Legume Genomics and Genetics 2025, Vol.16, No.2, 63-71 http://cropscipublisher.com/index.php/lgg 64 One core feature of WRKY transcription factors is that the networks they are involved in are very complex, and they play a versatile role in regulating plants' responses to environmental stresses such as pathogen invasion, drought, salinity and temperature. They can both regulate upwards and downwards. This "bidirectional regulation" enables them to play a key role in plants' adaptation to environmental changes (Wani et al., 2021). In chickpeas, some WRKY genes exhibit different expression patterns when exposed to various adverse conditions, which further confirms their significance in adverse adaptation (Mashaki et al., 2019). Based on these backgrounds, we conducted this study. The aim was not to provide a general overview but to systematically sort out the genome-wide characteristics of the WRKY family members in chickpeas, including their structure, evolutionary relationships, and expression traits. In addition, we also attempted to delve into the functions of several key WRKY members in actual stress responses, hoping to provide some valuable ideas for subsequent molecular improvement breeding. 2 Structural and Functional Classification of Chickpea WRKYGenes 2.1 Domain architecture and WRKY motifs (WRKYGQK) The name "WRKY" comes from a very short but crucial heptapeptide sequence - WRKYGQK. This small motif remains almost unchanged in all chickpea WRKY transcription factors, with only a very few cases showing variations (Kumar et al., 2016). This is not surprising, as it is the key to their ability to combine with DNA. This WRKY motif does not exist in isolation; it usually appears together with a zinc finger structure, and this combination enhances the binding stability of proteins and DNA. In addition, in the analysis of the chickpea WRKY protein, some other conserved motifs were also discovered, but these structures are often specific to the groups. This might also explain why the functions of the WRKY family are so diverse. 2.2 Classification into groups (I, II, III) based on structural features To group members of the WRKY family, there are actually two main considerations: one is how many WRKY domains they have, and the other is which type the zinc finger motif belongs to. According to this standard, the WRKY gene of chickpeas is divided into three groups: I, II and III. Among them, Group I is rather special, featuring two WRKY domains and one C2H2-type zinc finger. Group II has only one WRKY region, which is also of the C2H2 type, but it is further subdivided into several subgroups from IIa to IIe. Group III, on the other hand, had a C2HC-type zinc finger, which was a unique feature of theirs (Waqas et al., 2019). This classification is not merely a formal difference; to some extent, it also reflects the variations in the evolutionary paths and functional directions of these proteins (Figure 1). 2.3 DNA-binding properties and target W-box elements What exactly is the role of the WRKY protein? Simply put, their most core function is to recognize and bind to certain specific DNA sequences, such as the W-box in the promoter region of the target gene (the core sequence is usually TTGACC/T). The WRKYGQK motif here is the key to determining their recognition ability. Experiments have confirmed that proteins like CaWRKY50 can move into the cell nucleus, precisely lock onto and bind to the W-box, thereby activating or inhibiting some genes involved in the stress response (Kumar et al., 2016). Not only that, structural simulations and molecular dynamics studies also show that this combination not only has strong specificity but also good stability. Moreover, several amino acid residues that play a key role have also been identified (Konda et al., 2018). 3 Genome-Wide Identification and Annotation of WRKYGenes in Chickpea 3.1 Bioinformatics tools used for WRKYgene identification It is not easy to find these WRKY genes from the very beginning. Researchers usually have to start with existing public databases, such as iTAK. With the help of these platforms, they then use a complete set of bioinformatics tools to conduct subsequent identification and analysis - including finding sequences, extracting motifs, predicting gene structures, etc. For instance, MEME Suite is used to discover conserved motifs, GSDS is a common tool for analyzing exon and intron structures, while tools like MEGA and MUSCLE are employed for sequence alignment and the establishment of phylogenetic trees. Although this process sounds standard, there may still be steps in the
RkJQdWJsaXNoZXIy MjQ4ODYzNA==