doi: 10.1186/s12870-020-02625-8
[60]

Zhang C, Wang W, Wang D, Hu S, Zhang Q, et al. 2022. Genome-wide identification and characterization of the WRKY gene family in Scutellaria baicalensis Georgi under diverse abiotic stress. International Journal of Molecular Sciences 8:4225

doi: 10.3390/ijms23084225
[61]

Yang YL, Cushman SA, Wang SC, Wang F, Li Q, et al. 2023. Genome-wide investigation of the WRKY transcription factor gene family in weeping forsythia: expression profile and cold and drought stress responses. Genetica 151:153−165

doi: 10.1007/s10709-023-00184-y
[62]

Findling S, Fekete A, Warzecha H, Krischke M, Brandt H, et al. 2014. Manipulation of methyl jasmonate esterase activity renders tomato more susceptible to Sclerotinia sclerotiorum. Functional Plant Biology 41:133−143

doi: 10.1071/FP13103
[63]

Yu X, Zhang W, Zhang Y, Zhang X, Lang D, et al. 2019. The roles of methyl jasmonate to stress in plants. Functional Plant Biology 46:197−212

doi: 10.1071/FP18106
[64]

Chen J, Hou S, Zhang Q, Meng J, Zhang Y, et al. 2023. Genome-wide identification and analysis of the WRKY gene family in Asparagus officinalis. Genes 14:1704

doi: 10.3390/genes14091704